31,ç 4HEç#OMPLETEç2EFERENCE çç 4HIRDç%DITION
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31,ç 4HEç#OMPLETEç2EFERENCE ç 4HIRDç%DITION 0AUL 7EINBERG *AMES 'ROFF !NDREW /PPEL
.EW 9ORK #HICAGO 3AN &RANCISCO ,ISBON ,ONDON -ADRID -EXICO #ITY -ILAN .EW $ELHI 3AN *UAN 3EOUL 3INGAPORE 3YDNEY 4ORONTO
Copyright © 2010 by The McGraw-Hill Companies. All rights reserved. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. ISBN: 978-0-07-159256-7 MHID: 0-07-159256-3 The material in this eBook also appears in the print version of this title: ISBN: 978-0-07-159255-0, MHID: 0-07-159255-5. All trademarks are trademarks of their respective owners. Rather than put a trademark symbol after every occurrence of a trademarked name, we use names in an editorial fashion only, and to the benefit of the trademark owner, with no intention of infringement of the trademark. Where such designations appear in this book, they have been printed with initial caps. McGraw-Hill eBooks are available at special quantity discounts to use as premiums and sales promotions, or for use in corporate training programs. To contact a representative please e-mail us at
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!BOUTõTHEõ!UTHORS *AMES 2 'ROFF IS #%/ OF 0"WORKS WHOSE HOSTED COLLABORATION SOFTWARE HELPS TEAMS OF PEOPLE WORK TOGETHER MORE EFFECTIVELY AND EFFICIENTLY %ARLIER 'ROFF WAS #%/ OF 4IMES4EN THE LEADING PROVIDER OF IN MEMORY 31, DATABASES (E LED 4IMES4EN FROM ITS EARLY DAYS THROUGH EIGHT YEARS OF GROWTH AND A SUCCESSFUL ACQUISITION BY /RACLE IN WHERE HE SERVED AS A SENIOR VICE PRESIDENT AND /RACLE 4IMES4EN BECAME /RACLES FLAGSHIP REAL TIME DATABASE PRODUCT 'ROFF WAS THE COFOUNDER WITH 0AUL 7EINBERG OF .ETWORK )NNOVATIONS #ORPORATION A DEVELOPER OF 31, BASED NETWORKING SOFTWARE AND COAUTHOR WITH HIM OF 5NDERSTANDING 5.)8 ! #ONCEPTUAL 'UIDE AS WELL AS THIS BOOK 'ROFF HAS ALSO HELD SENIOR DIVISION MANAGEMENT AND MARKETING POSITIONS AT !PPLE #OMPUTER AND (EWLETT 0ACKARD (E HOLDS A "3 IN -ATHEMATICS FROM THE -ASSACHUSETTS )NSTITUTE OF 4ECHNOLOGY AND AN -"! FROM (ARVARD 5NIVERSITY 0AUL . 7EINBERG IS A SENIOR VICE PRESIDENT AT 3!0 WHERE HE RUNS CORE -$- -ASTER $ATA -ANAGEMENT DEVELOPMENT 0RIOR TO WORKING AT 3!0 7EINBERG WAS PRESIDENT OF !I )NC WHICH WAS ACQUIRED BY 3!0 IN FOR ITS ENTERPRISEWIDE PLATFORM FOR PRODUCT CONTENT MANAGEMENT AND CATALOG PUBLISHING 7EINBERG WAS THE COFOUNDER WITH *AMES 'ROFF OF .ETWORK )NNOVATIONS #ORPORATION A PIONEER IN CLIENTSERVER DATABASE ACCESS THAT WAS ACQUIRED BY !PPLE #OMPUTER IN AND COAUTHOR WITH HIM OF 5NDERSTANDING 5.)8 ! #ONCEPTUAL 'UIDE AS WELL AS THIS BOOK (E HAS ALSO HELD SOFTWARE DEVELOPMENT AND MARKETING POSITIONS AT "ELL ,ABORATORIES (EWLETT 0ACKARD AND 0LEXUS #OMPUTERS )N HE COLLABORATED ON 4HE 3IMPLE 3OLUTION TO 2UBIKS #UBE THE NUMBER ONE BEST SELLING BOOK OF THAT YEAR WITH OVER MILLION COPIES SOLD (E HOLDS A "3 FROM THE 5NIVERSITY OF -ICHIGAN AND AN -3 FROM 3TANFORD 5NIVERSITY BOTH IN #OMPUTER 3CIENCE !NDREW * !NDY /PPEL IS LEAD DATA MODELER AT "LUE 3HIELD OF #ALIFORNIA )N ADDITION HE HAS SERVED AS A PART TIME INSTRUCTOR IN DATABASE TECHNOLOGY WITH THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEY %XTENSION FOR MORE THAN YEARS !NDY HAS DESIGNED AND IMPLEMENTED HUNDREDS OF DATABASES FOR A WIDE RANGE OF APPLICATIONS INCLUDING HEATH CARE BANKING INSURANCE APPAREL MANUFACTURING TELECOMMUNICATIONS WIRELESS COMMUNICATIONS AND HUMAN RESOURCES (E IS THE AUTHOR OF $ATABASES $EMYSTIFIED 31, $EMYSTIFIED AND $ATABASES ! "EGINNERS 'UIDE AND IS COAUTHOR OF 31, ! "EGINNERS 'UIDE (E HOLDS A "! IN #OMPUTER 3CIENCE FROM 4RANSYLVANIA 5NIVERSITY ,EXINGTON +9
!BOUTõTHEõ4ECHNICALõ%DITOR !ARON $AVENPORT HAS BEEN WORKING WITH 31, BASED 2$"-3 TECHNOLOGIES FOR OVER TEN YEARS (E IS CURRENTLY A PRINCIPAL AT ,#3 4ECHNOLOGIES )NC A 3ACRAMENTO AND 3AN &RANCISCO "AY !REA DATABASE CONSULTING FIRM SPECIALIZING IN PERFORMANCE TUNING APPLICATION DEVELOPMENT AND DATABASE ARCHITECTURE 0RIOR TO JOINING ,#3 !ARON HAD TENURES AT 9AHOO 'AP )NC AND "LUE 3HIELD OF #ALIFORNIA
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#ONTENTSçATçAç'LANCE õ
0ARTõ)õ !Nõ/VERVIEWõOFõ31,
)NTRODUCTION
! 1UICK 4OUR OF 31,
31, IN 0ERSPECTIVE
2ELATIONAL $ATABASES
õ 0ARTõ))õ 2ETRIEVINGõ$ATA
31, "ASICS
3IMPLE 1UERIES
-ULTITABLE 1UERIES *OINS
3UMMARY 1UERIES
3UBQUERIES AND 1UERY %XPRESSIONS
õ 0ARTõ)))õ 5PDATINGõ$ATA
$ATABASE 5PDATES
$ATA )NTEGRITY
4RANSACTION 0ROCESSING
õ 0ARTõ)6õ $ATABASEõ3TRUCTURE
#REATING A $ATABASE
6IEWS
31, 3ECURITY
4HE 3YSTEM #ATALOG
VII
VIIIç õ
31,ç4HEç#OMPLETEç2EFERENCE
0ARTõ6õ 0ROGRAMMINGõWITHõ31,
%MBEDDED 31,
$YNAMIC 31,
31, !0)S
õ 0ARTõ6)õ 31,õ4ODAYõANDõ4OMORROW
$ATABASE 0ROCESSING AND 3TORED 0ROCEDURAL 31,
31, AND $ATA 7AREHOUSING
31, AND !PPLICATION 3ERVERS
31, .ETWORKING AND $ISTRIBUTED $ATABASES
31, AND /BJECTS
31, AND 8-,
3PECIALTY $ATABASES
4HE &UTURE OF 31,
õ 0ARTõ6))õ !PPENDIXES
! 4HE 3AMPLE $ATABASE
" $"-3 6ENDOR 0ROlLES
# 31, 3YNTAX 2EFERENCE
)NDEX
#ONTENTSç
#ONTENTS !CKNOWLEDGMENTS XXIII )NTRODUCTION XXV
õ
0ARTõ)õ !Nõ/VERVIEWõOFõ31,
)NTRODUCTION 4HE 31, ,ANGUAGE 4HE 2OLE OF 31, 31, 3UCCESS &ACTORS 6ENDOR )NDEPENDENCE 0ORTABILITY !CROSS #OMPUTER 3YSTEMS /FlCIAL 31, 3TANDARDS %ARLY )"- #OMMITMENT -ICROSOFT 3UPPORT 2ELATIONAL &OUNDATION (IGH ,EVEL %NGLISH ,IKE 3TRUCTURE )NTERACTIVE !D (OC 1UERIES 0ROGRAMMATIC $ATABASE !CCESS -ULTIPLE 6IEWS OF $ATA #OMPLETE $ATABASE ,ANGUAGE $YNAMIC $ATA $ElNITION #LIENT3ERVER !RCHITECTURE %NTERPRISE !PPLICATION 3UPPORT %XTENSIBILITY AND /BJECT 4ECHNOLOGY )NTERNET $ATABASE !CCESS *AVA )NTEGRATION *$"# /PEN 3OURCE 3UPPORT )NDUSTRY )NFRASTRUCTURE
! 1UICK 4OUR OF 31, ! 3IMPLE $ATABASE 2ETRIEVING $ATA 3UMMARIZING $ATA !DDING $ATA TO THE $ATABASE $ELETING $ATA 5PDATING THE $ATABASE 0ROTECTING $ATA #REATING A $ATABASE 3UMMARY
IX
IX
Xç
31,ç4HEç#OMPLETEç2EFERENCE
31, IN 0ERSPECTIVE 31, AND THE %VOLUTION OF $ATABASE -ANAGEMENT ! "RIEF (ISTORY OF 31, 4HE %ARLY 9EARS %ARLY 2ELATIONAL 0RODUCTS )"- 0RODUCTS #OMMERCIAL !CCEPTANCE 31, 3TANDARDS 4HE !.3))3/ 3TANDARDS /THER %ARLY 31, 3TANDARDS /$"# AND THE 31, !CCESS 'ROUP *$"# AND !PPLICATION 3ERVERS 31, AND 0ORTABILITY 31, AND .ETWORKING #ENTRALIZED !RCHITECTURE &ILE 3ERVER !RCHITECTURE #LIENT3ERVER !RCHITECTURE -ULTITIER !RCHITECTURE 4HE 0ROLIFERATION OF 31, 31, ON -AINFRAMES 31, ON -INICOMPUTERS 31, ON 5.)8 "ASED 3YSTEMS 31, ON 0ERSONAL #OMPUTERS 31, AND 4RANSACTION 0ROCESSING 31, AND 7ORKGROUP $ATABASES 31, $ATA 7AREHOUSING AND "USINESS )NTELLIGENCE 31, AND )NTERNET !PPLICATIONS 3UMMARY
2ELATIONAL $ATABASES %ARLY $ATA -ODELS &ILE -ANAGEMENT 3YSTEMS (IERARCHICAL $ATABASES .ETWORK $ATABASES 4HE 2ELATIONAL $ATA -ODEL 4HE 3AMPLE $ATABASE 4ABLES 0RIMARY +EYS 2ELATIONSHIPS &OREIGN +EYS #ODDS 2ULES FOR 2ELATIONAL $ATABASES 3UMMARY
#ONTENTSç
õ 0ARTõ))õ 2ETRIEVINGõ$ATA
31, "ASICS 3TATEMENTS .AMES 4ABLE .AMES #OLUMN .AMES $ATA 4YPES #ONSTANTS .UMERIC #ONSTANTS 3TRING #ONSTANTS $ATE AND 4IME #ONSTANTS 3YMBOLIC #ONSTANTS %XPRESSIONS "UILT )N &UNCTIONS -ISSING $ATA .5,, 6ALUES 3UMMARY
3IMPLE 1UERIES 4HE 3%,%#4 3TATEMENT 4HE 3%,%#4 #LAUSE 4HE &2/- #LAUSE 1UERY 2ESULTS 3IMPLE 1UERIES #ALCULATED #OLUMNS 3ELECTING !LL #OLUMNS 3%,%#4 $UPLICATE 2OWS $)34).#4 2OW 3ELECTION 7(%2% #LAUSE 3EARCH #ONDITIONS 4HE #OMPARISON 4EST 4HE 2ANGE 4EST "%47%%. 4HE 3ET -EMBERSHIP 4EST ). 4HE 0ATTERN -ATCHING 4EST ,)+% 4HE .ULL 6ALUE 4EST )3 .5,, #OMPOUND 3EARCH #ONDITIONS !.$ /2 AND ./4 3ORTING 1UERY 2ESULTS /2$%2 "9 #LAUSE 2ULES FOR 3INGLE 4ABLE 1UERY 0ROCESSING #OMBINING 1UERY 2ESULTS 5.)/. 5NIONS AND $UPLICATE 2OWS 5NIONS AND 3ORTING -ULTIPLE 5.)/.S 3UMMARY
XI
XIIç
31,ç4HEç#OMPLETEç2EFERENCE
-ULTITABLE 1UERIES *OINS ! 4WO 4ABLE 1UERY %XAMPLE 3IMPLE *OINS %QUI *OINS 0ARENT#HILD 1UERIES !N !LTERNATIVE 7AY TO 3PECIFY *OINS *OINS WITH 2OW 3ELECTION #RITERIA -ULTIPLE -ATCHING #OLUMNS .ATURAL *OINS 1UERIES WITH 4HREE OR -ORE 4ABLES /THER %QUI *OINS .ON %QUI *OINS 31, #ONSIDERATIONS FOR -ULTITABLE 1UERIES 1UALIlED #OLUMN .AMES !LL #OLUMN 3ELECTIONS 3ELF *OINS 4ABLE !LIASES -ULTITABLE 1UERY 0ERFORMANCE 4HE 3TRUCTURE OF A *OIN 4ABLE -ULTIPLICATION 2ULES FOR -ULTITABLE 1UERY 0ROCESSING /UTER *OINS ,EFT AND 2IGHT /UTER *OINS /LDER /UTER *OIN .OTATION *OINS AND THE 31, 3TANDARD )NNER *OINS IN 3TANDARD 31, /UTER *OINS IN 3TANDARD 31, #ROSS *OINS IN 3TANDARD 31, -ULTITABLE *OINS IN 3TANDARD 31, 3UMMARY
3UMMARY 1UERIES #OLUMN &UNCTIONS #OMPUTING A #OLUMN 4OTAL 35- #OMPUTING A #OLUMN !VERAGE !6' &INDING %XTREME 6ALUES -). AND -!8 #OUNTING $ATA 6ALUES #/5.4 #OLUMN &UNCTIONS IN THE 3ELECT ,IST .5,, 6ALUES AND #OLUMN &UNCTIONS $UPLICATE 2OW %LIMINATION $)34).#4 'ROUPED 1UERIES '2/50 "9 #LAUSE -ULTIPLE 'ROUPING #OLUMNS 2ESTRICTIONS ON 'ROUPED 1UERIES .5,, 6ALUES IN 'ROUPING #OLUMNS
#ONTENTSç
'ROUP 3EARCH #ONDITIONS (!6).' #LAUSE 2ESTRICTIONS ON 'ROUP 3EARCH #ONDITIONS .5,, 6ALUES AND 'ROUP 3EARCH #ONDITIONS (!6).' 7ITHOUT '2/50 "9 3UMMARY
3UBQUERIES AND 1UERY %XPRESSIONS 5SING 3UBQUERIES 7HAT )S A 3UBQUERY 3UBQUERIES IN THE 7(%2% #LAUSE /UTER 2EFERENCES 3UBQUERY 3EARCH #ONDITIONS 4HE 3UBQUERY #OMPARISON 4EST 4HE 3ET -EMBERSHIP 4EST ). 4HE %XISTENCE 4EST %8)343 1UANTIlED 4ESTS !.9 AND !,, 3UBQUERIES AND *OINS .ESTED 3UBQUERIES #ORRELATED 3UBQUERIES 3UBQUERIES IN THE (!6).' #LAUSE 3UBQUERY 3UMMARY !DVANCED 1UERIES 3CALAR 6ALUED %XPRESSIONS 2OW 6ALUED %XPRESSIONS 4ABLE 6ALUED %XPRESSIONS 1UERY %XPRESSIONS 31, 1UERIES ! &INAL 3UMMARY
õ 0ARTõ)))õ 5PDATINGõ$ATA
$ATABASE 5PDATES !DDING $ATA TO THE $ATABASE 4HE 3INGLE 2OW ).3%24 3TATEMENT 4HE -ULTIROW ).3%24 3TATEMENT "ULK ,OAD 5TILITIES $ELETING $ATA FROM THE $ATABASE 4HE $%,%4% 3TATEMENT $ELETING !LL 2OWS $%,%4% WITH 3UBQUERY -ODIFYING $ATA IN THE $ATABASE 4HE 50$!4% 3TATEMENT 5PDATING !LL 2OWS 50$!4% WITH 3UBQUERY 3UMMARY
XIII
XIVç
31,ç4HEç#OMPLETEç2EFERENCE
$ATA )NTEGRITY 7HAT )S $ATA )NTEGRITY 2EQUIRED $ATA 3IMPLE 6ALIDITY #HECKING #OLUMN #HECK #ONSTRAINTS $OMAINS %NTITY )NTEGRITY /THER 5NIQUENESS #ONSTRAINTS 5NIQUENESS AND .5,, 6ALUES 2EFERENTIAL )NTEGRITY 2EFERENTIAL )NTEGRITY 0ROBLEMS $ELETE AND 5PDATE 2ULES #ASCADED $ELETES AND 5PDATES 2EFERENTIAL #YCLES &OREIGN +EYS AND .5,, 6ALUES !DVANCED #ONSTRAINT #APABILITIES !SSERTIONS 31, #ONSTRAINT 4YPES $EFERRED #ONSTRAINT #HECKING "USINESS 2ULES 7HAT )S A 4RIGGER 4RIGGERS AND 2EFERENTIAL )NTEGRITY 4RIGGER !DVANTAGES AND $ISADVANTAGES 4RIGGERS AND THE 31, 3TANDARD 3UMMARY
4RANSACTION 0ROCESSING 7HAT )S A 4RANSACTION 4HE !.3))3/ 31, 4RANSACTION -ODEL 4HE 34!24 42!.3!#4)/. AND 3%4 42!.3!#4)/. 3TATEMENTS 4HE 3!6%0/).4 AND 2%,%!3% 3!6%0/).4 3TATEMENTS 4HE #/--)4 AND 2/,,"!#+ 3TATEMENTS 4RANSACTIONS "EHIND THE 3CENES 4RANSACTIONS AND -ULTIUSER 0ROCESSING 4HE ,OST 5PDATE 0ROBLEM 4HE 5NCOMMITTED $ATA 0ROBLEM 4HE )NCONSISTENT $ATA 0ROBLEM 4HE 0HANTOM )NSERT 0ROBLEM #ONCURRENT 4RANSACTIONS ,OCKING ,OCKING ,EVELS 3HARED AND %XCLUSIVE ,OCKS $EADLOCKS !DVANCED ,OCKING 4ECHNIQUES
#ONTENTSç
6ERSIONING 6ERSIONING IN /PERATION 6ERSIONING !DVANTAGES AND $ISADVANTAGES 3UMMARY
õ 0ARTõ)6õ $ATABASEõ3TRUCTURE
#REATING A $ATABASE 4HE $ATA $ElNITION ,ANGUAGE #REATING A $ATABASE 4ABLE $ElNITIONS #REATING A 4ABLE #2%!4% 4!",% 2EMOVING A 4ABLE $2/0 4!",% #HANGING A 4ABLE $ElNITION !,4%2 4!",% #ONSTRAINT $ElNITIONS !SSERTIONS $OMAINS !LIASES AND 3YNONYMS #2%!4%$2/0 !,)!3 )NDEXES #2%!4%$2/0 ).$%8 -ANAGING /THER $ATABASE /BJECTS $ATABASE 3TRUCTURE 3INGLE $ATABASE !RCHITECTURE -ULTIDATABASE !RCHITECTURE -ULTILOCATION !RCHITECTURE $ATABASES ON -ULTIPLE 3ERVERS $ATABASE 3TRUCTURE AND THE !.3))3/ 3TANDARD #ATALOGS 3CHEMAS 3UMMARY
6IEW 7HAT )S A 6IEW (OW THE $"-3 (ANDLES 6IEWS !DVANTAGES OF 6IEWS $ISADVANTAGES OF 6IEWS #REATING A 6IEW #2%!4% 6)%7 (ORIZONTAL 6IEWS 6ERTICAL 6IEWS 2OW#OLUMN 3UBSET 6IEWS 'ROUPED 6IEWS *OINED 6IEWS 5PDATING A 6IEW 6IEW 5PDATES AND THE !.3))3/ 3TANDARD 6IEW 5PDATES IN #OMMERCIAL 31, 0RODUCTS #HECKING 6IEW 5PDATES #(%#+ /04)/.
XV
XVIç
31,ç4HEç#OMPLETEç2EFERENCE
$ROPPING A 6IEW $2/0 6)%7 -ATERIALIZED 6IEWS 3UMMARY
31, 3ECURITY 31, 3ECURITY #ONCEPTS 5SER )DS 3ECURITY /BJECTS 0RIVILEGES 6IEWS AND 31, 3ECURITY 'RANTING 0RIVILEGES '2!.4 #OLUMN 0RIVILEGES 0ASSING 0RIVILEGES '2!.4 /04)/. 2EVOKING 0RIVILEGES 2%6/+% 2%6/+% AND THE '2!.4 /04)/. 2%6/+% AND THE !.3))3/ 3TANDARD 2OLE "ASED 3ECURITY 3UMMARY
4HE 3YSTEM #ATALOG 7HAT )S THE 3YSTEM #ATALOG 4HE #ATALOG AND 1UERY 4OOLS 4HE #ATALOG AND THE !.3))3/ 3TANDARD #ATALOG #ONTENTS 4ABLE )NFORMATION #OLUMN )NFORMATION 6IEW )NFORMATION 2EMARKS 2ELATIONSHIP )NFORMATION 5SER )NFORMATION 0RIVILEGES )NFORMATION 4HE 31, )NFORMATION 3CHEMA /THER #ATALOG )NFORMATION 3UMMARY
õ
0ARTõ6õ 0ROGRAMMINGõWITHõ31, %MBEDDED 31, 0ROGRAMMATIC 31, 4ECHNIQUES $"-3 3TATEMENT 0ROCESSING %MBEDDED 31, #ONCEPTS $EVELOPING AN %MBEDDED 31, 0ROGRAM 2UNNING AN %MBEDDED 31, 0ROGRAM
#ONTENTSç
3IMPLE %MBEDDED 31, 3TATEMENTS $ECLARING 4ABLES %RROR (ANDLING 5SING (OST 6ARIABLES $ATA 2ETRIEVAL IN %MBEDDED 31, 3INGLE 2OW 1UERIES -ULTIROW 1UERIES #URSOR "ASED $ELETES AND 5PDATES #URSORS AND 4RANSACTION 0ROCESSING 3UMMARY
$YNAMIC 31, ,IMITATIONS OF 3TATIC 31, $YNAMIC 31, #ONCEPTS $YNAMIC 3TATEMENT %XECUTION %8%#54% )--%$)!4% 4WO 3TEP $YNAMIC %XECUTION 4HE 02%0!2% 3TATEMENT 4HE %8%#54% 3TATEMENT $YNAMIC 1UERIES 4HE $%3#2)"% 3TATEMENT 4HE $%#,!2% #523/2 3TATEMENT 4HE $YNAMIC /0%. 3TATEMENT 4HE $YNAMIC &%4#( 3TATEMENT 4HE $YNAMIC #,/3% 3TATEMENT $YNAMIC 31, $IALECTS $YNAMIC 31, IN /RACLE $YNAMIC 31, AND THE 31, 3TANDARD "ASIC $YNAMIC 31, 3TATEMENTS 4HE 3TANDARD 31,$! 4HE 31, 3TANDARD AND $YNAMIC 31, 1UERIES 3UMMARY
31, !0)S !0) #ONCEPTS 4HE DBLIB !0) 31, 3ERVER "ASIC 31, 3ERVER 4ECHNIQUES 31, 3ERVER 1UERIES 0OSITIONED 5PDATES $YNAMIC 1UERIES /$"# AND THE 31,#,) 3TANDARD 4HE #ALL ,EVEL )NTERFACE 3TANDARDIZATION #,) 3TRUCTURES #,) 3TATEMENT 0ROCESSING #,) %RRORS AND $IAGNOSTIC )NFORMATION #,) !TTRIBUTES #,) )NFORMATION #ALLS
XVII
XVIIIç
31,ç4HEç#OMPLETEç2EFERENCE
4HE /$"# !0) 4HE 3TRUCTURE OF /$"# /$"# AND $"-3 )NDEPENDENCE /$"# #ATALOG &UNCTIONS %XTENDED /$"# #APABILITIES 4HE /RACLE #ALL )NTERFACE /#) /#) (ANDLES /RACLE 3ERVER #ONNECTION 3TATEMENT %XECUTION 1UERY 2ESULTS 0ROCESSING $ESCRIPTOR (ANDLING 4RANSACTION -ANAGEMENT *AVA $ATABASE #ONNECTIVITY *$"# *$"# (ISTORY AND 6ERSIONS *$"# )MPLEMENTATIONS AND $RIVER 4YPES 4HE *$"# !0) 3UMMARY
õ 0ARTõ6)õ 31,õ4ODAYõANDõ4OMORROW
$ATABASE 0ROCESSING AND 3TORED 0ROCEDURAL 31, 0ROCEDURAL 31, #ONCEPTS ! "ASIC %XAMPLE 5SING 3TORED 0ROCEDURES #REATING A 3TORED 0ROCEDURE #ALLING A 3TORED 0ROCEDURE 3TORED 0ROCEDURE 6ARIABLES 3TATEMENT "LOCKS &UNCTIONS 2ETURNING 6ALUES VIA 0ARAMETERS #ONDITIONAL %XECUTION 2EPEATED %XECUTION /THER &LOW OF #ONTROL #ONSTRUCTS #URSOR "ASED 2EPETITION (ANDLING %RROR #ONDITIONS !DVANTAGES OF 3TORED 0ROCEDURES 3TORED 0ROCEDURE 0ERFORMANCE 3YSTEM $ElNED 3TORED 0ROCEDURES %XTERNAL 3TORED 0ROCEDURES 4RIGGERS !DVANTAGES AND $ISADVANTAGES OF 4RIGGERS 4RIGGERS IN 4RANSACT 31, 4RIGGERS IN )NFORMIX 30, 4RIGGERS IN /RACLE 0,31, /THER 4RIGGER #ONSIDERATIONS
#ONTENTSç
3TORED 0ROCEDURES &UNCTIONS 4RIGGERS AND THE 31, 3TANDARD 4HE 31,03- 3TORED 0ROCEDURES 3TANDARD 4HE 31,03- 4RIGGERS 3TANDARD 3UMMARY
31, AND $ATA 7AREHOUSING $ATA 7AREHOUSING #ONCEPTS #OMPONENTS OF A $ATA 7AREHOUSE 4HE %VOLUTION OF $ATA 7AREHOUSING $ATABASE !RCHITECTURE FOR 7AREHOUSING &ACT #UBES 3TAR 3CHEMAS -ULTILEVEL $IMENSIONS 31, %XTENSIONS FOR $ATA 7AREHOUSING 7AREHOUSE 0ERFORMANCE ,OAD 0ERFORMANCE 1UERY 0ERFORMANCE 3UMMARY
31, AND !PPLICATION 3ERVERS 31, AND 7EB 3ITES %ARLY )MPLEMENTATIONS !PPLICATION 3ERVERS AND 4HREE 4IER 7EB 3ITE !RCHITECTURES $ATABASE !CCESS FROM !PPLICATION 3ERVERS %*" 4YPES 3ESSION "EAN $ATABASE !CCESS %NTITY "EAN $ATABASE !CCESS %*" %NHANCEMENTS %*" %NHANCEMENTS /PEN 3OURCE !PPLICATION $EVELOPMENT !PPLICATION 3ERVER #ACHING 3UMMARY
31, .ETWORKING AND $ISTRIBUTED $ATABASES 4HE #HALLENGE OF $ISTRIBUTED $ATA -ANAGEMENT $ISTRIBUTING $ATA 0RACTICAL !PPROACHES 2EMOTE $ATABASE !CCESS 2EMOTE $ATA 4RANSPARENCY 4ABLE %XTRACTS 4ABLE 2EPLICATION 5PDATEABLE 2EPLICAS 2EPLICATION 4RADE /FFS 4YPICAL 2EPLICATION !RCHITECTURES $ISTRIBUTED $ATABASE !CCESS 2EMOTE 2EQUESTS 2EMOTE 4RANSACTIONS $ISTRIBUTED 4RANSACTIONS $ISTRIBUTED 2EQUESTS
XIX
XXç
31,ç4HEç#OMPLETEç2EFERENCE
4HE 4WO 0HASE #OMMIT 0ROTOCOL .ETWORK !PPLICATIONS AND $ATABASE !RCHITECTURE #LIENT3ERVER !PPLICATIONS AND $ATABASE !RCHITECTURE #LIENT3ERVER !PPLICATIONS WITH 3TORED 0ROCEDURES %NTERPRISE !PPLICATIONS AND $ATA #ACHING (IGH 6OLUME )NTERNET $ATA -ANAGEMENT 3UMMARY
31, AND /BJECTS /BJECT /RIENTED $ATABASES /BJECT /RIENTED $ATABASE #HARACTERISTICS 0ROS AND #ONS OF /BJECT /RIENTED $ATABASES /BJECTS AND THE $ATABASE -ARKET /BJECT 2ELATIONAL $ATABASES ,ARGE /BJECT 3UPPORT ,/"S IN THE 2ELATIONAL -ODEL 3PECIALIZED ,/" 0ROCESSING !BSTRACT 3TRUCTURED $ATA 4YPES $ElNING !BSTRACT $ATA 4YPES -ANIPULATING !BSTRACT $ATA 4YPES )NHERITANCE 4ABLE )NHERITANCE )MPLEMENTING /BJECT #LASSES 3ETS !RRAYS AND #OLLECTIONS $ElNING #OLLECTIONS 1UERYING #OLLECTION $ATA -ANIPULATING #OLLECTION $ATA #OLLECTIONS AND 3TORED 0ROCEDURES 5SER $ElNED $ATA 4YPES -ETHODS AND 3TORED 0ROCEDURES /BJECT 3UPPORT IN THE 31, 3TANDARD 3UMMARY
31, AND 8-, 7HAT )S 8-, 8-, "ASICS 8-, FOR $ATA 8-, AND 31, %LEMENTS VS !TTRIBUTES 5SING 8-, WITH $ATABASES 8-, /UTPUT 8-, )NPUT 8-, $ATA %XCHANGE 8-, 3TORAGE AND )NTEGRATION
#ONTENTSç
8-, AND -ETADATA $OCUMENT 4YPE $ElNITIONS $4$S 8-, 3CHEMA 8-, AND 1UERIES 81UERY #ONCEPTS 1UERY 0ROCESSING IN 81UERY 8-, $ATABASES 3UMMARY
3PECIALTY $ATABASES 6ERY ,OW ,ATENCY AND )N -EMORY $ATABASES !NATOMY OF AN )N -EMORY $ATABASE )N -EMORY $ATABASE )MPLEMENTATIONS #ACHING WITH )N -EMORY $ATABASES #OMPLEX %VENT 0ROCESSING AND 3TREAM $ATABASES #ONTINUOUS 1UERIES IN 3TREAM $ATABASES 3TREAM $ATABASE )MPLEMENTATIONS 3TREAM $ATABASE #OMPONENTS %MBEDDED $ATABASES %MBEDDED $ATABASE #HARACTERISTICS %MBEDDED $ATABASE )MPLEMENTATIONS -OBILE $ATABASES -OBILE $ATABASE 2OLES -OBILE $ATABASE )MPLEMENTATIONS 3UMMARY
4HE &UTURE OF 31, $ATABASE -ARKET 4RENDS %NTERPRISE $ATABASE -ARKET -ATURITY -ARKET $IVERSITY AND 3EGMENTATION 0ACKAGED %NTERPRISE !PPLICATIONS 3OFTWARE AS A 3ERVICE 3AA3 (ARDWARE 0ERFORMANCE 'AINS $ATABASE 3ERVER !PPLIANCES 31, 3TANDARDIZATION 31, IN THE .EXT $ECADE $ISTRIBUTED $ATABASES -ASSIVE $ATA 7AREHOUSING FOR "USINESS /PTIMIZATION 5LTRAHIGH 0ERFORMANCE $ATABASES )NTERNET AND .ETWORK 3ERVICES )NTEGRATION %MBEDDED $ATABASES /BJECT )NTEGRATION #LOUD "ASED AND (ORIZONTALLY 3CALABLE $ATABASES 3UMMARY
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31,ç4HEç#OMPLETEç2EFERENCE
õ 0ARTõ6))õ !PPENDIXES
! 4HE 3AMPLE $ATABASE
" $"-3 6ENDOR 0ROlLES
# 31, 3YNTAX 2EFERENCE $ATA $ElNITION 3TATEMENTS !CCESS #ONTROL 3TATEMENTS "ASIC $ATA -ANIPULATION 3TATEMENTS 4RANSACTION 0ROCESSING 3TATEMENTS #URSOR "ASED 3TATEMENTS 1UERY %XPRESSIONS 3EARCH #ONDITIONS %XPRESSIONS 3TATEMENT %LEMENTS 3IMPLE %LEMENTS
)NDEX
)NTRODUCTIONç
!CKNOWLEDGMENTS
3
PECIAL THANKS TO !NDY /PPEL OUR NEW COAUTHOR FOR THIS THIRD EDITION OF 31, 4HE #OMPLETE 2EFERENCE (IS IMPRESSIVE HIGH LEVEL MASTERY OF THE SUBJECT MATTER COUPLED WITH HIS METICULOUS ATTENTION TO DETAIL MADE THIS A BETTER BOOK AND WE ARE FORTUNATE TO HAVE HAD HIS INVOLVEMENT *IM AND 0AUL
)TS AN HONOR TO JOIN SUCH AN ACCOMPLISHED TEAM OF AUTHORS FOR THIS EDITION OF 31, 4HE #OMPLETE 2EFERENCE -Y THANKS FOR THE EXCELLENT SUPPORT OF THE ENTIRE -C'RAW (ILL TEAM FOR THEIR TIRELESS SUPPORT IN THIS EFFORT )N PARTICULAR ) WISH TO THANK TECHNICAL EDITOR !ARON $AVENPORT AND COPY EDITOR *AN *UE FOR THEIR PERSISTENCE AND ATTENTION TO DETAIL WHICH CONTRIBUTED SO MUCH TO THE OVERALL QUALITY OF THIS BOOK !NDY
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)NTRODUCTION
3
1, 4HE #OMPLETE 2EFERENCE 4HIRD %DITION PROVIDES A COMPREHENSIVE IN DEPTH TREATMENT OF THE 31, LANGUAGE FOR BOTH TECHNICAL AND NONTECHNICAL USERS PROGRAMMERS DATA PROCESSING PROFESSIONALS AND MANAGERS WHO WANT TO UNDERSTAND THE IMPACT OF 31, IN TODAYS COMPUTER INDUSTRY 4HIS BOOK OFFERS A CONCEPTUAL FRAMEWORK FOR UNDERSTANDING AND USING 31, DESCRIBES THE HISTORY OF 31, AND 31, STANDARDS AND EXPLAINS THE ROLE OF 31, IN VARIOUS COMPUTER INDUSTRY SEGMENTS FROM ENTERPRISE DATA PROCESSING TO DATA WAREHOUSING TO WEB SITE ARCHITECTURES 4HIS NEW EDITION CONTAINS NEW CHAPTERS SPECIALLY FOCUSED ON THE ROLE OF 31, IN APPLICATION SERVER ARCHITECTURES AND THE INTEGRATION OF 31, WITH 8-, AND OTHER OBJECT BASED TECHNOLOGIES 4HIS BOOK WILL SHOW YOU STEP BY STEP HOW TO USE 31, FEATURES WITH MANY ILLUSTRATIONS AND REALISTIC EXAMPLES TO CLARIFY 31, CONCEPTS 4HE BOOK ALSO COMPARES 31, PRODUCTS FROM LEADING $"-3 VENDORSDESCRIBING THEIR ADVANTAGES BENEFITS AND TRADE OFFSTO HELP YOU SELECT THE RIGHT PRODUCT FOR YOUR APPLICATION -OST OF THE EXAMPLES IN THIS BOOK ARE BASED ON THE SAMPLE DATABASE DESCRIBED IN !PPENDIX ! 4HE SAMPLE DATABASE CONTAINS DATA THAT SUPPORTS A SIMPLE ORDER PROCESSING APPLICATION FOR A SMALL DISTRIBUTION COMPANY !PPENDIX ! ALSO CONTAINS INSTRUCTIONS FOR DOWNLOADING THE 31, STATEMENTS REQUIRED TO CREATE AND POPULATE THE SAMPLE DATABASE TABLES IN A $"-3 OF YOU CHOICE SUCH AS /RACLE 31, 3ERVER -Y31, AND $" 4HIS ALLOWS YOU TO TRY THE EXAMPLES IN THE BOOK YOURSELF AND GAIN ACTUAL EXPERIENCE WRITING AND RUNNING 31, STATEMENTS )N SOME OF THE CHAPTERS THE SUBJECT MATTER IS EXPLORED AT TWO DIFFERENT LEVELSA FUNDAMENTAL DESCRIPTION OF THE TOPIC AND AN ADVANCED DISCUSSION INTENDED FOR COMPUTER PROFESSIONALS WHO NEED TO UNDERSTAND SOME OF THE INTERNALS BEHIND 31, 4HE MORE ADVANCED INFORMATION IS COVERED IN SECTIONS MARKED WITH AN ASTERISK 9OU DO NOT NEED TO READ THESE SECTIONS TO OBTAIN AN UNDERSTANDING OF WHAT 31, IS AND WHAT IT DOES
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31,ç4HEç#OMPLETEç2EFERENCE
(OWõ4HISõ"OOKõ)Sõ/RGANIZED 4HE BOOK IS DIVIDED INTO SIX PARTS THAT COVER VARIOUS ASPECTS OF THE 31, LANGUAGE s 0ART ) h!N /VERVIEW OF 31, v PROVIDES AN INTRODUCTION TO 31, AND A MARKET PERSPECTIVE OF ITS ROLE AS A DATABASE LANGUAGE )TS FOUR CHAPTERS DESCRIBE THE HISTORY OF 31, THE EVOLUTION OF 31, STANDARDS AND HOW 31, RELATES TO THE RELATIONAL DATA MODEL AND TO EARLIER DATABASE TECHNOLOGIES 0ART ) ALSO CONTAINS A QUICK TOUR OF 31, THAT BRIEFLY ILLUSTRATES ITS MOST IMPORTANT FEATURES AND PROVIDES YOU WITH AN OVERVIEW OF THE ENTIRE LANGUAGE EARLY IN THE BOOK s 0ART )) h2ETRIEVING $ATA v DESCRIBES THE FEATURES OF 31, THAT ALLOW YOU TO PERFORM DATABASE QUERIES 4HE FIRST CHAPTER IN THIS PART DESCRIBES THE BASIC STRUCTURE OF THE 31, LANGUAGE 4HE NEXT FOUR CHAPTERS START WITH THE SIMPLEST 31, QUERIES AND PROGRESSIVELY BUILD TO MORE COMPLEX QUERIES INCLUDING MULTITABLE QUERIES SUMMARY QUERIES AND QUERIES THAT USE SUBQUERIES s 0ART ))) h5PDATING $ATA v SHOWS HOW YOU CAN USE 31, TO ADD NEW DATA TO A DATABASE DELETE DATA FROM A DATABASE AND MODIFY EXISTING DATABASE DATA )T ALSO DESCRIBES THE DATABASE INTEGRITY ISSUES THAT ARISE WHEN DATA IS UPDATED AND HOW 31, ADDRESSES THESE ISSUES 4HE LAST OF THE THREE CHAPTERS IN THIS PART DISCUSSES THE 31, TRANSACTION CONCEPT AND 31, SUPPORT FOR MULTIUSER TRANSACTION PROCESSING s 0ART )6 h$ATABASE 3TRUCTURE v DEALS WITH CREATING AND ADMINISTERING A 31, BASED DATABASE )TS FOUR CHAPTERS TELL YOU HOW TO CREATE THE TABLES VIEWS AND INDEXES THAT FORM THE STRUCTURE OF A RELATIONAL DATABASE )T ALSO DESCRIBES THE 31, SECURITY SCHEME THAT PREVENTS UNAUTHORIZED ACCESS TO DATA AND THE 31, SYSTEM CATALOG THAT DESCRIBES THE STRUCTURE OF A DATABASE 4HIS PART ALSO DISCUSSES THE SIGNIFICANT DIFFERENCES BETWEEN THE DATABASE STRUCTURES SUPPORTED BY VARIOUS 31, BASED $"-3 PRODUCTS s 0ART 6 h0ROGRAMMING WITH 31, v DESCRIBES HOW APPLICATION PROGRAMS USE 31, FOR DATABASE ACCESS )T DISCUSSES THE EMBEDDED 31, SPECIFIED BY THE !.3) STANDARD AND USED BY )"- /RACLE )NGRES )NFORMIX AND MANY OTHER 31, BASED $"-3 PRODUCTS )T ALSO DESCRIBES THE DYNAMIC 31, INTERFACE THAT IS USED TO BUILD GENERAL PURPOSE DATABASE TABLES SUCH AS REPORT WRITERS AND DATABASE BROWSING PROGRAMS &INALLY THIS PART DESCRIBES THE POPULAR 31, !0)S INCLUDING /$"# THE )3/ STANDARD #ALL ,EVEL )NTERFACE AND *$"# THE STANDARD CALL LEVEL INTERFACE FOR *AVA AS WELL AS PROPRIETARY CALL LEVEL INTERFACES SUCH AS /RACLES /#) !0) s 0ART 6) h31, 4ODAY AND 4OMORROW v EXAMINES THE USE OF 31, IN SEVERAL OF TODAYS hHOTTESTv APPLICATION AREAS AND THE CURRENT STATE OF 31, BASED $"-3 PRODUCTS 4WO CHAPTERS DESCRIBE THE USE OF 31, STORED PROCEDURES AND TRIGGERS FOR ONLINE TRANSACTION PROCESSING AND THE CONTRASTING USE OF 31, FOR DATA WAREHOUSING &OUR ADDITIONAL CHAPTERS DESCRIBE 31, BASED DISTRIBUTED DATABASES THE INFLUENCE OF OBJECT TECHNOLOGIES ON 31, SPECIALTY DATABASES AND THE INTEGRATION OF 31, WITH 8-, TECHNOLOGIES &INALLY THE LAST CHAPTER EXPLORES THE FUTURE OF 31, AND SOME OF THE MOST IMPORTANT TRENDS IN 31, BASED DATA MANAGEMENT
)NTRODUCTIONç
#ONVENTIONSõ5SEDõINõ4HISõ"OOK 31, 4HE #OMPLETE 2EFERENCE 4HIRD %DITION DESCRIBES THE 31, FEATURES AND FUNCTIONS AVAILABLE IN THE MOST POPULAR 31, BASED $"-3 PRODUCTS AND THOSE DESCRIBED IN THE !.3))3/ 31, STANDARDS 7HENEVER POSSIBLE THE 31, STATEMENT SYNTAX DESCRIBED IN THIS BOOK AND USED IN THE EXAMPLES APPLIES TO ALL DIALECTS OF 31, 7HEN THE DIALECTS DIFFER THE DIFFERENCES ARE POINTED OUT IN THE TEXT AND THE EXAMPLES FOLLOW THE MOST COMMON PRACTICE )N THESE CASES YOU MAY HAVE TO MODIFY THE 31, STATEMENTS IN THE EXAMPLES SLIGHTLY TO SUIT YOUR PARTICULAR BRAND OF $"-3 4HROUGHOUT THE BOOK TECHNICAL TERMS APPEAR IN ITALICS THE FIRST TIME THEY ARE USED AND DEFINED 31, LANGUAGE ELEMENTS INCLUDING 31, KEYWORDS TABLE AND COLUMN NAMES AND SAMPLE 31, STATEMENTS APPEAR IN AN 500%2#!3% -/./30!#% FONT 31, !0) FUNCTION NAMES APPEAR IN A LOWERCASE MONOSPACE FONT 0ROGRAM LISTINGS ALSO APPEAR IN MONOSPACE FONT AND USE THE NORMAL CASE CONVENTIONS FOR THE PARTICULAR PROGRAMMING LANGUAGE UPPERCASE FOR #/"/, AND &/242!. LOWERCASE FOR # AND *AVA .OTE THAT THESE CONVENTIONS ARE USED SOLELY TO IMPROVE READABILITY MOST 31, IMPLEMENTATIONS WILL ACCEPT EITHER UPPERCASE OR LOWERCASE STATEMENTS -ANY OF THE 31, EXAMPLES INCLUDE QUERY RESULTS WHICH APPEAR IMMEDIATELY FOLLOWING THE 31, STATEMENT AS THEY WOULD IN AN INTERACTIVE 31, SESSION )N SOME CASES LONG QUERY RESULTS ARE TRUNCATED AFTER A FEW ROWS THIS IS INDICATED BY A VERTICAL ELLIPSIS x FOLLOWING THE LAST ROW OF QUERY RESULTS
7HYõ4HISõ"OOKõ)SõFORõ9OU 31, 4HE #OMPLETE 2EFERENCE 4HIRD %DITION IS THE RIGHT BOOK FOR ANYONE WHO WANTS TO UNDERSTAND AND LEARN 31, INCLUDING DATABASE USERS DATA PROCESSING PROFESSIONALS AND ARCHITECTS PROGRAMMERS STUDENTS AND MANAGERS )T DESCRIBESIN SIMPLE UNDERSTANDABLE LANGUAGE LIBERALLY ILLUSTRATED WITH FIGURES AND EXAMPLESWHAT 31, IS WHY IT IS IMPORTANT AND HOW YOU USE IT 4HIS BOOK IS NOT SPECIFIC TO ONE PARTICULAR BRAND OR DIALECT OF 31, 2ATHER IT DESCRIBES THE STANDARD CENTRAL CORE OF THE 31, LANGUAGE AND THEN GOES ON TO DESCRIBE THE DIFFERENCES AMONG THE MOST POPULAR 31, PRODUCTS INCLUDING /RACLE -ICROSOFT 31, 3ERVER )"-S $" 5NIVERSAL $ATABASE AND )NFORMIX 3YBASE AND -Y31, )T ALSO EXPLAINS THE IMPORTANCE OF 31, BASED STANDARDS SUCH AS /$"# AND *$"# AND THE !.3) )3/ STANDARDS FOR 31, AND 31, RELATED TECHNOLOGIES 4HIS THIRD EDITION CONTAINS NEW CHAPTERS AND SECTIONS THAT COVER THE LATEST 31, INNOVATIONS IN THE AREAS OF OBJECT RELATIONAL TECHNOLOGIES 8-, AND APPLICATION SERVER ARCHITECTURES )F YOU ARE NEW TO 31, THIS BOOK OFFERS COMPREHENSIVE STEP BY STEP TREATMENT OF THE LANGUAGE BUILDING FROM SIMPLE QUERIES TO MORE ADVANCED CONCEPTS 4HE STRUCTURE OF THE BOOK WILL ALLOW YOU TO QUICKLY START USING 31, BUT THE BOOK WILL CONTINUE TO BE VALUABLE AS YOU BEGIN TO USE THE MORE COMPLEX FEATURES OF THE LANGUAGE 9OU CAN CREATE THE SAMPLE DATABASE USING AN 31, SCRIPT AVAILABLE ON THE -C'RAW (ILL WEBSITE SEE !PPENDIX ! AND USE IT TO TRY OUT THE EXAMPLES AND BUILD YOUR 31, SKILLS )F YOU ARE A DATA PROCESSING PROFESSIONAL ARCHITECT OR MANAGER THIS BOOK WILL GIVE YOU A PERSPECTIVE ON THE IMPACT THAT 31, IS HAVING ACROSS THE INFORMATION TECHNOLOGY INDUSTRYFROM PERSONAL COMPUTERS TO MAINFRAMES TO DATA WAREHOUSING TO )NTERNET WEB SITES AND )NTERNET BASED DISTRIBUTED APPLICATIONS 4HE EARLY CHAPTERS DESCRIBE THE HISTORY OF 31, ITS ROLE IN THE MARKET AND ITS EVOLUTION FROM EARLIER DATABASE TECHNOLOGIES ,ATER CHAPTERS DESCRIBE THE FUTURE OF 31, AND THE DEVELOPMENT OF NEW DATABASE TECHNOLOGIES SUCH AS DISTRIBUTED DATABASES OBJECT ORIENTED EXTENSIONS TO 31, BUSINESS INTELLIGENCE DATABASES AND DATABASE8-, INTEGRATION
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31,ç4HEç#OMPLETEç2EFERENCE
)F YOU ARE A PROGRAMMER THIS BOOK OFFERS A VERY COMPLETE TREATMENT OF PROGRAMMING WITH 31, 5NLIKE THE REFERENCE MANUALS OF MANY $"-3 PRODUCTS IT OFFERS A CONCEPTUAL FRAMEWORK FOR 31, PROGRAMMING EXPLAINING THE WHY AS WELL AS THE HOW OF DEVELOPING A 31, BASED APPLICATION )T CONTRASTS THE 31, PROGRAMMING INTERFACES OFFERED BY ALL OF THE LEADING 31, PRODUCTS INCLUDING EMBEDDED 31, DYNAMIC 31, /$"# *$"# AND PROPRIETARY !0)S SUCH AS THE /RACLE #ALL )NTERFACE 4HE DESCRIPTION AND COMPARISON OF PROGRAMMING TECHNIQUES PROVIDES A PERSPECTIVE NOT FOUND IN ANY OTHER BOOK )F YOU ARE SELECTING A $"-3 PRODUCT THIS BOOK OFFERS A COMPARISON OF THE 31, FEATURES ADVANTAGES AND BENEFITS OFFERED BY THE VARIOUS $"-3 VENDORS 4HE DIFFERENCES BETWEEN THE LEADING $"-3 PRODUCTS ARE EXPLAINED NOT ONLY IN TECHNICAL TERMS BUT ALSO IN TERMS OF THEIR IMPACT ON APPLICATIONS AND THEIR EVOLVING COMPETITIVE POSITION IN THE MARKETPLACE 4HE hSAMPLE DATABASEv CAN BE USED TO TRY THESE FEATURES IN A PROTOTYPE OF YOUR OWN APPLICATION )N SHORT BOTH TECHNICAL AND NONTECHNICAL USERS CAN BENEFIT FROM THIS BOOK )T IS THE MOST COMPREHENSIVE SOURCE OF INFORMATION AVAILABLE ABOUT THE 31, LANGUAGE 31, FEATURES AND BENEFITS POPULAR 31, BASED PRODUCTS THE HISTORY OF 31, AND THE IMPACT OF 31, ON THE FUTURE DIRECTION OF THE INFORMATION TECHNOLOGY INDUSTRY
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HE FIRST FOUR CHAPTERS OF THIS BOOK PROVIDE A PERSPECTIVE AND A QUICK INTRODUCTION TO 31, #HAPTER DESCRIBES WHAT 31, IS AND EXPLAINS ITS MAJOR FEATURES AND BENEFITS )N #HAPTER A QUICK TOUR OF 31, SHOWS YOU MANY OF ITS CAPABILITIES WITH SIMPLE RAPID FIRE EXAMPLES #HAPTER OFFERS A MARKET PERSPECTIVE OF 31, BY TRACING ITS HISTORY DESCRIBING THE 31, STANDARDS AND THE MAJOR VENDORS OF 31, BASED PRODUCTS AND BY IDENTIFYING THE REASONS FOR 31,S PROMINENCE TODAY #HAPTER DESCRIBES THE RELATIONAL DATA MODEL UPON WHICH 31, IS BASED AND COMPARES IT WITH EARLIER DATA MODELS
#(!04%2ç )NTRODUCTION $)"15&3 ! 1UICK 4OUR OF 31, $)"15&3 31, IN 0ERSPECTIVE $)"15&3 2ELATIONAL $ATABASES
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#(!04%2
)NTRODUCTION
4
HE 31, LANGUAGE AND RELATIONAL DATABASE SYSTEMS BASED ON IT CONSTITUTE ONE OF THE MOST IMPORTANT FOUNDATION TECHNOLOGIES IN THE COMPUTER INDUSTRY /VER THE LAST THREE DECADES 31, HAS GROWN FROM ITS FIRST COMMERCIAL USE INTO A COMPUTER PRODUCT AND SERVICES MARKET SEGMENT WORTH TENS OF BILLIONS OF DOLLARS PER YEAR AND 31, STANDS TODAY AS THE STANDARD COMPUTER DATABASE LANGUAGE (UNDREDS OF DATABASE PRODUCTS NOW SUPPORT 31, RUNNING ON COMPUTER SYSTEMS FROM MAINFRAMES TO PERSONAL COMPUTERS ! 31, BASED DATABASE MAY EVEN BE EMBEDDED IN YOUR MOBILE PHONE OR 0$! OR IN THE ENTERTAINMENT SYSTEM OF YOUR CAR !N OFFICIAL INTERNATIONAL 31, STANDARD HAS BEEN ADOPTED AND EXPANDED SEVERAL TIMES %VERY MAJOR ENTERPRISE SOFTWARE PRODUCT RELIES ON 31, FOR ITS DATA MANAGEMENT AND 31, IS AT THE CORE OF THE FLAGSHIP DATABASE PRODUCTS FROM -ICROSOFT /RACLE AND )"- THREE OF THE LARGEST SOFTWARE COMPANIES IN THE WORLD 31, IS ALSO AT THE HEART OF OPEN SOURCE DATABASE PRODUCTS SUCH AS -Y31, AND 0OSTGRES THAT ARE HELPING TO FUEL THE POPULARITY OF ,INUX AND THE OPEN SOURCE MOVEMENT &ROM ITS OBSCURE BEGINNINGS AS AN )"- RESEARCH PROJECT 31, HAS GROWN TO BECOME BOTH AN IMPORTANT PIECE OF INFORMATION TECHNOLOGY AND A POWERFUL MARKET FORCE 7HAT EXACTLY IS 31, 7HY IS IT IMPORTANT 7HAT CAN IT DO AND HOW DOES IT WORK )F 31, IS REALLY A STANDARD WHY DO WE HAVE SO MANY DIFFERENT VERSIONS AND DIALECTS (OW DO POPULAR 31, PRODUCTS LIKE 31, 3ERVER /RACLE -Y31, 3YBASE AND $" COMPARE (OW DOES 31, RELATE TO -ICROSOFT STANDARDS SUCH AS /$"# AND .%4 (OW DOES *$"# LINK 31, TO THE WORLD OF *AVA AND OBJECT TECHNOLOGY 7HAT ROLE DOES IT PLAY IN THE 3ERVICE /RIENTED !RCHITECTURE 3/! AND WEB SERVICES BEING EMBRACED BY ENTERPRISE )4 ORGANIZATIONS $OES 31, REALLY SCALE FROM MAINFRAMES TO HANDHELD DEVICES (AS IT REALLY DELIVERED THE PERFORMANCE NEEDED FOR HIGH VOLUME TRANSACTION PROCESSING (OW WILL 31, IMPACT THE WAY YOU USE COMPUTERS AND HOW CAN YOU GET THE MOST OUT OF THIS IMPORTANT DATA MANAGEMENT TOOL 4HIS BOOK ANSWERS THOSE QUESTIONS BY GIVING YOU A COMPLETE PERSPECTIVE AND A SOLID WORKING KNOWLEDGE OF 31,
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4HEõ31,õ,ANGUAGE 31, IS A TOOL FOR ORGANIZING MANAGING AND RETRIEVING DATA STORED BY A COMPUTER DATABASE 4HE ORIGINAL NAME GIVEN IT BY )"- WAS 3TRUCTURED %NGLISH 1UERY ,ANGUAGE SHORTENED TO THE ACRONYM 3%15%, 7HEN )"- DISCOVERED THAT 3%15%, WAS A TRADEMARK OWNED BY THE (AWKER 3IDDELEY !IRCRAFT #OMPANY OF THE 5NITED +INGDOM THEY SHORTENED THE ACRONYM TO 31, 4HE WORD h%NGLISHv WAS THEN DROPPED FROM THE SPELLED OUT NAME TO MATCH THE NEW ACRONYM 4O THIS DAY YOU WILL HEAR THE ACRONYM 31, PRONOUNCED AS EITHER A WORD hSEQUELv OR AS A STRING OF LETTERS h3 1 ,v AND WHILE THE LATTER IS GENERALLY PREFERRED BOTH ARE CONSIDERED CORRECT !S THE NAME IMPLIES 31, IS A COMPUTER LANGUAGE THAT YOU USE TO INTERACT WITH A DATABASE )N FACT 31, WORKS WITH ONE SPECIFIC TYPE OF DATABASE CALLED A RELATIONAL DATABASE WHICH HAS BECOME THE MAINSTREAM WAY TO ORGANIZE DATA ACROSS A VERY BROAD RANGE OF COMPUTER APPLICATIONS &IGURE SHOWS HOW 31, WORKS 4HE COMPUTER SYSTEM IN THE FIGURE HAS A DATABASE THAT STORES IMPORTANT INFORMATION )F THE COMPUTER SYSTEM IS IN A BUSINESS THE DATABASE MIGHT STORE INVENTORY PRODUCTION SALES OR PAYROLL DATA /N A PERSONAL COMPUTER THE DATABASE MIGHT STORE DATA ABOUT THE CHECKS YOU HAVE WRITTEN LISTS OF PEOPLE AND THEIR PHONE NUMBERS OR DATA EXTRACTED FROM A LARGER COMPUTER SYSTEM 4HE COMPUTER PROGRAM THAT CONTROLS THE DATABASE IS CALLED A DATABASE MANAGEMENT SYSTEM $"-3 7HEN YOU NEED TO RETRIEVE DATA FROM A DATABASE YOU USE THE 31, TO MAKE THE REQUEST 4HE $"-3 PROCESSES THE 31, REQUEST RETRIEVES THE REQUESTED DATA AND RETURNS IT TO YOU 4HIS PROCESS OF REQUESTING DATA FROM A DATABASE AND RECEIVING THE RESULTS IS CALLED A DATABASE QUERYHENCE THE NAME 3TRUCTURED 1UERY ,ANGUAGE h3TRUCTURED 1UERY ,ANGUAGEv IS ACTUALLY SOMEWHAT OF A MISNOMER &IRST OF ALL 31, IS FAR MORE THAN A QUERY TOOL ALTHOUGH THAT WAS ITS ORIGINAL PURPOSE AND RETRIEVING DATA IS STILL ONE OF ITS MOST IMPORTANT FUNCTIONS 31, IS USED TO CONTROL ALL OF THE FUNCTIONS THAT A $"-3 PROVIDES FOR ITS USERS INCLUDING
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s $ATA DEFINITION 31, LETS A USER DEFINE THE STRUCTURE AND ORGANIZATION OF THE STORED DATA AND RELATIONSHIPS AMONG THE STORED DATA ITEMS
s $ATA MANIPULATION 31, ALLOWS A USER OR AN APPLICATION PROGRAM TO UPDATE THE DATABASE BY ADDING NEW DATA REMOVING OLD DATA AND MODIFYING PREVIOUSLY STORED DATA s !CCESS CONTROL 31, CAN BE USED TO RESTRICT A USERS ABILITY TO RETRIEVE ADD AND MODIFY DATA PROTECTING STORED DATA AGAINST UNAUTHORIZED ACCESS s $ATA SHARING 31, IS USED TO COORDINATE DATA SHARING BY CONCURRENT USERS ENSURING THAT CHANGES MADE BY ONE USER DO NOT INADVERTENTLY WIPE OUT CHANGES MADE AT NEARLY THE SAME TIME BY ANOTHER USER s $ATA INTEGRITY 31, DEFINES INTEGRITY CONSTRAINTS IN THE DATABASE PROTECTING IT FROM CORRUPTION DUE TO INCONSISTENT UPDATES OR SYSTEM FAILURES 31, IS THUS A COMPREHENSIVE LANGUAGE FOR CONTROLLING AND INTERACTING WITH A DATABASE MANAGEMENT SYSTEM 3ECOND 31, IS NOT REALLY A COMPLETE COMPUTER LANGUAGE LIKE #/"/, # # OR *AVA )NSTEAD 31, IS A DATABASE SUBLANGUAGE CONSISTING OF ABOUT STATEMENTS SPECIALIZED FOR DATABASE MANAGEMENT TASKS 4HESE 31, STATEMENTS CAN BE EMBEDDED INTO ANOTHER LANGUAGE SUCH AS #/"/, OR # TO EXTEND THAT LANGUAGE FOR USE IN DATABASE ACCESS !LTERNATIVELY THE STATEMENTS CAN BE EXPLICITLY SENT TO A DATABASE MANAGEMENT SYSTEM FOR PROCESSING VIA A CALL LEVEL INTERFACE FROM A LANGUAGE SUCH AS # # OR *AVA OR VIA MESSAGES SENT OVER A COMPUTER NETWORK 31, ALSO DIFFERS FROM OTHER COMPUTER LANGUAGES BECAUSE IT DESCRIBES WHAT THE USER WANTS THE COMPUTER TO DO RATHER THAN HOW THE COMPUTER SHOULD DO IT )N MORE TECHNICAL TERMS 31, IS A DECLARATIVE OR DESCRIPTIVE LANGUAGE RATHER THAN A PROCEDURAL ONE 31, CONTAINS NO )& STATEMENT FOR TESTING CONDITIONS AND NO '/4/ $/ OR &/2 STATEMENTS FOR PROGRAM FLOW CONTROL 2ATHER 31, STATEMENTS DESCRIBE HOW A COLLECTION OF DATA IS TO BE ORGANIZED OR WHAT DATA IS TO BE RETRIEVED OR ADDED TO THE DATABASE 4HE SEQUENCE OF STEPS TO DO THOSE TASKS IS LEFT FOR THE $"-3 TO DETERMINE &INALLY 31, IS NOT A PARTICULARLY STRUCTURED LANGUAGE ESPECIALLY WHEN COMPARED WITH HIGHLY STRUCTURED LANGUAGES SUCH AS # 0ASCAL OR *AVA )NSTEAD 31, STATEMENTS RESEMBLE %NGLISH SENTENCES COMPLETE WITH hNOISE WORDSv THAT DONT ADD TO THE MEANING OF THE STATEMENT BUT MAKE IT READ MORE NATURALLY 4HE 31, HAS QUITE A FEW INCONSISTENCIES AND ALSO SOME SPECIAL RULES TO PREVENT YOU FROM CONSTRUCTING 31, STATEMENTS THAT LOOK PERFECTLY LEGAL BUT THAT DONT MAKE SENSE $ESPITE THE INACCURACY OF ITS NAME 31, HAS EMERGED AS THE STANDARD LANGUAGE FOR USING RELATIONAL DATABASES 31, IS BOTH A POWERFUL LANGUAGE AND ONE THAT IS RELATIVELY EASY TO LEARN 4HE QUICK TOUR OF 31, IN #HAPTER WILL GIVE YOU A GOOD OVERVIEW OF THE LANGUAGE AND ITS CAPABILITIES
0!24ç)
s $ATA RETRIEVAL 31, ALLOWS A USER OR AN APPLICATION PROGRAM TO RETRIEVE STORED DATA FROM THE DATABASE AND USE IT
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4HEõ2OLEõOFõ31, 31, IS NOT ITSELF A DATABASE MANAGEMENT SYSTEM NOR IS IT A STAND ALONE PRODUCT 9OU CANNOT GO TO A COMPUTER RETAILER OR A WEB SITE SELLING COMPUTER SOFTWARE AND BUY 31, )NSTEAD 31, IS AN INTEGRAL PART OF A DATABASE MANAGEMENT SYSTEM A LANGUAGE AND A TOOL FOR COMMUNICATING WITH THE $"-3 &IGURE SHOWS SOME OF THE COMPONENTS OF A TYPICAL $"-3 AND HOW 31, LINKS THEM TOGETHER 4HE DATABASE ENGINE IS THE HEART OF THE $"-3 RESPONSIBLE FOR ACTUALLY STRUCTURING STORING AND RETRIEVING THE DATA IN THE DATABASE )T ACCEPTS 31, REQUESTS FROM OTHER $"-3 COMPONENTS SUCH AS A FORMS FACILITY REPORT WRITER OR INTERACTIVE QUERY FACILITY FROM USER WRITTEN APPLICATION PROGRAMS AND EVEN FROM OTHER COMPUTER SYSTEMS !S THE FIGURE SHOWS 31, PLAYS MANY DIFFERENT ROLES s 31, IS AN INTERACTIVE QUERY LANGUAGE 5SERS TYPE 31, COMMANDS INTO AN INTERACTIVE 31, PROGRAM TO RETRIEVE DATA AND DISPLAY IT ON THE SCREEN PROVIDING A CONVENIENT EASY TO USE TOOL FOR AD HOC DATABASE QUERIES s 31, IS A DATABASE PROGRAMMING LANGUAGE 0ROGRAMMERS EMBED 31, COMMANDS INTO THEIR APPLICATION PROGRAMS TO ACCESS THE DATA IN A DATABASE "OTH USER WRITTEN PROGRAMS AND DATABASE UTILITY PROGRAMS SUCH AS REPORT WRITERS AND DATA ENTRY TOOLS USE THIS TECHNIQUE FOR DATABASE ACCESS
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)NTRODUCTIONç
s 31, IS A CLIENTSERVER LANGUAGE 0ERSONAL COMPUTER PROGRAMS USE 31, TO COMMUNICATE OVER A NETWORK WITH DATABASE SERVERS THAT STORE SHARED DATA 4HIS CLIENTSERVER ARCHITECTURE IS USED BY MANY POPULAR ENTERPRISE CLASS APPLICATIONS s 31, IS AN )NTERNET DATA ACCESS LANGUAGE )NTERNET WEB SERVERS THAT INTERACT WITH CORPORATE DATA AND )NTERNET APPLICATION SERVERS ALL USE 31, AS A STANDARD LANGUAGE FOR ACCESSING CORPORATE DATABASES OFTEN BY EMBEDDING 31, DATABASE ACCESS WITHIN POPULAR SCRIPTING LANGUAGES LIKE 0(0 OR 0ERL s 31, IS A DISTRIBUTED DATABASE LANGUAGE $ISTRIBUTED DATABASE MANAGEMENT SYSTEMS USE 31, TO HELP DISTRIBUTE DATA ACROSS MANY CONNECTED COMPUTER SYSTEMS 4HE $"-3 SOFTWARE ON EACH SYSTEM USES 31, TO COMMUNICATE WITH THE OTHER SYSTEMS SENDING REQUESTS FOR DATA ACCESS s 31, IS A DATABASE GATEWAY LANGUAGE )N A COMPUTER NETWORK WITH A MIX OF DIFFERENT $"-3 PRODUCTS 31, IS OFTEN USED IN A GATEWAY THAT ALLOWS ONE BRAND OF $"-3 TO COMMUNICATE WITH ANOTHER BRAND 31, HAS THUS EMERGED AS A USEFUL POWERFUL TOOL FOR LINKING PEOPLE COMPUTER PROGRAMS AND COMPUTER SYSTEMS TO THE DATA STORED IN A RELATIONAL DATABASE
31,õ3UCCESSõ&ACTORS )N HISTORICAL TERMS 31, HAS BEEN AN EXTRAORDINARILY SUCCESSFUL INFORMATION TECHNOLOGY 4HINK ABOUT THE COMPUTER MARKET IN THE MID S WHEN 31, FIRST STARTED TO BECOME IMPORTANT -AINFRAMES AND MINICOMPUTERS DOMINATED CORPORATE COMPUTING 4HE )"- PERSONAL COMPUTER HAD BEEN INTRODUCED ONLY A FEW YEARS BEFORE AND THE -3 $/3 COMMAND LINE WAS ITS USER INTERFACE )"-S MAINFRAME OPERATING SYSTEMS AND MINICOMPUTER OPERATING SYSTEMS FROM $IGITAL %QUIPMENT $ATA 'ENERAL (EWLETT 0ACKARD AND OTHERS DOMINATED BUSINESS COMPUTING 0ROPRIETARY NETWORKING SCHEMES LIKE )"-S 3.! OR $IGITAL %QUIPMENTS $%#NET LINKED COMPUTERS TOGETHER 4HE )NTERNET WAS STILL A TOOL FOR COLLABORATION AMONG RESEARCH LABS AND THE 7ORLD 7IDE 7EB HAD NOT YET APPEARED ON THE SCENE #/"/, # AND 0ASCAL WERE DOMINANT COMPUTER LANGUAGES OBJECT ORIENTED PROGRAMMING WAS ONLY BEGINNING TO EMERGE AND *AVA HAD NOT BEEN INVENTED !CROSS ALL OF THESE AREAS OF COMPUTER TECHNOLOGYFROM COMPUTER HARDWARE TO OPERATING SYSTEMS TO NETWORKING TO LANGUAGESTHE IMPORTANT KEY TECHNOLOGIES OF THE MID S HAVE FADED OR BECOME OBSOLETE REPLACED BY SIGNIFICANT NEW ONES "UT IN THE WORLD OF DATA MANAGEMENT THE RELATIONAL DATABASE AND 31, CONTINUE TO DOMINATE THE LANDSCAPE 4HEY HAVE EXPANDED OVER THE YEARS TO SUPPORT NEW HARDWARE OPERATING SYSTEMS NETWORKS AND LANGUAGES BUT DESPITE MANY ATTEMPTS TO DETHRONE THEM THE CORE RELATIONAL MODEL AND THE 31, HAVE THRIVED AND REMAIN THE DOMINANT FORCES IN DATA MANAGEMENT (ERE ARE SOME OF THE MAJOR FEATURES AND MARKET FORCES THAT HAVE CONTRIBUTED TO THIS SUCCESS OVER THE PAST YEARS s 6ENDOR INDEPENDENCE s 0ORTABILITY ACROSS COMPUTER SYSTEMS
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s 31, IS A DATABASE ADMINISTRATION LANGUAGE 4HE DATABASE ADMINISTRATOR RESPONSIBLE FOR MANAGING A MINICOMPUTER OR MAINFRAME DATABASE USES 31, TO DEFINE THE DATABASE STRUCTURE AND TO CONTROL ACCESS TO THE STORED DATA
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!Nç/VERVIEWçOFç31,
s /FFICIAL 31, STANDARDS s %ARLY )"- COMMITMENT s -ICROSOFT SUPPORT s 2ELATIONAL FOUNDATION s (IGH LEVEL %NGLISH LIKE STRUCTURE s )NTERACTIVE AD HOC QUERIES s 0ROGRAMMATIC DATABASE ACCESS s -ULTIPLE VIEWS OF DATA s #OMPLETE DATABASE LANGUAGE s $YNAMIC DATA DEFINITION s #LIENT3ERVER ARCHITECTURE s %NTERPRISE APPLICATION SUPPORT s %XTENSIBILITY AND OBJECT TECHNOLOGY s )NTERNET DATABASE ACCESS s *AVA INTEGRATION *$"# s /PEN SOURCE SUPPORT s )NDUSTRY INFRASTRUCTURE 4HE SECTIONS THAT FOLLOW BRIEFLY DESCRIBE EACH OF THESE AND HOW THEY CONTRIBUTED TO 31,S SUCCESS
6ENDORõ)NDEPENDENCE 31, IS OFFERED BY ALL OF THE LEADING $"-3 VENDORS AND NO NEW DATABASE PRODUCT OVER THE LAST DECADE HAS BEEN HIGHLY SUCCESSFUL WITHOUT 31, SUPPORT ! 31, BASED DATABASE AND THE PROGRAMS THAT USE IT CAN BE MOVED FROM ONE $"-3 TO ANOTHER VENDORS $"-3 WITH MINIMAL CONVERSION EFFORT AND LITTLE RETRAINING OF PERSONNEL $ATABASE TOOLS SUCH AS QUERY TOOLS REPORT WRITERS AND APPLICATION GENERATORS WORK WITH MANY DIFFERENT BRANDS OF 31, DATABASES 4HE VENDOR INDEPENDENCE THUS PROVIDED BY 31, WAS ONE OF THE MOST IMPORTANT REASONS FOR ITS EARLY POPULARITY AND REMAINS AN IMPORTANT FEATURE TODAY
0ORTABILITYõ!CROSSõ#OMPUTERõ3YSTEMS 31, BASED DATABASE PRODUCTS RUN ON COMPUTER SYSTEMS RANGING FROM MAINFRAMES AND MIDRANGE SYSTEMS TO PERSONAL COMPUTERS WORKSTATIONS A WIDE RANGE OF SPECIALIZED SERVER COMPUTERS AND EVEN HANDHELD DEVICES 4HEY OPERATE ON STAND ALONE COMPUTER SYSTEMS IN DEPARTMENTAL LOCAL AREA NETWORKS AND IN ENTERPRISEWIDE OR )NTERNETWIDE NETWORKS 31, BASED APPLICATIONS THAT BEGIN ON SINGLE USER OR DEPARTMENTAL SERVER SYSTEMS CAN BE MOVED TO LARGER SERVER SYSTEMS AS THEY GROW $ATA FROM CORPORATE 31, BASED DATABASES CAN BE EXTRACTED AND DOWNLOADED INTO DEPARTMENTAL OR PERSONAL DATABASES &INALLY ECONOMICAL PERSONAL COMPUTERS CAN BE USED TO TEST A PROTOTYPE OF A 31, BASED DATABASE APPLICATION BEFORE MOVING IT TO AN EXPENSIVE MULTIUSER SYSTEM
#HAPTERçç
)NTRODUCTIONç
/FFICIALõ31,õ3TANDARDS
%ARLYõ)"-õ#OMMITMENT 31, WAS ORIGINALLY INVENTED BY )"- RESEARCHERS AND FAIRLY QUICKLY BECAME A STRATEGIC PRODUCT FOR )"- BASED ON ITS FLAGSHIP $" DATABASE 31, SUPPORT IS AVAILABLE ON ALL MAJOR )"- PRODUCT FAMILIES FROM PERSONAL COMPUTERS THROUGH MIDRANGE SYSTEMS AND 5.)8 BASED SERVERS TO )"- MAINFRAMES )"-S INITIAL WORK PROVIDED A CLEAR SIGNAL OF )"-S DIRECTION FOR OTHER DATABASE AND SYSTEM VENDORS TO FOLLOW EARLY IN THE DEVELOPMENT OF 31, AND RELATIONAL DATABASES ,ATER )"-S COMMITMENT AND BROAD SUPPORT SPEEDED THE MARKET ACCEPTANCE OF 31, )N THE S )"- WAS THE DOMINANT FORCE IN BUSINESS COMPUTING SO ITS EARLY AND SUSTAINED SUPPORT AS THE INVENTOR AND CHAMPION OF 31, ENSURED ITS EARLY IMPORTANCE
-ICROSOFTõ3UPPORT -ICROSOFT HAS LONG CONSIDERED DATABASE ACCESS A KEY PART OF ITS 7INDOWS PERSONAL COMPUTER SOFTWARE ARCHITECTURE "OTH DESKTOP AND SERVER VERSIONS OF 7INDOWS PROVIDE STANDARDIZED RELATIONAL DATABASE ACCESS THROUGH /PEN $ATABASE #ONNECTIVITY /$"# A 31, BASED CALL LEVEL !0) APPLICATION PROGRAMMING INTERFACE ,EADING 7INDOWS SOFTWARE APPLICATIONS SPREADSHEETS WORD PROCESSORS DATABASES ETC FROM -ICROSOFT AND OTHER VENDORS SUPPORT /$"# AND ALL LEADING 31, DATABASES PROVIDE /$"# ACCESS -ICROSOFT HAS ENHANCED /$"# SUPPORT WITH HIGHER LEVEL MORE OBJECT ORIENTED DATABASE ACCESS LAYERS OVER THE YEARS INCLUDING DATA MANAGEMENT SUPPORT IN .%4 TODAY "UT THESE NEW TECHNOLOGIES COULD ALWAYS INTERACT WITH RELATIONAL DATABASES THROUGH THE /$"#31, LAYERS BELOW 7HEN -ICROSOFT BEGAN ITS EFFORT IN THE LATE S TO MAKE 7INDOWS A VIABLE SERVER OPERATING SYSTEM IT INTRODUCED 31, 3ERVER AS ITS OWN 31, BASED OFFERING 31, 3ERVER CONTINUES TODAY AS A FLAGSHIP -ICROSOFT PRODUCT AND AS A KEY COMPONENT OF THE -ICROSOFT .%4 ARCHITECTURE FOR WEB SERVICES
2ELATIONALõ&OUNDATION 31, IS A LANGUAGE FOR RELATIONAL DATABASES AND IT HAS BECOME POPULAR ALONG WITH THE RELATIONAL DATABASE MODEL 4HE TABULAR ROWCOLUMN STRUCTURE OF A RELATIONAL DATABASE IS INTUITIVE TO USERS KEEPING THE 31, SIMPLE AND EASY TO UNDERSTAND 4HE RELATIONAL MODEL ALSO HAS A STRONG THEORETICAL FOUNDATION THAT HAS GUIDED THE EVOLUTION AND IMPLEMENTATION OF RELATIONAL DATABASES 2IDING A WAVE OF ACCEPTANCE BROUGHT ABOUT BY THE SUCCESS OF THE RELATIONAL MODEL 31, HAS BECOME THE DATABASE LANGUAGE FOR RELATIONAL DATABASES
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!N OFFICIAL STANDARD FOR 31, WAS INITIALLY PUBLISHED BY THE !MERICAN .ATIONAL 3TANDARDS )NSTITUTE !.3) AND THE )NTERNATIONAL 3TANDARDS /RGANIZATION )3/ IN AND WAS EXPANDED IN AND AGAIN IN AND 31, IS ALSO A 53 &EDERAL )NFORMATION 0ROCESSING 3TANDARD &)03 MAKING IT A KEY REQUIREMENT FOR LARGE GOVERNMENT COMPUTER CONTRACTS /VER THE YEARS OTHER INTERNATIONAL GOVERNMENT AND VENDOR GROUPS HAVE PIONEERED THE STANDARDIZATION OF NEW 31, CAPABILITIES SUCH AS CALL LEVEL INTERFACES OR OBJECT BASED EXTENSIONS -ANY OF THESE NEW INITIATIVES HAVE BEEN INCORPORATED INTO THE !.3))3/ STANDARD OVER TIME 4HE EVOLVING STANDARDS SERVE AS AN OFFICIAL STAMP OF APPROVAL FOR 31, AND HAVE SPEEDED ITS MARKET ACCEPTANCE
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!Nç/VERVIEWçOFç31,
(IGH ,EVEL õ%NGLISH ,IKEõ3TRUCTURE 31, STATEMENTS LOOK LIKE SIMPLE %NGLISH SENTENCES MAKING 31, RELATIVELY EASY TO LEARN AND UNDERSTAND 4HIS IS IN PART BECAUSE 31, STATEMENTS DESCRIBE THE DATA TO BE RETRIEVED RATHER THAN SPECIFYING HOW TO FIND THE DATA 4ABLES AND COLUMNS IN A 31, DATABASE CAN HAVE LONG DESCRIPTIVE NAMES !S A RESULT MOST 31, STATEMENTS hSAY WHAT THEY MEANv AND CAN BE READ AS CLEAR NATURAL SENTENCES
)NTERACTIVE õ!Dõ(OCõ1UERIES 31, IS AN INTERACTIVE QUERY LANGUAGE THAT GIVES USERS AD HOC ACCESS TO STORED DATA 5SING 31, INTERACTIVELY A USER CAN GET ANSWERS EVEN TO COMPLEX QUESTIONS IN MINUTES OR SECONDS IN SHARP CONTRAST TO THE DAYS OR WEEKS IT WOULD TAKE FOR A PROGRAMMER TO WRITE A CUSTOM REPORT PROGRAM "ECAUSE OF THE 31, AD HOC QUERY POWER DATA IS MORE ACCESSIBLE AND CAN BE USED TO HELP AN ORGANIZATION MAKE BETTER MORE INFORMED DECISIONS 31,S AD HOC QUERY CAPABILITY WAS AN IMPORTANT ADVANTAGE OVER NONRELATIONAL DATABASES EARLY IN ITS EVOLUTION AND MORE RECENTLY HAS CONTINUED AS A KEY ADVANTAGE OVER PURE OBJECT BASED DATABASES
0ROGRAMMATICõ$ATABASEõ!CCESS 31, IS ALSO A DATABASE LANGUAGE USED BY PROGRAMMERS TO WRITE APPLICATIONS THAT ACCESS A DATABASE 4HE SAME 31, STATEMENTS ARE USED FOR BOTH INTERACTIVE AND PROGRAMMATIC ACCESS SO THE DATABASE ACCESS PARTS OF A PROGRAM CAN BE TESTED FIRST WITH INTERACTIVE 31, AND THEN EMBEDDED INTO THE PROGRAM )N CONTRAST NONRELATIONAL OR OBJECT ORIENTED DATABASES PROVIDED ONE SET OF TOOLS FOR PROGRAMMATIC ACCESS AND A SEPARATE QUERY FACILITY FOR AD HOC REQUESTS WITHOUT ANY SYNERGY BETWEEN THE TWO MODES OF ACCESS
-ULTIPLEõ6IEWSõOFõ$ATA 5SING 31, THE CREATOR OF A DATABASE CAN GIVE DIFFERENT USERS OF THE DATABASE DIFFERENT VIEWS OF ITS STRUCTURE AND CONTENTS &OR EXAMPLE THE DATABASE CAN BE CONSTRUCTED SO THAT EACH USER SEES DATA ONLY FOR HIS OR HER DEPARTMENT OR SALES REGION )N ADDITION DATA FROM SEVERAL DIFFERENT PARTS OF THE DATABASE CAN BE COMBINED AND PRESENTED TO THE USER AS A SIMPLE ROW COLUMN TABLE 31, VIEWS CAN THUS BE USED TO ENHANCE THE SECURITY OF A DATABASE AND TO TAILOR IT TO THE PARTICULAR NEEDS OF INDIVIDUAL USERS WHILE PRESERVING THE FUNDAMENTAL ROWCOLUMN STRUCTURE OF THE DATA
#OMPLETEõ$ATABASEõ,ANGUAGE 31, WAS FIRST DEVELOPED AS AN AD HOC QUERY LANGUAGE BUT ITS POWERS NOW GO FAR BEYOND DATA RETRIEVAL 31, PROVIDES A COMPLETE CONSISTENT LANGUAGE FOR CREATING A DATABASE MANAGING ITS SECURITY UPDATING ITS CONTENTS RETRIEVING DATA AND SHARING DATA AMONG MANY CONCURRENT USERS 31, CONCEPTS THAT ARE LEARNED IN ONE PART OF THE LANGUAGE CAN BE APPLIED TO OTHER 31, COMMANDS MAKING USERS MORE PRODUCTIVE
$YNAMICõ$ATAõ$EFINITION 5SING 31, THE STRUCTURE OF A DATABASE CAN BE CHANGED AND EXPANDED DYNAMICALLY EVEN WHILE USERS ARE ACCESSING DATABASE CONTENTS 4HIS IS A MAJOR ADVANCE OVER STATIC DATA DEFINITION LANGUAGES WHICH PREVENTED ACCESS TO THE DATABASE WHILE ITS STRUCTURE WAS BEING CHANGED 31, THUS PROVIDES MAXIMUM FLEXIBILITY ALLOWING A DATABASE TO ADAPT TO CHANGING REQUIREMENTS WHILE ONLINE APPLICATIONS CONTINUE UNINTERRUPTED
#HAPTERçç
)NTRODUCTIONç
#LIENT3ERVERõ!RCHITECTURE
%NTERPRISEõ!PPLICATIONõ3UPPORT 4HE LARGEST ENTERPRISE APPLICATIONS THAT SUPPORT THE DAILY OPERATION OF LARGE COMPANIES AND ORGANIZATIONS ALL USE 31, BASED DATABASES TO STORE AND ORGANIZE THEIR DATA )N THE S DRIVEN BY THE IMPENDING DEADLINE FOR SUPPORTING DATES IN THE YEAR AND BEYOND THE SO CALLED h9+v PROBLEM LARGE ENTERPRISES MOVED EN MASSE TO ABANDON THEIR HOMEGROWN SYSTEMS AND CONVERT TO PACKAGED ENTERPRISE APPLICATIONS FROM VENDORS LIKE 3!0 /RACLE 0EOPLE3OFT 3IEBEL AND OTHERS 4HE DATA PROCESSED BY THESE APPLICATIONS ORDERS SALES AMOUNTS CUSTOMERS INVENTORY LEVELS PAYMENT AMOUNTS ETC TENDS TO HAVE A STRUCTURED RECORDS AND FIELDS FORMAT WHICH CONVERTS EASILY INTO THE ROWCOLUMN FORMAT OF 31, "Y CONSTRUCTING THEIR APPLICATIONS TO USE ENTERPRISE CLASS 31, DATABASES THE MAJOR APPLICATION VENDORS ELIMINATED THE NEED TO DEVELOP THEIR OWN DATA MANAGEMENT SOFTWARE AND BENEFITED FROM EXISTING TOOLS AND PROGRAMMING SKILLS "ECAUSE EVERY MAJOR ENTERPRISE APPLICATION REQUIRES A 31, BASED DATABASE FOR ITS OPERATION NEW SALES OF ENTERPRISE APPLICATIONS AUTOMATICALLY GENERATE hDRAG ALONGv DEMAND FOR NEW COPIES OF DATABASE SOFTWARE
%XTENSIBILITYõANDõ/BJECTõ4ECHNOLOGY 4HE MAJOR CHALLENGE TO 31,S CONTINUED DOMINANCE AS A DATABASE STANDARD HAS COME FROM THE EMERGENCE OF OBJECT BASED PROGRAMMING THROUGH LANGUAGES SUCH AS *AVA AND # AND FROM THE INTRODUCTION OF OBJECT BASED DATABASES AS AN EXTENSION OF THE BROAD MARKET TREND TOWARD OBJECT BASED TECHNOLOGY 31, BASED DATABASE VENDORS HAVE RESPONDED TO THIS CHALLENGE BY SLOWLY EXPANDING AND ENHANCING 31, TO INCLUDE OBJECT FEATURES 4HESE hOBJECT RELATIONALv DATABASES WHICH CONTINUE TO BE BASED ON 31, HAVE EMERGED AS A MORE POPULAR ALTERNATIVE TO hPURE OBJECTv DATABASES AND HAVE PERPETUATED 31,S DOMINANCE THROUGH THE LAST DECADE 4HE NEWEST WAVE OF OBJECT TECHNOLOGY EMBODIED IN THE 8-, STANDARD AND WEB SERVICES ARCHITECTURES ONCE AGAIN CREATED A CROP OF h8-, DATABASESv AND ALTERNATIVE QUERY LANGUAGES TO CHALLENGE 31, IN THE EARLY S "UT ONCE AGAIN THE MAJOR VENDORS OF 31, BASED DATABASES RESPONDED BY ADDING 8-, BASED EXTENSIONS MEETING THE CHALLENGE AND SECURING 31,S CONTINUING IMPORTANCE (ISTORY SUGGESTS THAT THIS hEXTEND AND INTEGRATEv APPROACH WILL BE SUCCESSFUL IN WARDING OFF NEW CHALLENGES IN THE FUTURE AS WELL
)NTERNETõ$ATABASEõ!CCESS 7ITH THE EXPLODING POPULARITY OF THE )NTERNET AND THE 7ORLD 7IDE 7EB AND THEIR STANDARDS BASED FOUNDATION 31, FOUND A NEW ROLE IN THE LATE S AS AN )NTERNET DATA ACCESS STANDARD %ARLY IN THE DEVELOPMENT OF THE 7EB DEVELOPERS NEEDED A WAY TO RETRIEVE AND PRESENT DATABASE INFORMATION ON WEB PAGES AND USED 31, AS A COMMON LANGUAGE FOR DATABASE GATEWAYS -ORE RECENTLY THE EMERGENCE OF THREE TIERED )NTERNET ARCHITECTURES WITH DISTINCT THIN CLIENT APPLICATION SERVER AND DATABASE SERVER LAYERS HAS ESTABLISHED 31, AS THE STANDARD LINK BETWEEN THE APPLICATION AND DATABASE TIERS 4HE ROLE OF 31, IN MULTITIER
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31, IS A NATURAL VEHICLE FOR IMPLEMENTING APPLICATIONS USING A DISTRIBUTED CLIENTSERVER ARCHITECTURE )N THIS ROLE 31, SERVES AS THE LINK BETWEEN hFRONT ENDv COMPUTER SYSTEMS OPTIMIZED FOR USER INTERACTION AND hBACK ENDv SYSTEMS SPECIALIZED FOR DATABASE MANAGEMENT ALLOWING EACH SYSTEM TO DO WHAT IT DOES BEST 31, ALSO ALLOWS PERSONAL COMPUTERS TO FUNCTION AS FRONT ENDS TO NETWORK SERVERS OR TO LARGER MINICOMPUTER AND MAINFRAME DATABASES PROVIDING ACCESS TO CORPORATE DATA FROM PERSONAL COMPUTER APPLICATIONS
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ARCHITECTURES IS NOW BEGINNING TO EXTEND BEYOND THE BACK END DATABASE LAYER TO INCLUDE DATA CACHING AND REAL TIME DATA MANAGEMENT IN OR NEAR THE APPLICATION TIER
*AVAõ)NTEGRATIONõ*$"# ! MAJOR AREA OF 31, DEVELOPMENT OVER THE LAST FIVE TO TEN YEARS HAS BEEN THE INTEGRATION OF 31, WITH *AVA 3EEING THE NEED TO LINK THE *AVA LANGUAGE TO EXISTING RELATIONAL DATABASES 3UN -ICROSYSTEMS THE CREATOR OF *AVA INTRODUCED *AVA $ATABASE #ONNECTIVITY *$"# A STANDARD !0) THAT ALLOWS *AVA PROGRAMS TO USE 31, FOR DATABASE ACCESS *$"# RECEIVED A FURTHER BOOST WHEN IT WAS ADOPTED AS THE DATA ACCESS STANDARD WITHIN THE *AVA %NTERPRISE %DITION *%% SPECIFICATION WHICH DEFINES THE OPERATING ENVIRONMENT PROVIDED BY MOST OF THE LEADING )NTERNET APPLICATION SERVERS )N ADDITION TO THE ROLE OF *AVA AS A PROGRAMMING LANGUAGE FROM WHICH DATABASES ARE USED MANY OF THE LEADING DATABASE VENDORS HAVE ALSO ANNOUNCED OR IMPLEMENTED *AVA SUPPORT WITHIN THEIR DATABASE SYSTEMS ALLOWING *AVA TO BE USED AS A LANGUAGE FOR STORED PROCEDURES AND BUSINESS LOGIC WITHIN THE DATABASE ITSELF 4HIS TREND TOWARD INTEGRATION BETWEEN *AVA AND 31, WILL ENSURE THE CONTINUED IMPORTANCE OF 31, IN THE NEW ERA OF *AVA BASED PROGRAMMING
/PENõ3OURCEõ3UPPORT /NE OF THE NEWER IMPORTANT DEVELOPMENTS IN THE COMPUTER INDUSTRY IS THE EMERGENCE OF AN hOPEN SOURCEv APPROACH TO BUILDING COMPLEX SOFTWARE SYSTEMS 7ITH THIS APPROACH THE SOURCE CODE THAT DEFINES THE OPERATION OF A SOFTWARE SYSTEM IS OPEN AND FREELY AVAILABLE AND MANY DIFFERENT PROGRAMMERS CAN CONTRIBUTE TO IT ADDING FEATURES FIXING BUGS ENHANCING ITS FUNCTIONALITY AND PROVIDING SUPPORT FOR ITS USE 4HIS COMMUNITY OF PROGRAMMERS POTENTIALLY SPREAD ACROSS THOUSANDS OF DIFFERENT ORGANIZATIONS AND AROUND THE GLOBE WITH SOME COORDINATION BECOMES THE ENGINE THAT DRIVES THE FURTHER DEVELOPMENT OF THE TECHNOLOGY /PEN SOURCE SOFTWARE IS GENERALLY AVAILABLE AT VERY LOW PRICES OR FREE ADDING TO ITS APPEAL 3EVERAL SUCCESSFUL OPEN SOURCE 31, BASED DATABASES HAVE BEEN BUILT IN THE LAST DECADE AND ONE OF THESE -Y31, IS A STANDARD COMPONENT OF THE MOST POPULAR OPEN SOURCE hSTACKv OF SOFTWARETHE ,!-0 STACKWHICH ALSO INCLUDES ,INUX THE !PACHE WEB SERVER AND THE 0(0 SCRIPTING LANGUAGE 4HE WIDESPREAD AVAILABILITY OF FREE 31, BASED OPEN SOURCE DATABASES HAS EXPOSED 31, TO AN EVEN BROADER RANGE OF PROGRAMMERS CONTINUING TO BUILD ITS POPULARITY
)NDUSTRYõ)NFRASTRUCTURE 0ERHAPS THE MOST IMPORTANT FACTOR CONTRIBUTING TO THE GROWING IMPORTANCE OF 31, IS THE EMERGENCE OF AN ENTIRE COMPUTER INDUSTRY INFRASTRUCTURE BASED ON 31, 31, BASED RELATIONAL DATABASE SYSTEMS ARE AN IMPORTANT PART OF THIS INFRASTRUCTURE %NTERPRISE APPLICATIONS THAT USE 31, AND REQUIRE A 31, BASED DATABASE ARE ANOTHER IMPORTANT PART AS ARE REPORTING TOOLS DATA ENTRY TOOLS DESIGN TOOLS PROGRAMMING TOOLS AND A HOST OF OTHER TOOLS THAT SIMPLIFY THE USE OF 31, ! LARGE POOL OF EXPERIENCED 31, PROGRAMMERS IS A CRITICAL PART OF THE INFRASTRUCTURE !NOTHER IMPORTANT PART IS THE TRAINING AND SUPPORT SERVICES THAT SURROUND 31, AND HELP TO CREATE AND PERPETUATE 31, EXPERTISE !N ENTIRE SUBINDUSTRY HAS EMERGED AROUND 31, CONSULTING OPTIMIZATION AND PERFORMANCE TUNING !LL PARTS OF THIS INFRASTRUCTURE TEND TO REINFORCE ONE ANOTHER AND TO CONTRIBUTE TO THE ONGOING SUCCESS OF THE OTHER PARTS 3IMPLY STATED TO SOLVE DATA MANAGEMENT PROBLEMS THE EASIEST LOWEST RISK LOWEST COST SOLUTION IS ALMOST ALWAYS A SOLUTION BASED ON 31,
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EFORE WE DIVE INTO THE DETAILS OF 31, ITS A GOOD IDEA TO DEVELOP AN OVERALL PERSPECTIVE ON THE LANGUAGE AND HOW IT WORKS 4HIS CHAPTER CONTAINS A QUICK TOUR OF 31, THAT ILLUSTRATES ITS MAJOR FEATURES AND FUNCTIONS 4HE GOAL OF THE QUICK TOUR IS NOT TO MAKE YOU PROFICIENT IN WRITING 31, STATEMENTS THATS THE GOAL OF 0ART )) OF THIS BOOK 2ATHER BY THE TIME YOUVE FINISHED THIS CHAPTER YOU WILL HAVE A BASIC FAMILIARITY WITH THE 31, AND AN OVERVIEW OF ITS CAPABILITIES
!õ3IMPLEõ$ATABASE 4HE EXAMPLES IN THIS QUICK TOUR ARE BASED ON A SIMPLE RELATIONAL DATABASE FOR A SMALL DISTRIBUTION COMPANY 4HE DATABASE SHOWN IN &IGURE STORES THE INFORMATION NEEDED TO IMPLEMENT A SMALL ORDER PROCESSING APPLICATION 9OU WILL FIND INSTRUCTIONS FOR CREATING THE SAMPLE DATABASE IN !PPENDIX ! SO YOU CAN TRY THESE QUERIES YOURSELF AS YOU READ 3PECIFICALLY IT STORES THE FOLLOWING INFORMATION s 4HE CUSTOMERS WHO BUY THE COMPANYS PRODUCTS s 4HE ORDERS PLACED BY THOSE CUSTOMERS s 4HE SALESPEOPLE WHO SELL THE PRODUCTS TO CUSTOMERS s 4HE SALES OFFICES WHERE THOSE SALESPEOPLE WORK 4HIS DATABASE LIKE MOST OTHERS IS A MODEL OF THE hREAL WORLDv 4HE DATA STORED IN THE DATABASE REPRESENTS REAL ENTITIESCUSTOMERS ORDERS SALESPEOPLE AND OFFICES %ACH DIFFERENT KIND OF ENTITY HAS A SEPARATE TABLE OF DATA &OR EXAMPLE IN THE 3!,%32%03 TABLE EACH SALESPERSON IS REPRESENTED BY ONE ROW AND EACH COLUMN HOLDS ONE TYPE OF INFORMATION ABOUT SALESPEOPLE SUCH AS THEIR NAME OR THE SALES OFFICE WHERE THEY ARE ASSIGNED $ATABASE REQUESTS THAT YOU MAKE USING THE 31, PARALLEL REAL WORLD ACTIVITIES AS CUSTOMERS PLACE CANCEL AND CHANGE ORDERS AS YOU HIRE AND FIRE SALESPEOPLE AND SO ON ,ETS SEE HOW YOU CAN USE 31, TO MANIPULATE DATA
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2ETRIEVINGõ$ATA &IRST LETS LIST THE SALES OFFICES SHOWING THE CITY WHERE EACH ONE IS ITS OFFICE NUMBER AND ITS YEAR TO DATE SALES 4HE 31, STATEMENT THAT RETRIEVES DATA FROM THE DATABASE IS CALLED 3%,%#4 4HIS 31, STATEMENT RETRIEVES THE DATA YOU WANT 3%,%#4 #)49 /&&)#% 3!,%3 &2/- /&&)#%3 #)49 /&&)#% 3!,%3
$ENVER .EW 9ORK #HICAGO !TLANTA ,OS !NGELES
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3%,%#4 .!-% 2%0?/&&)#% 3!,%3 15/4! &2/- 3!,%32%03 .!-% 2%0?/&&)#% 3!,%3 15/4!
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH $AN 2OBERTS 4OM 3NYDER .5,, .5,, ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI
4HE .5,, VALUES FOR 4OM 3NYDER REPRESENT MISSING OR UNKNOWN DATA (E IS NEW TO THE COMPANY AND HAS NOT YET BEEN ASSIGNED TO A SALES OFFICE OR BEEN GIVEN A SALES QUOTA (OWEVER HE HAS ALREADY MADE SOME SALES 4HE DATA IN HIS ROW OF QUERY RESULTS SHOWS THIS CLEARLY 31, ALSO LETS YOU ASK FOR CALCULATED RESULTS &OR EXAMPLE YOU CAN ASK 31, TO CALCULATE THE AMOUNT BY WHICH EACH SALESPERSON IS OVER OR UNDER QUOTA 3%,%#4 .!-% 3!,%3 15/4! 3!,%3 n 15/4! &2/- 3!,%32%03 .!-% 3!,%3 15/4! 3!,%3n15/4!
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH n $AN 2OBERTS 4OM 3NYDER .5,, .5,, ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI n
4HE REQUESTED DATA INCLUDING THE CALCULATED DIFFERENCE BETWEEN SALES AND QUOTA FOR EACH SALESPERSON ONCE AGAIN APPEARS IN A ROWCOLUMN TABLE 0ERHAPS YOU WOULD LIKE TO FOCUS ON THE SALESPEOPLE WHOSE SALES ARE LESS THAN THEIR QUOTAS 31, LETS YOU RETRIEVE THAT
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4HE 3%,%#4 STATEMENT ASKS FOR THREE PIECES OF DATATHE CITY THE OFFICE NUMBER AND THE AMOUNT OF SALESFOR EACH OFFICE )T ALSO SPECIFIES THAT ALL OF THIS DATA COMES FROM THE /&&)#%3 TABLE WHICH STORES DATA ABOUT SALES OFFICES 4HE RESULTS OF THE QUERY APPEAR IN TABULAR FORM IMMEDIATELY AFTER THE REQUEST .OTE THAT THE FORMATTING OF THE QUERY RESULTS WILL VARY FROM ONE 31, IMPLEMENTATION TO ANOTHER 4HE 3%,%#4 STATEMENT IS USED FOR ALL 31, QUERIES &OR EXAMPLE HERE IS A QUERY THAT LISTS THE NAMES AND YEAR TO DATE SALES FOR EACH SALESPERSON IN THE DATABASE )T ALSO SHOWS THE QUOTA SALES TARGET AND THE OFFICE NUMBER WHERE EACH PERSON WORKS )N THIS CASE THE DATA COMES FROM THE 3!,%32%03 TABLE
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KIND OF SELECTIVE INFORMATION VERY EASILY BY ADDING A MATHEMATICAL COMPARISON TO THE PREVIOUS REQUEST 3%,%#4 .!-% 3!,%3 15/4! 3!,%3 n 15/4! &2/- 3!,%32%03 7(%2% 3!,%3 15/4! .!-% 3!,%3 15/4! 3!,%3n15/4!
"OB 3MITH n .ANCY !NGELLI n
9OU CAN USE THE SAME TECHNIQUE TO LIST LARGE ORDERS IN THE DATABASE AND FIND OUT WHICH CUSTOMER PLACED THE ORDER WHICH PRODUCT WAS ORDERED AND IN WHAT QUANTITY 9OU CAN ALSO ASK 31, TO SORT THE ORDERS BASED ON THE ORDER AMOUNT 3%,%#4 /2$%2?.5- #534 02/$5#4 149 !-/5.4 &2/- /2$%23 7(%2% !-/5.4 /2$%2 "9 !-/5.4 /2$%2?.5- #534 02/$5#4 149 !-/5.4
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3UMMARIZINGõ$ATA 31, NOT ONLY RETRIEVES INDIVIDUAL PIECES OF DATA FROM THE DATABASE BUT IT ALSO CAN SUMMARIZE THE DATABASE CONTENTS 7HATS THE AVERAGE SIZE OF AN ORDER IN THE DATABASE 4HIS REQUEST ASKS 31, TO LOOK AT ALL THE ORDERS AND FIND THE AVERAGE AMOUNT 3%,%#4 !6'!-/5.4 &2/- /2$%23 !6'!-/5.4
9OU COULD ALSO ASK FOR THE AVERAGE ORDER SIZE FOR A PARTICULAR CUSTOMER 3%,%#4 !6'!-/5.4 &2/- /2$%23 7(%2% #534 !6'!-/5.4
#HAPTERçç
! ç 1 U I C K ç 4O U R ç O F ç 3 1 , ç
3%,%#4 #534 35-!-/5.4 &2/- /2$%23 '2/50 "9 #534 #534 35-!-/5.4
!DDINGõ$ATAõTOõTHEõ$ATABASE 9OU ALSO USE 31, TO ADD NEW DATA TO THE DATABASE &OR EXAMPLE SUPPOSE YOU JUST OPENED A NEW 7ESTERN REGION SALES OFFICE IN $ALLAS WITH TARGET SALES OF (ERES THE ).3%24 STATEMENT THAT ADDS THE NEW OFFICE TO THE DATABASE AS OFFICE NUMBER ).3%24 ).4/ /&&)#%3 #)49 2%')/. 4!2'%4 3!,%3 /&&)#% 6!,5%3 g$ALLASg g7ESTERNg ROW INSERTED
3IMILARLY IF -ARY *ONES EMPLOYEE NUMBER SIGNS UP A NEW CUSTOMER !CME )NDUSTRIES THIS ).3%24 STATEMENT ADDS THE CUSTOMER TO THE DATABASE AS CUSTOMER NUMBER WITH A CREDIT LIMIT ).3%24 ).4/ #534/-%23 #/-0!.9 #534?2%0 #534?.5- #2%$)4?,)-)4 6!,5%3 g!CME )NDUSTRIESg ROW INSERTED
9OU MAY HAVE NOTICED THAT THE 31, ENGINE RETURNED FEEDBACK ROW INSERTED TO TELL YOU THAT THE STATEMENTS WORKED 4HE EXACT WORDING AND FORMATTING OF THIS FEEDBACK WILL VARY FROM ONE 31, IMPLEMENTATION TO ANOTHER
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&INALLY LETS FIND OUT THE TOTAL VALUE OF THE ORDERS PLACED BY EACH CUSTOMER 4O DO THIS YOU CAN ASK 31, TO GROUP THE ORDERS TOGETHER BY CUSTOMER NUMBER AND THEN TOTAL THE ORDERS FOR EACH CUSTOMER
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!Nç/VERVIEWçOFç31,
$ELETINGõ$ATA *UST AS THE 31, ).3%24 STATEMENT ADDS NEW DATA TO THE DATABASE THE 31, $%,%4% STATEMENT REMOVES DATA FROM THE DATABASE )F !CME )NDUSTRIES DECIDES A FEW DAYS LATER TO SWITCH TO A COMPETITOR YOU CAN DELETE !CMES CUSTOMER INFORMATION FROM THE DATABASE WITH THIS STATEMENT $%,%4% &2/- #534/-%23 7(%2% #/-0!.9 g!CME )NDUSTRIESg ROW DELETED
!ND IF YOU DECIDE TO TERMINATE ALL SALESPEOPLE WHOSE SALES ARE LESS THAN THEIR QUOTAS YOU CAN REMOVE THEM FROM THE DATABASE WITH THIS $%,%4% STATEMENT $%,%4% &2/- 3!,%32%03 7(%2% 3!,%3 15/4! ROWS DELETED
5PDATINGõTHEõ$ATABASE 9OU CAN USE 31, TO MODIFY DATA THAT IS ALREADY STORED IN THE DATABASE &OR EXAMPLE TO INCREASE THE CREDIT LIMIT FOR &IRST #ORP TO YOU WOULD USE THE 31, 50$!4% STATEMENT 50$!4% #534/-%23 3%4 #2%$)4?,)-)4 7(%2% #/-0!.9 g&IRST #ORPg ROW UPDATED
4HE 50$!4% STATEMENT CAN ALSO MAKE MANY CHANGES IN THE DATABASE AT ONCE &OR EXAMPLE THIS 50$!4% STATEMENT RAISES THE QUOTA FOR ALL SALESPEOPLE BY 50$!4% 3!,%32%03 3%4 15/4! 15/4! ROWS UPDATED
0ROTECTINGõ$ATA !N IMPORTANT ROLE OF A DATABASE IS TO PROTECT THE STORED DATA FROM ACCESS OR MODIFICATION BY UNAUTHORIZED USERS &OR EXAMPLE SUPPOSE YOUR ASSISTANT -ARY HAS A DATABASE ACCOUNT BUT HAS NOT BEEN PREVIOUSLY AUTHORIZED TO INSERT DATA ABOUT NEW CUSTOMERS INTO THE DATABASE 4HIS 31, STATEMENT GRANTS HER THAT PERMISSION '2!.4 ).3%24 /. #534/-%23 4/ -!29 0RIVILEGE GRANTED
#HAPTERçç
! ç 1 U I C K ç 4O U R ç O F ç 3 1 , ç
3IMILARLY THE FOLLOWING 31, STATEMENT GIVES -ARY PERMISSION TO UPDATE DATA ABOUT CUSTOMERS AND TO RETRIEVE CUSTOMER DATA WITH THE 3%,%#4 STATEMENT
)F -ARY IS NO LONGER ALLOWED TO ADD NEW CUSTOMERS TO THE DATABASE THIS 2%6/+% STATEMENT WILL DISALLOW IT 2%6/+% ).3%24 /. #534/-%23 &2/- -!29 0RIVILEGE REVOKED
3IMILARLY THIS 2%6/+% STATEMENT WILL REVOKE ALL OF -ARYS PRIVILEGES TO ACCESS OR MODIFY CUSTOMER DATA IN ANY WAY 2%6/+% !,, /. #534/-%23 &2/- -!29 0RIVILEGE REVOKED
#REATINGõAõ$ATABASE "EFORE YOU CAN STORE DATA IN A DATABASE YOU MUST FIRST DEFINE THE STRUCTURE OF THE DATA 3UPPOSE YOU WANT TO EXPAND THE SAMPLE DATABASE BY ADDING A TABLE OF DATA ABOUT THE PRODUCTS YOUR COMPANY SELLS &OR EACH PRODUCT THE DATA TO BE STORED INCLUDES THE FOLLOWING s ! THREE CHARACTER MANUFACTURER )$ CODE s ! FIVE CHARACTER PRODUCT )$ CODE s ! PRODUCT DESCRIPTION OF UP TO CHARACTERS s 4HE PRICE OF THE PRODUCT s 4HE QUANTITY CURRENTLY ON HAND 4HIS 31, #2%!4% 4!",% STATEMENT DEFINES A NEW TABLE TO STORE THE PRODUCTS DATA #2%!4% 4!",% 02/$5#43 -&2?)$ #(!2 02/$5#4?)$ #(!2 $%3#2)04)/. 6!2#(!2 02)#% $%#)-!, 149?/.?(!.$ ).4%'%2 4ABLE CREATED
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'2!.4 50$!4% 3%,%#4 /. #534/-%23 4/ -!29 0RIVILEGE GRANTED
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!Nç/VERVIEWçOFç31,
!LTHOUGH MORE CRYPTIC THAN THE PREVIOUS 31, STATEMENT EXAMPLES THE #2%!4% 4!",% STATEMENT IS STILL FAIRLY STRAIGHTFORWARD )T ASSIGNS THE NAME 02/$5#43 TO THE NEW TABLE AND SPECIFIES THE NAME AND TYPE OF DATA STORED IN EACH OF ITS FIVE COLUMNS 4HE MANUFACTURER AND PRODUCT )$S ARE STORED AS FIXED LENGTH SEQUENCES OF CHARACTERS THE PRODUCT DESCRIPTION IS A VARIABLE LENGTH CHARACTER STRING THE PRICE IS DECIMAL DATA A REAL NUMBER AND THE QUANTITY IS AN INTEGER /NCE THE TABLE HAS BEEN CREATED YOU CAN FILL IT WITH DATA (ERES AN ).3%24 STATEMENT FOR A NEW SHIPMENT OF SIZE WIDGETS PRODUCT !#) WHICH COST APIECE ).3%24 ).4/ 02/$5#43 -&2?)$ 02/$5#4?)$ $%3#2)04)/. 02)#% 149?/.?(!.$ 6!,5%3 g!#)g gg g3IZE 7IDGETg ROW INSERTED
&INALLY IF YOU DISCOVER LATER THAT YOU NO LONGER NEED TO STORE THE PRODUCTS DATA IN THE DATABASE YOU CAN ERASE THE TABLE AND ALL OF THE DATA IT CONTAINS WITH THE $2/0 4!",% STATEMENT $2/0 4!",% 02/$5#43 4ABLE DROPPED
3UMMARY 4HIS QUICK TOUR OF 31, SHOWED YOU WHAT 31, CAN DO AND ILLUSTRATED THE STYLE OF THE 31, BY USING EIGHT OF THE MOST COMMONLY USED 31, STATEMENTS 4O SUMMARIZE s 5SE 31, TO RETRIEVE DATA FROM THE DATABASE BY USING THE 3%,%#4 STATEMENT 9OU CAN RETRIEVE ALL OR PART OF THE STORED DATA SORT IT AND ASK 31, TO SUMMARIZE THE DATA USING TOTALS AND AVERAGES s 5SE 31, TO UPDATE THE DATABASE BY ADDING NEW DATA WITH THE ).3%24 STATEMENT DELETING DATA WITH THE $%,%4% STATEMENT AND MODIFYING EXISTING DATA WITH THE 50$!4% STATEMENT s 5SE 31, TO CONTROL ACCESS TO THE DATABASE BY GRANTING AND REVOKING SPECIFIC PRIVILEGES FOR SPECIFIC USERS WITH THE '2!.4 AND 2%6/+% STATEMENTS s 5SE 31, TO CREATEMODIFY THE DATABASE BY DEFINING THE STRUCTURE OF NEW TABLES AND DROPPING TABLES WHEN THEY ARE NO LONGER NEEDED BY USING THE #2%!4% AND $2/0 STATEMENTS
#(!04%2
31,çINç0ERSPECTIVE
3
1, IS THE STANDARD LANGUAGE FOR DATABASE MANAGEMENT TODAY 7HAT DOES IT MEAN FOR 31, TO BE A STANDARD (OW DID IT BECOME A STANDARD 7HAT ROLE DOES THE OFFICIAL 31, STANDARD PLAY (OW BROADLY ADOPTED IS IT AND WHY ARE THERE STILL DIALECTS OF 31, DESPITE THE STANDARD (OW BROAD IS 31,S IMPACT ON VARIOUS SEGMENTS OF THE )4 LANDSCAPE 4O ANSWER THESE QUESTIONS THIS CHAPTER TRACES THE HISTORY OF 31, AND DESCRIBES ITS CURRENT ROLE IN THE COMPUTER MARKET
31,õANDõTHEõ%VOLUTIONõOFõ$ATABASEõ-ANAGEMENT /NE OF THE MAJOR TASKS OF A COMPUTER SYSTEM IS TO STORE AND MANAGE DATA 4O HANDLE THIS TASK SPECIALIZED COMPUTER PROGRAMS KNOWN AS DATABASE MANAGEMENT SYSTEMS BEGAN TO APPEAR IN THE LATE S AND EARLY S ! DATABASE MANAGEMENT SYSTEM OR $"-3 HELPED COMPUTER USERS TO ORGANIZE AND STRUCTURE THEIR DATA AND ALLOWED THE COMPUTER SYSTEM TO PLAY A MORE ACTIVE ROLE IN MANAGING THE DATA !LTHOUGH DATABASE MANAGEMENT SYSTEMS WERE FIRST DEVELOPED ON LARGE MAINFRAME SYSTEMS THEIR POPULARITY QUICKLY SPREAD TO MINICOMPUTERS AND THEN TO COMPUTER WORKSTATIONS PERSONAL COMPUTERS AND SPECIALIZED SERVER COMPUTERS $ATABASE MANAGEMENT HAS ALSO PLAYED A KEY ROLE IN THE EXPLOSION OF COMPUTER NETWORKING AND THE )NTERNET %ARLY DATABASE SYSTEMS RAN ON LARGE MONOLITHIC COMPUTER SYSTEMS WHERE THE DATA THE DATABASE MANAGEMENT SOFTWARE AND THE USERS OR APPLICATION PROGRAMS ACCESSING THE DATABASE ALL OPERATED ON THE SAME SYSTEM 4HE S AND S SAW THE EXPLOSION OF A NEW CLIENTSERVER MODEL FOR DATABASE ACCESS IN WHICH A USER OR AN APPLICATION PROGRAM RUNNING ON A PERSONAL COMPUTER ACCESSES A DATABASE ON A SEPARATE COMPUTER SYSTEM BY USING A NETWORK )N THE LATE S THE INCREASING POPULARITY OF THE )NTERNET AND THE 7ORLD 7IDE 7EB IMPACTED THE ARCHITECTURE OF DATA MANAGEMENT AGAIN 4ODAY USERS REQUIRE LITTLE MORE THAN A WEB BROWSER TO ACCESS AND INTERACT WITH DATABASES NOT ONLY WITHIN THEIR OWN ORGANIZATIONS BUT ALSO AROUND THE WORLD 4HESE )NTERNET BASED ARCHITECTURES USUALLY INVOLVE THREE OR MORE COMPUTER SYSTEMSONE THAT RUNS THE WEB BROWSER AND INTERACTS WITH THE USER CONNECTED OVER THE )NTERNET TO A SECOND SYSTEM THAT RUNS AN APPLICATION PROGRAM OR APPLICATION SERVER WHICH IS IN TURN CONNECTED TO A THIRD SYSTEM THAT RUNS THE DATABASE MANAGEMENT SYSTEM $ATABASE MANAGEMENT HAS BECOME A VERY BIG BUSINESS )NDEPENDENT SOFTWARE COMPANIES AND COMPUTER VENDORS SHIP BILLIONS OF DOLLARS WORTH OF DATABASE MANAGEMENT PRODUCTS EVERY YEAR 6IRTUALLY ALL ENTERPRISE CLASS COMPUTER APPLICATIONS THAT SUPPORT THE DAILY OPERATION
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OF LARGE COMPANIES AND OTHER ORGANIZATIONS USE DATABASES 4HESE APPLICATIONS INCLUDE SOME OF THE FASTEST GROWING APPLICATION CATEGORIES SUCH AS %NTERPRISE 2ESOURCE 0LANNING %20 #USTOMER 2ELATIONSHIP -ANAGEMENT #2- 3UPPLY #HAIN -ANAGEMENT 3#- 3ALES &ORCE !UTOMATION 3&! AND FINANCIAL APPLICATIONS 3PECIALIZED HIGH PERFORMANCE SERVER COMPUTERS OPTIMIZED TO RUN THE MOST POPULAR DATABASE SOFTWARE CONSTITUTE A MULTIBILLION DOLLAR MARKET AND LOW COST SERVERS USED EXCLUSIVELY FOR DATA MANAGEMENT ADD BILLIONS MORE $ATABASES PROVIDE THE INTELLIGENCE BEHIND MOST TRANSACTION ORIENTED WEB SITES AND THEY ARE USED TO CAPTURE AND ANALYZE USER INTERACTIONS WITH WEB SITES $ATABASE MANAGEMENT THUS TOUCHES EVERY SEGMENT OF THE COMPUTER MARKET 3INCE THE LATE S A SPECIFIC TYPE OF $"-3 CALLED A RELATIONAL DATABASE MANAGEMENT SYSTEM 2$"-3 HAS BECOME SO POPULAR THAT IT IS THE STANDARD DATABASE FORM 2ELATIONAL DATABASES ORGANIZE DATA IN A SIMPLE TABULAR FORM AND PROVIDE MANY ADVANTAGES OVER EARLIER TYPES OF DATABASES 31, IS SPECIFICALLY A RELATIONAL DATABASE LANGUAGE USED TO WORK WITH RELATIONAL DATABASES
!õ"RIEFõ(ISTORYõOFõ31, 4HE HISTORY OF THE 31, IS INTIMATELY INTERTWINED WITH THE DEVELOPMENT OF RELATIONAL DATABASES 4ABLE SHOWS SOME OF THE EARLY MILESTONES IN ITS YEAR HISTORY 4HE RELATIONAL DATABASE CONCEPT WAS ORIGINALLY DEVELOPED BY %DGAR &RANK h4EDv #ODD AN )"- RESEARCHER )N *UNE #ODD PUBLISHED AN ARTICLE ENTITLED h! 2ELATIONAL -ODEL OF $ATA FOR ,ARGE 3HARED $ATA "ANKS v WHICH OUTLINED A MATHEMATICAL THEORY OF HOW DATA COULD BE STORED AND MANIPULATED USING A TABULAR STRUCTURE 2ELATIONAL DATABASES AND 31, TRACE THEIR ORIGINS TO THIS ARTICLE WHICH APPEARED IN THE #OMMUNICATIONS OF THE !SSOCIATION FOR #OMPUTING -ACHINERY
4HEõ%ARLYõ9EARS #ODDS ARTICLE TRIGGERED A FLURRY OF RELATIONAL DATABASE RESEARCH INCLUDING A MAJOR RESEARCH PROJECT WITHIN )"- 4HE GOAL OF THE PROJECT CALLED 3YSTEM2 WAS TO PROVE THE WORKABILITY OF THE RELATIONAL CONCEPT AND TO PROVIDE SOME EXPERIENCE IN ACTUALLY IMPLEMENTING A RELATIONAL $"-3 7ORK ON 3YSTEM2 BEGAN IN THE MID S AT )"-S 3ANTA 4ERESA LABORATORIES IN 3AN *OSE #ALIFORNIA )N AND THE FIRST PHASE OF THE 3YSTEM2 PROJECT PRODUCED A MINIMAL PROTOTYPE OF A RELATIONAL $"-3 )N ADDITION TO THE $"-3 ITSELF THE 3YSTEM2 PROJECT INCLUDED WORK ON DATABASE QUERY LANGUAGES /NE OF THESE LANGUAGES WAS CALLED 3%15%, AN ACRONYM FOR 3TRUCTURED %NGLISH 1UERY ,ANGUAGE )N AND THE 3YSTEM2 RESEARCH PROTOTYPE WAS REWRITTEN FROM SCRATCH AND THE NEW IMPLEMENTATION WAS DISTRIBUTED TO SELECTED )"- CUSTOMERS FOR EVALUATION IN AND 4HESE EARLY CUSTOMER SITES PROVIDED SOME ACTUAL USER EXPERIENCE WITH 3YSTEM2 AND ITS DATABASE LANGUAGE WHICH FOR LEGAL REASONS HAD BEEN RENAMED 31, OR 3TRUCTURED 1UERY ,ANGUAGE )N THE 3YSTEM2 RESEARCH PROJECT CAME TO AN END WITH )"- CONCLUDING THAT RELATIONAL DATABASES WERE NOT ONLY FEASIBLE BUT ALSO COULD BE THE BASIS FOR A USEFUL COMMERCIAL PRODUCT
%ARLYõ2ELATIONALõ0RODUCTS 4HE 3YSTEM2 PROJECT AND ITS 31, DATABASE LANGUAGE WERE WELL CHRONICLED IN TECHNICAL JOURNALS DURING THE S 3EMINARS ON DATABASE TECHNOLOGY FEATURED DEBATES ON THE MERITS OF THE NEW AND HERETICAL RELATIONAL MODEL "Y IT WAS APPARENT THAT )"- WAS BECOMING ENTHUSIASTIC ABOUT RELATIONAL DATABASE TECHNOLOGY AND THAT IT WAS MAKING A MAJOR COMMITMENT TO 31,
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!Nç/VERVIEWçOFç31,
4HE PUBLICITY ABOUT 3YSTEM2 ATTRACTED THE ATTENTION OF A GROUP OF ENGINEERS IN -ENLO 0ARK #ALIFORNIA WHO DECIDED THAT )"-S RESEARCH FORESHADOWED A COMMERCIAL MARKET FOR RELATIONAL DATABASES )N THEY FORMED A COMPANY 2ELATIONAL 3OFTWARE )NC TO BUILD A RELATIONAL $"-3 BASED ON 31, 4HEIR PRODUCT NAMED /RACLE SHIPPED IN AND BECAME THE FIRST COMMERCIALLY AVAILABLE RELATIONAL $"-3 /RACLE BEAT )"-S FIRST PRODUCT TO MARKET BY A FULL TWO YEARS AND /RACLE RAN ON $IGITALS 6!8 MINICOMPUTERS WHICH WERE LESS EXPENSIVE THAN )"- MAINFRAMES 4HE COMPANY AGGRESSIVELY SOLD THE MERITS OF THE NEW RELATIONAL STYLE OF DATABASE MANAGEMENT AND EVENTUALLY RENAMED ITSELF AFTER ITS FLAGSHIP PRODUCT 4ODAY /RACLE #ORPORATION IS THE LEADING VENDOR OF RELATIONAL DATABASE MANAGEMENT SYSTEMS AND A MAJOR VENDOR OF ENTERPRISE APPLICATIONS BASED ON THE /RACLE DATABASE WITH ANNUAL SALES OF TENS OF BILLIONS OF DOLLARS 0ROFESSORS AT THE 5NIVERSITY OF #ALIFORNIAS "ERKELEY COMPUTER LABORATORIES WERE ALSO RESEARCHING RELATIONAL DATABASES IN THE MID S ,IKE THE )"- RESEARCH TEAM THEY BUILT A PROTOTYPE OF A RELATIONAL $"-3 AND CALLED THEIR SYSTEM )NGRES 4HE )NGRES PROJECT INCLUDED A QUERY LANGUAGE NAMED 15%, THAT ALTHOUGH MORE STRUCTURED THAN 31, WAS LESS %NGLISH LIKE -ANY DATABASE PIONEERS KEY DATABASE DEVELOPERS AND FOUNDERS OF DATABASE STARTUP COMPANIES TRACE THEIR HISTORY BACK TO THE "ERKELEY )NGRES PROJECT )N SEVERAL PROFESSORS LEFT "ERKELEY AND FOUNDED 2ELATIONAL 4ECHNOLOGY )NC TO BUILD A COMMERCIAL VERSION OF )NGRES WHICH WAS ANNOUNCED IN )NGRES AND /RACLE QUICKLY BECAME BITTER ARCHRIVALS BUT THEIR RIVALRY HELPED TO CALL ATTENTION TO RELATIONAL DATABASE TECHNOLOGY IN THIS EARLY STAGE $ESPITE ITS TECHNICAL SUPERIORITY IN MANY AREAS )NGRES BECAME A CLEAR SECOND PLACE PLAYER IN THE MARKET COMPETING AGAINST THE 31, BASED CAPABILITIES AND THE AGGRESSIVE MARKETING AND SALES STRATEGIES OF /RACLE 4HE ORIGINAL 15%, QUERY LANGUAGE WAS EFFECTIVELY REPLACED BY 31, IN A TESTIMONY TO THE MARKET POWER OF THE 31, STANDARD "Y THE MID S THE )NGRES TECHNOLOGY HAD BEEN SOLD TO #OMPUTER !SSOCIATES A LEADING MAINFRAME SOFTWARE VENDOR #OMPUTER !SSOCIATES SOLD ITS INTEREST IN )NGRES TO A PRIVATE EQUITY COMPANY IN
)"-õ0RODUCTS 7HILE /RACLE AND )NGRES RACED TO BECOME COMMERCIAL PRODUCTS )"-S 3YSTEM2 PROJECT HAD ALSO TURNED INTO AN EFFORT TO BUILD A COMMERCIAL PRODUCT NAMED 31,$ATA 3YSTEM 31,$3 )"- ANNOUNCED 31,$3 IN AND BEGAN SHIPPING THE PRODUCT IN )N )"- ANNOUNCED A VERSION OF 31,$3 FOR 6-#-3 AN OPERATING SYSTEM THAT WAS FREQUENTLY USED ON )"- MAINFRAMES IN CORPORATE INFORMATION CENTER APPLICATIONS )N )"- ALSO INTRODUCED $ATABASE $" ANOTHER RELATIONAL $"-3 FOR ITS MAINFRAME SYSTEMS $" OPERATED UNDER )"-S -63 OPERATING SYSTEM THE WORKHORSE OPERATING SYSTEM USED IN LARGE MAINFRAME DATA CENTERS 4HE FIRST RELEASE OF $" BEGAN SHIPPING IN AND )"- OFFICIALS HAILED IT AS A STRATEGIC PIECE OF )"- SOFTWARE TECHNOLOGY $" HAS SINCE BECOME )"-S FLAGSHIP RELATIONAL $"-3 AND WITH )"-S WEIGHT BEHIND IT $"S 31, BECAME THE DE FACTO STANDARD DATABASE LANGUAGE $" TECHNOLOGY HAS NOW MIGRATED ACROSS ALL )"- PRODUCT LINES FROM PERSONAL COMPUTERS TO NETWORK SERVERS TO MAINFRAMES )N )"- TOOK THE $" CROSS PLATFORM STRATEGY EVEN FURTHER BY ANNOUNCING $" VERSIONS FOR SERVERS FROM )"- HARDWARE RIVALS 3UN -ICROSYSTEMS AND (EWLETT 0ACKARD $" ON MAINFRAMES REMAINS THE CENTERPIECE OF )"-S DATABASE STRATEGY HOWEVER AND IS A VITAL FORCE IN ENTERPRISE COMPUTING
#HAPTERçç
31,çINç0ERSPECTIVEç
#OMMERCIALõ!CCEPTANCE
0!24ç)
$URING THE FIRST HALF OF THE S THE RELATIONAL DATABASE VENDORS STRUGGLED FOR COMMERCIAL ACCEPTANCE OF THEIR PRODUCTS 4HE RELATIONAL PRODUCTS HAD SEVERAL DISADVANTAGES COMPARED WITH THE TRADITIONAL DATABASE ARCHITECTURES 4HE PERFORMANCE OF RELATIONAL DATABASES WAS SERIOUSLY INFERIOR TO THAT OF TRADITIONAL DATABASES %XCEPT FOR THE )"- PRODUCTS THE RELATIONAL DATABASES CAME FROM SMALL UPSTART VENDORS !ND EXCEPT FOR THE )"- PRODUCTS THE RELATIONAL DATABASES TENDED TO RUN ON MINICOMPUTERS RATHER THAN ON )"- MAINFRAMES 4HE RELATIONAL PRODUCTS DID HAVE ONE MAJOR ADVANTAGE HOWEVER 4HEIR RELATIONAL QUERY LANGUAGES 31, 15%, AND OTHERS ALLOWED USERS TO POSE AD HOC QUERIES TO THE DATABASE AND GET IMMEDIATE ANSWERSWITHOUT WRITING PROGRAMS !S A RESULT RELATIONAL DATABASES BEGAN SLOWLY TURNING UP IN INFORMATION CENTER APPLICATIONS AS DECISION SUPPORT TOOLS "Y -AY /RACLE PROUDLY CLAIMED TO HAVE OVER INSTALLATIONS )NGRES WAS INSTALLED IN A COMPARABLE NUMBER OF SITES $" AND 31,$3 WERE ALSO BEING SLOWLY ACCEPTED AND COUNTED THEIR COMBINED INSTALLATIONS AT SLIGHTLY OVER SITES $URING THE LAST HALF OF THE S 31, AND RELATIONAL DATABASES WERE RAPIDLY ACCEPTED AS THE DATABASE TECHNOLOGY OF THE FUTURE 4HE PERFORMANCE OF THE RELATIONAL DATABASE PRODUCTS IMPROVED DRAMATICALLY )NGRES AND /RACLE IN PARTICULAR LEAPFROGGED WITH EACH NEW VERSION CLAIMING SUPERIORITY OVER THE COMPETITOR AND TWO OR THREE TIMES THE PERFORMANCE OF THE PREVIOUS RELEASE )MPROVEMENTS IN THE PROCESSING POWER OF THE UNDERLYING COMPUTER HARDWARE ALSO HELPED TO BOOST PERFORMANCE -ARKET FORCES ALSO BOOSTED THE POPULARITY OF 31, IN THE LATE S )"- STEPPED UP ITS EVANGELISM OF 31, POSITIONING $" AS THE DATA MANAGEMENT SOLUTION FOR THE S 0UBLICATION OF THE FIRST !.3))3/ STANDARD FOR 31, 31, IN GAVE 31, OFFICIAL STATUS AS A STANDARD 31, ALSO EMERGED AS A STANDARD ON 5.)8 BASED COMPUTER SYSTEMS WHOSE POPULARITY ACCELERATED IN THE S !S PERSONAL COMPUTERS BECAME MORE POWERFUL AND WERE LINKED IN LOCAL AREA NETWORKS ,!.S THEY NEEDED MORE SOPHISTICATED DATABASE MANAGEMENT 0# DATABASE VENDORS EMBRACED 31, AS THE SOLUTION TO THESE NEEDS AND MINICOMPUTER DATABASE VENDORS MOVED DOWN MARKET TO COMPETE IN THE EMERGING 0# LOCAL AREA NETWORK MARKET 4HROUGH THE EARLY S STEADILY IMPROVING 31, IMPLEMENTATIONS AND DRAMATIC IMPROVEMENTS IN PROCESSOR SPEEDS MADE 31, A PRACTICAL SOLUTION FOR TRANSACTION PROCESSING APPLICATIONS 31, BECAME A KEY PART OF THE CLIENTSERVER ARCHITECTURE THAT USED 0#S LOCAL AREA NETWORKS AND NETWORK SERVERS TO BUILD MUCH LOWER COST INFORMATION PROCESSING SYSTEMS 7HEN THE )NTERNET AND THE DOT COM BOOM BURST UPON THE )4 LANDSCAPE 31, FOUND A NEW ROLE AS THE DATABASE LANGUAGE FOR )NTERNET APPLICATIONS AND E COMMERCE 31,S SUPREMACY IN THE DATABASE WORLD HAS NOT GONE UNCHALLENGED /BJECT ORIENTED PROGRAMMING EMERGED IN THE S AS THE METHOD OF CHOICE FOR APPLICATIONS DEVELOPMENT ESPECIALLY FOR PERSONAL COMPUTERS AND THEIR GRAPHICAL USER INTERFACES 4HE OBJECT MODEL WITH ITS OBJECTS CLASSES METHODS AND INHERITANCE DID NOT FIT WELL WITH THE RELATIONAL MODEL OF TABLES ROWS AND COLUMNS OF DATA %ARLY hOBJECT DATABASEv PRODUCTS INCLUDED 3ERVIO ,OGICS 'EMSTONE 'RAPHAELS 'BASE AND /NTOLOGICS 6BASE ! NEW GENERATION OF VENTURE CAPITALnBACKED OBJECT DATABASE COMPANIES SPRANG UP IN THE EARLY TO MID S HOPING TO MAKE RELATIONAL DATABASES AND THEIR VENDORS OBSOLETE JUST AS 31, HAD DONE TO THE EARLIER NONRELATIONAL VENDORS 4HESE PRODUCTS INCLUDED )TASCA 3YSTEMS )4!3#! &UJITSUS *ASMINE -ATISSE 3OFTWARES -ATISSE /BJECTIVITYS /BJECTIVITY$" /NTOS )NCS RENAMED FROM /NTOLOGIC /.4/3 / 4ECHNOLOGYS / ALONG WITH PERHAPS A HALF DOZEN OTHERS (OWEVER 31, AND THE RELATIONAL MODEL MORE THAN WITHSTOOD THE CHALLENGE ! FEW OF THESE PRODUCTS
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0ARTç)ç
!Nç/VERVIEWçOFç31,
REMAIN IN THE MARKET TODAY BUT MOST HAVE BEEN ACQUIRED OR SIMPLY FADED AWAY &OR EXAMPLE / 4ECHNOLOGY MERGED WITH SEVERAL COMPANIES WAS ACQUIRED BY )NFORMIX AND )NFORMIX WAS LATER ACQUIRED BY )"- 4OTAL ANNUAL REVENUES FOR OBJECT ORIENTED DATABASES ARE MEASURED IN THE LOW MILLIONS OF DOLLARS WHILE 31, AND RELATIONAL DATABASE SYSTEMS TOOLS AND SERVICES PRODUCE TENS OF BILLIONS OF DOLLARS OF SALES PER YEAR !S 31, GREW TO ADDRESS AN EVER WIDER VARIETY OF DATA MANAGEMENT TASKS THE ONE SIZE FITS ALL APPROACH OF THE EARLIER 31, PRODUCTS SHOWED SERIOUS STRAIN 3PECIALIZED DATABASE SYSTEMS SPRANG UP TO SUPPORT DIFFERENT MARKET NEEDS /NE OF THE FASTEST GROWING SEGMENTS WAS DATA WAREHOUSING WHERE DATABASES WERE USED TO SEARCH THROUGH HUGE AMOUNTS OF DATA TO DISCOVER UNDERLYING TRENDS AND PATTERNS ! SECOND MAJOR TREND WAS THE INCORPORATION OF NEW DATA TYPES SUCH AS MULTIMEDIA DATA AND OBJECT ORIENTED PRINCIPLES INTO 31, ! THIRD IMPORTANT SEGMENT WAS MOBILE DATABASES FOR PORTABLE PERSONAL COMPUTERS THAT COULD OPERATE WHEN SOMETIMES CONNECTED TO AND SOMETIMES DISCONNECTED FROM A CENTRALIZED DATABASE SYSTEM !NOTHER IMPORTANT APPLICATION SEGMENT WAS EMBEDDED DATABASES FOR USE WITHIN INTELLIGENT DEVICES SUCH AS NETWORK EQUIPMENT )N MEMORY DATABASES EMERGED AS ANOTHER SEGMENT DESIGNED FOR VERY HIGH LEVELS OF PERFORMANCE AND STREAM ORIENTED DATABASES FOCUSED ON MANAGING DATA AS IT FLOWED OVER A NETWORK $ESPITE THE EMERGENCE OF SUBSEGMENTS OF THE DATABASE MARKET 31, HAS REMAINED A COMMON DENOMINATOR ACROSS THEM ALL &ORTY YEARS AFTER IT FIRST EMERGED 31, HAS BROADENED TREMENDOUSLY AND 31,S DOMINANCE AS THE DATABASE STANDARD REMAINS VERY STRONG .EW CHALLENGES CONTINUE TO EMERGETHE NEED TO INCORPORATE 8-, AND ITS HIERARCHICAL DATA MODEL AND THE NEED TO SUPPORT MASSIVE QUANTITIES OF DATA TO SUPPORT DATA MANAGEMENT ON THE SCALE OF THE )NTERNET ARE TWO OF THE MOST RECENT "UT THE HISTORY OF THE PAST YEARS INDICATES THAT 31, AND THE RELATIONAL MODEL HAVE A POWERFUL ABILITY TO EMBRACE AND ADAPT TO NEW DATA MANAGEMENT NEEDS
31,õ3TANDARDS /NE OF THE MOST IMPORTANT DEVELOPMENTS IN THE MARKET ACCEPTANCE OF 31, IS THE EMERGENCE OF 31, STANDARDS 2EFERENCES TO hTHE 31, STANDARDv USUALLY MEAN THE OFFICIAL STANDARD ADOPTED BY THE !MERICAN .ATIONAL 3TANDARDS )NSTITUTE !.3) AND THE )NTERNATIONAL /RGANIZATION FOR 3TANDARDIZATION )3/ (OWEVER THERE ARE OTHER IMPORTANT 31, STANDARDS INCLUDING THE DE FACTO STANDARD FOR SOME PARTS OF THE 31, THAT HAVE BEEN DEFINED BY )"-S $" PRODUCT FAMILY AND /RACLES 31, DIALECT WHICH HAS A DOMINANT INSTALLED BASE MARKET SHARE
4HEõ!.3))3/õ3TANDARDS 7ORK ON THE OFFICIAL 31, STANDARD BEGAN IN WHEN !.3) CHARGED ITS 8( COMMITTEE WITH DEFINING A STANDARD RELATIONAL DATABASE LANGUAGE !T FIRST THE COMMITTEE DEBATED THE MERITS OF VARIOUS PROPOSED DATABASE LANGUAGES (OWEVER AS )"-S COMMITMENT TO 31, INCREASED AND 31, EMERGED AS A DE FACTO STANDARD IN THE MARKET THE COMMITTEE SELECTED 31, AS THEIR RELATIONAL DATABASE LANGUAGE AND TURNED THEIR ATTENTION TO STANDARDIZING IT
#HAPTERçç
31,çINç0ERSPECTIVEç
0!24ç)
4HE RESULTING !.3) STANDARD FOR 31, WAS LARGELY BASED ON $" 31, ALTHOUGH IT CONTAINED A FEW MAJOR DIFFERENCES FROM $" !FTER SEVERAL REVISIONS THE STANDARD WAS OFFICIALLY ADOPTED AS !.3) STANDARD 8 IN AND AS AN )3/ STANDARD IN 4HE !.3))3/ STANDARD WAS ALSO ADOPTED AS A &EDERAL )NFORMATION 0ROCESSING 3TANDARD &)03 BY THE 5 3 GOVERNMENT 4HIS EARLY 31, STANDARD SLIGHTLY REVISED AND EXPANDED IN IS USUALLY CALLED THE 31, STANDARD OR 31, -ANY OF THE !.3) AND )3/ STANDARDS COMMITTEE MEMBERS WERE REPRESENTATIVES FROM DATABASE VENDORS WHO HAD EXISTING 31, PRODUCTS EACH IMPLEMENTING A SLIGHTLY DIFFERENT 31, DIALECT ,IKE DIALECTS OF HUMAN LANGUAGES THE 31, DIALECTS WERE GENERALLY VERY SIMILAR TO ONE ANOTHER BUT WERE INCOMPATIBLE IN THEIR DETAILS )N MANY AREAS THE COMMITTEE SIMPLY SIDESTEPPED THESE DIFFERENCES BY OMITTING SOME PARTS OF THE LANGUAGE FROM THE STANDARD AND SPECIFYING OTHERS AS hIMPLEMENTER DEFINEDv 4HESE DECISIONS ALLOWED EXISTING 31, IMPLEMENTATIONS TO CLAIM BROAD ADHERENCE TO THE RESULTING !.3))3/ STANDARD BUT MADE THE INITIAL STANDARD RELATIVELY WEAK 4O ADDRESS THE HOLES IN THE ORIGINAL STANDARD THE !.3) COMMITTEE CONTINUED ITS WORK AND DRAFTS FOR A NEW MORE RIGOROUS h31,v STANDARD WERE CIRCULATED 5NLIKE THE STANDARD THE 31, DRAFTS SPECIFIED FEATURES CONSIDERABLY BEYOND THOSE FOUND IN CURRENT COMMERCIAL 31, PRODUCTS %VEN MORE FAR REACHING CHANGES WERE PROPOSED FOR A FOLLOW ON 31, STANDARD )N ADDITION THE DRAFT STANDARDS ATTEMPTED TO OFFICIALLY STANDARDIZE PARTS OF THE 31, WHERE DIFFERENT PROPRIETARY STANDARDS HAD LONG SINCE BEEN SET BY THE VARIOUS MAJOR $"-3 BRANDS !S A RESULT THE PROPOSED 31, AND 31, STANDARDS WERE A GOOD DEAL MORE CONTROVERSIAL THAN THE INITIAL 31, STANDARD 4HE 31, STANDARD WEAVED ITS WAY THROUGH THE !.3) APPROVAL PROCESS AND WAS FINALLY APPROVED IN /CTOBER 7HILE THE ORIGINAL STANDARD HAD LESS THAN PAGES THE REVISED STANDARD OFFICIALLY CALLED 31, HAD NEARLY PAGES 4HE STANDARDS COMMITTEE ACKNOWLEDGED THE LARGE STEP FROM 31, TO 31, BY EXPLICITLY CREATING THREE LEVELS OF 31, STANDARDS COMPLIANCE 4HE LOWEST COMPLIANCE LEVEL %NTRY ,EVEL REQUIRED ONLY MINIMAL ADDITIONAL CAPABILITY BEYOND THE 31, STANDARD 4HE MIDDLE ONE )NTERMEDIATE ,EVEL WAS CREATED AS AN ACHIEVABLE MAJOR STEP BEYOND 31, BUT AVOIDED THE MOST COMPLEX SYSTEM DEPENDENT AND $"-3 BRAND DEPENDENT ISSUES 4HE THIRD COMPLIANCE LEVEL &ULL REQUIRED A FULL IMPLEMENTATION OF ALL AREAS 4HROUGHOUT THE PUBLISHED STANDARD EACH DESCRIPTION OF EACH FEATURE INCLUDES A DEFINITION OF THE SPECIFIC ASPECTS OF THAT FEATURE THAT MUST BE SUPPORTED TO ACHIEVE VARIOUS LEVELS OF COMPLIANCE 4ODAY SPECIALIZED DATABASES SUCH AS THOSE USED IN EMBEDDED APPLICATIONS OR SUPPORTED BY OPEN SOURCE EFFORTS STILL OFFER LOWER LEVELS OF 31, STANDARD COMPLIANCE IN SOME AREAS BUT ALL OF THE MAJOR ENTERPRISE CLASS DATABASE SYSTEMS HAVE EVOLVED TO FULLY SUPPORT THE 31, STANDARD !FTER THE ADOPTION OF 31, 31, STANDARDS WORK TOOK A DIFFERENT DIRECTION 4HE SINGLE STANDARDS COMMITTEE BROKE UP INTO A NUMBER OF DIFFERENT COMMITTEES FOCUSED ON DIFFERENT EXTENSIONS TO THE LANGUAGE 3OME OF THESE SUCH AS STORED PROCEDURE CAPABILITIES WERE ALREADY FOUND IN MANY COMMERCIAL 31, PRODUCTS AND POSED THE SAME STANDARDIZATION CHALLENGES FACED BY 31, /THERS SUCH AS PROPOSED OBJECT EXTENSIONS TO 31, WERE NOT YET WIDELY AVAILABLE OR FULLY IMPLEMENTED BUT THE DATABASE VENDORS WERE UNDER SIGNIFICANT PRESSURE TO ADDRESS THEM AS OBJECT ORIENTED TECHNOLOGIES AND 8-, SURGED IN IMPORTANCE .EW REVISIONS TO THE STANDARD WERE PRODUCED IN AND AGAIN IN AND 4HE REVISION INCLUDED SIGNIFICANT EXTENSION TO THE 8-, PARTS OF THE STANDARD
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0ARTç)ç
!Nç/VERVIEWçOFç31,
!T THIS WRITING THE !.3))3/ STANDARD HAD BEEN EXPANDED INTO DEFINED h0ARTSv ! FEW OF THEM WERE DROPPED AFTER SOME INITIAL ACTIVITY SOME WERE MERGED BACK INTO OTHER PARTS AND SOME CONTINUE AS STAND ALONE PARALLEL EFFORTS WITHIN THE OVERALL STANDARD v 0ART n 31,&RAMEWORK CONTAINS COMMON DEFINITIONS AND SERVES AS A hTABLE OF CONTENTSv FOR THE OTHER PARTS v 0ART n 31,&OUNDATION IS THE LARGEST PART AND CARRIES THE MAINSTREAM DEFINITION OF THE 31, STATEMENTS THAT DEFINE THE STRUCTURE OF A DATABASE AND MANIPULATE DATA )T IS THE DESCENDANT OF THE EARLY 31, AND 31, VERSIONS OF THE STANDARD )T HAS BEEN SIGNIFICANTLY EXTENDED TO INCLUDE 31, STRUCTURES FOR BUSINESS ANALYTICS v 0ART n 31,#,) #ALL ,EVEL )NTERFACE DESCRIBES THE PROCEDURAL CALL LEVEL INTERFACE BETTER KNOWN AS -ICROSOFTS /$"# STANDARD )T DEBUTED IN v 0ART n 31,03- 0ERSISTENT 3TORED -ODULES DESCRIBES PROCEDURAL EXTENSIONS TO 31, PARALLELING THE FEATURES FOUND IN POPULAR 31, PROCEDURAL LANGUAGES LIKE /RACLES 0,31, v 0ART n 31,"INDINGS DESCRIBED HOW 31, IS EMBEDDED IN OTHER PROCEDURAL LANGUAGES 4HIS PART WAS MERGED INTO 0ART n 31,&OUNDATIONS IN THE 31, VERSION OF THE STANDARD v 0ART n 31,4RANSACTION WAS FOCUSED ON EXTENSIONS TO THE 8! DISTRIBUTED TRANSACTION STANDARD BUT WAS DROPPED v 0ART n 31,4EMPORAL WAS FOCUSED ON EXTENDING 31, TO DEAL WITH TIME ORIENTED DATA BUT WAS DROPPED v 0ART n 31,/BJECTS HELD THE OBJECT ORIENTED EXTENSIONS TO 31, DURING THE DEVELOPMENT OF 31, 4HESE EXTENSIONS WERE MERGED BACK INTO 0ART n &OUNDATION IN 31, v 0ART n 31,-%$ -ANAGEMENT OF %XTERNAL $ATA ADDS FACILITIES TO ALLOW 31, TO PROCESS NON RELATIONAL DATA SOURCES AND APPEARED IN 31, v 0ART n 31,/," /BJECT ,ANGUAGE "INDINGS DESCRIBES ACCESS TO 31, FROM *AVA )T IS RELATED TO *$"# AND EMBEDDED 31, FOR *AVA AND APPEARED IN 31, v 0ART n 31,3CHEMATA CONTAINS STANDARDS FOR THE hDATABASE CATALOGv OR SYSTEM INFORMATION TABLES THAT SELF DESCRIBE A DATABASE 4HIS SPECIFICATION WAS IN 0ART IN 31, BUT WAS SEPARATED OUT INTO ITS OWN PART IN 31, v 0ART n 31,2EPLICATION WAS STARTED TO DEFINE STANDARDS FOR HOW REPLICATION FROM ONE 31, DATABASE TO ANOTHER IS SPECIFIED BUT WAS DROPPED v 0ART n 31,*24 *AVA 2OUTINES AND 4YPES DESCRIBES ROUTINES AND TYPES USED IN THE *AVA LANGUAGE TO ACCESS 31, DATABASES AND FIRST APPEARED IN 31, v 0ART n 31,8-, DESCRIBES HOW %XTENSIBLE -ARKUP ,ANGUAGE 8-, IS INTEGRATED INTO THE 31, LANGUAGE )T FIRST APPEARED IN 31, AND HAS BEEN SIGNIFICANTLY EXPANDED SINCE &ROM A FEW HUNDRED PAGES DESCRIBING THE COMMON CORE FEATURES OF THE 31, LANGUAGE IN THE !.3))3/ 31, STANDARD HAS THUS GROWN DRAMATICALLY IN COMPLEXITY SCOPE AND LENGTH 4HE hREALv 31, STANDARD OF COURSE IS THE 31, IMPLEMENTED IN PRODUCTS THAT ARE
#HAPTERçç
31,çINç0ERSPECTIVEç
/THERõ%ARLYõ31,õ3TANDARDS !LTHOUGH IT WAS THE MOST WIDELY RECOGNIZED THE !.3))3/ STANDARD WAS NOT THE ONLY STANDARD IN THE EARLY DAYS OF 31, 8/0%. A %UROPEAN VENDOR GROUP ALSO ADOPTED 31, AS PART OF ITS SUITE OF STANDARDS FOR A PORTABLE APPLICATION ENVIRONMENT BASED ON 5.)8 4HE 8/0%. STANDARDS PLAYED A MAJOR ROLE IN THE DEVELOPMENT OF THE %UROPEAN COMPUTER MARKET WHERE PORTABILITY AMONG COMPUTER SYSTEMS FROM DIFFERENT VENDORS WAS A KEY CONCERN )"- ALSO INCLUDED 31, IN THE SPECIFICATION OF ITS BOLD S 3YSTEMS !PPLICATION !RCHITECTURE 3!! BLUEPRINT PROMISING THAT ALL OF ITS 31, PRODUCTS WOULD EVENTUALLY MOVE TO THIS 3!! 31, DIALECT !LTHOUGH 3!! FAILED TO ACHIEVE ITS PROMISE OF UNIFYING THE )"- PRODUCT LINE THE MOMENTUM TOWARD A UNIFIED )"- 31, CONTINUED 7ITH ITS MAINFRAME $" DATABASE AS THE FLAGSHIP )"- INTRODUCED $" IMPLEMENTATIONS FOR /3 ITS PERSONAL COMPUTER OPERATING SYSTEM AND FOR ITS 23 LINE OF 5.)8 BASED WORKSTATIONS AND SERVERS 4HE EXPANSION OF $" NOT ONLY ACROSS HARDWARE SYSTEMS BUT ALSO ACROSS MANY DIFFERENT TYPES OF DATA WAS EMBODIED IN )"-S NAMING ONE OF ITS LATER IMPLEMENTATIONS $" 5NIVERSAL $ATABASE OR 5$"
/$"#õANDõTHEõ31,õ!CCESSõ'ROUP !N IMPORTANT AREA OF DATABASE TECHNOLOGY NOT ADDRESSED BY THE EARLIER OFFICIAL STANDARDS IS DATABASE INTEROPERABILITYTHE METHODS BY WHICH DATA CAN BE EXCHANGED AMONG DIFFERENT DATABASES USUALLY OVER A NETWORK )N A GROUP OF VENDORS FORMED THE 31, !CCESS 'ROUP TO ADDRESS THIS PROBLEM 4HE RESULTING 31, !CCESS 'ROUP SPECIFICATION FOR 2EMOTE $ATABASE !CCESS 2$! WAS PUBLISHED IN 5NFORTUNATELY THE 2$! SPECIFICATION WAS CLOSELY TIED TO THE /3) NETWORKING PROTOCOLS WHICH LOST THE NETWORKING BATTLE TO THE )NTERNETS 4#0)0 SUITE SO 2$! WAS NEVER WIDELY IMPLEMENTED ! SECOND STANDARD FROM THE 31, !CCESS 'ROUP HAD FAR MORE MARKET IMPACT !T -ICROSOFTS URGING AND INSISTENCE THE 31, !CCESS 'ROUP EXPANDED ITS FOCUS TO INCLUDE A CALL LEVEL INTERFACE FOR 31, "ASED ON A DRAFT FROM -ICROSOFT THE RESULTING #ALL ,EVEL )NTERFACE #,) SPECIFICATION WAS PUBLISHED IN -ICROSOFTS OWN /PEN $ATABASE #ONNECTIVITY /$"# SPECIFICATION BASED ON THE #,) STANDARD WAS PUBLISHED THE SAME YEAR 7ITH THE MARKET POWER OF -ICROSOFT BEHIND IT AND THE hOPEN STANDARDSv BLESSING OF THE 31, !CCESS 'ROUP /$"# EMERGED AS THE DE FACTO STANDARD INTERFACE FOR 0# ACCESS TO 31, DATABASES !PPLE AND -ICROSOFT ANNOUNCED AN AGREEMENT TO SUPPORT /$"# ON -ACINTOSH AND 7INDOWS IN THE SPRING OF GIVING /$"# INDUSTRY STANDARD STATUS IN BOTH POPULAR GRAPHICAL USER INTERFACE ENVIRONMENTS /$"# IMPLEMENTATIONS FOR 5.)8 BASED SYSTEMS SOON FOLLOWED )N THE /$"# INTERFACE EFFECTIVELY BECAME AN !.3) )3/ STANDARD WITH THE PUBLICATION OF THE 31,#ALL ,EVEL )NTERFACE #,) STANDARD /VER THE PAST DECADE /$"# HAS CONTINUED TO EVOLVE BUT AT A SLOWER PACE -ICROSOFT STILL SUPPORTS /$"# BUT HAS FOCUSED MAJOR EFFORT INTO BUILDING HIGHER LEVEL MORE OBJECT ORIENTED
0!24ç)
BROADLY ACCEPTED BY THE MARKETPLACE &OR THE MOST PART PROGRAMMERS AND USERS TEND TO STICK WITH THOSE PARTS OF THE LANGUAGE THAT ARE THE SAME ACROSS A BROAD RANGE OF PRODUCTS 4HE INNOVATION OF THE DATABASE VENDORS CONTINUES TO DRIVE THE INVENTION OF MOST NEW 31, EXTENSIONS 3OME OF THESE FAIL TO GAIN TRACTION AND FADE FROM THE LANGUAGE OVER TIME /THERS ARE INTRODUCED AND REMAIN YEARS LATER ONLY FOR BACKWARD COMPATIBILITY OTHERS FIND COMMERCIAL SUCCESS AND MOVE INTO THE MAINSTREAM AND EVENTUALLY FIND THEIR WAY INTO THE OFFICIAL STANDARD
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0ARTç)ç
!Nç/VERVIEWçOFç31,
INTERFACES FOR UNIVERSAL DATABASE ACCESS (OWEVER /$"# STILL PLAYS A MAJOR ROLE PROVIDING PORTABILITY ACROSS DATABASES FOR MAJOR ENTERPRISE APPLICATIONS AND FOR DATABASE TOOLS )TS QUITE COMMON FOR A DATABASE TOOL OR AN ENTERPRISE APPLICATION TO SUPPORT SPECIFIC hDRIVERSv THAT OPTIMIZE IT FOR DIRECT ACCESS TO /RACLE AND $" AND 31, 3ERVER USING THEIR PROPRIETARY CALL LEVEL INTERFACES 4HE APPLICATION WILL TYPICALLY INCLUDE AN ADDITIONAL DRIVER THAT USES /$"# AS A WAY TO SUPPORT A BROAD RANGE OF OTHER DATABASES "ECAUSE SO MANY APPLICATIONS AND TOOLS ADOPT THIS APPROACH NEARLY ALL DATABASE VENDORS OFFER /$"# ACCESS SOMETIMES AS THEIR PRIMARY CALL LEVEL INTERFACE AND SOMETIMES AS A SUPPLEMENT TO A HIGHER PERFORMANCE PROPRIETARY INTERFACE
*$"#õANDõ!PPLICATIONõ3ERVERS 4HE EXPLOSIVE POPULARITY OF THE )NTERNET DROVE THE FURTHER DEVELOPMENT OF DATABASE ACCESS STANDARDS TO SUPPORT THE ACCOMPANYING RISE OF THE OBJECT ORIENTED *AVA PROGRAMMING LANGUAGE *AVA EVENTUALLY BECAME THE STANDARD LANGUAGE FOR BUILDING )NTERNET DELIVERED APPLICATIONS THAT RAN ON *AVA BASED APPLICATION SERVERS 3UN -ICROSYSTEMS THE INVENTOR OF *AVA LED THE EFFORT TO STANDARDIZE THE USE OF *AVA FOR APPLICATION SERVERS THROUGH THE *AVA %NTERPRISE %DITION *%% SPECIFICATION *%% INCLUDED *AVA $ATABASE #ONNECTIVITY *$"# AS ITS STANDARD FOR *AVA ACCESS TO RELATIONAL DATABASES 5NLIKE DATABASE ACCESS FOR THE # PROGRAMMING LANGUAGE WHERE PROPRIETARY CALL LANGUAGE INTERFACES PREDATED /$"# BY MANY YEARS THE *$"# STANDARD WAS DEVELOPED RELATIVELY EARLY IN THE EXPLOSION OF *AVA POPULARITY !S A RESULT PROPRIETARY *AVA INTERFACES FAILED TO EMERGE AND *$"# IS THE STANDARD FOR 31, ACCESS FROM THE *AVA LANGUAGE
31,õANDõ0ORTABILITY 4HE EXISTENCE OF PUBLISHED 31, STANDARDS HAS SPAWNED QUITE A FEW EXAGGERATED CLAIMS ABOUT 31, AND APPLICATIONS PORTABILITY $IAGRAMS SUCH AS THE ONE IN &IGURE ARE FREQUENTLY DRAWN TO SHOW HOW AN APPLICATION USING 31, CAN WORK INTERCHANGEABLY WITH ANY 31, BASED DATABASE MANAGEMENT SYSTEM )N FACT THE DIFFERENCES BETWEEN 31, DIALECTS ARE SIGNIFICANT ENOUGH THAT AN APPLICATION MUST OFTEN BE MODIFIED WHEN MOVED FROM ONE
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#HAPTERçç
31,çINç0ERSPECTIVEç
v $ATA TYPES 4HE 31, STANDARD HAS EVOLVED TO ADDRESS AN EVER BROADER SET OF DATA TYPES BUT VENDORS KEEP ADDING NEW ONES %VEN OLDER DATA TYPES CAN CAUSE PORTABILITY ISSUES/RACLES .5-"%2 DATA TYPE FOR EXAMPLE IS THE MOST WIDELY USED TO REPRESENT NUMERIC DATA IN AN /RACLE DATABASE AND ITS PECULIARITIES ARE COMPLETELY UNIQUE TO /RACLE v "ACKWARD COMPATIBILITY )TS NOT UNCOMMON FOR ENTERPRISE APPLICATIONS TO STILL BE IN USE OR YEARS AFTER THEY WERE FIRST WRITTEN LONG AFTER THE PROGRAMMERS WHO DEVELOPED THEM ARE GONE 4HESE PROGRAMS TEND TO BECOME hUNTOUCHABLE v SINCE THE DETAILED KNOWLEDGE OF HOW THEY WORK HAS OFTEN BEEN LOST ,ARGE SECTIONS OF THESE PROGRAMS MAY DEPEND ON OLDER PROPRIETARY 31, FEATURES AND DATABASE VENDORS ARE FORCED TO MAINTAIN BACKWARD COMPATIBILITY WITH THEM OR RISK hBREAKINGv THE APPLICATIONS 4HIS PERPETUATES DIALECT DIFFERENCES THAT INHIBIT PORTABILITY v 3YSTEM TABLES 4HE 31, STANDARD ADDRESSED THE SYSTEM TABLES THAT PROVIDE INFORMATION ABOUT THE STRUCTURE OF THE DATABASE ITSELF STARTING WITH THE 31, STANDARD "Y THIS TIME DATABASE VENDORS HAD BUILT THEIR OWN PROPRIETARY SYSTEM TABLE STRUCTURES AND THEY HAVE CONTINUED TO EVOLVE THEM OFTEN CONTAINING USEFUL INFORMATION THAT GOES WELL BEYOND THE ITEMS SPECIFIED IN THE STANDARD !PPLICATIONS THAT USE THESE PROPRIETARY SYSTEM TABLES ARE NOT PORTABLE v 0ROGRAMMATIC INTERFACE 4HE EARLY 31, STANDARD SPECIFIED AN ABSTRACT TECHNIQUE FOR USING 31, FROM WITHIN AN APPLICATIONS PROGRAM WRITTEN IN #/"/, # &/242!. AND OTHER PROGRAMMING LANGUAGES WHICH WAS NOT WIDELY ADOPTED 4HE 31, #,) STANDARD FINALLY ADDRESSED PROGRAMMATIC 31, ACCESS BUT BY THEN COMMERCIAL $"-3 PRODUCTS HAD POPULARIZED PROPRIETARY INTERFACES AND DEEPLY EMBEDDED THEM IN HUNDREDS OF THOUSANDS OF USER APPLICATIONS AND APPLICATION PACKAGES !LTHOUGH STANDARD !0)S ARE NOW WIDELY SUPPORTED MOST DATABASE VENDORS STILL MAINTAIN PROPRIETARY INTERFACES THAT OFFER HIGHER PERFORMANCE AND RICHER FUNCTIONALITY WITH THE SIDE EFFECT OF LOCKING IN APPLICATIONS v 3EMANTIC DIFFERENCES "ECAUSE THE STANDARDS SPECIFY CERTAIN DETAILS AS IMPLEMENTER DEFINED ITS POSSIBLE TO RUN THE SAME QUERY AGAINST TWO DIFFERENT CONFORMING 31, IMPLEMENTATIONS AND PRODUCE TWO DIFFERENT SETS OF QUERY RESULTS %XAMPLES OF THESE DIFFERENCES CAN BE FOUND IN AREAS LIKE THE HANDLING OF .5,, VALUES COLUMN FUNCTIONS AND DUPLICATE ROW ELIMINATION v 2EPLICATION AND DATA MIRRORING -ANY PRODUCTION DATABASES CONTAIN TABLES THAT ARE REPLICATED IN TWO OR MORE GEOGRAPHICALLY SEPARATED DATABASES TO PROVIDE HIGH AVAILABILITY OR DISASTER RECOVERY TO SPREAD OUT PROCESSING WORKLOADS OR TO REDUCE NETWORK DELAYS 4HE TECHNIQUES FOR SPECIFYING AND MANAGING THESE REPLICATION SCHEMES ARE PROPRIETARY TO EACH DATABASE SYSTEM AND ATTEMPTS TO STANDARDIZE REPLICATION HAVE BEEN ABANDONED
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31, DATABASE TO ANOTHER /VER TIME THE CORE OF THE LANGUAGE HAS BECOME MORE STANDARD AND HAS BROADENED BUT AT THE SAME TIME NEW CAPABILITIES HAVE BEEN ADDED BY THE DATABASE VENDORS OFTEN WITH PROPRIETARY LANGUAGE EXTENSIONS %XAMPLES OF AREAS WHERE THESE DIFFERENCES ARISE INCLUDE
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v %RROR CODES 4HE 31, STANDARD INTRODUCED STANDARD ERROR CODES TO BE RETURNED WHEN 31, DETECTS AN ERROR BUT ALL OF THE POPULAR DATABASE SYSTEMS HAD LONG BEEN USING THEIR OWN PROPRIETARY ERROR CODES BY THIS TIME %VEN WHEN USED IN A MODE WITH STANDARD ERROR CODES PROPRIETARY EXTENSIONS CAN GENERATE THEIR OWN ERRORS THAT ARE OUTSIDE THE SPECIFIED STANDARD CODES v $ATABASE STRUCTURE 4HE 31, STANDARD SPECIFIED THE 31, LANGUAGE TO BE USED ONCE A PARTICULAR DATABASE HAS BEEN OPENED AND IS READY FOR PROCESSING 4HE DETAILS OF DATABASE NAMING AND HOW THE INITIAL CONNECTION TO THE DATABASE IS ESTABLISHED WERE ALREADY DIVERSE AND NOT PORTABLE BY THE TIME THIS INITIAL STANDARD WAS WRITTEN 4HE 31, STANDARD CREATED MORE UNIFORMITY BUT THE STANDARD CANNOT COMPLETELY MASK THESE IMPLEMENTATION DETAILS $ESPITE THESE DIFFERENCES COMMERCIAL DATABASE TOOLS BOASTING PORTABILITY ACROSS SEVERAL DIFFERENT BRANDS OF 31, DATABASES BEGAN TO EMERGE IN THE EARLY S AND ARE BROADLY POPULAR TODAY )N PRACTICE THESE TOOLS ALWAYS INCLUDE SPECIFIC DRIVERS FOR COMMUNICATING WITH EACH OF THE MAJOR $"-3 BRANDS WHICH GENERATE THE APPROPRIATE 31, DIALECT HANDLE DATA TYPE CONVERSION TRANSLATE ERROR CODES AND SO ON
31,õANDõ.ETWORKING 4HE DRAMATIC GROWTH OF COMPUTER NETWORKING IN THE S HAD A MAJOR IMPACT ON DATABASE MANAGEMENT AND GAVE 31, A NEW PROMINENCE !S NETWORKS BECAME MORE COMMON APPLICATIONS THAT TRADITIONALLY RAN ON A CENTRAL MINICOMPUTER OR MAINFRAME MOVED TO LOCAL AREA NETWORKS OF DESKTOP WORKSTATIONS AND SERVERS )N THESE NETWORKS 31, PLAYS A CRUCIAL ROLE AS THE LINK BETWEEN AN APPLICATION RUNNING ON A DESKTOP WORKSTATION WITH A GRAPHICAL USER INTERFACE AND THE $"-3 THAT MANAGES SHARED DATA ON A COST EFFECTIVE SERVER -ORE RECENTLY THE EXPLODING POPULARITY OF THE )NTERNET AND THE 7ORLD 7IDE 7EB HAS REINFORCED THE NETWORK ROLE FOR 31, )N THE EMERGING THREE TIER )NTERNET ARCHITECTURE 31, ONCE AGAIN PROVIDES THE LINK BETWEEN THE APPLICATION LOGIC NOW RUNNING IN THE MIDDLE TIER ON AN APPLICATION SERVER OR WEB SERVER AND THE DATABASE RESIDING IN THE BACK END TIER 4HE NEXT FEW SECTIONS DISCUSS THE EVOLUTION OF DATABASE NETWORK ARCHITECTURES AND THE ROLE OF 31, IN EACH ONE
#ENTRALIZEDõ!RCHITECTURE &IGURE SHOWS THE TRADITIONAL DATABASE ARCHITECTURE USED BY $" AND THE ORIGINAL MINICOMPUTER DATABASES SUCH AS /RACLE AND )NGRES )N THIS ARCHITECTURE THE $"-3 AND THE PHYSICAL DATA BOTH RESIDE ON A CENTRAL MINICOMPUTER OR MAINFRAME SYSTEM ALONG WITH THE APPLICATION PROGRAM THAT ACCEPTS INPUT FROM THE USERS TERMINAL AND DISPLAYS DATA ON THE USERS SCREEN 4HE APPLICATION PROGRAM COMMUNICATES WITH THE $"-3 USING 31,
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31,çINç0ERSPECTIVEç
&ILEõ3ERVERõ!RCHITECTURE 4HE INTRODUCTION OF PERSONAL COMPUTERS AND LOCAL AREA NETWORKS LED TO THE DEVELOPMENT OF THE FILE SERVER ARCHITECTURE SHOWN IN &IGURE )N THIS ARCHITECTURE AN APPLICATION RUNNING ON A PERSONAL COMPUTER CAN TRANSPARENTLY ACCESS DATA LOCATED ON A FILE SERVER WHICH STORES SHARED FILES 7HEN A 0# APPLICATION REQUESTS DATA FROM A SHARED FILE THE NETWORKING SOFTWARE AUTOMATICALLY RETRIEVES THE REQUESTED BLOCK OF THE FILE FROM THE SERVER %ARLY 0# DATABASES SUCH AS D"!3% AND LATER -ICROSOFTS !CCESS SUPPORTED THIS FILE SERVER APPROACH WITH EACH PERSONAL COMPUTER RUNNING ITS OWN COPY OF THE $"-3 SOFTWARE &OR TYPICAL QUERIES THAT RETRIEVE ONLY ONE ROW OR A FEW ROWS FROM THE DATABASE THIS ARCHITECTURE PROVIDES EXCELLENT PERFORMANCE BECAUSE EACH USER HAS THE FULL POWER OF A PERSONAL COMPUTER RUNNING ITS OWN COPY OF THE $"-3 (OWEVER CONSIDER THE QUERY MADE IN THE PREVIOUS EXAMPLE "ECAUSE THE QUERY REQUIRES A SEQUENTIAL SCAN OF THE DATABASE THE $"-3 REPEATEDLY REQUESTS BLOCKS OF DATA FROM THE DATABASE WHICH IS PHYSICALLY LOCATED ACROSS THE NETWORK ON THE SERVER %VENTUALLY EVERY BLOCK OF THE FILE WILL BE REQUESTED AND SENT ACROSS THE NETWORK /BVIOUSLY THIS ARCHITECTURE PRODUCES VERY HEAVY NETWORK TRAFFIC AND SLOW PERFORMANCE FOR QUERIES OF THIS TYPE
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3UPPOSE THE USER TYPES A QUERY THAT REQUIRES A SEQUENTIAL SEARCH OF A DATABASE SUCH AS A REQUEST TO FIND THE AVERAGE ORDER SIZE FOR ALL ORDERS 4HE $"-3 RECEIVES THE QUERY SCANS THROUGH THE DATABASE FETCHING EACH RECORD OF DATA FROM THE DISK OR MEMORY CALCULATES THE AVERAGE AND DISPLAYS THE RESULT ON THE TERMINAL SCREEN "OTH THE APPLICATION PROCESSING AND THE DATABASE PROCESSING OCCUR ON THE CENTRAL COMPUTER SO EXECUTION OF THIS TYPE OF QUERY AND IN FACT ALL KINDS OF QUERIES IS VERY EFFICIENT 4HE DISADVANTAGE OF THE CENTRALIZED ARCHITECTURE IS SCALABILITY !S MORE AND MORE USERS ARE ADDED EACH OF THEM ADDS APPLICATION PROCESSING WORKLOAD TO THE SYSTEM "ECAUSE THE SYSTEM IS SHARED EACH USER EXPERIENCES DEGRADED PERFORMANCE AS THE SYSTEM BECOMES MORE HEAVILY LOADED
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#LIENT3ERVERõ!RCHITECTURE &IGURE SHOWS THE NEXT STAGE OF NETWORK DATABASE EVOLUTIONTHE CLIENTSERVER DATABASE ARCHITECTURE )N THIS SCHEME PERSONAL COMPUTERS ARE COMBINED IN A LOCAL AREA NETWORK WITH A DATABASE SERVER THAT STORES SHARED DATABASES 4HE FUNCTIONS OF THE $"-3 ARE SPLIT INTO TWO PARTS $ATABASE FRONT ENDS SUCH AS INTERACTIVE QUERY TOOLS REPORT WRITERS AND APPLICATION PROGRAMS RUN ON THE PERSONAL COMPUTER 4HE BACK END DATABASE ENGINE THAT STORES AND MANAGES THE DATA RUNS ON THE SERVER !S THE CLIENTSERVER ARCHITECTURE GREW IN POPULARITY DURING THE S 31, BECAME THE STANDARD DATABASE LANGUAGE FOR COMMUNICATION BETWEEN THE FRONT END TOOLS AND THE BACK END ENGINE IN THIS ARCHITECTURE #ONSIDER ONCE MORE THE QUERY REQUESTING THE AVERAGE ORDER SIZE )N THE CLIENTSERVER ARCHITECTURE THE QUERY TRAVELS ACROSS THE NETWORK TO THE DATABASE SERVER AS A 31, REQUEST 4HE DATABASE ENGINE ON THE SERVER PROCESSES THE REQUEST AND SCANS THE DATABASE WHICH ALSO RESIDES ON THE SERVER 7HEN THE RESULT IS CALCULATED THE DATABASE ENGINE SENDS IT BACK ACROSS THE NETWORK AS A SINGLE REPLY TO THE INITIAL REQUEST AND THE FRONT END APPLICATION DISPLAYS IT ON THE 0# SCREEN 4HE CLIENTSERVER ARCHITECTURE REDUCES THE NETWORK TRAFFIC AND SPLITS THE DATABASE WORKLOAD 5SER INTENSIVE FUNCTIONS SUCH AS HANDLING INPUT AND DISPLAYING DATA ARE CONCENTRATED ON THE USERS 0# $ATA INTENSIVE FUNCTIONS SUCH AS FILE )/ AND QUERY PROCESSING ARE CONCENTRATED IN THE DATABASE SERVER -OST IMPORTANTLY THE 31, PROVIDES A WELL DEFINED INTERFACE BETWEEN THE FRONT END AND BACK END SYSTEMS COMMUNICATING DATABASE ACCESS REQUESTS IN AN EFFICIENT MANNER "Y THE MID S THESE ADVANTAGES MADE THE CLIENTSERVER ARCHITECTURE THE MOST POPULAR SCHEME FOR IMPLEMENTING NEW APPLICATIONS !LL OF THE MOST POPULAR $"-3 PRODUCTS/RACLE )NFORMIX 3YBASE 31, 3ERVER $" AND MANY MOREOFFERED CLIENT SERVER CAPABILITY 4HE DATABASE INDUSTRY GREW TO INCLUDE MANY COMPANIES OFFERING TOOLS FOR BUILDING CLIENTSERVER APPLICATIONS 3OME OF THESE CAME FROM THE DATABASE COMPANIES THEMSELVES OTHERS CAME FROM INDEPENDENT COMPANIES ,IKE ALL ARCHITECTURES CLIENTSERVER HAD ITS DISADVANTAGES 4HE MOST SERIOUS OF THESE WAS THE PROBLEM OF MANAGING THE APPLICATIONS SOFTWARE THAT WAS NOW DISTRIBUTED ACROSS HUNDREDS OR THOUSANDS OF DESKTOP 0#S INSTEAD OF RUNNING ON A CENTRAL MINICOMPUTER OR MAINFRAME 4O UPDATE AN APPLICATION PROGRAM IN A LARGE COMPANY THE INFORMATION SYSTEMS DEPARTMENT HAD TO UPDATE THOUSANDS OF 0# SYSTEMS ONE AT A TIME 4HE SITUATION WAS EVEN WORSE IF CHANGES TO THE APPLICATION PROGRAM HAD TO BE SYNCHRONIZED WITH CHANGES TO OTHER APPLICATIONS OR TO THE
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31,çINç0ERSPECTIVEç
-ULTITIERõ!RCHITECTURE 7ITH THE EMERGENCE OF THE )NTERNET AND ESPECIALLY THE 7ORLD 7IDE 7EB NETWORK DATABASE ARCHITECTURE TOOK ANOTHER STEP IN ITS EVOLUTION !T FIRST THE 7EB WAS USED TO ACCESS BROWSE STATIC DOCUMENTS AND EVOLVED OUTSIDE OF THE DATABASE WORLD "UT AS THE USE OF WEB BROWSERS BECAME WIDESPREAD IT WASNT LONG BEFORE COMPANIES THOUGHT ABOUT USING THEM AS A SIMPLE WAY TO PROVIDE ACCESS TO CORPORATE DATABASES AS WELL &OR EXAMPLE SUPPOSE A COMPANY STARTS USING THE 7EB TO PROVIDE PRODUCT INFORMATION TO ITS CUSTOMERS BY MAKING PRODUCT DESCRIPTIONS AND GRAPHICS AVAILABLE ON ITS WEB SITE ! NATURAL NEXT STEP IS TO GIVE CUSTOMERS ACCESS TO CURRENT PRODUCT AVAILABILITY INFORMATION THROUGH THE SAME WEB BROWSER INTERFACE 4HIS REQUIRES LINKING THE WEB SERVER TO THE DATABASE SYSTEM THAT STORES THE CONSTANTLY CHANGING CURRENT PRODUCT INVENTORY LEVELS 4HE METHODS USED TO LINK WEB SERVERS AND $"-3 SYSTEMS EVOLVED RAPIDLY IN THE LATE S AND EARLY S AND HAVE CONVERGED ON THE THREE TIER NETWORK ARCHITECTURE SHOWN IN &IGURE 4HE USER INTERFACE IS A WEB BROWSER RUNNING ON A 0# OR SOME OTHER THIN CLIENT
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$"-3 SYSTEM ITSELF )N ADDITION WITH PERSONAL COMPUTERS ON USERS DESKS USERS TENDED TO ADD NEW PERSONAL SOFTWARE OF THEIR OWN OR TO CHANGE THE CONFIGURATION OF THEIR SYSTEMS 3UCH CHANGES OFTEN DISRUPTED EXISTING APPLICATIONS ADDING TO THE SUPPORT BURDEN #OMPANIES DEVELOPED STRATEGIES TO DEAL WITH THESE ISSUES BUT BY THE LATE S THERE WAS GROWING CONCERN ABOUT THE MANAGEABILITY OF CLIENTSERVER APPLICATIONS ON LARGE DISTRIBUTED 0# NETWORKS
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!Nç/VERVIEWçOFç31,
DEVICE SUCH AS SMART PHONE IN THE FRONT END TIER )T COMMUNICATES WITH A WEB SERVER IN THE MIDDLE TIER 7HEN THE USER REQUEST IS FOR SOMETHING MORE COMPLEX THAN A SIMPLE WEB PAGE THE WEB SERVER PASSES THE REQUEST TO AN APPLICATION SERVER WHOSE ROLE IS TO HANDLE THE BUSINESS LOGIC REQUIRED TO PROCESS THE REQUEST /FTEN THE REQUEST WILL INVOLVE ACCESS TO AN EXISTING LEGACY APPLICATION RUNNING ON A MAINFRAME SYSTEM OR TO A CORPORATE DATABASE 4HESE SYSTEMS RUN IN THE BACK END TIER OF THE ARCHITECTURE !S WITH THE CLIENTSERVER ARCHITECTURE 31, IS SOLIDLY ENTRENCHED AS THE STANDARD DATABASE LANGUAGE FOR COMMUNICATING BETWEEN THE APPLICATION SERVER AND BACK END DATABASES !LL OF THE PACKAGED APPLICATION SERVER PRODUCTS PROVIDE A 31, BASED CALLABLE !0) FOR DATABASE ACCESS !S MUCH OF THE APPLICATION SERVER MARKET HAS CONVERGED AROUND THE *AVA %NTERPRISE %DITION *%% STANDARD *AVA $ATABASE #ONNECTIVITY *$"# HAS EMERGED AS THE LEADING STANDARD !0) FOR APPLICATION SERVER ACCESS TO DATABASES
4HEõ0ROLIFERATIONõOFõ31, !S THE STANDARD FOR RELATIONAL DATABASE ACCESS 31, HAS HAD A MAJOR IMPACT ON ALL PARTS OF THE COMPUTER MARKET )"-S 31, BASED $" DOMINATES MAINFRAME DATA MANAGEMENT /RACLES 31, BASED DATABASE DOMINATES THE MARKET FOR 5.)8 BASED COMPUTER SYSTEMS AND SERVERS -ICROSOFTS 31, 3ERVER DOMINATES ON SERVER ORIENTED 7INDOWS OPERATING SYSTEMS FOR WORKGROUPS AND DEPARTMENTAL APPLICATIONS -Y31, DOMINATES THE OPEN SOURCE DATABASE MARKET 31, IS ACCEPTED AS A TECHNOLOGY FOR ONLINE TRANSACTION PROCESSING /,40 FULLY REFUTING THE CONVENTIONAL WISDOM OF THE S THAT RELATIONAL DATABASES WOULD NEVER OFFER PERFORMANCE GOOD ENOUGH FOR TRANSACTION PROCESSING APPLICATIONS 31, BASED DATA WAREHOUSING AND DATA MINING APPLICATIONS ARE THE STANDARD FOR HELPING COMPANIES TO DISCOVER CUSTOMER PURCHASE PATTERNS AND TO OFFER BETTER PRODUCTS AND SERVICES /N THE )NTERNET 31, BASED DATABASES ARE THE FOUNDATION OF MORE PERSONALIZED PRODUCTS SERVICES AND INFORMATION SERVICES THAT ARE A KEY BENEFIT OF ELECTRONIC COMMERCE
31,õONõ-AINFRAMES !LTHOUGH )"-S HIERARCHICAL )-3 DATABASE IS STILL OFFERED ON )"- MAINFRAMES AND STILL RUNS MANY HIGH PERFORMANCE MAINFRAME APPLICATIONS )"-S 31, BASED $" HAS BEEN ITS FLAGSHIP MAINFRAME DATABASE FOR MORE THAN TWO DECADES )"- OFFERS $" IMPLEMENTATIONS ACROSS DIFFERENT COMPUTER SYSTEMS ARCHITECTURES BUT THE MAINFRAME $" IS STILL THE hMOTHER SHIP v GENERATING THE VAST MAJORITY OF )"-S DATABASE REVENUES !NY NEW DATABASE DEVELOPMENT ON MAINFRAME SYSTEMS TODAY USES $" CEMENTING 31,S DOMINANT ROLE FOR MAINFRAME DATA MANAGEMENT
31,õONõ-INICOMPUTERS -INICOMPUTERS WERE ONE OF THE MOST FERTILE EARLY MARKETS FOR 31, BASED DATABASE SYSTEMS /RACLE AND )NGRES WERE BOTH ORIGINALLY MARKETED ON $IGITALS 6!86-3 MINICOMPUTER SYSTEMS "OTH PRODUCTS WERE SUBSEQUENTLY PORTED TO MANY OTHER PLATFORMS 3YBASE A LATER DATABASE SYSTEM SPECIALIZED FOR ONLINE TRANSACTION PROCESSING ALSO TARGETED THE 6!8 AS ONE OF ITS PRIMARY PLATFORMS 4HROUGH THE S THE MINICOMPUTER VENDORS ALSO DEVELOPED THEIR OWN PROPRIETARY RELATIONAL DATABASES FEATURING 31, $IGITAL CONSIDERED RELATIONAL DATABASES SO IMPORTANT THAT IT BUNDLED A RUNTIME VERSION OF ITS 2DB6-3 DATABASE WITH EVERY 6!86-3 SYSTEM
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31,çINç0ERSPECTIVEç
31,õONõ5.)8 "ASEDõ3YSTEMS 31, IS FIRMLY ESTABLISHED AS THE DATA MANAGEMENT SOLUTION OF CHOICE FOR 5.)8 BASED COMPUTER SYSTEMS /RIGINALLY DEVELOPED AT "ELL ,ABORATORIES 5.)8 BECAME VERY POPULAR IN THE S AS A VENDOR INDEPENDENT STANDARD OPERATING SYSTEM )T RUNS ON A WIDE RANGE OF COMPUTER SYSTEMS FROM WORKSTATIONS TO MAINFRAMES AND HAS BECOME THE STANDARD OPERATING SYSTEM FOR HIGH END SERVER SYSTEMS INCLUDING DATABASE SERVERS )N THE EARLY S FOUR MAJOR DATABASES WERE ALREADY AVAILABLE FOR 5.)8 SYSTEMS 4WO OF THEM )NGRES AND /RACLE WERE 5.)8 VERSIONS OF THE PRODUCTS THAT RAN ON $%#S PROPRIETARY MINICOMPUTERS 4HE OTHER TWO )NFORMIX AND 5NIFY WERE WRITTEN SPECIFICALLY FOR 5.)8 .EITHER OF THEM ORIGINALLY OFFERED 31, SUPPORT BUT BY 5NIFY OFFERED A 31, QUERY LANGUAGE AND )NFORMIX HAD BEEN REWRITTEN AS )NFORMIX 31, WITH FULL 31, SUPPORT 4ODAY THE /RACLE DATABASE DOMINATES THE 5.)8 BASED DATABASE MARKET AND IS AVAILABLE ON ALL OF THE LEADING 5.)8 SERVER PLATFORMS )NFORMIX WAS ACQUIRED BY )"- WHICH STILL OFFERS THE PRODUCT FOR ITS OWN AND OTHER 5.)8 BASED SERVERS 5.)8 BASED AND INCREASINGLY ,INUX BASED DATABASE SERVERS ARE A MAINSTREAM BUILDING BLOCK FOR BOTH CLIENTSERVER AND THREE TIER )NTERNET ARCHITECTURES 4HE CONSTANT SEARCH FOR HIGHER 31, DATABASE PERFORMANCE HAS DRIVEN SOME OF THE MOST IMPORTANT TRENDS IN 5.)8 SYSTEM HARDWARE 4HESE INCLUDE THE EMERGENCE OF SYMMETRIC MULTIPROCESSING 3-0 AS A MAINSTREAM SERVER ARCHITECTURE THE DEVELOPMENT OF MULTICORE MICROPROCESSORS WHICH TOOK 3-0 TO THE CHIP LEVEL AND THE USE OF 2!)$ 2EDUNDANT !RRAY OF )NDEPENDENT $ISKS TECHNOLOGY TO BOOST )/ PERFORMANCE
31,õONõ0ERSONALõ#OMPUTERS $ATABASES HAVE BEEN POPULAR ON PERSONAL COMPUTERS SINCE THE EARLY DAYS OF THE )"- 0# !SHTON 4ATES D"!3% PRODUCT REACHED AN INSTALLED BASE OF OVER MILLION -3 $/3 BASED 0#S !LTHOUGH THESE EARLY 0# DATABASES OFTEN PRESENTED DATA IN TABULAR FORM THEY LACKED THE FULL POWER OF A RELATIONAL $"-3 AND A RELATIONAL DATABASE LANGUAGE SUCH AS 31, 4HE FIRST 31, BASED 0# DATABASES WERE VERSIONS OF POPULAR MINICOMPUTER PRODUCTS THAT BARELY FIT ON PERSONAL COMPUTERS &OR EXAMPLE 0ROFESSIONAL /RACLE FOR THE )"- 0# INTRODUCED IN REQUIRED TWO MEGABYTES OF MEMORYWELL ABOVE THE TYPICAL +" 0# CONFIGURATION OF THE DAY 4HE REAL IMPACT OF 31, ON PERSONAL COMPUTERS BEGAN WITH THE ANNOUNCEMENT OF /3 BY )"- AND -ICROSOFT IN !PRIL )N ADDITION TO THE STANDARD /3 PRODUCT )"- ANNOUNCED A PROPRIETARY /3 %XTENDED %DITION /3 %% WITH A BUILT IN 31, DATABASE
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(EWLETT 0ACKARD OFFERED !LLBASE A DATABASE THAT SUPPORTED BOTH ITS (031, DIALECT AND A NONRELATIONAL INTERFACE $ATA 'ENERALS $'31, DATABASE REPLACED ITS OLDER NONRELATIONAL DATABASES AS $'S STRATEGIC DATA MANAGEMENT TOOL )N ADDITION MANY OF THE MINICOMPUTER VENDORS RESOLD RELATIONAL DATABASES FROM THE INDEPENDENT DATABASE SOFTWARE VENDORS 4HESE EFFORTS HELPED TO ESTABLISH 31, AS AN IMPORTANT TECHNOLOGY FOR MIDRANGE COMPUTER SYSTEMS "Y THE MID S THE MINICOMPUTER VENDORS 31, PRODUCTS HAD LARGELY DISAPPEARED BEATEN IN THE MARKETPLACE BY MULTIPLATFORM SOFTWARE FROM /RACLE )NFORMIX 3YBASE AND OTHERS /RACLE ACQUIRED $IGITALS 2DB AND THE OTHER PRODUCTS WERE GRADUALLY DROPPED 0ARALLELING THIS TREND THE IMPORTANCE OF PROPRIETARY MINICOMPUTER OPERATING SYSTEMS FADED REPLACED BY WIDESPREAD USE OF 5.)8 ON MIDRANGE SYSTEMS 9ESTERDAYS MINICOMPUTER 31, MARKET HAS EFFECTIVELY BECOME TODAYS MARKET FOR 5.)8 BASED DATABASE SERVERS BASED ON 31,
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!Nç/VERVIEWçOFç31,
AND COMMUNICATIONS SUPPORT 7ITH THE INTRODUCTION )"- AGAIN SIGNALED ITS STRONG COMMITMENT TO 31, SAYING IN EFFECT THAT 31, WAS SO IMPORTANT THAT IT BELONGED IN THE COMPUTERS OPERATING SYSTEM /3 %XTENDED %DITION PRESENTED -ICROSOFT WITH A PROBLEM !S THE DEVELOPER AND DISTRIBUTOR OF STANDARD /3 TO OTHER PERSONAL COMPUTER MANUFACTURERS -ICROSOFT NEEDED AN ALTERNATIVE TO THE %XTENDED %DITION -ICROSOFT RESPONDED BY LICENSING THE 3YBASE $"-3 WHICH HAD BEEN DEVELOPED FOR 6!8 AND BEGAN PORTING IT TO /3 )N *ANUARY IN A SURPRISE MOVE -ICROSOFT AND !SHTON 4ATE THE 0# DATABASE LEADER AT THE TIME WITH ITS D"!3% PRODUCT ANNOUNCED THAT THEY WOULD JOINTLY SELL THE RESULTING /3 BASED PRODUCT RENAMED 31, 3ERVER -ICROSOFT WOULD SELL 31, 3ERVER WITH /3 TO COMPUTER MANUFACTURERS !SHTON 4ATE WOULD SELL THE PRODUCT THROUGH RETAIL CHANNELS TO 0# USERS )N 3EPTEMBER ,OTUS $EVELOPMENT THE OTHER MEMBER OF THE BIG THREE OF 0# SOFTWARE AT THE TIME ADDED ITS ENDORSEMENT OF 31, 3ERVER BY INVESTING IN 3YBASE ,ATER THAT YEAR !SHTON 4ATE RELINQUISHED ITS EXCLUSIVE RETAIL DISTRIBUTION RIGHTS AND SOLD ITS INVESTMENT TO ,OTUS 31, 3ERVER FOR /3 MET WITH ONLY LIMITED SUCCESS AS DID THE /3 OPERATING SYSTEM ITSELF "UT IN TYPICAL -ICROSOFT FASHION -ICROSOFT CONTINUED TO INVEST HEAVILY IN 31, 3ERVER DEVELOPMENT AND PORTED IT TO ITS 7INDOWS .4 OPERATING SYSTEM &OR A WHILE -ICROSOFT AND 3YBASE REMAINED PARTNERS WITH 3YBASE FOCUSED ON THE MINICOMPUTER AND 5.)8 BASED SERVER MARKETS AND -ICROSOFT FOCUSED ON 0# ,!.S AND 7INDOWS .4 !S 7INDOWS .4 AND 5.)8 SYSTEMS BECAME MORE AND MORE COMPETITIVE AS DATABASE SERVER OPERATING SYSTEM PLATFORMS THE RELATIONSHIP BECAME LESS COOPERATIVE AND MORE COMPETITIVE %VENTUALLY 3YBASE AND -ICROSOFT WENT THEIR SEPARATE WAYS 4HE COMMON HERITAGE OF 3YBASES AND -ICROSOFTS 31, PRODUCTS CAN STILL BE SEEN IN PRODUCT CAPABILITIES AND SOME COMMON 31, EXTENSIONS FOR EXAMPLE STORED PROCEDURES BUT THE PRODUCT LINES HAVE ALREADY DIVERGED SIGNIFICANTLY 4ODAY 31, 3ERVER IS A MAJOR DATABASE SYSTEM ON 7INDOWS BASED SERVERS )T HAS HAD A MAJOR NEW RELEASE EVERY TWO TO THREE YEARS ADDING MAJOR CAPABILITIES IN AREAS AS DIVERSE AS 8-, PROCESSING SPECIAL DATA FULL TEXT SEARCH DATA WAREHOUSING AND ANALYTICS AND HIGH AVAILABILITY 7HILE 5.)8 BASED SERVERS AND /RACLE DATABASES CONTINUE TO DOMINATE THE LARGEST DATABASE SERVER INSTALLATIONS SERVER CONFIGURATIONS OF THE 7INDOWS OPERATING SYSTEM AND THE )NTEL ARCHITECTURE SYSTEMS ON WHICH IT RUNS HAVE ACHIEVED CREDIBILITY IN THE MIDRANGE MARKET
31,õANDõ4RANSACTIONõ0ROCESSING 31, AND RELATIONAL DATABASES ORIGINALLY HAD VERY LITTLE IMPACT IN ONLINE TRANSACTION PROCESSING /,40 APPLICATIONS 7ITH THEIR EMPHASIS ON QUERIES RELATIONAL DATABASES WERE CONFINED TO DECISION SUPPORT AND LOW VOLUME ONLINE APPLICATIONS WHERE THEIR SLOWER PERFORMANCE WAS NOT A DISADVANTAGE &OR /,40 APPLICATIONS WHERE HUNDREDS OF USERS NEEDED ONLINE ACCESS TO DATA AND SUBSECOND RESPONSE TIMES )"-S NONRELATIONAL )NFORMATION -ANAGEMENT 3YSTEM )-3 REIGNED AS THE DOMINANT $"-3 )N A NEW $"-3 VENDOR 3YBASE INTRODUCED A NEW 31, BASED DATABASE ESPECIALLY DESIGNED FOR /,40 APPLICATIONS 4HE 3YBASE $"-3 RAN ON 6!86-3 MINICOMPUTERS AND 3UN WORKSTATIONS AND FOCUSED ON MAXIMUM ONLINE PERFORMANCE /RACLE #ORPORATION AND 2ELATIONAL 4ECHNOLOGY FOLLOWED SHORTLY WITH ANNOUNCEMENTS THAT THEY TOO WOULD OFFER /,40 VERSIONS OF THEIR POPULAR /RACLE AND )NGRES DATABASE SYSTEMS )N THE 5.)8 MARKET )NFORMIX ANNOUNCED AN /,40 VERSION OF ITS $"-3 NAMED )NFORMIX 4URBO
#HAPTERçç
31,çINç0ERSPECTIVEç
31,õANDõ7ORKGROUPõ$ATABASES 4HE DRAMATIC GROWTH OF 0# ,!.S THROUGH THE S AND S CREATED A NEW OPPORTUNITY FOR DEPARTMENTAL OR WORKGROUP DATABASE MANAGEMENT 4HE ORIGINAL DATABASE SYSTEMS FOCUSED ON THIS MARKET SEGMENT RAN ON )"-S /3 OPERATING SYSTEM )N FACT 31, 3ERVER NOW A KEY PART OF -ICROSOFTS 7INDOWS STRATEGY ORIGINALLY MADE ITS DEBUT AS AN /3 DATABASE PRODUCT )N THE MID S .OVELL ALSO MADE A CONCENTRATED EFFORT TO MAKE ITS .ET7ARE OPERATING SYSTEM AN ATTRACTIVE WORKGROUP DATABASE SERVER PLATFORM &ROM THE EARLIEST DAYS OF 0# ,!.S .ET7ARE HAD BECOME ESTABLISHED AS THE DOMINANT NETWORK OPERATING SYSTEM FOR FILE AND PRINT SERVERS 4HROUGH DEALS WITH /RACLE AND OTHERS .OVELL SOUGHT TO EXTEND THIS LEADERSHIP TO WORKGROUP DATABASE SERVERS AS WELL 4HE ARRIVAL OF 7INDOWS .4 A SPECIALIZED VERSION OF 7INDOWS TUNED FOR SERVER USE WAS THE CATALYST THAT CAUSED THE WORKGROUP DATABASE MARKET TO REALLY TAKE OFF 7HILE .ET7ARE OFFERED A CLEAR PERFORMANCE ADVANTAGE OVER .4 AS A WORKGROUP FILE SERVER .4 HAD A MORE ROBUST GENERAL PURPOSE ARCHITECTURE MORE LIKE THE MINICOMPUTER OPERATING SYSTEMS -ICROSOFT SUCCESSFULLY POSITIONED .4 AS A MORE ATTRACTIVE PLATFORM FOR RUNNING WORKGROUP APPLICATIONS AS AN APPLICATION SERVER AND WORKGROUP DATABASES -ICROSOFTS OWN 31, 3ERVER PRODUCT WAS MARKETED AND OFTEN BUNDLED WITH .4 AS A TIGHTLY INTEGRATED WORKGROUP DATABASE PLATFORM #ORPORATE INFORMATION SYSTEMS DEPARTMENTS WERE AT FIRST VERY CAUTIOUS ABOUT USING RELATIVELY NEW AND UNPROVEN TECHNOLOGY BUT THE .431, 3ERVER COMBINATION ALLOWED DEPARTMENTS AND NON )3 EXECUTIVES TO UNDERTAKE SMALLER SCALE WORKGROUP LEVEL PROJECTS ON THEIR OWN WITHOUT CORPORATE )3 HELP 4HIS PHENOMENON LIKE THE GRASSROOTS SUPPORT FOR PERSONAL COMPUTERS A DECADE EARLIER FUELED THE EARLY GROWTH OF THE WORKGROUP DATABASE SEGMENT
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)N )"- JUMPED ON THE RELATIONAL /,40 BANDWAGON WITH $" 6ERSION WITH BENCHMARKS SHOWING THE NEW VERSION OPERATING AT OVER TRANSACTIONS PER SECOND ON LARGE MAINFRAMES )"- CLAIMED THAT $" PERFORMANCE WAS NOW SUITABLE FOR ALL BUT THE MOST DEMANDING /,40 APPLICATIONS AND ENCOURAGED CUSTOMERS TO CONSIDER IT AS A SERIOUS ALTERNATIVE TO )-3 /,40 BENCHMARKS BECAME A STANDARD SALES TOOL FOR RELATIONAL DATABASES DESPITE SERIOUS QUESTIONS ABOUT HOW WELL THE BENCHMARKS ACTUALLY MEASURE PERFORMANCE IN REAL APPLICATIONS 4HE SUITABILITY OF 31, FOR /,40 IMPROVED DRAMATICALLY OVER THE NEXT DECADE WITH ADVANCES IN RELATIONAL TECHNOLOGY AND MORE POWERFUL COMPUTER HARDWARE BOTH LEADING TO EVER HIGHER TRANSACTION RATES $"-3 VENDORS STARTED TO POSITION THEIR PRODUCTS BASED ON THEIR /,40 PERFORMANCE AND FOR A FEW YEARS DATABASE ADVERTISING FOCUSED ALMOST ENTIRELY ON THESE PERFORMANCE BENCHMARK WARS ! VENDOR INDEPENDENT ORGANIZATION THE 4RANSACTION 0ROCESSING #OUNCIL JUMPED INTO THE BENCHMARKING FRAY WITH A SERIES OF VENDOR INDEPENDENT BENCHMARKS 40# ! 40# " AND 40# # WHICH ONLY SERVED TO INTENSIFY THE PERFORMANCE FOCUS OF THE VENDORS "Y THE EARLY S 31, BASED RELATIONAL DATABASES ON HIGH END 5.)8 BASED DATABASE SERVERS EVOLVED WELL PAST THE TRANSACTIONS PER SECOND MARK #LIENTSERVER SYSTEMS USING 31, DATABASES HAVE BECOME THE ACCEPTED ARCHITECTURE FOR IMPLEMENTING /,40 APPLICATIONS &ROM A POSITION AS hUNSUITABLE FOR /,40 v 31, HAS GROWN TO BE THE INDUSTRY STANDARD FOUNDATION FOR BUILDING /,40 APPLICATIONS
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!Nç/VERVIEWçOFç31,
4ODAY 31, IS WELL ESTABLISHED AS A WORKGROUP DATABASE STANDARD )N ADDITION TO -ICROSOFTS NEWER VERSIONS OF 7INDOWS FOR SERVERS ,INUX HAS EMERGED AS A VERY POPULAR PLATFORM FOR WORKGROUP SERVERS -ICROSOFT 31, 3ERVER AND /RACLE SHARE THE LARGEST PART OF THE MARKET BUT OPEN SOURCE DATABASES LIKE -Y31, HAVE EMERGED AS A VERY STRONG AND COST EFFECTIVE ALTERNATIVE 0OSTGRES ANOTHER OPEN SOURCE PRODUCT DEVELOPED AT THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEY AS A FOLLOW ON TO )NGRES HAS ALSO GAINED A SMALLER BUT LOYAL FOLLOWING IN THIS SEGMENT
31, õ$ATAõ7AREHOUSING õANDõ"USINESSõ)NTELLIGENCE &OR SEVERAL YEARS THE EFFORT TO MAKE 31, A VIABLE TECHNOLOGY FOR /,40 APPLICATIONS SHIFTED THE FOCUS AWAY FROM THE ORIGINAL RELATIONAL DATABASE STRENGTHS OF QUERY PROCESSING AND DECISION MAKING 0ERFORMANCE BENCHMARKS AND COMPETITION AMONG THE MAJOR $"-3 BRANDS FOCUSED ON SIMPLE TRANSACTIONS LIKE ADDING A NEW ORDER TO THE DATABASE OR DETERMINING A CUSTOMERS ACCOUNT BALANCE "ECAUSE OF THE POWER OF THE RELATIONAL DATABASE MODEL THE DATABASES THAT COMPANIES USED TO HANDLE DAILY BUSINESS OPERATIONS COULD ALSO BE USED TO ANALYZE THE GROWING AMOUNTS OF DATA THAT WERE BEING ACCUMULATED ! FREQUENT THEME OF CONFERENCES AND TRADESHOW SPEECHES FOR )3 MANAGERS WAS THAT A CORPORATIONS ACCUMULATED DATA STORED IN 31, DATABASES OF COURSE SHOULD BE TREATED AS A VALUABLE ASSET AND USED TO HELP IMPROVE THE QUALITY OF BUSINESS DECISION MAKING !LTHOUGH RELATIONAL DATABASES COULD IN THEORY EASILY PERFORM BOTH /,40 AND DECISION MAKING APPLICATIONS THERE WERE SOME VERY SIGNIFICANT PRACTICAL PROBLEMS /,40 WORKLOADS CONSISTED OF MANY SHORT DATABASE TRANSACTIONS AND THE RESPONSE TIME FOR USERS WAS VERY IMPORTANT )N CONTRAST DECISION SUPPORT QUERIES COULD INVOLVE SEQUENTIAL SCANS OF LARGE DATABASE TABLES TO ANSWER QUESTIONS LIKE h7HAT IS THE AVERAGE ORDER SIZE BY SALES REGION v OR h(OW DO INVENTORY TRENDS COMPARE WITH THE SAME TIME A YEAR AGO v 4HESE QUERIES COULD TAKE MINUTES OR HOURS )F A BUSINESS ANALYST TRIED TO RUN ONE OF THESE QUERIES DURING A TIME WHEN BUSINESS TRANSACTION VOLUMES REACHED THEIR PEAK IT COULD CAUSE SERIOUS DEGRADATION IN /,40 PERFORMANCE !NOTHER PROBLEM WAS THAT THE DATA TO ANSWER USEFUL QUESTIONS ABOUT BUSINESS TRENDS WAS OFTEN SPREAD ACROSS MANY DIFFERENT DATABASES TYPICALLY INVOLVING DIFFERENT $"-3 VENDORS AND DIFFERENT COMPUTER PLATFORMS 4HE DESIRE TO TAKE ADVANTAGE OF ACCUMULATED BUSINESS DATA AND THE PRACTICAL PERFORMANCE PROBLEMS IT CAUSED FOR /,40 APPLICATIONS LED TO THE CONCEPT OF A DATA WAREHOUSE SHOWN IN &IGURE "USINESS DATA IS EXTRACTED FROM /,40 SYSTEMS REFORMATTED AND VALIDATED AS NECESSARY AND THEN PLACED INTO A SEPARATE DATABASE THAT IS DEDICATED TO DECISION MAKING QUERIES THE hWAREHOUSEv 4HE DATA EXTRACTION AND TRANSFORMATION CAN BE SCHEDULED FOR OFF HOURS BATCH PROCESSING )DEALLY ONLY NEW OR CHANGED DATA CAN BE EXTRACTED MINIMIZING THE AMOUNT OF DATA TO BE PROCESSED IN THE MONTHLY WEEKLY OR DAILY WAREHOUSE REFRESH CYCLE 7ITH THIS SCHEME THE TIME CONSUMING BUSINESS ANALYSIS QUERIES USE THE DATA WAREHOUSE NOT THE /,40 DATABASE AS THEIR SOURCE OF DATA 31, BASED RELATIONAL DATABASES WERE A CLEAR CHOICE FOR THE WAREHOUSE DATA STORE BECAUSE OF THEIR FLEXIBLE QUERY PROCESSING ! SERIES OF NEW COMPANIES WAS FORMED TO BUILD THE DATA EXTRACTION TRANSFORMATION AND DATABASE QUERY TOOLS NEEDED BY THE DATA WAREHOUSE MODEL )N ADDITION $"-3 VENDORS STARTED TO FOCUS ON THE KINDS OF DATABASE QUERIES THAT CUSTOMERS TENDED TO RUN IN THE DATA WAREHOUSE 4HESE QUERIES TENDED TO BE LARGE AND COMPLEXSUCH AS ANALYZING TENS OR HUNDREDS OF MILLIONS OF INDIVIDUAL CASH REGISTER RECEIPTS LOOKING FOR PRODUCT PURCHASE PATTERNS 4HEY OFTEN INVOLVED TIME SERIES DATAFOR EXAMPLE ANALYZING
#HAPTERçç
31,çINç0ERSPECTIVEç
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PRODUCT SALES OR MARKET SHARE DATA OVER TIME 4HEY ALSO TENDED TO INVOLVE STATISTICAL SUMMARIES OF DATATOTAL SALES AVERAGE ORDER VOLUME PERCENT GROWTH AND SO ONRATHER THAN THE INDIVIDUAL DATA ITEMS THEMSELVES 4O ADDRESS THE SPECIALIZED NEEDS OF DATA WAREHOUSING APPLICATIONS OFTEN CALLED /NLINE !NALYTICAL 0ROCESSING OR /,!0 SPECIALIZED DATABASES BEGAN TO APPEAR 4HESE DATABASES WERE OPTIMIZED FOR /,!0 WORKLOADS IN SEVERAL DIFFERENT WAYS 4HEIR PERFORMANCE WAS TUNED FOR COMPLEX READ ONLY QUERY ACCESS 4HEY SUPPORTED ADVANCED STATISTICAL AND OTHER DATA FUNCTIONS SUCH AS BUILT IN TIME SERIES PROCESSING 4HEY SUPPORTED PRECALCULATION OF DATABASE STATISTICAL DATA SO THAT RETRIEVING AVERAGES AND TOTALS COULD BE DRAMATICALLY FASTER 3OME OF THESE SPECIALIZED DATABASES DID NOT USE 31, BUT MANY DID LEADING TO THE COMPANION TERM 2/,!0 FOR 2ELATIONAL /NLINE !NALYTICAL 0ROCESSING !S THE MARKET FOR DATA WAREHOUSING CONTINUED TO EVOLVE THE TOOLS TO TAP THE WAREHOUSE EMERGED AS AN IMPORTANT MARKET SEGMENT IN THEIR OWN RIGHT OFTEN LABELED BUSINESS INTELLIGENCE 4HE LINES BETWEEN THE VENDORS THAT SUPPLIED THE WAREHOUSE DATABASES THE TOOLS TO POPULATE THEM AND THE TOOLS TO ANALYZE DATA GRADUALLY BLURRED AS THE MARKET GREW 4HREE OF THE LARGEST BUSINESS INTELLIGENCE VENDORS BECAME SUCCESSFUL PUBLIC COMPANIES IN THEIR OWN RIGHT BEFORE
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!Nç/VERVIEWçOFç31,
BEING ACQUIRED BY THREE OF THE INDUSTRY GIANTS "USINESS /BJECTS WAS ACQUIRED BY 3!0 THE LEADING VENDOR OF ENTERPRISE APPLICATIONS (YPERION WAS ACQUIRED BY /RACLE AND #OGNOS WAS ACQUIRED BY )"- !S WITH SO MANY SEGMENTS OF THE )4 MARKET 31,S ADVANTAGES AS A STANDARD PROVED TO BE A POWERFUL FORCE AND 31, BASED DATA WAREHOUSES AND ANALYTIC TOOLS ARE FIRMLY ENTRENCHED
31,õANDõ)NTERNETõ!PPLICATIONS $URING THE LATE S THE 7ORLD 7IDE 7EB AND THE WEB BROWSING CAPABILITY THAT IT ENABLED WERE THE DRIVING FORCE BEHIND THE GROWTH OF THE )NTERNET 7ITH ITS FOCUS ON DELIVERING CONTENT IN THE FORM OF TEXT AND GRAPHICS THE EARLY USES OF THE 7EB HAD LITTLE TO DO WITH DATA MANAGEMENT "Y THE MID S HOWEVER MUCH OF THE CONTENT DELIVERED FROM CORPORATE WEB SITES HAD ITS ORIGINS IN 31, BASED CORPORATE DATABASES &OR EXAMPLE ON A COMMERCIAL WEB SITE FOR A RETAILER WEB PAGES THAT CONTAIN INFORMATION ABOUT PRODUCTS AVAILABLE FOR SALE THEIR PRICES PRODUCT AVAILABILITY SPECIAL PROMOTIONS AND THE LIKE ARE TYPICALLY CREATED ON DEMAND BASED ON DATA RETRIEVED FROM A 31, DATABASE 4HE VAST MAJORITY OF THE PAGES DISPLAYED BY AN ONLINE AUCTION SITE OR BY AN ONLINE TRAVEL SITE ARE SIMILARLY BASED ON DATA RETRIEVED FROM 31, DATABASES TRANSFORMED INTO THE 7EBS (4-, PAGE FORMAT )N THE OTHER DIRECTION DATA ENTERED BY A USER INTO BROWSER PAGE FORMS IS ALMOST ALWAYS CAPTURED INTO 31, DATABASES THAT FORM PART OF THE WEB SITE ARCHITECTURE "Y THE EARLY S INDUSTRY ATTENTION HAD TURNED TO THE NEXT PHASE OF THE )NTERNET AND THE ROLE THAT )NTERNET TECHNOLOGIES CAN PLAY IN CONNECTING COMPUTER APPLICATIONS TO ONE ANOTHER 4HESE DISTRIBUTED APPLICATIONS ARCHITECTURES RECEIVED WIDESPREAD TRADE PRESS COVERAGE UNDER THE BANNER OF WEB SERVICES )N THE LONGSTANDING TRADITION OF THE COMPUTER INDUSTRY COMPETING CAMPS EMERGED CHAMPIONING DIFFERENT SETS OF STANDARDS AND LANGUAGES FOR IMPLEMENTING THEMA -ICROSOFT LED CAMP UNDER THE .%4 &RAMEWORK AND A RIVAL CAMP FOCUSED ON *AVA AND *%% BASED APPLICATION SERVERS "OTH ARCHITECTURES EMBRACE A KEY ROLE FOR 8-, A STANDARD FOR EXCHANGING STRUCTURED DATA LIKE THE DATA THAT RESIDES IN 31, DATABASES )N RESPONSE TO THE INDUSTRY ATTENTION ON WEB SERVICES A FLURRY OF PRODUCTS HAS BEEN ANNOUNCED THAT LINK 8-, FORMATTED MESSAGES TO 31, BASED DATABASES 3TARTUP DATABASE VENDORS AND SOME OF THE OBJECT DATABASE VENDORS ANNOUNCED 8-, BASED DATABASE PRODUCTS ARGUING THAT THEY PROVIDE AN IDEAL NATIVE MATCH FOR THE 8-, FORMATTED EXCHANGE OF DATA OVER THE )NTERNET 4HE ESTABLISHED RELATIONAL DATABASE PLAYERS RESPONDED WITH THEIR OWN 8-, INITIATIVES ADDING 8-, INPUTOUTPUT CAPABILITIES AND THEN NATIVE 8-, DATA TYPE SUPPORT TO THEIR PRODUCTS 4IGHTER INTEGRATION BETWEEN 8-, AND 31, REMAINS AN ACTIVE AREA OF INVESTMENT BY ALL OF THE MAJOR DATABASE VENDORS TODAY 4HE )NTERNET APPROACH TO SCALABILITY IS ALSO HAVING A MAJOR IMPACT ON DATABASE SOFTWARE PRODUCTS -ANY )NTERNET SOFTWARE ELEMENTS OPERATE AT h)NTERNET SCALEv THROUGH A HORIZONTAL SCALING APPROACH SPREADING OUT THEIR WORKLOAD ACROSS DOZENS OR HUNDREDS OF LOW COST COMMODITY SERVERS 4HE 'OOGLE SEARCH ENGINE IS ONE OF THE MOST EXTREME EXAMPLES OF THIS ARCHITECTURE WHERE EVEN A SINGLE SEARCH CAN BE DISTRIBUTED ACROSS DOZENS OF SERVERS AND THE TOTAL SEARCH VOLUME IS DISTRIBUTED ACROSS TENS OF THOUSANDS OF SERVERS ALL LOCATED IN THE h)NTERNET CLOUDv 4HERE ARE MAJOR CHALLENGES TO APPLYING THIS APPROACH TO DATABASE MANAGEMENT BUT PROVIDING DATA MANAGEMENT hIN THE CLOUDv IS AN ACTIVE TOPIC OF RESEARCH AND DEVELOPMENT IN THE DATABASE COMMUNITY
#HAPTERçç
31,çINç0ERSPECTIVEç
3UMMARY s 31, WAS ORIGINALLY DEVELOPED BY )"- RESEARCHERS AND )"-S STRONG SUPPORT OF 31, WAS A KEY REASON FOR ITS EARLY SUCCESS s 4HERE IS AN OFFICIAL !.3))3/ 31, STANDARD WHICH HAS GROWN TREMENDOUSLY IN SCOPE AND COMPLEXITY SINCE ITS DEBUT IN s $ESPITE THE EXISTENCE OF A STANDARD THERE ARE MANY SMALL VARIATIONS AMONG COMMERCIAL 31, DIALECTS NO TWO 31, IMPLEMENTATIONS ARE EXACTLY THE SAME s 31, HAS BECOME THE STANDARD DATABASE MANAGEMENT LANGUAGE ACROSS A BROAD RANGE OF COMPUTER SYSTEMS AND APPLICATIONS AREAS INCLUDING MAINFRAMES WORKSTATIONS PERSONAL COMPUTERS /,40 SYSTEMS CLIENTSERVER SYSTEMS DATA WAREHOUSING AND THE )NTERNET
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4HIS CHAPTER DESCRIBED THE DEVELOPMENT OF 31, AND ITS ROLE AS A STANDARD LANGUAGE FOR RELATIONAL DATABASE MANAGEMENT
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#(!04%2
2ELATIONALç$ATABASES
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ATABASE MANAGEMENT SYSTEMS ORGANIZE AND STRUCTURE DATA SO THAT IT CAN BE SAVED AND RETRIEVED BY USERS AND APPLICATION PROGRAMS 4HE DATA STRUCTURES AND ACCESS TECHNIQUES PROVIDED BY A PARTICULAR $"-3 ARE CALLED ITS DATA MODEL ! DATA MODEL DETERMINES BOTH THE hPERSONALITYv OF A $"-3 AND THE APPLICATIONS FOR WHICH IT IS PARTICULARLY WELL SUITED 31, IS A DATABASE LANGUAGE FOR DATABASES THAT USE THE RELATIONAL DATA MODEL 7HAT EXACTLY IS A RELATIONAL DATABASE (OW IS DATA STORED IN A RELATIONAL DATABASE (OW DO RELATIONAL DATABASES COMPARE WITH EARLIER TECHNOLOGIES SUCH AS HIERARCHICAL AND NETWORK DATABASES 7HAT ARE THE ADVANTAGES AND DISADVANTAGES OF THE RELATIONAL MODEL 4HIS CHAPTER DESCRIBES THE RELATIONAL DATA MODEL SUPPORTED BY 31, AND COMPARES IT WITH EARLIER STRATEGIES FOR DATABASE ORGANIZATION
%ARLYõ$ATAõ-ODELS !S DATABASE MANAGEMENT BECAME POPULAR DURING THE S AND S A HANDFUL OF POPULAR DATA MODELS EMERGED %ACH OF THESE EARLY DATA MODELS HAD ADVANTAGES AND DISADVANTAGES THAT PLAYED KEY ROLES IN THE DEVELOPMENT OF THE RELATIONAL DATA MODEL )N MANY WAYS THE RELATIONAL DATA MODEL REPRESENTED AN ATTEMPT TO STREAMLINE AND SIMPLIFY THE EARLIER DATA MODELS 4O UNDERSTAND THE ROLE AND CONTRIBUTION OF 31, AND THE RELATIONAL MODEL IT IS USEFUL TO BRIEFLY EXAMINE SOME DATA MODELS THAT PRECEDED THE DEVELOPMENT OF 31, SOME OF WHICH ARE STILL IN USE TODAY
&ILEõ-ANAGEMENTõ3YSTEMS "EFORE THE INTRODUCTION OF DATABASE MANAGEMENT SYSTEMS ALL DATA PERMANENTLY STORED ON A COMPUTER SYSTEM SUCH AS PAYROLL AND ACCOUNTING RECORDS WAS STORED IN INDIVIDUAL FILES ! FILE MANAGEMENT SYSTEM USUALLY PROVIDED AS PART OF THE COMPUTERS OPERATING SYSTEM KEPT TRACK OF THE NAMES AND LOCATIONS OF THE FILES &ILE MANAGEMENT SYSTEMS ARE STILL WIDELY USED TODAYYOU ARE PROBABLY FAMILIAR WITH THE FILES AND FOLDERS STRUCTURE PROVIDED BY THE FILE SYSTEM ON -ICROSOFT 7INDOWS OR !PPLES -ACINTOSH OPERATING SYSTEMS 3IMILAR FILE SYSTEMS ARE USED BY 5.)8 BASED SERVERS AND ALL COMMERCIAL COMPUTER SYSTEMS ! FILE MANAGEMENT SYSTEM BASICALLY HAS NO DATA MODEL IT KNOWS NOTHING ABOUT THE INTERNAL CONTENTS OF FILES !T BEST THE FILE SYSTEM MIGHT MAINTAIN hFILE TYPEv INFORMATION
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!Nç/VERVIEWçOFç31,
ALONG WITH THE FILENAME ALLOWING IT TO DISTINGUISH BETWEEN A WORD PROCESSING DOCUMENT AND A FILE CONTAINING PAYROLL DATA "UT KNOWLEDGE ABOUT THE INTERNAL CONTENTS OF A FILEWHAT INDIVIDUAL PIECES OF DATA IT CONTAINS AND HOW THAT DATA IS ORGANIZEDIS EMBEDDED IN THE APPLICATION PROGRAMS THAT USE THE FILE AS SHOWN IN &IGURE )N THIS PAYROLL APPLICATION EACH OF THE #/"/, PROGRAMS THAT PROCESSES THE EMPLOYEE MASTER FILE CONTAINS A FILE DESCRIPTION &$ THAT DESCRIBES THE LAYOUT OF THE DATA IN THE FILE )F THE STRUCTURE OF THE DATA CHANGESFOR EXAMPLE IF AN ADDITIONAL ITEM OF DATA IS TO BE STORED FOR EACH EMPLOYEE EVERY PROGRAM THAT ACCESSES THE FILE HAS TO BE MODIFIED 4HIS ISNT A PROBLEM FOR FILES CONTAINING WORD PROCESSING DOCUMENTS OR SPREADSHEETS WHICH ARE USUALLY PROCESSED BY A SINGLE PROGRAM "UT IN CORPORATE DATA PROCESSING FILES ARE OFTEN SHARED AMONG DOZENS OR EVEN HUNDREDS OF PROGRAMS AS IN &IGURE !S THE NUMBER OF FILES AND PROGRAMS GROWS OVER TIME MORE AND MORE OF A DATA PROCESSING DEPARTMENTS EFFORT GOES INTO MAINTAINING EXISTING APPLICATIONS RATHER THAN DEVELOPING NEW ONES 4HE PROBLEMS OF MAINTAINING LARGE FILE BASED SYSTEMS LED IN THE LATE S TO THE DEVELOPMENT OF DATABASE MANAGEMENT SYSTEMS 4HE IDEA BEHIND THESE SYSTEMS WAS SIMPLE MOVE THE DEFINITION OF A FILES CONTENT AND STRUCTURE OUT OF THE INDIVIDUAL PROGRAMS AND STORE IT TOGETHER WITH THE DATA IN A DATABASE 5SING THE INFORMATION IN THE DATABASE THE $"-3 THAT CONTROLLED IT COULD TAKE A MUCH MORE ACTIVE ROLE IN MANAGING BOTH THE DATA AND CHANGES TO THE DATABASE STRUCTURE -OREOVER $"-3S ARE AN EXTENSION OF FILE MANAGEMENT SYSTEMS RATHER THAN A REPLACEMENT FOR THEM $"-3S USE FILE MANAGEMENT SYSTEMS USUALLY THE ONES SUPPLIED WITH THE OPERATING SYSTEM TO STORE THE DATABASE STRUCTURES 4HE DATABASE USER THEN REFERENCES THE $"-3 AND THE $"-3 HANDLES THE PHYSICAL STORAGE DETAILS )T IS THIS LAYER OF ABSTRACTION THAT PROVIDES PHYSICAL DATA INDEPENDENCE
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#HAPTERçç
2ELATIONALç$ATABASESç
(IERARCHICALõ$ATABASES
s &IND A PARTICULAR PART BY NUMBER SUCH AS THE LEFT DOOR s -OVE hDOWNv TO THE FIRST CHILD THE DOOR HANDLE s -OVE hUPv TO ITS PARENT THE BODY s -OVE hSIDEWAYSv TO THE NEXT CHILD THE RIGHT DOOR 2ETRIEVING THE DATA IN A HIERARCHICAL DATABASE THUS REQUIRED NAVIGATING THROUGH THE RECORDS MOVING UP DOWN AND SIDEWAYS ONE RECORD AT A TIME
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/NE OF THE MOST IMPORTANT APPLICATIONS FOR THE EARLIEST DATABASE MANAGEMENT SYSTEMS WAS MANAGING OPERATIONS FOR MANUFACTURING COMPANIES )F AN AUTOMOBILE MANUFACTURER DECIDED TO PRODUCE UNITS OF ONE CAR MODEL AND UNITS OF ANOTHER MODEL IT NEEDED TO KNOW HOW MANY PARTS TO ORDER FROM ITS SUPPLIERS 4O ANSWER THE QUESTION THE PRODUCT A CAR HAD TO BE DECOMPOSED INTO HUNDREDS OF ASSEMBLIES ENGINE BODY CHASSIS WHICH WERE DECOMPOSED INTO THOUSANDS OF SUBASSEMBLIES VALVES CYLINDERS SPARK PLUGS AND THEN INTO SUB SUBASSEMBLIES AND SO ON (ANDLING THIS LIST OF PARTS KNOWN AS A BILL OF MATERIALS WAS A JOB TAILOR MADE FOR COMPUTERS 4HE BILL OF MATERIALS FOR A PRODUCT HAS A NATURAL HIERARCHICAL STRUCTURE 4O STORE THIS DATA THE HIERARCHICAL DATA MODEL ILLUSTRATED IN &IGURE WAS DEVELOPED )N THIS MODEL EACH RECORD IN THE DATABASE REPRESENTED A SPECIFIC PART 4HE RECORDS HAD PARENTCHILD RELATIONSHIPS LINKING EACH PART TO ITS SUBPART AND SO ON 4O ACCESS THE DATA IN THE DATABASE A PROGRAM COULD PERFORM THE FOLLOWING TASKS
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/NE OF THE MOST POPULAR HIERARCHICAL DATABASE MANAGEMENT SYSTEMS WAS )"-S )NFORMATION -ANAGEMENT 3YSTEM )-3 FIRST INTRODUCED IN 4HE ADVANTAGES OF )-3 AND ITS HIERARCHICAL MODEL FOLLOW s 3IMPLE STRUCTURE 4HE ORGANIZATION OF AN )-3 DATABASE WAS EASY TO UNDERSTAND 4HE DATABASE HIERARCHY PARALLELED THAT OF A COMPANY ORGANIZATION CHART OR A FAMILY TREE s 0ARENTCHILD ORGANIZATION !N )-3 DATABASE WAS EXCELLENT FOR REPRESENTING PARENTCHILD RELATIONSHIPS SUCH AS h! IS A PART OF "v OR h! IS OWNED BY "v s 0ERFORMANCE )-3 STORED PARENTCHILD RELATIONSHIPS AS PHYSICAL POINTERS FROM ONE DATA RECORD TO ANOTHER SO THAT MOVEMENT THROUGH THE DATABASE WAS RAPID )-3 IS STILL A WIDELY USED $"-3 ON )"- MAINFRAMES )TS RAW PERFORMANCE MAKES IT IDEAL FOR VERY HIGH VOLUME TRANSACTION PROCESSING APPLICATIONS SUCH AS PROCESSING CREDIT CARD TRANSACTIONS OR BOOKING AIRLINE RESERVATIONS $RAMATIC IMPROVEMENTS IN RELATIONAL DATABASE PERFORMANCE OVER THE LAST TWO DECADES HAVE NARROWED )-3S PERFORMANCE ADVANTAGE BUT THE LARGE AMOUNT OF CORPORATE DATA STORED IN )-3 DATABASES AND THE LARGE NUMBER OF MATURE APPLICATIONS THAT PROCESS THAT DATA ENSURE THAT )-3 USE WILL CONTINUE FOR MANY YEARS TO COME
.ETWORKõ$ATABASES 4HE SIMPLE STRUCTURE OF A HIERARCHICAL DATABASE BECAME A DISADVANTAGE WHEN THE DATA HAD A MORE COMPLEX STRUCTURE )N AN ORDER PROCESSING DATABASE FOR EXAMPLE A SINGLE ORDER MIGHT PARTICIPATE IN THREE DIFFERENT PARENTCHILD RELATIONSHIPS LINKING THE ORDER TO THE CUSTOMER WHO PLACED IT THE SALESPERSON WHO TOOK IT AND THE PRODUCT ORDERED AS SHOWN IN &IGURE 4HIS TYPE OF DATA STRUCTURE SIMPLY DIDNT FIT THE STRICT HIERARCHY OF )-3 4O DEAL WITH APPLICATIONS SUCH AS ORDER PROCESSING A NEW NETWORK DATA MODEL WAS DEVELOPED 4HE NETWORK DATA MODEL EXTENDED THE HIERARCHICAL MODEL BY ALLOWING A RECORD TO PARTICIPATE IN MULTIPLE PARENTCHILD RELATIONSHIPS CALLED SETS AS SHOWN IN &IGURE
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2ELATIONALç$ATABASESç
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1, Ê{{Ê ÊiÌÜÀÊ " -9 ®ÊÀ`iÀ«ÀViÃÃ}Ê`>Ì>L>Ãi
)N THE #ONFERENCE ON $ATA 3YSTEMS ,ANGUAGES PUBLISHED AN OFFICIAL STANDARD FOR NETWORK DATABASES CALLED THE #/$!39, MODEL )"- NEVER DEVELOPED A NETWORK $"-3 BUT DURING THE S INDEPENDENT SOFTWARE COMPANIES RUSHED TO EMBRACE THE NETWORK MODEL CREATING PRODUCTS SUCH AS #ULLINETS )$-3 #INCOMS 4OTAL AND THE !DABAS $"-3 THAT BECAME VERY POPULAR (OWEVER )"- ENHANCED )-3 TO PROVIDE A WORKAROUND TO THE SINGLE PARENT RULE IN CLASSIC HIERARCHICAL STRUCTURES CALLING THE ADDITIONAL PARENTS LOGICAL PARENTS 4HE DATA MODEL BECAME KNOWN AS THE EXTENDED HIERARCHICAL MODEL AND IT MADE )-3 A DIRECT COMPETITOR WITH THE NETWORK $"-3 PRODUCTS &OR A PROGRAMMER ACCESSING A NETWORK DATABASE WAS VERY SIMILAR TO ACCESSING A HIERARCHICAL DATABASE !N APPLICATION PROGRAM COULD DO THE FOLLOWING s &IND A SPECIFIC PARENT RECORD BY KEY SUCH AS A CUSTOMER NUMBER s -OVE DOWN TO THE FIRST CHILD IN A PARTICULAR SET THE FIRST ORDER PLACED BY THIS CUSTOMER s -OVE SIDEWAYS FROM ONE CHILD TO THE NEXT IN THE SET THE NEXT ORDER PLACED BY THE SAME CUSTOMER s -OVE UP FROM A CHILD TO ITS PARENT IN ANOTHER SET THE SALESPERSON WHO TOOK THE ORDER /NCE AGAIN THE PROGRAMMER HAD TO NAVIGATE THE DATABASE RECORD BY RECORD THIS TIME SPECIFYING WHICH RELATIONSHIP TO NAVIGATE AS WELL AS THE DIRECTION .ETWORK DATABASES HAD SEVERAL ADVANTAGES s &LEXIBILITY -ULTIPLE PARENTCHILD RELATIONSHIPS ALLOWED A NETWORK DATABASE TO REPRESENT DATA THAT DID NOT HAVE A SIMPLE HIERARCHICAL STRUCTURE s 3TANDARDIZATION 4HE #/$!39, STANDARD BOOSTED THE POPULARITY OF THE NETWORK MODEL MAKING IT EASIER FOR PROGRAMMERS TO MOVE BETWEEN $"-3 PRODUCTS s 0ERFORMANCE 0ARENTCHILD SETS WERE REPRESENTED BY POINTERS TO PHYSICAL DATA RECORDS ALLOWING RAPID NAVIGATION THROUGH THESE RELATIONSHIPS
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.ETWORK DATABASES HAD THEIR DISADVANTAGES TOO ,IKE HIERARCHICAL DATABASES THEY WERE VERY RIGID 4HE SET RELATIONSHIPS AND THE STRUCTURE OF THE RECORDS HAD TO BE SPECIFIED IN ADVANCE #HANGING THE DATABASE STRUCTURE TYPICALLY REQUIRED REBUILDING THE ENTIRE DATABASE "OTH HIERARCHICAL AND NETWORK DATABASES WERE TOOLS FOR PROGRAMMERS 4O ANSWER A QUESTION SUCH AS h7HAT IS THE MOST POPULAR PRODUCT ORDERED BY !CME -ANUFACTURING v OR h(OW MANY ORDERS ARE THERE FOR 3IZE 7IDGETS v A PROGRAMMER HAD TO WRITE A PROGRAM THAT NAVIGATED ITS WAY THROUGH THE DATABASE FOUND THE APPROPRIATE RECORDS AND CALCULATED THE RESULT 4HE BACKLOG OF REQUESTS FOR CUSTOM REPORTS OFTEN STRETCHED TO WEEKS OR MONTHS AND BY THE TIME THE PROGRAM WAS WRITTEN THE INFORMATION IT DELIVERED WAS OFTEN WORTHLESS 4HE DISADVANTAGES OF THE HIERARCHICAL AND NETWORK MODELS LED TO INTENSE INTEREST IN THE NEW RELATIONAL DATA MODEL WHEN IT WAS FIRST DESCRIBED BY 4ED #ODD IN !T FIRST THE RELATIONAL MODEL WAS LITTLE MORE THAN AN ACADEMIC CURIOSITY .ETWORK DATABASES CONTINUED TO BE IMPORTANT THROUGHOUT THE S AND EARLY S PARTICULARLY ON THE MINICOMPUTER SYSTEMS THAT WERE SURGING IN POPULARITY (OWEVER BY THE MID S THE RELATIONAL MODEL WAS CLEARLY EMERGING AS THE hNEW WAVEv IN DATA MANAGEMENT "Y THE EARLY S NETWORK AND HIERARCHICAL DATABASES WERE CLEARLY DECLINING IN IMPORTANCE AND TODAY THEY PLAY ONLY A MINOR ROLE IN THE DATABASE MARKET
4HEõ2ELATIONALõ$ATAõ-ODEL 4HE RELATIONAL MODEL PROPOSED BY #ODD WAS AN ATTEMPT TO SIMPLIFY DATABASE STRUCTURE )T ELIMINATED THE EXPLICIT PARENTCHILD STRUCTURES FROM THE DATABASE AND INSTEAD REPRESENTED ALL DATA IN THE DATABASE AS SIMPLE ROWCOLUMN TABLES OF DATA VALUES &IGURE SHOWS A RELATIONAL VERSION OF THE NETWORK ORDER PROCESSING DATABASE IN &IGURE
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! RELATIONAL DATABASE IS A DATABASE WHERE ALL DATA VISIBLE TO THE USER IS ORGANIZED STRICTLY AS TABLES OF DATA VALUES AND WHERE ALL DATABASE OPERATIONS WORK ON THESE TABLES 4HE DEFINITION IS INTENDED SPECIFICALLY TO RULE OUT ANY USER VISIBLE STRUCTURES SUCH AS THE EMBEDDED POINTERS OF A HIERARCHICAL OR NETWORK DATABASE ! RELATIONAL $"-3 CAN REPRESENT PARENTCHILD RELATIONSHIPS BUT THEY ARE VISIBLE ONLY THROUGH THE DATA VALUES CONTAINED IN THE DATABASE TABLES
4HEõ3AMPLEõ$ATABASE &IGURE SHOWS A SMALL RELATIONAL DATABASE FOR AN ORDER PROCESSING APPLICATION 4HIS SAMPLE DATABASE IS USED THROUGHOUT THIS BOOK AND PROVIDES THE BASIS FOR MOST OF THE EXAMPLES !PPENDIX ! CONTAINS A COMPLETE DESCRIPTION OF THE DATABASE STRUCTURE AND ITS CONTENTS &IGURE SHOWS ONLY A FEW ROWS OF EACH TABLE n THE COMPLETE CONTENTS OF EACH TABLE ARE INCLUDED IN !PPENDIX !
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#ODDS WORK PRODUCED A PRECISE MATHEMATICAL DEFINITION OF A RELATIONAL DATABASE AND A THEORETICAL BASIS FOR THE DATABASE OPERATIONS THAT COULD BE PERFORMED ON IT (OWEVER A MORE INFORMAL DEFINITION OF A RELATIONAL DATABASE IS USEFUL
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4HE SAMPLE DATABASE CONTAINS FIVE TABLES %ACH TABLE STORES INFORMATION ABOUT ONE PARTICULAR KIND OF ENTITY s 4HE 3!,%32%03 TABLE STORES THE EMPLOYEE NUMBER NAME AGE YEAR TO DATE SALES AND OTHER DATA ABOUT EACH SALESPERSON s 4HE 02/$5#43 TABLE STORES DATA ABOUT EACH PRODUCT AVAILABLE FOR SALE SUCH AS THE MANUFACTURER PRODUCT NUMBER DESCRIPTION AND PRICE s 4HE /2$%23 TABLE KEEPS TRACK OF EVERY ORDER PLACED BY A CUSTOMER IDENTIFYING THE SALESPERSON WHO TOOK THE ORDER THE PRODUCT ORDERED THE QUANTITY AND AMOUNT OF THE ORDER AND SO ON &OR SIMPLICITY EACH ORDER IS FOR ONLY ONE PRODUCT s 4HE /&&)#%3 TABLE STORES DATA ABOUT EACH OF THE SALES OFFICES INCLUDING THE CITY WHERE THE OFFICE IS THE SALES REGION IT BELONGS TO AND SO ON s 4HE #534/-%23 TABLE STORES DATA ABOUT EACH CUSTOMER SUCH AS THE COMPANY NAME CREDIT LIMIT AND THE SALESPERSON WHO CALLS ON THE CUSTOMER
4ABLES 4HE ORGANIZING PRINCIPLE IN A RELATIONAL DATABASE IS THE TABLE A RECTANGULAR ROWCOLUMN ARRANGEMENT OF DATA VALUES %ACH TABLE IN A DATABASE HAS A UNIQUE TABLE NAME THAT IDENTIFIES ITS CONTENTS !CTUALLY EACH USER CAN CHOOSE HIS OR HER OWN TABLE NAMES WITHOUT WORRYING ABOUT THE NAMES CHOSEN BY OTHER USERS AS EXPLAINED IN #HAPTER 4HE ROWCOLUMN STRUCTURE OF A TABLE IS SHOWN MORE CLEARLY IN &IGURE WHICH IS AN ENLARGED VIEW OF THE /&&)#%3 TABLE %ACH HORIZONTAL ROW OF THE /&&)#%3 TABLE REPRESENTS A SINGLE PHYSICAL ENTITYA SINGLE SALES OFFICE 4OGETHER THE FIVE ROWS OF THE TABLE REPRESENT ALL FIVE OF THE COMPANYS SALES OFFICES !LL OF THE DATA IN A PARTICULAR ROW OF THE TABLE APPLIES TO THE OFFICE REPRESENTED BY THAT ROW %ACH COLUMN OF THE /&&)#%3 TABLE REPRESENTS ONE ITEM OF DATA THAT IS STORED IN THE DATABASE FOR EACH OFFICE &OR EXAMPLE THE #)49 COLUMN HOLDS THE LOCATION OF EACH OFFICE 4HE 3!,%3 COLUMN CONTAINS EACH OFFICES YEAR TO DATE SALES TOTAL 4HE -'2 COLUMN SHOWS THE EMPLOYEE NUMBER OF THE PERSON WHO MANAGES THE OFFICE %ACH ROW OF A TABLE CONTAINS EXACTLY ONE DATA VALUE IN EACH COLUMN )N THE ROW REPRESENTING THE .EW 9ORK OFFICE FOR EXAMPLE THE #)49 COLUMN CONTAINS THE VALUE h.EW 9ORKv 4HE 3!,%3 COLUMN CONTAINS THE VALUE h v WHICH IS THE YEAR TO DATE SALES TOTAL FOR THE .EW 9ORK OFFICE &OR EACH COLUMN OF A TABLE ALL OF THE DATA VALUES IN THAT COLUMN HOLD THE SAME TYPE OF DATA &OR EXAMPLE ALL OF THE #)49 COLUMN VALUES ARE TEXT ALL OF THE 3!,%3 VALUES ARE MONEY AMOUNTS AND ALL OF THE -'2 VALUES ARE INTEGERS REPRESENTING EMPLOYEE NUMBERS 4HE SET OF DATA VALUES THAT A COLUMN CAN CONTAIN IS CALLED THE DOMAIN OF THE COLUMN 4HE DOMAIN OF THE #)49 COLUMN IS THE SET OF ALL NAMES OF CITIES 4HE DOMAIN OF THE 3!,%3 COLUMN IS ANY MONEY AMOUNT 4HE DOMAIN OF THE 2%')/. COLUMN IS JUST TWO DATA VALUES h%ASTERN v AND h7ESTERN v BECAUSE THOSE ARE THE ONLY TWO SALES REGIONS THE COMPANY HAS %ACH COLUMN IN A TABLE HAS A COLUMN NAME WHICH IS USUALLY WRITTEN AS A HEADING AT THE TOP OF THE COLUMN 4HE COLUMNS OF A TABLE MUST ALL HAVE DIFFERENT NAMES BUT THERE IS NO PROHIBITION AGAINST TWO COLUMNS IN TWO DIFFERENT TABLES HAVING IDENTICAL NAMES )N FACT FREQUENTLY USED COLUMN NAMES SUCH AS .!-% !$$2%33 149 02)#% AND 3!,%3 ARE OFTEN FOUND IN MANY DIFFERENT TABLES OF A PRODUCTION DATABASE
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4HE COLUMNS OF A TABLE HAVE A LEFT TO RIGHT ORDER WHICH IS DEFINED WHEN THE TABLE IS FIRST CREATED ! TABLE ALWAYS HAS AT LEAST ONE COLUMN 4HE !.3))3/ 31, STANDARD DOES NOT SPECIFY A MAXIMUM NUMBER OF COLUMNS IN A TABLE BUT ALMOST ALL COMMERCIAL 31, PRODUCTS DO IMPOSE A LIMIT WHICH IS SELDOM LESS THAN COLUMNS 5NLIKE THE COLUMNS THE ROWS IN A TABLE DO NOT HAVE ANY PARTICULAR ORDER )N FACT IF YOU USE TWO CONSECUTIVE DATABASE QUERIES TO DISPLAY THE CONTENTS OF A TABLE THERE IS NO GUARANTEE THAT THE ROWS WILL BE LISTED IN THE SAME ORDER TWICE /F COURSE YOU CAN ASK 31, TO SORT THE ROWS BEFORE DISPLAYING THEM BUT THE SORTED ORDER HAS NOTHING TO DO WITH THE ACTUAL ARRANGEMENT OF THE ROWS WITHIN THE TABLE ! TABLE CAN HAVE ANY NUMBER OF ROWS ! TABLE OF ZERO ROWS IS PERFECTLY LEGAL AND IS CALLED AN EMPTY TABLE FOR OBVIOUS REASONS !N EMPTY TABLE STILL HAS A STRUCTURE IMPOSED BY ITS COLUMNS IT SIMPLY CONTAINS NO DATA 4HE !.3))3/ STANDARD DOES NOT LIMIT THE NUMBER OF ROWS IN A TABLE AND MANY 31, PRODUCTS WILL ALLOW A TABLE TO GROW UNTIL IT EXHAUSTS THE AVAILABLE STORAGE /THER 31, PRODUCTS IMPOSE A LIMIT BUT IT IS ALWAYS A VERY GENEROUS ONE BILLION ROWS OR MORE IS COMMON
0RIMARYõ+EYS "ECAUSE THE ROWS OF A RELATIONAL TABLE ARE UNORDERED YOU CANNOT SELECT A SPECIFIC ROW BY ITS POSITION IN THE TABLE 4HERE IS NO hFIRST ROW v hLAST ROW v OR hTH ROWv OF A TABLE (OW THEN CAN YOU SPECIFY A PARTICULAR ROW SUCH AS THE ROW FOR THE $ENVER SALES OFFICE )N A WELL DESIGNED RELATIONAL DATABASE EVERY TABLE HAS SOME COLUMN OR COMBINATION OF COLUMNS WHOSE VALUES UNIQUELY IDENTIFY EACH ROW IN THE TABLE 4HIS COLUMN OR COLUMNS IS CALLED THE PRIMARY KEY OF THE TABLE ,OOK ONCE AGAIN AT THE /&&)#%3 TABLE IN &IGURE
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!T FIRST GLANCE EITHER THE /&&)#% COLUMN OR THE #)49 COLUMN COULD SERVE AS A PRIMARY KEY FOR THE TABLE "UT IF THE COMPANY EXPANDS AND OPENS TWO SALES OFFICES IN THE SAME CITY THE #)49 COLUMN COULD NO LONGER SERVE AS THE PRIMARY KEY )N PRACTICE h)$ NUMBERSv SUCH AS AN OFFICE NUMBER /&&)#% IN THE /&&)#%3 TABLE AN EMPLOYEE NUMBER %-0,?.5- IN THE 3!,%32%03 TABLE AND CUSTOMER NUMBERS #534?.5- IN THE #534/-%23 TABLE ARE OFTEN CHOSEN AS PRIMARY KEYS )N THE CASE OF THE /2$%23 TABLE YOU HAVE NO CHOICETHE ONLY THING THAT UNIQUELY IDENTIFIES AN ORDER IS ITS ORDER NUMBER /2$%2?.5- 4HE 02/$5#43 TABLE PART OF WHICH IS SHOWN IN &IGURE IS AN EXAMPLE OF A TABLE WHERE THE PRIMARY KEY MUST BE A COMBINATION OF COLUMNS 4HE -&2?)$ COLUMN IDENTIFIES THE MANUFACTURER OF EACH PRODUCT IN THE TABLE AND THE 02/$5#4?)$ COLUMN SPECIFIES THE MANUFACTURERS PRODUCT NUMBER 4HE 02/$5#4?)$ COLUMN MIGHT APPEAR TO MAKE A GOOD PRIMARY KEY BUT THERES NOTHING TO PREVENT TWO DIFFERENT MANUFACTURERS FROM USING THE SAME NUMBER FOR THEIR PRODUCTS 4HEREFORE A COMBINATION OF THE -&2?)$ AND 02/$5#4?)$ COLUMNS MUST BE USED AS THE PRIMARY KEY OF THE 02/$5#43 TABLE %VERY PRODUCT IN THE TABLE IS GUARANTEED TO HAVE A UNIQUE COMBINATION OF DATA VALUES IN THESE TWO COLUMNS 4HE PRIMARY KEY HAS A DIFFERENT UNIQUE VALUE FOR EACH ROW IN A TABLE SO NO TWO ROWS OF A TABLE WITH A PRIMARY KEY ARE EXACT DUPLICATES OF ONE ANOTHER ! TABLE WHERE EVERY ROW IS DIFFERENT FROM ALL OTHER ROWS IS CALLED A RELATION IN MATHEMATICAL TERMS 4HE NAME hRELATIONAL DATABASEv COMES FROM THIS TERM BECAUSE RELATIONS TABLES WITH DISTINCT ROWS ARE AT THE HEART OF A RELATIONAL DATABASE !LTHOUGH PRIMARY KEYS ARE AN ESSENTIAL PART OF THE RELATIONAL DATA MODEL EARLY RELATIONAL DATABASE MANAGEMENT SYSTEMS 3YSTEM2 $" /RACLE AND OTHERS DID NOT PROVIDE EXPLICIT SUPPORT FOR PRIMARY KEYS $ATABASE DESIGNERS USUALLY ENSURED THAT ALL OF THE TABLES IN THEIR DATABASES HAD A PRIMARY KEY BUT THE $"-3 ITSELF DID NOT PROVIDE A WAY TO IDENTIFY THE PRIMARY KEY OF A TABLE $" 6ERSION INTRODUCED IN !PRIL WAS THE FIRST OF )"-S COMMERCIAL 31, PRODUCTS TO SUPPORT PRIMARY KEYS 4HE !.3))3/ STANDARD WAS SUBSEQUENTLY EXPANDED TO INCLUDE A DEFINITION OF PRIMARY KEY SUPPORT AND TODAY NEARLY ALL RELATIONAL DATABASE MANAGEMENT SYSTEMS PROVIDE IT
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/NE OF THE MAJOR DIFFERENCES BETWEEN THE RELATIONAL MODEL AND EARLIER DATA MODELS IS THAT EXPLICIT POINTERS SUCH AS THE PARENTCHILD RELATIONSHIPS OF A HIERARCHICAL DATABASE ARE BANNED FROM RELATIONAL DATABASES 9ET OBVIOUSLY THESE RELATIONSHIPS EXIST IN A RELATIONAL DATABASE &OR EXAMPLE IN THE SAMPLE DATABASE EACH SALESPERSON IS ASSIGNED TO A PARTICULAR SALES OFFICE SO THERE IS AN OBVIOUS RELATIONSHIP BETWEEN THE ROWS OF THE /&&)#%3 TABLE AND THE ROWS OF THE 3!,%32%03 TABLE $OESNT THE RELATIONAL MODEL hLOSE INFORMATIONv BY BANNING THESE RELATIONSHIPS FROM THE DATABASE !S SHOWN IN &IGURE THE ANSWER TO THE QUESTION IS hNOv 4HE FIGURE SHOWS A CLOSE UP OF A FEW ROWS OF THE /&&)#%3 AND 3!,%32%03 TABLES .OTE THAT THE 2%0?/&&)#% COLUMN OF THE 3!,%32%03 TABLE CONTAINS THE OFFICE NUMBER OF THE SALES OFFICE WHERE EACH SALESPERSON WORKS 4HE DOMAIN OF THIS COLUMN THE SET OF LEGAL VALUES IT MAY CONTAIN IS PRECISELY THE SET OF OFFICE NUMBERS FOUND IN THE /&&)#% COLUMN OF THE /&&)#%3 TABLE )N FACT YOU CAN FIND THE SALES OFFICE WHERE -ARY *ONES WORKS BY FINDING THE VALUE IN -ARYS 2%0?/&&)#% COLUMN AND FINDING THE ROW OF THE /&&)#%3 TABLE THAT HAS A MATCHING VALUE IN THE /&&)#% COLUMN IN THE ROW FOR THE .EW 9ORK OFFICE 3IMILARLY TO FIND ALL THE SALESPEOPLE WHO WORK IN .EW 9ORK YOU COULD NOTE THE /&&)#% VALUE FOR THE .EW 9ORK ROW AND THEN SCAN DOWN THE 2%0?/&&)#% COLUMN OF THE 3!,%32%03 TABLE LOOKING FOR MATCHING VALUES IN THE ROWS FOR -ARY *ONES AND 3AM #LARK 4HE PARENTCHILD RELATIONSHIP BETWEEN A SALES OFFICE AND THE PEOPLE WHO WORK THERE ISNT LOST BY THE RELATIONAL MODEL ITS JUST NOT REPRESENTED BY AN EXPLICIT POINTER VISIBLE TO THE USER )NSTEAD THE RELATIONSHIP IS REPRESENTED BY COMMON DATA VALUES STORED IN THE TWO TABLES !LL RELATIONSHIPS IN A RELATIONAL DATABASE ARE REPRESENTED THIS WAY /NE OF THE MAIN GOALS OF THE 31, IS TO LET YOU RETRIEVE RELATED DATA FROM THE DATABASE BY MANIPULATING THESE RELATIONSHIPS IN A SIMPLE STRAIGHTFORWARD WAY
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&OREIGNõ+EYS ! COLUMN IN ONE TABLE WHOSE VALUE MATCHES THE PRIMARY KEY IN SOME OTHER TABLE IS CALLED A FOREIGN KEY )N &IGURE THE 2%0?/&&)#% COLUMN IS A FOREIGN KEY FOR THE /&&)#%3 TABLE !LTHOUGH 2%0?/&&)#% IS A COLUMN IN THE 3!,%32%03 TABLE THE VALUES THAT THIS COLUMN CONTAINS ARE OFFICE NUMBERS 4HEY MATCH VALUES IN THE /&&)#% COLUMN WHICH IS THE PRIMARY KEY FOR THE /&&)#%3 TABLE 4OGETHER A PRIMARY KEY AND A FOREIGN KEY CREATE A PARENTCHILD RELATIONSHIP BETWEEN THE TABLES THAT CONTAIN THEM JUST LIKE THE PARENTCHILD RELATIONSHIPS IN A HIERARCHICAL DATABASE *UST AS A COMBINATION OF COLUMNS CAN SERVE AS THE PRIMARY KEY OF A TABLE A FOREIGN KEY CAN ALSO BE A COMBINATION OF COLUMNS )N FACT THE FOREIGN KEY WILL ALWAYS BE A COMPOUND MULTICOLUMN KEY WHEN IT REFERENCES A TABLE WITH A COMPOUND PRIMARY KEY /BVIOUSLY THE NUMBER OF COLUMNS AND THE DATA TYPES OF THE COLUMNS IN THE FOREIGN KEY AND THE PRIMARY KEY MUST BE IDENTICAL TO ONE ANOTHER ! TABLE CAN CONTAIN MORE THAN ONE FOREIGN KEY IF IT IS RELATED TO MORE THAN ONE OTHER TABLE &IGURE SHOWS THE THREE FOREIGN KEYS IN THE /2$%23 TABLE OF THE SAMPLE DATABASE s 4HE #534 COLUMN IS A FOREIGN KEY FOR THE #534/-%23 TABLE RELATING EACH ORDER TO THE CUSTOMER WHO PLACED IT s 4HE 2%0 COLUMN IS A FOREIGN KEY FOR THE 3!,%32%03 TABLE RELATING EACH ORDER TO THE SALESPERSON WHO TOOK IT s 4HE -&2 AND 02/$5#4 COLUMNS TOGETHER ARE A COMPOSITE FOREIGN KEY FOR THE 02/$5#43 TABLE RELATING EACH ORDER TO THE PRODUCT BEING ORDERED 4HE MULTIPLE PARENTCHILD RELATIONSHIPS CREATED BY THE THREE FOREIGN KEYS IN THE /2$%23 TABLE MAY SEEM FAMILIAR TO YOU AND THEY SHOULD 4HEY ARE PRECISELY THE SAME RELATIONSHIPS AS THOSE IN THE NETWORK DATABASE OF &IGURE !S THE EXAMPLE SHOWS THE RELATIONAL DATA MODEL HAS ALL OF THE POWER OF THE NETWORK MODEL TO EXPRESS COMPLEX RELATIONSHIPS
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2ELATIONALç$ATABASESç
#ODDSõõ2ULESõFORõ2ELATIONALõ$ATABASES
!S THE RELATIONAL DATABASE MODEL STARTED TO BECOME VERY POPULAR IN THE MID S EVERY $"-3 VENDOR SCRAMBLED TO DESCRIBE THEIR PRODUCT AS hRELATIONALv 3OME OF THESE PRODUCTS HAD ONLY A 31, LIKE QUERY LANGUAGE LAYERED ON TOP OF AN UNDERLYING NETWORK OR HIERARCHICAL DATABASE 3OME OF THEM IMPLEMENTED ONLY A VERY RUDIMENTARY TABLE STRUCTURE AND NO QUERY LANGUAGE AT ALL 3OON THE QUESTION OF h7HAT IS A TRUE RELATIONAL DATABASE v BECAME A TOPIC OF DEBATE AND $"-3 VENDORS BEGAN CLAIMING THAT THEIR PRODUCTS WERE hMORE RELATIONALv THAN THE COMPETITION )N 4ED #ODD WHOSE SEMINAL TECHNICAL ARTICLE YEARS EARLIER HAD DEFINED THE RELATIONAL DATA MODEL ADDRESSED THIS QUESTION IN #OMPUTERWORLD ONE OF THE LEADING TRADE PUBLICATIONS )N HIS TWO PART ARTICLE ENTITLED )S 9OUR $"-3 2EALLY 2ELATIONAL /CTOBER AND $OES 9OUR $"-3 2UN "Y THE 2ULES /CTOBER #ODD PRESENTED RULES THAT A DATABASE MUST OBEY IF IT IS TO BE CONSIDERED TRULY RELATIONAL
)NFORMATION RULE !LL INFORMATION IN A RELATIONAL DATABASE IS REPRESENTED EXPLICITLY AT THE LOGICAL LEVEL AND IN EXACTLY ONE WAYBY VALUES IN TABLES
'UARANTEED ACCESS RULE %ACH AND EVERY DATUM ATOMIC VALUE IN A RELATIONAL DATABASE IS GUARANTEED TO BE LOGICALLY ACCESSIBLE BY RESORTING TO A COMBINATION OF TABLE NAME PRIMARY KEY VALUE AND COLUMN NAME
3YSTEMATIC TREATMENT OF .5,, VALUES .5,, VALUES DISTINCT FROM AN EMPTY CHARACTER STRING OR A STRING OF BLANK CHARACTERS AND DISTINCT FROM ZERO OR ANY OTHER NUMBER ARE SUPPORTED IN A FULLY RELATIONAL $"-3 FOR REPRESENTING MISSING INFORMATION AND INAPPLICABLE INFORMATION IN A SYSTEMATIC WAY INDEPENDENT OF THE DATA TYPE
$YNAMIC ONLINE CATALOG BASED ON THE RELATIONAL MODEL 4HE DATABASE DESCRIPTION IS REPRESENTED AT THE LOGICAL LEVEL IN THE SAME WAY AS ORDINARY DATA SO THAT AUTHORIZED USERS CAN APPLY THE SAME RELATIONAL LANGUAGE TO ITS INTERROGATION AS THEY APPLY TO THE REGULAR DATA
#OMPREHENSIVE DATA SUBLANGUAGE RULE ! RELATIONAL SYSTEM MAY SUPPORT SEVERAL LANGUAGES AND VARIOUS MODES OF TERMINAL USE FOR EXAMPLE THE FILL IN THE BLANKS MODE (OWEVER THERE MUST BE AT LEAST ONE LANGUAGE WHOSE STATEMENTS ARE EXPRESSIBLE PER SOME WELL DEFINED SYNTAX AS CHARACTER STRINGS AND THAT IS COMPREHENSIVE IN SUPPORTING ALL OF THE FOLLOWING ITEMS s $ATA DEFINITION s 6IEW DEFINITION s $ATA MANIPULATION INTERACTIVE AND BY PROGRAM s )NTEGRITY CONSTRAINTS s !UTHORIZATION s 4RANSACTION BOUNDARIES BEGIN COMMIT AND ROLLBACK
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&OREIGN KEYS ARE A FUNDAMENTAL PART OF THE RELATIONAL MODEL BECAUSE THEY CREATE RELATIONSHIPS AMONG TABLES IN THE DATABASE !S WITH PRIMARY KEYS FOREIGN KEY SUPPORT WAS MISSING FROM EARLY RELATIONAL DATABASE MANAGEMENT SYSTEMS 4HEY WERE ADDED TO $" 6ERSION WERE SUBSEQUENTLY ADDED TO THE !.3))3/ STANDARD AND NOW APPEAR IN ALL OF THE MAJOR COMMERCIAL PRODUCTS
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6IEW UPDATING RULE !LL VIEWS THAT ARE THEORETICALLY UPDATEABLE ARE ALSO UPDATEABLE BY THE SYSTEM
(IGH LEVEL INSERT UPDATE AND DELETE 4HE CAPABILITY OF HANDLING A BASE RELATION OR A DERIVED RELATION AS A SINGLE OPERAND APPLIES NOT ONLY TO THE RETRIEVAL OF DATA BUT ALSO TO THE INSERTION UPDATE AND DELETION OF DATA
0HYSICAL DATA INDEPENDENCE !PPLICATION PROGRAMS AND TERMINAL ACTIVITIES REMAIN LOGICALLY UNIMPAIRED WHENEVER ANY CHANGES ARE MADE IN EITHER STORAGE REPRESENTATIONS OR ACCESS METHODS
,OGICAL DATA INDEPENDENCE !PPLICATION PROGRAMS AND TERMINAL ACTIVITIES REMAIN LOGICALLY UNIMPAIRED WHEN INFORMATION PRESERVING CHANGES OF ANY KIND THAT THEORETICALLY PERMIT UNIMPAIRMENT ARE MADE TO THE BASE TABLES
)NTEGRITY INDEPENDENCE )NTEGRITY CONSTRAINTS SPECIFIC TO A PARTICULAR RELATIONAL DATABASE MUST BE DEFINABLE IN THE RELATIONAL DATA SUBLANGUAGE AND STORABLE IN THE CATALOG NOT IN THE APPLICATION PROGRAMS $ISTRIBUTION INDEPENDENCE ! RELATIONAL $"-3 HAS DISTRIBUTION INDEPENDENCE .ONSUBVERSION RULE )F A RELATIONAL SYSTEM HAS A LOW LEVEL SINGLE RECORD AT A TIME LANGUAGE THAT LOW LEVEL CANNOT BE USED TO SUBVERT OR BYPASS THE INTEGRITY RULES AND CONSTRAINTS EXPRESSED IN THE HIGHER LEVEL RELATIONAL LANGUAGE MULTIPLE RECORDS AT A TIME !LTHOUGH THE CONTROVERSY HAS LONG SINCE DIED OUT THE RULES ARE INTERESTING FROM A HISTORICAL PERSPECTIVE BECAUSE THEY RESOLVED THE ISSUE ONCE AND FOR ALL AND THEY DO OFFER A GOOD INFORMAL WORKING DEFINITION 2ULE IS BASICALLY THE SINGLE SENTENCE FUNDAMENTAL DEFINITION PRESENTED EARLIER IN THIS CHAPTER THE OTHERS PROVIDE ADDITIONAL REFINEMENT AND REQUIREMENTS 2ULE STRESSES THE IMPORTANCE OF PRIMARY KEYS FOR LOCATING DATA IN THE DATABASE 4HE TABLE NAME LOCATES THE CORRECT TABLE THE COLUMN NAME FINDS THE CORRECT COLUMN AND THE PRIMARY KEY VALUE FINDS THE ROW CONTAINING AN INDIVIDUAL DATA ITEM OF INTEREST 2ULE REQUIRES SUPPORT FOR MISSING DATA THROUGH .5,, VALUES WHICH ARE DESCRIBED IN #HAPTER 2ULE REQUIRES THAT A RELATIONAL DATABASE BE SELF DESCRIBING THROUGH SYSTEM TABLES WHOSE COLUMNS DESCRIBE THE STRUCTURE OF THE DATABASE ITSELF 4HESE TABLES ARE DESCRIBED IN #HAPTER 2ULE MANDATES USING A RELATIONAL DATABASE LANGUAGE SUCH AS 31, ALTHOUGH 31, IS NOT SPECIFICALLY REQUIRED 4HE LANGUAGE MUST BE ABLE TO SUPPORT ALL THE CENTRAL FUNCTIONS OF A $"-3 NOT JUST DATABASE QUERIES 2ULE DEALS WITH VIEWS WHICH ARE VIRTUAL TABLES USED TO GIVE VARIOUS USERS OF A DATABASE DIFFERENT VIEWS OF ITS STRUCTURE 6IEWS ARE DESCRIBED IN #HAPTER 2ULE STRESSES THE SET ORIENTED NATURE OF A RELATIONAL DATABASE )T REQUIRES THAT ROWS BE TREATED AS SETS IN INSERT DELETE AND UPDATE OPERATIONS )T PROHIBITS SYSTEMS THAT SUPPORT ONLY ROW AT A TIME NAVIGATIONAL MODIFICATION OF THE DATABASE 2ULE AND 2ULE INSULATE THE USER OR APPLICATION PROGRAM FROM THE LOW LEVEL IMPLEMENTATION OF THE DATABASE AND EVEN FROM CHANGES IN THE STRUCTURE OF THE TABLES 2ULE SAYS THAT THE DATABASE LANGUAGE SHOULD SUPPORT THE ABILITY TO DEFINE RESTRICTIONS ON THE DATA THAT CAN BE ENTERED AND THE DATABASE MODIFICATIONS THAT CAN BE MADE
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3UMMARY 31, IS BASED ON THE RELATIONAL DATA MODEL THAT ORGANIZES THE DATA IN A DATABASE AS A COLLECTION OF TABLES s %ACH TABLE HAS A TABLE NAME THAT UNIQUELY IDENTIFIES IT s %ACH TABLE HAS ONE OR MORE NAMED COLUMNS WHICH ARE ARRANGED IN A SPECIFIC LEFT TO RIGHT ORDER s %ACH TABLE HAS ZERO OR MORE ROWS EACH CONTAINING A SINGLE DATA VALUE IN EACH COLUMN 4HE ROWS ARE UNORDERED s !LL DATA VALUES IN A GIVEN COLUMN HAVE THE SAME DATA TYPE AND ARE DRAWN FROM A SET OF LEGAL VALUES CALLED THE DOMAIN OF THE COLUMN 4ABLES ARE RELATED TO ONE ANOTHER BY THE DATA THEY CONTAIN 4HE RELATIONAL DATA MODEL USES PRIMARY KEYS AND FOREIGN KEYS TO REPRESENT THESE RELATIONSHIPS AMONG TABLES s ! PRIMARY KEY IS A COLUMN OR COMBINATION OF COLUMNS IN A TABLE WHOSE VALUES UNIQUELY IDENTIFY EACH ROW OF THE TABLE ! TABLE HAS ONLY ONE PRIMARY KEY s ! FOREIGN KEY IS A COLUMN OR COMBINATION OF COLUMNS IN A TABLE WHOSE VALUES ARE A PRIMARY KEY VALUE FOR SOME OTHER TABLE ! TABLE CAN CONTAIN MORE THAN ONE FOREIGN KEY LINKING IT TO ONE OR MORE OTHER TABLES s ! PRIMARY KEYFOREIGN KEY COMBINATION CREATES A PARENTCHILD RELATIONSHIP BETWEEN THE TABLES THAT CONTAIN THEM
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2ULE SAYS THAT THE DATABASE LANGUAGE MUST BE ABLE TO MANIPULATE DISTRIBUTED DATA LOCATED ON OTHER COMPUTER SYSTEMS IF THE $"-3 SUPPORTS IT &INALLY 2ULE PREVENTS hOTHER PATHSv INTO THE DATABASE THAT MIGHT SUBVERT ITS RELATIONAL STRUCTURE AND INTEGRITY
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#(!04%2ç 31, "ASICS #(!04%2ç 3IMPLE 1UERIES
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UERIES ARE THE HEART OF 31, AND MANY PEOPLE USE 31, AS A DATABASE QUERY TOOL 4HE NEXT FIVE CHAPTERS DESCRIBE 31, QUERIES IN DEPTH #HAPTER DESCRIBES THE BASIC 31, STRUCTURES THAT YOU USE TO FORM 31, STATEMENTS #HAPTER DISCUSSES SIMPLE QUERIES THAT DRAW DATA FROM A SINGLE TABLE OF DATA #HAPTER EXPANDS THE DISCUSSION TO MULTITABLE QUERIES 1UERIES THAT SUMMARIZE DATA ARE DESCRIBED IN #HAPTER &INALLY #HAPTER EXPLAINS THE 31, SUBQUERY CAPABILITY THAT IS USED TO HANDLE COMPLEX QUERIES
#(!04%2ç -ULTITABLE 1UERIES *OINS #(!04%2ç 3UMMARY 1UERIES #(!04%2ç 3UBQUERIES AND 1UERY %XPRESSIONS
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HIS CHAPTER BEGINS A DETAILED DESCRIPTION OF THE FEATURES OF 31, )T DESCRIBES THE BASIC STRUCTURE OF A 31, STATEMENT AND THE BASIC ELEMENTS OF THE LANGUAGE SUCH AS KEYWORDS DATA TYPES AND EXPRESSIONS (OW 31, HANDLES MISSING DATA THROUGH .5,, VALUES IS ALSO DESCRIBED !LTHOUGH THESE ARE BASIC FEATURES OF 31, THEY HAVE SOME SUBTLE DIFFERENCES IN THE WAY THEY ARE IMPLEMENTED BY VARIOUS POPULAR 31, PRODUCTS AND IN MANY CASES THE 31, PRODUCTS PROVIDE SIGNIFICANT EXTENSIONS TO THE CAPABILITIES SPECIFIED IN THE !.3))3/ 31, STANDARD 4HESE DIFFERENCES AND EXTENSIONS ARE ALSO DESCRIBED IN THIS CHAPTER
3TATEMENTS 4HE MAIN BODY OF 31, CONSISTS OF ABOUT STATEMENTS 4HE MOST IMPORTANT AND FREQUENTLY USED STATEMENTS ARE SUMMARIZED IN 4ABLE .OTE THAT NOT ALL 31, IMPLEMENTATIONS SUPPORT ALL THESE STATEMENTS %ACH STATEMENT REQUESTS A SPECIFIC ACTION FROM THE $"-3 SUCH AS CREATING A NEW TABLE RETRIEVING DATA OR INSERTING NEW DATA INTO THE DATABASE !LL 31, STATEMENTS HAVE THE SAME BASIC FORM ILLUSTRATED IN &IGURE %VERY 31, STATEMENT BEGINS WITH A VERB A KEYWORD THAT DESCRIBES WHAT THE STATEMENT DOES #2%!4% ).3%24 $%,%4% AND #/--)4 ARE TYPICAL VERBS 4HE STATEMENT CONTINUES WITH ONE OR MORE CLAUSES ! CLAUSE MAY SPECIFY THE DATA TO BE ACTED ON BY THE STATEMENT OR PROVIDE MORE DETAIL ABOUT WHAT THE STATEMENT IS SUPPOSED TO DO %VERY CLAUSE ALSO BEGINS WITH A KEYWORD SUCH AS 7(%2% &2/- ).4/ AND (!6).' 3OME CLAUSES ARE OPTIONAL OTHERS ARE REQUIRED 4HE SPECIFIC STRUCTURE AND CONTENT VARY FROM ONE CLAUSE TO ANOTHER -ANY CLAUSES CONTAIN TABLE OR COLUMN NAMES SOME MAY CONTAIN ADDITIONAL KEYWORDS CONSTANTS OR EXPRESSIONS 4HE !.3))3/ 31, STANDARD SPECIFIES A SET OF RESERVED KEYWORDS AND NONRESERVED KEYWORDS THAT ARE USED WITHIN 31, STATEMENTS !CCORDING TO THE STANDARD RESERVED KEYWORDS CANNOT BE USED AS THE EXACT NAME OF DATABASE OBJECTS SUCH AS TABLES COLUMNS AND USERS -ANY 31, IMPLEMENTATIONS RELAX THIS RESTRICTION BUT ITS GENERALLY A GOOD IDEA
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6ARIABLE ITEMS IN A 31, STATEMENT SUCH AS THE TABLE NAME AND SEARCH CONDITION IN &IGURE ARE SHOWN IN LOWERCASE ITALICS )TS UP TO YOU TO SPECIFY THE APPROPRIATE ITEM VALUES EACH TIME THE STATEMENT IS USED /PTIONAL CLAUSES AND KEYWORDS SUCH AS THE 7(%2% CLAUSE IN &IGURE ARE INDICATED BY ALTERNATE PATHS THROUGH THE SYNTAX DIAGRAM 7HEN A CHOICE OF OPTIONAL KEYWORDS IS OFFERED THE DEFAULT CHOICE THAT IS THE BEHAVIOR OF THE STATEMENT IF NO KEYWORD IS SPECIFIED IS 5.$%2,).%$
.AMES 4HE OBJECTS IN A 31, BASED DATABASE ARE IDENTIFIED BY ASSIGNING THEM UNIQUE NAMES .AMES ARE USED IN 31, STATEMENTS TO IDENTIFY THE DATABASE OBJECT ON WHICH THE STATEMENT SHOULD ACT 4HE MOST FUNDAMENTAL NAMED OBJECTS IN A RELATIONAL DATABASE ARE TABLE NAMES WHICH IDENTIFY TABLES COLUMN NAMES WHICH IDENTIFY COLUMNS AND USER NAMES WHICH IDENTIFY USERS OF THE DATABASE THE ORIGINAL 31, STANDARD SPECIFIED CONVENTIONS FOR NAMING THESE OBJECTS 3UBSEQUENT VERSIONS OF THE 31, STANDARD SIGNIFICANTLY EXPANDED THE LIST OF NAMED ENTITIES TO INCLUDE SCHEMAS COLLECTIONS OF TABLES CONSTRAINTS RESTRICTIONS ON THE CONTENTS OF TABLES AND THEIR RELATIONSHIPS DOMAINS SETS OF LEGAL VALUES THAT MAY BE ASSIGNED TO A COLUMN AND SEVERAL OTHER TYPES OF OBJECTS -ANY 31, IMPLEMENTATIONS SUPPORT ADDITIONAL NAMED OBJECTS SUCH AS STORED PROCEDURES PRIMARY KEYFOREIGN KEY RELATIONSHIPS DATA ENTRY FORMS AND DATA REPLICATION SCHEMES 4HE ORIGINAL !.3))3/ STANDARD SPECIFIED THAT 31, NAMES MUST CONTAIN TO CHARACTERS MUST BEGIN WITH A LETTER AND MAY NOT CONTAIN ANY SPACES OR SPECIAL PUNCTUATION CHARACTERS 4HE 31, STANDARD INCREASED THE MAXIMUM TO CHARACTERS THE STANDARD ACTUALLY SPECIFIES hLESS THAN v AND THIS REMAINS UNCHANGED THROUGH 31, )N PRACTICE THE NAMES SUPPORTED BY 31, BASED $"-3 PRODUCTS VARY SIGNIFICANTLY )TS COMMON TO SEE TIGHTER RESTRICTIONS ON NAMES THAT ARE CONNECTED TO OTHER SOFTWARE OUTSIDE OF THE DATABASE SUCH AS USER NAMES WHICH MAY CORRESPOND TO LOGIN NAMES USED BY AN OPERATING SYSTEM AND LOOSER RESTRICTIONS ON NAMES THAT ARE PRIVATE INTERNAL TO THE DATABASE 4HE VARIOUS PRODUCTS ALSO DIFFER IN THE SPECIAL CHARACTERS THEY PERMIT IN TABLE NAMES &OR PORTABILITY ITS BEST TO KEEP NAMES RELATIVELY SHORT AND TO AVOID THE USE OF SPECIAL CHARACTERS EXCEPT OF COURSE THE UNDERSCORE CHARACTER ? WHICH IS USED TO SEPARATE WORDS IN 31, NAMES
4ABLEõ.AMES 7HEN YOU SPECIFY A TABLE NAME IN A 31, STATEMENT 31, ASSUMES THAT YOU ARE REFERRING TO ONE OF YOUR OWN TABLES THAT IS A TABLE THAT YOU CREATED 5SUALLY YOU WILL WANT TO CHOOSE TABLE NAMES THAT ARE SHORT BUT DESCRIPTIVE
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! QUALIFIED TABLE NAME GENERALLY CAN BE USED IN A 31, STATEMENT WHEREVER A TABLE NAME CAN APPEAR 4HE !.3))3/ 31, STANDARD GENERALIZES THE NOTION OF A QUALIFIED TABLE NAME EVEN FURTHER )T ALLOWS YOU TO CREATE A NAMED COLLECTION OF TABLES CALLED A SCHEMA 9OU CAN REFER TO A TABLE IN A SPECIFIC SCHEMA BY USING A QUALIFIED TABLE NAME &OR EXAMPLE THE ")24($!93 TABLE IN THE %-0,/9%%?).&/ SCHEMA WOULD BE REFERENCED AS %-0,/9%%?).&/")24($!93
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$ATAõ4YPES 4HE !.3))3/ 31, STANDARD SPECIFIES THE VARIOUS TYPES OF DATA THAT CAN BE STORED IN A 31, BASED DATABASE AND MANIPULATED BY 31, 4HE ORIGINAL 31, STANDARD SPECIFIED ONLY A MINIMAL SET OF DATA TYPES 3UBSEQUENT VERSIONS OF THE STANDARD EXPANDED THIS LIST TO INCLUDE VARIABLE LENGTH CHARACTER STRINGS DATE AND TIME DATA BIT STRINGS %XTENSIBLE -ARKUP ,ANGUAGE 8-, AND OTHER TYPES 4ODAY COMMERCIAL $"-3 PRODUCTS CAN PROCESS A RICH VARIETY OF DATA AND THERE IS CONSIDERABLE DIVERSITY IN THE PARTICULAR DATA TYPES SUPPORTED ACROSS DIFFERENT $"-3 BRANDS 4YPICAL DATA TYPES INCLUDE THE FOLLOWING s )NTEGERS #OLUMNS HOLDING THIS TYPE OF DATA TYPICALLY STORE COUNTS QUANTITIES AGES AND SO ON )NTEGER COLUMNS ARE ALSO FREQUENTLY USED TO CONTAIN )$ NUMBERS SUCH AS CUSTOMER EMPLOYEE AND ORDER NUMBERS s $ECIMAL NUMBERS #OLUMNS WITH THIS DATA TYPE STORE NUMBERS THAT HAVE FRACTIONAL PARTS AND THAT MUST BE CALCULATED EXACTLY SUCH AS RATES AND PERCENTAGES 4HEY ARE ALSO FREQUENTLY USED TO STORE MONEY AMOUNTS s &LOATING POINT NUMBERS #OLUMNS WITH THIS DATA TYPE ARE USED TO STORE SCIENTIFIC NUMBERS THAT CAN BE CALCULATED APPROXIMATELY SUCH AS WEIGHTS AND DISTANCES &LOATING POINT NUMBERS CAN REPRESENT A LARGER RANGE OF VALUES THAN DECIMAL NUMBERS BUT CAN PRODUCE ROUND OFF ERRORS IN COMPUTATIONS s &IXED LENGTH CHARACTER STRINGS #OLUMNS HOLDING THIS TYPE OF DATA TYPICALLY STORE CHARACTER STRINGS THAT ARE ALWAYS THE SAME LENGTH SUCH AS POSTAL CODES STATE PROVINCE ABBREVIATIONS SHORT DESCRIPTIONS AND SO ON 7HENEVER THE STRING TO BE STORED IS SMALLER THAN THE LENGTH DEFINED FOR A FIXED LENGTH COLUMN IT IS PADDED WITH SPACES SO IT FITS THE EXACT STORAGE LENGTH s 6ARIABLE LENGTH CHARACTER STRINGS 4HIS DATA TYPE ALLOWS A COLUMN TO STORE CHARACTER STRINGS THAT VARY IN LENGTH FROM ROW TO ROW UP TO SOME MAXIMUM LENGTH 4HE 31, STANDARD PERMITTED ONLY FIXED LENGTH CHARACTER STRINGS WHICH ARE EASIER FOR THE $"-3 TO PROCESS BUT CAN WASTE CONSIDERABLE SPACE #OLUMNS HOLDING THIS TYPE OF DATA TYPICALLY STORE NAMES OF PEOPLE AND COMPANIES ADDRESSES DESCRIPTIONS AND SO ON 5NLIKE FIXED LENGTH CHARACTER STRINGS VARIABLE LENGTH STRINGS ARE NOT PADDED WITH SPACESTHE EXACT NUMBER OF CHARACTERS PROVIDED IS STORED ALONG WITH THE LENGTH OF THE DATA STRING s -ONEY AMOUNTS 3OME 31, PRODUCTS SUPPORT A -/.%9 OR #522%.#9 TYPE WHICH IS USUALLY STORED AS A DECIMAL OR FLOATING POINT NUMBER (AVING A DISTINCT MONEY TYPE ALLOWS THE $"-3 TO PROPERLY FORMAT MONEY AMOUNTS WHEN THEY ARE DISPLAYED (OWEVER THE 31, 3TANDARD DOES NOT SPECIFY SUCH A DATA TYPE s $ATES AND TIMES 3UPPORT FOR DATETIME VALUES IS ALSO COMMON IN 31, PRODUCTS ALTHOUGH THE DETAILS CAN VARY CONSIDERABLY FROM ONE PRODUCT TO ANOTHER LARGELY BECAUSE VENDORS IMPLEMENTED THESE DATA TYPES BEFORE THE 31, STANDARD WAS DEVELOPED 6ARIOUS COMBINATIONS OF DATES TIMES TIMESTAMPS TIME INTERVALS AND DATETIME ARITHMETIC ARE GENERALLY SUPPORTED 4HE 31, STANDARD INCLUDES AN ELABORATE SPECIFICATION FOR $!4% 4)-% 4)-%34!-0 AND ).4%26!, DATA TYPES INCLUDING SUPPORT FOR TIME ZONES AND TIME PRECISION FOR EXAMPLE TENTHS OR HUNDREDTHS OF SECONDS
#HAPTERçç
31,ç"ASICSç
s "OOLEAN DATA 3OME 31, PRODUCTS SUCH AS -ICROSOFT 31, 3ERVER SUPPORT LOGICAL 425% OR &!,3% VALUES AS AN EXPLICIT TYPE AND SOME PERMIT LOGICAL OPERATIONS COMPARISON !.$/2 AND SO ON ON THE STORED DATA WITHIN 31, STATEMENTS
s ,ARGE BINARY OBJECTS 4HE 31, STANDARD ALSO ADDED THE ",/" DATA TYPE THAT SUPPORTS STORING UNSTRUCTURED VARIABLE LENGTH SEQUENCES OF BYTES #OLUMNS CONTAINING THIS DATA ARE USED TO STORE COMPRESSED VIDEO IMAGES EXECUTABLE CODE AND OTHER TYPES OF UNSTRUCTURED DATA 0RIOR TO THE PUBLICATION OF THE STANDARD VENDORS IMPLEMENTED THEIR OWN PROPRIETARY SOLUTIONS SUCH AS 31, 3ERVERS )-!'% AND /RACLES ,/.' 2!7 DATA TYPES WHICH CAN STORE UP TO GIGABYTES OF DATA s .ON 2OMAN CHARACTERS !S DATABASES GREW TO SUPPORT GLOBAL APPLICATIONS $"-3 VENDORS ADDED SUPPORT FOR FIXED LENGTH AND VARIABLE LENGTH STRINGS OF MULTIBYTE CHARACTERS USED TO REPRESENT +ANJI AND OTHER !SIAN AND !RABIC CHARACTERS USING PROPRIETARY TYPES SUCH AS THE '2!0()# AND 6!2'2!0()# DATA TYPES IN 31, 3ERVER 4HE !.3))3/ STANDARD NOW SPECIFIES NATIONAL CHARACTER SET VERSIONS OF THE VARIOUS CHARACTER DATA TYPES .#(!2 .6!2#(!2 AND .#,/" 7HILE MOST MODERN DATABASES SUPPORT STORING AND RETRIEVING SUCH CHARACTERS OFTEN USING THE 5.)#/$% CONVENTION FOR REPRESENTING THEM SUPPORT FOR SEARCHING AND SORTING ON THESE TYPES VARIES WIDELY 4ABLE LISTS THE DATA TYPES SPECIFIED IN THE !.3))3/ 31, STANDARD 4HE DIFFERENCES BETWEEN THE DATA TYPES OFFERED IN VARIOUS 31, IMPLEMENTATIONS FORM ONE OF THE PRACTICAL BARRIERS TO THE PORTABILITY OF 31, BASED APPLICATIONS 4HESE DIFFERENCES HAVE COME ABOUT AS A RESULT OF INNOVATION AS RELATIONAL DATABASES HAVE EVOLVED TO INCLUDE A BROADER RANGE OF CAPABILITIES 4HIS HAS BEEN THE TYPICAL PATTERN s ! $"-3 VENDOR ADDS A NEW DATA TYPE THAT PROVIDES USEFUL NEW CAPABILITIES FOR A CERTAIN GROUP OF USERS s /THER $"-3 VENDORS ADD THE SAME OR SIMILAR DATA TYPES ADDING THEIR OWN INNOVATIONS TO DIFFERENTIATE THEIR PRODUCTS FROM THE OTHERS s /VER SEVERAL YEARS THE POPULARITY OF THE DATA TYPE GROWS AND IT BECOMES A PART OF THE hMAINSTREAMv SET OF DATA TYPES SUPPORTED BY MOST 31, IMPLEMENTATIONS s 4HE STANDARDS BODIES BECOME INVOLVED TO TRY TO STANDARDIZE THE NEW DATA TYPE AND ELIMINATE ARBITRARY DIFFERENCES BETWEEN THE VENDOR IMPLEMENTATIONS 4HE MORE WELL ENTRENCHED THE DATA TYPE HAS BECOME THE MORE DIFFICULT THE SET OF COMPROMISES FACED BY THE STANDARDS GROUP 5SUALLY THIS RESULTS IN AN ADDITION TO THE STANDARD THAT DOES NOT EXACTLY MATCH ANY OF THE CURRENT IMPLEMENTATIONS
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s ,ARGE CHARACTER OBJECTS 4HE 31, STANDARD ADDED THE #,/" DATA TYPE THAT SUPPORTS STORING LARGE CHARACTER STRINGS UP TO A SPECIFIED AMOUNT WITH A TYPICAL MAXIMUM LENGTH IN THE MULTI GIGABYTE RANGE 4HIS ALLOWS THE DATABASE TO STORE ENTIRE DOCUMENTS PRODUCT DESCRIPTIONS TECHNICAL PAPERS R£SUM£S AND SIMILAR UNSTRUCTURED TEXT DATA 3EVERAL 31, BASED DATABASES SUPPORT PROPRIETARY DATA TYPES ADDED BEFORE THE 31, STANDARD CAPABLE OF STORING LONG TEXT STRINGS TYPICALLY UP TO OR CHARACTERS AND IN SOME CASES EVEN LARGER 4HE $"-3 USUALLY RESTRICTS THE USE OF LARGE CHARACTER COLUMNS IN INTERACTIVE QUERIES AND SEARCHES
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s $"-3 VENDORS SLOWLY ADD SUPPORT FOR THE NEW STANDARDIZED DATA TYPE AS AN OPTION TO THEIR SYSTEMS BUT BECAUSE THEY HAVE A LARGE INSTALLED BASE THAT IS USING THE OLDER NOW hPROPRIETARYv VERSION OF THE DATA TYPE THEY MUST MAINTAIN SUPPORT FOR THIS FORM OF THE DATA TYPE AS WELL s /VER A VERY LONG PERIOD TYPICALLY SEVERAL MAJOR RELEASES OF THE $"-3 PRODUCT USERS MIGRATE TO THE NEW STANDARDIZED FORM OF THE DATA TYPE AND THE $"-3 VENDOR CAN BEGIN THE PROCESS OF PHASING OUT THE PROPRIETARY VERSION >Ì>Ê/Þ«i
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$ATETIME DATA PROVIDES AN EXCELLENT EXAMPLE OF THIS PHENOMENON AND THE DATA TYPE VARIATIONS IT CREATES $" OFFERED EARLY DATETIME SUPPORT WITH THREE DIFFERENT DATETIME DATA TYPES s $!4%
3TORES A DATE LIKE *UNE
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3TORES A TIME OF DAY LIKE 0-
s 4)-%34!-0 ! SPECIFIC INSTANT IN HISTORY WITH A PRECISION DOWN TO THE NANOSECOND
3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% gg $!93
31, 3ERVER WAS INTRODUCED WITH A SINGLE DATETIME DATA TYPE CALLED $!4%4)-% WHICH CLOSELY RESEMBLES THE $" 4)-%34!-0 DATA TYPE )F ()2%?$!4% CONTAINED $!4%4)-% DATA 31, 3ERVER COULD ACCEPT THIS VERSION OF THE QUERY WITHOUT THE DATE ARITHMETIC 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% gg
3INCE NO SPECIFIC TIME ON *UNE IS SPECIFIED IN THE QUERY 31, 3ERVER DEFAULTS TO MIDNIGHT ON THAT DATE 4HE 31, 3ERVER QUERY THUS REALLY MEANS 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% g !-g
31, 3ERVER ALSO SUPPORTS DATE ARITHMETIC THROUGH A SET OF BUILT IN FUNCTIONS 4HUS THE $" STYLE QUERY CAN ALSO BE SPECIFIED IN THIS WAY 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% $!4%!$$$!9 gg
WHICH IS CONSIDERABLY DIFFERENT FROM THE $" SYNTAX /RACLE HAS LONG SUPPORTED DATETIME DATA WITH A SINGLE DATA TYPE CALLED $!4% .OTE HOWEVER THAT /RACLE ADDED SUPPORT FOR THE 31, 3TANDARD $!4%4)-% AND 4)-%34!-0 DATA TYPES STARTING WITH /RACLE I ,IKE 31, 3ERVERS $!4%4)-% TYPE AN /RACLE $!4% IS IN FACT A TIMESTAMP !LSO AS WITH 31, 3ERVER THE TIME PART OF AN /RACLE $!4% VALUE DEFAULTS TO MIDNIGHT IF NO TIME IS EXPLICITLY SPECIFIED 4HE DEFAULT /RACLE DATE FORMAT IS DIFFERENT FROM THE $" AND 31, 3ERVER FORMATS SO THE /RACLE VERSION OF THE QUERY BECOMES 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% g *5. g
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3PECIFIC DATES AND TIMES CAN BE SPECIFIED AS STRING CONSTANTS AND DATE ARITHMETIC IS SUPPORTED (ERE IS AN EXAMPLE OF A VALID QUERY USING $" DATES ASSUMING THAT THE ()2%? $!4% COLUMN CONTAINS $!4% DATA
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/RACLE ALSO SUPPORTS LIMITED DATE ARITHMETIC SO THE $" STYLE QUERY CAN ALSO BE SPECIFIED BUT WITHOUT THE $!93 KEYWORD 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% g -!9 g
.OTE HOWEVER THAT THIS STATEMENT REQUIRES THE $"-3 TO IMPLICITLY CONVERT THE STRING TO AN APPROPRIATE DATE DATA TYPE BEFORE ADDING TO IT AND THAT NOT ALL 31, IMPLEMENTATIONS SUPPORT SUCH CONVERSION /RACLE FOR EXAMPLE WILL REPORT AN ERROR UNLESS A FUNCTION SUCH AS 4/?$!4% OR #!34 CONVERTS THE CHARACTER STRING TO AN /RACLE $!4% OR $!4%4)-% TYPE BEFORE ATTEMPTING DATE ARITHMETIC &ORTUNATELY WITH THE ADVENT OF THE YEAR CONVERSION MOST $"-3 VENDORS ADDED UNIVERSAL SUPPORT FOR DATES IN 31, STATEMENTS WITH FOUR DIGIT YEARS IN A STANDARD 9999 -- $$ FORMAT WHICH WE USE FOR MOST OF THE EXAMPLES IN THIS BOOK )N /RACLES CASE THE DEFAULT FORMAT IS STILL AS SHOWN IN THE PRECEDING EXAMPLES BUT IT CAN BE CHANGED AT EITHER THE DATABASE OR USER SESSION WITH A SIMPLE COMMAND )F YOU ARE USING /RACLE AND YOU TRY ANY OF THE EXAMPLES IN THIS BOOK SIMPLY ENTER THIS COMMAND TO CHANGE YOUR DEFAULT DATE FORMAT !,4%2 3%33)/. 3%4 .,3?$!4%?&/2-!4 g9999 -- $$g
#ARE MUST BE TAKEN WHEN FORMING QUERIES THAT SEARCH FOR EXACT DATE MATCHES USING THE EQUAL OPERATOR AND THE DATES HAVE TIME COMPONENTS STORED IN THEM #ONSIDER THE FOLLOWING EXAMPLE 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% gg
)F A SALESPERSONS HIRE DATE WERE STORED IN THE DATABASE AS NOON ON *UNE THE SALESPERSON WOULD NOT BE INCLUDED IN THE QUERY RESULTS FROM /RACLE OR 31, 3ERVER DATABASES 4HE $"-3 WOULD ASSUME A TIME OF MIDNIGHT FOR THE STRING SUPPLIED WITH THE 31, STATEMENT AND SINCE MIDNIGHT IS NOT EQUAL TO NOON THE ROW WOULD NOT BE SELECTED /N THE OTHER HAND FOR A $" DATABASE WHERE THE TIME IS NOT STORED WITH A $!4% DATA TYPE THE ROW WOULD APPEAR IN THE QUERY RESULTS &INALLY STARTING WITH 31, THE !.3))3/ STANDARD ADDED SUPPORT FOR DATETIME DATA WITH A SET OF DATA TYPES BASED ON BUT NOT IDENTICAL TO THE $" TYPES )N ADDITION TO THE $!4% 4)-% AND 4)-%34!-0 DATA TYPES THE STANDARD SPECIFIES AN ).4%26!, DATA TYPE WHICH CAN BE USED TO STORE A TIME INTERVAL FOR EXAMPLE A TIMESPAN MEASURED IN DAYS OR A DURATION MEASURED IN HOURS MINUTES AND SECONDS 4HE STANDARD ALSO PROVIDES A VERY ELABORATE AND COMPLEX METHOD FOR DEALING WITH DATETIME ARITHMETIC SPECIFYING THE PRECISION OF INTERVALS ADJUSTING FOR TIME ZONE DIFFERENCES AND SO ON -OST 31, IMPLEMENTATIONS NOW HAVE SUPPORT FOR THESE STANDARD TYPES /NE NOTABLE EXCEPTION HOWEVER IS THAT 31, 3ERVER HAS LONG USED THE 4)-%34!-0 DATA TYPE FOR AN ENTIRELY DIFFERENT PURPOSE SO SUPPORTING THE !.3))3/ SPECIFICATION FOR IT PRESENTS A VERY REAL CHALLENGE !S THESE EXAMPLES ILLUSTRATE THE SUBTLE DIFFERENCES IN DATA TYPES AMONG VARIOUS 31, PRODUCTS LEAD TO SOME SIGNIFICANT DIFFERENCES IN 31, STATEMENT SYNTAX
#HAPTERçç
31,ç"ASICSç
4HEY CAN EVEN CAUSE THE SAME 31, QUERY TO PRODUCE SLIGHTLY DIFFERENT RESULTS ON DIFFERENT DATABASE MANAGEMENT SYSTEMS 4HE WIDELY PRAISED PORTABILITY OF 31, IS THUS TRUE BUT ONLY AT A GENERAL LEVEL !N APPLICATION CAN BE MOVED FROM ONE 31, DATABASE TO ANOTHER AND IT CAN BE HIGHLY PORTABLE IF IT USES ONLY THE MOST MAINSTREAM BASIC 31, CAPABILITIES (OWEVER THE SUBTLE VARIATIONS IN 31, IMPLEMENTATIONS MEAN THAT DATA TYPES AND 31, STATEMENTS MUST ALMOST ALWAYS BE ADJUSTED SOMEWHAT IF THEY ARE TO BE MOVED ACROSS $"-3 BRANDS 4HE MORE COMPLEX THE APPLICATION THE MORE LIKELY IT IS TO BECOME DEPENDENT ON $"-3 SPECIFIC FEATURES AND NUANCES AND THE LESS PORTABLE IT WILL BECOME
)N SOME 31, STATEMENTS A NUMERIC CHARACTER OR DATE DATA VALUE MUST BE EXPRESSED IN TEXT FORM &OR EXAMPLE IN THIS ).3%24 STATEMENT WHICH ADDS A SALESPERSON TO THE DATABASE ).3%24 ).4/ 3!,%32%03 %-0,?.5- .!-% 15/4! ()2%?$!4% 3!,%3 6!,5%3 g$ENNIS )RVINGg g g
THE VALUE FOR EACH COLUMN IN THE NEWLY INSERTED ROW IS SPECIFIED IN THE 6!,5%3 CLAUSE #ONSTANT DATA VALUES ARE ALSO USED IN EXPRESSIONS SUCH AS IN THIS 3%,%#4 STATEMENT 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 4!2'%4 3!,%3
4HE !.3))3/ 31, STANDARD SPECIFIES THE FORMAT OF NUMERIC AND STRING CONSTANTS OR LITERALS WHICH REPRESENT SPECIFIC DATA VALUES 4HESE CONVENTIONS ARE FOLLOWED BY MOST 31, IMPLEMENTATIONS
.UMERICõ#ONSTANTS )NTEGER AND DECIMAL CONSTANTS ALSO CALLED EXACT NUMERIC LITERALS ARE WRITTEN AS ORDINARY DECIMAL NUMBERS IN 31, STATEMENTS WITH AN OPTIONAL LEADING PLUS OR MINUS SIGN
9OU MUST NOT PUT A COMMA BETWEEN THE DIGITS OF A NUMERIC CONSTANT AND NOT ALL 31, DIALECTS ALLOW THE LEADING PLUS SIGN SO ITS BEST TO AVOID IT &OR MONEY DATA MOST 31, IMPLEMENTATIONS SIMPLY USE INTEGER OR DECIMAL CONSTANTS ALTHOUGH SOME ALLOW THE CONSTANT TO BE SPECIFIED WITH A CURRENCY SYMBOL
&LOATING POINT CONSTANTS ALSO CALLED APPROXIMATE NUMERIC LITERALS ARE SPECIFIED USING THE % NOTATION COMMONLY FOUND IN PROGRAMMING LANGUAGES SUCH AS # AND &/242!. (ERE ARE SOME VALID 31, FLOATING POINT CONSTANTS % % % %
4HE % IS READ hTIMES TEN TO THE POWER OF v SO THE FIRST CONSTANT BECOMES h TIMES TEN TO THE THIRD POWER v OR
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3TRINGõ#ONSTANTS 4HE !.3))3/ STANDARD SPECIFIES THAT 31, CONSTANTS FOR CHARACTER DATA BE ENCLOSED IN SINGLE QUOTES g g AS IN THESE EXAMPLES g*ONES *OHN *g g.EW 9ORKg g7ESTERNg
)F A SINGLE QUOTE IS TO BE INCLUDED IN THE CONSTANT TEXT IT IS WRITTEN WITHIN THE CONSTANT AS TWO CONSECUTIVE SINGLE QUOTE CHARACTERS 4HUS THIS CONSTANT VALUE g) CANggTg
BECOMES THE SEVEN CHARACTER STRING ) CANgT 3OME 31, IMPLEMENTATIONS SUCH AS 31, 3ERVER ACCEPT STRING CONSTANTS ENCLOSED IN DOUBLE QUOTES *ONES *OHN * .EW 9ORK 7ESTERN
5NFORTUNATELY THE DOUBLE QUOTES CAN POSE PORTABILITY PROBLEMS WITH OTHER 31, PRODUCTS 4HE 31, STANDARD PROVIDES THE ADDITIONAL CAPABILITY TO SPECIFY STRING CONSTANTS FROM A SPECIFIC NATIONAL CHARACTER SET FOR EXAMPLE &RENCH OR 'ERMAN OR FROM A USER DEFINED CHARACTER SET 4HE USER DEFINED CHARACTER SET CAPABILITIES HAVE TYPICALLY NOT BEEN IMPLEMENTED IN MAINSTREAM 31, PRODUCTS
$ATEõANDõ4IMEõ#ONSTANTS )N 31, PRODUCTS THAT SUPPORT DATETIME DATA CONSTANT VALUES FOR DATES TIMES AND TIME INTERVALS ARE SPECIFIED AS STRING CONSTANTS 4HE FORMAT OF THESE CONSTANTS VARIES FROM ONE $"-3 TO THE NEXT %VEN MORE VARIATION IS INTRODUCED BY THE DIFFERENCES IN THE WAY DATES AND TIMES ARE WRITTEN IN DIFFERENT COUNTRIES )"-S $" SUPPORTS SEVERAL DIFFERENT INTERNATIONAL FORMATS FOR DATE TIME AND TIMESTAMP CONSTANTS AS SHOWN IN 4ABLE 4HE CHOICE OF FORMAT IS MADE WHEN THE $"-3 IS INSTALLED $" ALSO SUPPORTS DURATIONS SPECIFIED AS SPECIAL CONSTANTS AS IN THIS EXAMPLE ()2%?$!4% $!93
.OTE THAT A DURATION CANT BE STORED IN THE DATABASE HOWEVER BECAUSE $" DOESNT HAVE AN EXPLICIT $52!4)/. DATA TYPE 31, 3ERVER ALSO SUPPORTS DATETIME DATA AND ACCEPTS A VARIETY OF DIFFERENT FORMATS FOR DATE AND TIME CONSTANTS 4HE $"-3 AUTOMATICALLY ACCEPTS ALL OF THE ALTERNATE FORMATS AND YOU CAN INTERMIX THEM IF YOU LIKE (ERE ARE SOME EXAMPLES OF LEGAL 31, 3ERVER DATE CONSTANTS -ARCH -AR -!2
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#HAPTERçç
31,ç"ASICSç
AND HERE ARE SOME LEGAL TIME CONSTANTS 0- PM 0-
/RACLE DATES AND TIMES ARE ALSO WRITTEN AS STRING CONSTANTS USING THIS FORMAT -!2
9OU CAN ALSO USE /RACLES BUILT IN 4/?$!4% FUNCTION TO CONVERT DATE CONSTANTS WRITTEN IN OTHER FORMATS AS IN THIS EXAMPLE
4HE 31, STANDARD SPECIFIES A FORMAT FOR DATE AND TIME CONSTANTS BASED ON THE )3/ FORMAT IN 4ABLE EXCEPT THAT TIME CONSTANTS ARE WRITTEN WITH COLONS INSTEAD OF PERIODS SEPARATING THE HOURS MINUTES AND SECONDS 4HE 31, 3TANDARD 4)-%34!-0 TYPE NOT SHOWN IN THE TABLE HAS A FORMAT OF YYYY MM DD HHMMSSNNNNNNFOR EXAMPLE h v REPRESENTS AT ROUGHLY PM
3YMBOLICõ#ONSTANTS )N ADDITION TO USER SUPPLIED CONSTANTS THE 31, INCLUDES SPECIAL SYMBOLIC CONSTANTS THAT RETURN DATA VALUES MAINTAINED BY THE $"-3 ITSELF &OR EXAMPLE IN SOME $"-3 BRANDS THE SYMBOLIC CONSTANT #522%.4?$!4% YIELDS THE VALUE OF THE CURRENT DATE AND CAN BE USED IN QUERIES SUCH AS THE FOLLOWING WHICH LISTS THE SALESPEOPLE WHOSE HIRE DATE IS STILL IN THE FUTURE 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% #522%.4?$!4%
4HE 31, STANDARD SPECIFIED ONLY A SINGLE SYMBOLIC CONSTANT THE 53%2 CONSTANT DESCRIBED IN #HAPTER BUT MOST 31, PRODUCTS PROVIDE MANY MORE 'ENERALLY A SYMBOLIC CONSTANT CAN APPEAR IN A 31, STATEMENT ANYWHERE THAT AN ORDINARY CONSTANT OF THE SAME DATA TYPE COULD APPEAR 4HE 31, STANDARD ADOPTED THE MOST USEFUL SYMBOLIC CONSTANTS FROM CURRENT 31, IMPLEMENTATIONS AND PROVIDES FOR #522%.4?$!4% #522%.4?4)-% AND #522%.4?4)-%34!-0 NOTE THE UNDERSCORES AS WELL AS 53%2 3%33)/.?53%2 AND 3934%-?53%2 3OME 31, PRODUCTS INCLUDING 31, 3ERVER PROVIDE ACCESS TO SYSTEM VALUES THROUGH BUILT IN FUNCTIONS RATHER THAN SYMBOLIC CONSTANTS 4HE 31, 3ERVER VERSION OF THE PRECEDING QUERY IS 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% ()2%?$!4% '%4$!4%
"UILT IN FUNCTIONS ARE DESCRIBED LATER IN THIS CHAPTER IN THE SECTION h"UILT )N &UNCTIONSv
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%XPRESSIONS %XPRESSIONS ARE USED IN THE 31, TO CALCULATE VALUES THAT ARE RETRIEVED FROM A DATABASE AND TO CALCULATE VALUES USED IN SEARCHING THE DATABASE &OR EXAMPLE THIS QUERY CALCULATES THE SALES OF EACH OFFICE AS A PERCENTAGE OF ITS TARGET 3%,%#4 #)49 4!2'%4 3!,%3 3!,%34!2'%4 &2/- /&&)#%3
AND THIS QUERY LISTS THE OFFICES WHOSE SALES ARE MORE THAN OVER TARGET 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 3!,%3 4!2'%4
4HE !.3))3/ 31, STANDARD SPECIFIES FOUR ARITHMETIC OPERATIONS THAT CAN BE USED IN EXPRESSIONS ADDITION 8 9 SUBTRACTION 8 n 9 MULTIPLICATION 8 9 AND DIVISION 8 9 0ARENTHESES CAN ALSO BE USED TO FORM MORE COMPLICATED EXPRESSIONS LIKE THIS ONE 3!,%3 4!2'%4
3TRICTLY SPEAKING THE PARENTHESES ARE NOT REQUIRED IN THIS QUERY BECAUSE THE !.3))3/ STANDARD SPECIFIES THAT MULTIPLICATION AND DIVISION HAVE A HIGHER PRECEDENCE THAN ADDITION AND SUBTRACTION (OWEVER YOU SHOULD ALWAYS USE PARENTHESES TO MAKE YOUR EXPRESSIONS UNAMBIGUOUS BECAUSE DIFFERENT 31, DIALECTS MAY USE DIFFERENT RULES 4HE PARENTHESES ALSO INCREASE THE READABILITY OF THE STATEMENT AND MAKE PROGRAMMATIC 31, STATEMENTS EASIER TO MAINTAIN 4HE !.3))3/ 31, STANDARD ALSO SPECIFIES AUTOMATIC DATA TYPE CONVERSION FROM INTEGERS TO DECIMAL NUMBERS AND FROM DECIMAL NUMBERS TO FLOATING POINT NUMBERS AS REQUIRED 9OU CAN THUS MIX THESE DATA TYPES IN A NUMERIC EXPRESSION -ANY 31, IMPLEMENTATIONS SUPPORT OTHER OPERATORS AND ALLOW OPERATIONS ON CHARACTER AND DATE DATA 4HE 31, STANDARD SPECIFIES A STRING CONCATENATION OPERATOR WRITTEN AS TWO CONSECUTIVE VERTICAL BAR CHARACTERS \\ WHICH IS SUPPORTED BY MOST IMPLEMENTATIONS ! NOTABLE EXCEPTION IS 31, 3ERVER WHICH USES THE PLUS SIGN INSTEAD )F TWO COLUMNS NAMED &)234?.!-% AND ,!34?.!-% CONTAIN THE VALUES h*IMv AND h*ACKSONv THEN THIS $" EXPRESSION g-R-RS g \\ &)234?.!-% \\ g g \\ ,!34?.!-%
PRODUCES THE STRING h-R-RS *IM *ACKSONv !S ALREADY MENTIONED $" AND MANY OTHER IMPLEMENTATIONS ALSO SUPPORT ADDITION AND SUBTRACTION OF $!4% 4)-% AND 4)-%34!-0 DATA FOR OCCASIONS WHEN THOSE OPERATIONS MAKE SENSE 4HIS CAPABILITY HAS BEEN INCLUDED IN THE 31, STANDARD
"UILT )Nõ&UNCTIONS ! NUMBER OF USEFUL BUILT IN FUNCTIONS ARE SPECIFIED IN 31, STANDARD AND MOST 31, IMPLEMENTATIONS ADD MANY MORE 4HESE FACILITIES OFTEN PROVIDE DATA TYPE CONVERSION FACILITIES &OR EXAMPLE $"S BUILT IN -/.4( AND 9%!2 FUNCTIONS TAKE A $!4% OR 4)-%34!-0 VALUE AS THEIR INPUT AND RETURN AN INTEGER THAT IS THE MONTH OR YEAR PORTION OF THE VALUE 4HIS QUERY LISTS THE NAME AND MONTH OF HIRE FOR EACH SALESPERSON IN THE SAMPLE DATABASE 3%,%#4 .!-% -/.4(()2%?$!4% &2/- 3!,%32%03
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AND THIS ONE LISTS ALL SALESPEOPLE HIRED IN 3%,%#4 .!-% -/.4(()2%?$!4% &2/- 3!,%32%03 7(%2% 9%!2()2%?$!4%
"UILT IN FUNCTIONS ARE ALSO OFTEN USED FOR DATA REFORMATTING /RACLES BUILT IN 4/?#(!2 FUNCTION FOR EXAMPLE TAKES A $!4% DATA TYPE AND A FORMAT SPECIFICATION AS ITS ARGUMENTS AND RETURNS A STRING CONTAINING A FORMATTED CHARACTER STRING VERSION OF THE DATE 4HIS SAME FUNCTION IS ALSO CAPABLE OF CONVERTING NUMERIC VALUES TO FORMATTED CHARACTER STRINGS )N THE RESULTS PRODUCED BY THIS QUERY
THE HIRE DATES WILL ALL HAVE THE FORMAT h7EDNESDAY *UNE v BECAUSE OF THE BUILT IN FUNCTION )N GENERAL A BUILT IN FUNCTION CAN BE SPECIFIED IN A 31, EXPRESSION ANYWHERE THAT A CONSTANT OF THE SAME DATA TYPE CAN BE SPECIFIED 4HE BUILT IN FUNCTIONS SUPPORTED BY POPULAR 31, DIALECTS ARE TOO NUMEROUS TO LIST HERE 4HE )"- $" 31, DIALECTS INCLUDE ABOUT TWO DOZEN BUILT IN FUNCTIONS /RACLE SUPPORTS A DIFFERENT SET OF ABOUT TWO DOZEN BUILT IN FUNCTIONS AND 31, 3ERVER HAS SEVERAL DOZEN 4HE 31, STANDARD INCORPORATED THE MOST USEFUL BUILT IN FUNCTIONS FROM THESE IMPLEMENTATIONS IN MANY CASES WITH SLIGHTLY DIFFERENT SYNTAX 4HESE FUNCTIONS ARE SUMMARIZED IN 4ABLE ÕVÌ
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-ISSINGõ$ATAõ.5,,õ6ALUES "ECAUSE A DATABASE IS USUALLY A MODEL OF A REAL WORLD SITUATION CERTAIN PIECES OF DATA ARE INEVITABLY MISSING UNKNOWN OR DONT APPLY )N THE SAMPLE DATABASE FOR EXAMPLE THE 15/4! COLUMN IN THE 3!,%32%03 TABLE CONTAINS THE SALES GOAL FOR EACH SALESPERSON (OWEVER THE NEWEST SALESPERSON HAS NOT YET BEEN ASSIGNED A QUOTA THIS DATA IS MISSING FOR THAT ROW OF THE TABLE 9OU MIGHT BE TEMPTED TO PUT A ZERO IN THE COLUMN FOR THIS SALESPERSON BUT THAT WOULD NOT BE AN ACCURATE REFLECTION OF THE SITUATION 4HE SALESPERSON DOES NOT HAVE A ZERO QUOTA THE QUOTA IS JUST hNOT YET KNOWNv 3IMILARLY THE -!.!'%2 COLUMN IN THE 3!,%32%03 TABLE CONTAINS THE EMPLOYEE NUMBER OF EACH SALESPERSONS MANAGER "UT 3AM #LARK THE VICE PRESIDENT OF SALES HAS NO MANAGER IN THE SALES ORGANIZATION 4HIS COLUMN DOES NOT APPLY TO 3AM !GAIN YOU MIGHT THINK ABOUT ENTERING A ZERO OR A IN THE COLUMN BUT NEITHER OF THESE VALUES WOULD REALLY BE THE EMPLOYEE NUMBER OF 3AMS BOSS .O DATA VALUE IS APPLICABLE TO THIS ROW 31, SUPPORTS MISSING UNKNOWN OR INAPPLICABLE DATA EXPLICITLY THROUGH THE CONCEPT OF A NULL VALUE ! NULL VALUE IS AN INDICATOR THAT TELLS 31, AND THE USER THAT THE DATA IS MISSING OR NOT APPLICABLE !S A CONVENIENCE A MISSING PIECE OF DATA IS OFTEN SAID TO HAVE THE VALUE .5,, "UT THE .5,, VALUE IS NOT A REAL DATA VALUE LIKE OR h3AM #LARKv )NSTEAD ITS A SIGNAL OR A REMINDER THAT THE DATA VALUE IS MISSING OR UNKNOWN &IGURE SHOWS THE CONTENTS OF THE 3!,%32%03 TABLE .OTE THAT THE 15/4! AND 2%0?/&&)#% VALUES FOR 4OM 3NYDERS ROW AND THE -!.!'%2 VALUE FOR 3AM #LARKS ROW OF THE TABLE ALL CONTAIN .5,, VALUES !LSO NOTE THAT 31, TOOLS DO NOT DISPLAY NULL VALUES IN QUERY RESULTS IN THE SAME WAYWHILE MANY USE THE STRING .5,, AS SHOWN IN &IGURE OTHERS USE EMPTY SPACE OR CHARACTER STRINGS )N MANY SITUATIONS .5,, VALUES REQUIRE SPECIAL HANDLING BY THE $"-3 &OR EXAMPLE IF THE USER REQUESTS THE SUM OF THE 15/4! COLUMN HOW SHOULD THE $"-3 HANDLE THE MISSING DATA WHEN COMPUTING THE SUM 4HE ANSWER IS GIVEN BY A SET OF SPECIAL RULES THAT GOVERN .5,, VALUE HANDLING IN VARIOUS 31, STATEMENTS AND CLAUSES "ECAUSE OF THESE RULES SOME LEADING DATABASE AUTHORITIES FEEL STRONGLY THAT .5,, VALUES SHOULD NOT BE USED /THERS INCLUDING 4ED #ODD HAVE ADVOCATED THE USE OF MULTIPLE .5,, VALUES WITH DISTINCT INDICATORS FOR hUNKNOWNv AND hNOT APPLICABLEv DATA
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2EGARDLESS OF THE ACADEMIC DEBATES .5,, VALUES ARE A WELL ENTRENCHED PART OF THE !.3))3/ 31, STANDARD AND ARE SUPPORTED IN VIRTUALLY ALL COMMERCIAL 31, PRODUCTS 4HEY ALSO PLAY AN IMPORTANT PRACTICAL ROLE IN PRODUCTION OF 31, DATABASES 4HE SPECIAL RULES THAT APPLY TO .5,, VALUES AND THE CASES WHERE .5,, VALUES ARE HANDLED INCONSISTENTLY BY VARIOUS 31, PRODUCTS ARE POINTED OUT THROUGHOUT THIS BOOK
3UMMARY 4HIS CHAPTER DESCRIBED THE BASIC ELEMENTS OF 31, 4HE BASIC STRUCTURE OF 31, CAN BE SUMMARIZED AS FOLLOWS
s 31, BASED DATABASES CAN STORE VARIOUS TYPES OF DATA INCLUDING TEXT INTEGERS DECIMAL NUMBERS FLOATING POINT NUMBERS AND USUALLY MANY MORE VENDOR SPECIFIC DATA TYPES s 31, STATEMENTS CAN INCLUDE EXPRESSIONS THAT COMBINE COLUMN NAMES CONSTANTS AND BUILT IN FUNCTIONS USING ARITHMETIC AND OTHER VENDOR SPECIFIC OPERATORS s 6ARIATIONS IN DATA TYPES CONSTANTS AND BUILT IN FUNCTIONS MAKE PORTABILITY OF 31, STATEMENTS MORE DIFFICULT THAN IT MAY SEEM AT FIRST s .5,, VALUES PROVIDE A SYSTEMATIC WAY OF HANDLING MISSING OR INAPPLICABLE DATA IN THE 31,
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s 31, THAT IS IN COMMON USE INCLUDES ABOUT STATEMENTS EACH CONSISTING OF A VERB AND ONE OR MORE CLAUSES %ACH STATEMENT PERFORMS A SINGLE SPECIFIC FUNCTION
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N MANY WAYS QUERIES ARE THE HEART OF 31, 4HE 3%,%#4 STATEMENT WHICH IS USED TO EXPRESS 31, QUERIES IS THE MOST POWERFUL AND COMPLEX OF THE 31, STATEMENTS $ESPITE THE MANY OPTIONS AFFORDED BY THE 3%,%#4 STATEMENT ITS POSSIBLE TO START SIMPLY AND THEN WORK UP TO MORE COMPLEX QUERIES 4HIS CHAPTER DISCUSSES THE SIMPLEST 31, QUERIESTHOSE THAT RETRIEVE DATA FROM INDIVIDUAL ROWS OF A SINGLE TABLE IN THE DATABASE )F YOU HAVE NOT DONE SO ALREADY YOU WILL LEARN MORE IF YOU CREATE THE SAMPLE DATABASE ON YOUR OWN SYSTEM AND TRY THE QUERIES FOR YOURSELF AS YOU READ )NSTRUCTIONS FOR THE SAMPLE DATABASE ARE IN !PPENDIX !
4HEõ3%,%#4õ3TATEMENT 4HE 3%,%#4 STATEMENT RETRIEVES DATA FROM A DATABASE AND RETURNS IT TO YOU IN THE FORM OF QUERY RESULTS !S A REMINDER THE EXACT FORMAT OF THE QUERY RESULTS WILL VARY FROM ONE 31, PRODUCT TO ANOTHER 9OU HAVE ALREADY SEEN MANY EXAMPLES OF THE 3%,%#4 STATEMENT IN THE QUICK TOUR PRESENTED IN #HAPTER (ERE ARE SEVERAL MORE SAMPLE QUERIES THAT RETRIEVE INFORMATION ABOUT SALES OFFICES ,IST THE SALES OFFICES WITH THEIR TARGETS AND ACTUAL SALES 3%,%#4 #)49 4!2'%4 3!,%3 &2/- /&&)#%3 #)49 4!2'%4 3!,%3
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,IST THE %ASTERN REGION SALES OFFICES WITH THEIR TARGETS AND SALES 3%,%#4 #)49 4!2'%4 3!,%3 &2/- /&&)#%3 7(%2% 2%')/. g%ASTERNg #)49 4!2'%4 3!,%3
.EW 9ORK #HICAGO !TLANTA
,IST %ASTERN REGION SALES OFFICES WHOSE SALES EXCEED THEIR TARGETS SORTED IN ALPHABETICAL ORDER BY CITY 3%,%#4 #)49 4!2'%4 3!,%3 &2/- /&&)#%3 7(%2% 2%')/. g%ASTERNg !.$ 3!,%3 4!2'%4 /2$%2 "9 #)49 #)49 4!2'%4 3!,%3
!TLANTA .EW 9ORK
&OR SIMPLE QUERIES THE %NGLISH LANGUAGE REQUEST AND THE 31, 3%,%#4 STATEMENT ARE VERY SIMILAR 7HEN THE REQUESTS BECOME MORE COMPLEX MORE FEATURES OF THE 3%,%#4 STATEMENT MUST BE USED TO SPECIFY THE QUERY PRECISELY &IGURE SHOWS THE FULL FORM OF THE 3%,%#4 STATEMENT WHICH CONSISTS OF SIX CLAUSES 4HE 3%,%#4 AND &2/- CLAUSES OF THE STATEMENT ARE REQUIRED 4HE REMAINING FOUR CLAUSES ARE OPTIONAL 9OU INCLUDE THEM IN A 3%,%#4 STATEMENT ONLY WHEN YOU WANT TO USE THE FUNCTIONS THEY PROVIDE 4HE FOLLOWING LIST SUMMARIZES THE FUNCTION OF EACH CLAUSE s 4HE 3%,%#4 CLAUSE LISTS THE DATA ITEMS TO BE RETRIEVED BY THE 3%,%#4 STATEMENT 4HE ITEMS MAY BE COLUMNS FROM THE DATABASE OR COLUMNS TO BE CALCULATED BY 31, AS IT PERFORMS THE QUERY 4HE 3%,%#4 CLAUSE IS DESCRIBED IN THE NEXT SECTION s 4HE &2/- CLAUSE LISTS THE TABLES AND VIEWS THAT CONTAIN THE DATA TO BE RETRIEVED BY THE QUERY 6IEWS ARE DISCUSSED IN DETAIL IN #HAPTER 1UERIES THAT DRAW THEIR DATA FROM A SINGLE TABLE ARE DESCRIBED IN THIS CHAPTER -ORE COMPLEX QUERIES THAT COMBINE DATA FROM TWO OR MORE TABLES ARE DISCUSSED IN #HAPTER s 4HE 7(%2% CLAUSE TELLS 31, TO INCLUDE ONLY CERTAIN ROWS OF DATA IN THE QUERY RESULTS ! SEARCH CONDITION IS USED TO SPECIFY THE DESIRED ROWS 4HE BASIC USES OF THE 7(%2% CLAUSE ARE DESCRIBED IN THE h2OW 3ELECTION 7(%2% #LAUSE v SECTION LATER IN THIS CHAPTER 4HOSE THAT INVOLVE SUBQUERIES ARE DISCUSSED IN #HAPTER s 4HE '2/50 "9 CLAUSE SPECIFIES A SUMMARY QUERY )NSTEAD OF PRODUCING ONE ROW OF QUERY RESULTS FOR EACH ROW OF DATA IN THE DATABASE A SUMMARY QUERY GROUPS TOGETHER SIMILAR ROWS AND THEN PRODUCES ONE SUMMARY ROW OF QUERY RESULTS FOR EACH GROUP 3UMMARY QUERIES ARE DESCRIBED IN #HAPTER
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s 4HE (!6).' CLAUSE TELLS 31, TO INCLUDE ONLY CERTAIN GROUPS PRODUCED BY THE '2/50 "9 CLAUSE IN THE QUERY RESULTS ,IKE THE 7(%2% CLAUSE IT USES A SEARCH CONDITION TO SPECIFY THE DESIRED GROUPS 4HE (!6).' CLAUSE IS DESCRIBED IN #HAPTER s 4HE /2$%2 "9 CLAUSE SORTS THE QUERY RESULTS BASED ON THE DATA IN ONE OR MORE COLUMNS )F IT IS OMITTED THE QUERY RESULTS ARE NOT SORTED 4HE /2$%2 "9 CLAUSE IS DESCRIBED IN THE h3ORTING 1UERY 2ESULTS /2$%2 "9 #LAUSE v SECTION LATER IN THIS CHAPTER
4HEõ3%,%#4õ#LAUSE 4HE 3%,%#4 CLAUSE THAT BEGINS EACH 3%,%#4 STATEMENT SPECIFIES THE DATA ITEMS TO BE RETRIEVED BY THE QUERY 4HE ITEMS ARE USUALLY SPECIFIED BY A SELECT LIST A LIST OF SELECT ITEMS SEPARATED BY COMMAS %ACH SELECT ITEM IN THE LIST GENERATES A SINGLE COLUMN OF QUERY RESULTS IN LEFT TO RIGHT ORDER ! SELECT ITEM CAN BE ONE OF THE FOLLOWING s ! COLUMN NAME IDENTIFYING A COLUMN FROM THE TABLES NAMED IN THE &2/- CLAUSE 7HEN A COLUMN NAME APPEARS AS A SELECT ITEM 31, SIMPLY TAKES THE VALUE OF THAT COLUMN FROM EACH ROW OF THE DATABASE TABLE AND PLACES IT IN THE CORRESPONDING ROW OF QUERY RESULTS s ! CONSTANT SPECIFYING THAT THE SAME CONSTANT VALUE IS TO APPEAR IN EVERY ROW OF THE QUERY RESULTS s ! 31, EXPRESSION INDICATING THAT 31, MUST CALCULATE THE VALUE TO BE PLACED INTO THE QUERY RESULTS AS SPECIFIED BY THE EXPRESSION %ACH TYPE OF SELECT ITEM IS DESCRIBED LATER IN THIS CHAPTER
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4HEõ&2/-õ#LAUSE 4HE &2/- CLAUSE CONSISTS OF THE KEYWORD &2/- FOLLOWED BY A LIST OF TABLE SPECIFICATIONS SEPARATED BY COMMAS %ACH TABLE SPECIFICATION IDENTIFIES A TABLE OR VIEW CONTAINING DATA TO BE RETRIEVED BY THE QUERY 4HESE TABLES ARE CALLED THE SOURCE TABLES OF THE QUERY AND OF THE 3%,%#4 STATEMENT BECAUSE THEY ARE THE SOURCE OF ALL OF THE DATA IN THE QUERY RESULTS !LL OF THE QUERIES IN THIS CHAPTER HAVE A SINGLE SOURCE TABLE AND EVERY &2/- CLAUSE CONTAINS A SINGLE TABLE NAME
1UERYõ2ESULTS 4HE RESULT OF A 31, QUERY IS ALWAYS A TABLE OF DATA JUST LIKE THE TABLES IN THE DATABASE )F YOU TYPE A 3%,%#4 STATEMENT USING INTERACTIVE 31, THE $"-3 DISPLAYS THE QUERY RESULTS WHICH SOME VENDORS CALL A RESULT SET IN TABULAR FORM ON YOUR COMPUTER SCREEN )F A COMPUTER PROGRAM SENDS A QUERY TO THE $"-3 USING PROGRAMMATIC 31, THE TABLE OF QUERY RESULTS IS RETURNED TO THE PROGRAM FOR PROCESSING )N EITHER CASE THE QUERY RESULTS ALWAYS HAVE THE SAME TABULAR ROWCOLUMN FORMAT AS THE ACTUAL TABLES IN THE DATABASE AS SHOWN IN &IGURE 5SUALLY THE QUERY RESULTS WILL BE A TABLE WITH SEVERAL COLUMNS AND SEVERAL ROWS &OR EXAMPLE THE FOLLOWING QUERY PRODUCES A TABLE OF THREE COLUMNS BECAUSE IT ASKS FOR THREE ITEMS OF DATA AND TEN ROWS BECAUSE THERE ARE TEN SALESPEOPLE ,IST THE NAMES OFFICES AND HIRE DATES OF ALL SALESPEOPLE 3%,%#4 .!-% 2%0?/&&)#% ()2%?$!4% &2/- 3!,%32%03 .!-% 2%0?/&&)#% ()2%?$!4%
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH $AN 2OBERTS 4OM 3NYDER .5,, ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI
)N CONTRAST THE FOLLOWING QUERY PRODUCES A SINGLE ROW BECAUSE ONLY ONE SALESPERSON HAS THE REQUESTED EMPLOYEE NUMBER %VEN THOUGH THIS SINGLE ROW OF QUERY RESULTS LOOKS LESS hTABULARv THAN THE MULTIROW RESULTS 31, STILL CONSIDERS IT TO BE A TABLE OF THREE COLUMNS AND ONE ROW 7HAT ARE THE NAME QUOTA AND SALES OF EMPLOYEE NUMBER 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% %-0,?.5- .!-% 15/4! 3!,%3
.ANCY !NGELLI
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)N SOME CASES THE QUERY RESULTS CAN BE A SINGLE VALUE AS IN THE FOLLOWING EXAMPLE 7HAT ARE THE AVERAGE SALES OF OUR SALESPEOPLE 3%,%#4 !6'3!,%3 &2/- 3!,%32%03 !6'3!,%3
4HESE QUERY RESULTS ARE STILL A TABLE ALTHOUGH ITS A VERY SMALL ONE CONSISTING OF ONE COLUMN AND ONE ROW &INALLY ITS POSSIBLE FOR A QUERY TO PRODUCE ZERO ROWS OF QUERY RESULTS AS IN THIS EXAMPLE ,IST THE NAME AND HIRE DATE OF ANYONE WITH SALES OVER 3%,%#4 .!-% ()2%?$!4% &2/- 3!,%32%03 7(%2% 3!,%3 .!-% ()2%?$!4%
%VEN IN THIS SITUATION THE QUERY RESULTS ARE STILL A TABLE 4HIS ONE IS AN EMPTY TABLE WITH TWO COLUMNS AND ZERO ROWS .OTE THAT 31,S SUPPORT FOR MISSING DATA EXTENDS TO QUERY RESULTS AS WELL )F A DATA ITEM IN THE DATABASE HAS A .5,, VALUE THE .5,, VALUE APPEARS IN THE QUERY RESULTS WHEN THE
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DATA ITEM IS RETRIEVED &OR EXAMPLE THE 3!,%32%03 TABLE CONTAINS .5,, VALUES IN ITS 15/4! AND -!.!'%2 COLUMNS 4HE NEXT QUERY RETURNS THESE .5,, VALUES IN THE SECOND AND THIRD COLUMNS OF QUERY RESULTS .OTE THAT NOT ALL 31, PRODUCTS DISPLAY .5,, VALUES IN THE SAME WAY/RACLE AND $" FOR EXAMPLE DISPLAY NOTHING WHEN A .5,, VALUE IS ENCOUNTERED ,IST THE SALESPEOPLE THEIR QUOTAS AND THEIR MANAGERS 3%,%#4 .!-% 15/4! -!.!'%2 &2/- 3!,%32%03 .!-% 15/4! -!.!'%2
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK .5,, "OB 3MITH $AN 2OBERTS 4OM 3NYDER .5,, ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI
4HE FACT THAT A 31, QUERY ALWAYS PRODUCES A TABLE OF DATA IS VERY IMPORTANT )T MEANS THAT THE QUERY RESULTS CAN BE STORED BACK INTO THE DATABASE AS A TABLE )T MEANS THAT THE RESULTS OF TWO SIMILAR QUERIES CAN BE COMBINED TO FORM A LARGER TABLE OF QUERY RESULTS &INALLY IT MEANS THAT THE QUERY RESULTS CAN THEMSELVES BE THE TARGET OF FURTHER QUERIES ! RELATIONAL DATABASES TABULAR STRUCTURE THUS HAS A VERY SYNERGISTIC RELATIONSHIP WITH THE RELATIONAL QUERY FACILITIES OF 31, 4ABLES CAN BE QUERIED AND QUERIES PRODUCE TABLES
3IMPLEõ1UERIES 4HE SIMPLEST 31, QUERIES REQUEST COLUMNS OF DATA FROM A SINGLE TABLE IN THE DATABASE &OR EXAMPLE THIS QUERY REQUESTS THREE COLUMNS FROM THE /&&)#%3 TABLE ,IST THE LOCATION REGION AND SALES OF EACH SALES OFFICE 3%,%#4 #)49 2%')/. 3!,%3 &2/- /&&)#%3 #)49 2%')/. 3!,%3
$ENVER 7ESTERN .EW 9ORK %ASTERN #HICAGO %ASTERN !TLANTA %ASTERN ,OS !NGELES 7ESTERN
4HE 3%,%#4 STATEMENT FOR SIMPLE QUERIES LIKE THIS ONE INCLUDES ONLY THE TWO REQUIRED CLAUSES 4HE 3%,%#4 CLAUSE NAMES THE REQUESTED COLUMNS THE &2/- CLAUSE NAMES THE TABLE OR VIEW THAT CONTAINS THEM
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#ONCEPTUALLY 31, PROCESSES THE QUERY BY GOING THROUGH THE TABLE NAMED IN THE &2/- CLAUSE ONE ROW AT A TIME &OR EACH ROW 31, TAKES THE VALUES OF THE COLUMNS REQUESTED IN THE SELECT LIST AND PRODUCES A SINGLE ROW OF QUERY RESULTS 4HE QUERY RESULTS THUS CONTAIN ONE ROW OF DATA FOR EACH ROW IN THE TABLE
#ALCULATEDõ#OLUMNS
,IST THE CITY REGION AND AMOUNT OVERUNDER TARGET FOR EACH OFFICE 3%,%#4 #)49 2%')/. 3!,%3 4!2'%4 &2/- /&&)#%3 #)49 2%')/. 3!,%3 4!2'%4
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4O PROCESS THE QUERY 31, GOES THROUGH THE OFFICES GENERATING ONE ROW OF QUERY RESULTS FOR EACH ROW OF THE /&&)#%3 TABLE AS SHOWN IN &IGURE 4HE FIRST TWO COLUMNS OF QUERY RESULTS COME DIRECTLY FROM THE /&&)#%3 TABLE 4HE THIRD COLUMN OF QUERY RESULTS IS CALCULATED ROW BY ROW USING THE DATA VALUES FROM THE CURRENT ROW OF THE /&&)#%3 TABLE (ERE ARE OTHER EXAMPLES OF QUERIES THAT USE CALCULATED COLUMNS 3HOW THE VALUE OF THE INVENTORY FOR EACH PRODUCT /NLY THE FIRST ROWS IN THE RESULT SET ARE SHOWN 3%,%#4 -&2?)$ 02/$5#4?)$ $%3#2)04)/. 149?/.?(!.$ 02)#% &2/- 02/$5#43 -&2?)$ 02/$5#4?)$ $%3#2)04)/. 149?/.?(!.$ 02)#%
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)N ADDITION TO COLUMNS WHOSE VALUES COME DIRECTLY FROM THE DATABASE A 31, QUERY CAN INCLUDE CALCULATED COLUMNS WHOSE VALUES ARE CALCULATED FROM THE STORED DATA VALUES 4O REQUEST A CALCULATED COLUMN YOU SPECIFY A 31, EXPRESSION IN THE SELECT LIST !S DISCUSSED IN #HAPTER 31, EXPRESSIONS CAN INVOLVE ADDITION SUBTRACTION MULTIPLICATION AND DIVISION 9OU CAN ALSO USE PARENTHESES TO BUILD MORE COMPLEX EXPRESSIONS /F COURSE THE COLUMNS REFERENCED IN AN ARITHMETIC EXPRESSION MUST HAVE A NUMERIC TYPE )F YOU TRY TO ADD SUBTRACT MULTIPLY OR DIVIDE COLUMNS CONTAINING TEXT DATA 31, WILL REPORT AN ERROR 4HIS QUERY SHOWS A SIMPLE CALCULATED COLUMN
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3HOW ME THE RESULT IF ) RAISED EACH SALESPERSONS QUOTA BY PERCENT OF THEIR YEAR TO DATE SALES 3%,%#4 .!-% 15/4! 15/4! 3!,%3 &2/- 3!,%32%03 .!-% 15/4! 15/4! 3!,%3
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH $AN 2OBERTS 4OM 3NYDER .5,, .5,, ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI
!S MENTIONED IN #HAPTER MANY 31, PRODUCTS PROVIDE ADDITIONAL ARITHMETIC OPERATIONS CHARACTER STRING OPERATIONS AND BUILT IN FUNCTIONS THAT CAN BE USED IN 31, EXPRESSIONS 4HESE CAN APPEAR IN SELECT LIST EXPRESSIONS AS IN THE NEXT $" EXAMPLE WHICH EXTRACTS THE MONTH AND YEAR FROM A DATE ,IST THE NAME MONTH AND YEAR OF HIRE FOR EACH SALESPERSON &OR /RACLE DATABASES THE 4/?#(!2 FUNCTION MUST BE USED INSTEAD OF THE -/.4( AND 9%!2 FUNCTIONS 3%,%#4 .!-% -/.4(()2%?$!4% 9%!2()2%?$!4% &2/- 3!,%32%03
#HAPTERçç
3IMPLEç1UERIESç
31, CONSTANTS CAN ALSO BE USED BY THEMSELVES AS ITEMS IN A SELECT LIST 4HIS CAN BE USEFUL FOR PRODUCING QUERY RESULTS THAT ARE EASIER TO READ AND INTERPRET AS IN THE NEXT EXAMPLE ,IST THE SALES FOR EACH CITY
4HE QUERY RESULTS APPEAR TO CONSIST OF A SEPARATE hSENTENCEv FOR EACH OFFICE BUT THEYRE REALLY A TABLE OF THREE COLUMNS 4HE FIRST AND THIRD COLUMNS CONTAIN VALUES FROM THE /&&)#%3 TABLE 4HE SECOND COLUMN ALWAYS CONTAINS THE SAME CHARACTER TEXT STRING
3ELECTINGõ!LLõ#OLUMNSõ3%,%#4õ 3OMETIMES ITS CONVENIENT TO DISPLAY THE CONTENTS OF ALL THE COLUMNS OF A TABLE 4HIS CAN BE PARTICULARLY USEFUL WHEN YOU FIRST ENCOUNTER A NEW DATABASE AND WANT TO GET A QUICK UNDERSTANDING OF ITS STRUCTURE AND THE DATA IT CONTAINS !S A CONVENIENCE 31, LETS YOU USE AN ASTERISK IN PLACE OF THE SELECT LIST AS AN ABBREVIATION FOR hALL COLUMNSv 3HOW ME ALL THE DATA IN THE /&&)#%3 TABLE 3%,%#4 &2/- /&&)#%3 /&&)#% #)49 2%')/. -'2 4!2'%4 3!,%3
$ENVER 7ESTERN .EW 9ORK %ASTERN #HICAGO %ASTERN !TLANTA %ASTERN ,OS !NGELES 7ESTERN
4HE QUERY RESULTS CONTAIN ALL SIX COLUMNS OF THE /&&)#%3 TABLE IN THE SAME LEFT TO RIGHT ORDER AS IN THE TABLE ITSELF 4HE ALL COLUMNS SELECTION IS MOST APPROPRIATE WHEN YOU ARE USING INTERACTIVE 31, CASUALLY )T SHOULD BE AVOIDED IN PROGRAMMATIC 31, BECAUSE CHANGES IN THE DATABASE STRUCTURE CAN CAUSE A PROGRAM TO FAIL &OR EXAMPLE SUPPOSE THE /&&)#%3 TABLE WAS DROPPED FROM THE DATABASE AND THEN RE CREATED WITH ITS COLUMNS REARRANGED AND A NEW SEVENTH COLUMN ADDED 31, AUTOMATICALLY TAKES CARE OF THE DATABASE RELATED DETAILS OF SUCH CHANGES BUT IT CANNOT MODIFY YOUR APPLICATION PROGRAM FOR YOU )F YOUR PROGRAM EXPECTS A 3%,%#4 &2/- /&&)#%3 QUERY TO RETURN SIX COLUMNS OF QUERY RESULTS WITH CERTAIN DATA TYPES IT WILL ALMOST CERTAINLY STOP WORKING WHEN THE COLUMNS ARE REARRANGED AND A NEW ONE IS ADDED
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3%,%#4 #)49 gHAS SALES OFg 3!,%3 &2/- /&&)#%3 #)49 (!3 3!,%3 /& 3!,%3
$ENVER HAS SALES OF .EW 9ORK HAS SALES OF #HICAGO HAS SALES OF !TLANTA HAS SALES OF ,OS !NGELES HAS SALES OF
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4HESE DIFFICULTIES CAN BE AVOIDED IF YOU WRITE THE PROGRAM TO REQUEST THE COLUMNS IT NEEDS BY NAME &OR EXAMPLE THE FOLLOWING QUERY PRODUCES THE SAME RESULTS AS 3%,%#4 &2/- /&&)#%3 )T IS ALSO IMMUNE TO CHANGES IN THE DATABASE STRUCTURE AS LONG AS THE NAMED COLUMNS CONTINUE TO EXIST IN THE /&&)#%3 TABLE 3%,%#4 /&&)#% #)49 2%')/. -'2 4!2'%4 3!,%3 &2/- /&&)#%3
$UPLICATEõ2OWSõ$)34).#4 )F A QUERY INCLUDES THE PRIMARY KEY OF A TABLE IN ITS SELECT LIST THEN EVERY ROW OF QUERY RESULTS WILL BE UNIQUE BECAUSE THE PRIMARY KEY HAS A DIFFERENT VALUE IN EACH ROW )F THE PRIMARY KEY IS NOT INCLUDED IN THE QUERY RESULTS DUPLICATE ROWS CAN OCCUR &OR EXAMPLE SUPPOSE YOU MADE THIS REQUEST ,IST THE EMPLOYEE NUMBERS OF ALL SALES OFFICE MANAGERS 3%,%#4 -'2 &2/- /&&)#%3 -'2
4HE QUERY RESULTS HAVE FIVE ROWS ONE FOR EACH OFFICE BUT TWO OF THEM ARE EXACT DUPLICATES OF ONE ANOTHER 7HY "ECAUSE ,ARRY &ITCH MANAGES BOTH THE ,OS !NGELES AND $ENVER OFFICES AND HIS EMPLOYEE NUMBER APPEARS IN BOTH ROWS OF THE /&&)#%3 TABLE 4HESE QUERY RESULTS ARE PROBABLY NOT EXACTLY WHAT YOU HAD IN MIND )F THERE ARE FOUR DIFFERENT MANAGERS YOU MIGHT HAVE EXPECTED ONLY FOUR EMPLOYEE NUMBERS IN THE QUERY RESULTS 9OU CAN ELIMINATE DUPLICATE ROWS OF QUERY RESULTS BY INSERTING THE KEYWORD $)34).#4 IN THE 3%,%#4 STATEMENT JUST BEFORE THE SELECT LIST (ERE IS A VERSION OF THE PREVIOUS QUERY THAT PRODUCES THE RESULTS YOU WANT ,IST THE EMPLOYEE NUMBERS OF ALL SALES OFFICE MANAGERS 3%,%#4 $)34).#4 -'2 &2/- /&&)#%3 -'2
#ONCEPTUALLY 31, CARRIES OUT THIS QUERY BY FIRST GENERATING A FULL SET OF QUERY RESULTS FIVE ROWS AND THEN ELIMINATING ROWS THAT ARE EXACT DUPLICATES OF ONE ANOTHER TO FORM THE
#HAPTERçç
3IMPLEç1UERIESç
FINAL QUERY RESULTS 4HE $)34).#4 KEYWORD CAN BE SPECIFIED REGARDLESS OF THE CONTENTS OF THE 3%,%#4 LIST WITH CERTAIN RESTRICTIONS FOR SUMMARY QUERIES AS DESCRIBED IN #HAPTER "E AWARE THAT THE 31, ENGINE MAY HAVE TO APPLY A SORT TO IDENTIFY THE DUPLICATE ROWS AND THAT SORTS OF LARGE NUMBERS OF ROWS CAN CAUSE PERFORMANCE PROBLEMS )F THE $)34).#4 KEYWORD IS OMITTED 31, DOES NOT ELIMINATE DUPLICATE ROWS 9OU CAN ALSO SPECIFY THE KEYWORD !,, TO EXPLICITLY INDICATE THAT DUPLICATE ROWS ARE TO BE RETAINED BUT IT IS UNNECESSARY SINCE THIS IS THE DEFAULT BEHAVIOR
2OWõ3ELECTIONõ7(%2%õ#LAUSE
3HOW ME THE OFFICES WHERE SALES EXCEED TARGET 3%,%#4 #)49 3!,%3 4!2'%4 &2/- /&&)#%3 7(%2% 3!,%3 4!2'%4 #)49 3!,%3 4!2'%4
.EW 9ORK !TLANTA ,OS !NGELES
3HOW ME THE NAME SALES AND QUOTA OF EMPLOYEE NUMBER 3%,%#4 .!-% 3!,%3 15/4! &2/- 3!,%32%03 7(%2% %-0,?.5- .!-% 3!,%3 15/4!
"ILL !DAMS
3HOW ME THE EMPLOYEES MANAGED BY "OB 3MITH EMPLOYEE 3%,%#4 .!-% 3!,%3 &2/- 3!,%32%03 7(%2% -!.!'%2 .!-% 3!,%3
"ILL !DAMS $AN 2OBERTS 0AUL #RUZ
4HE 7(%2% CLAUSE CONSISTS OF THE KEYWORD 7(%2% FOLLOWED BY A SEARCH CONDITION THAT SPECIFIES THE ROWS TO BE RETRIEVED )N THE PREVIOUS QUERY FOR EXAMPLE THE SEARCH CONDITION IS -!.!'%2 &IGURE SHOWS HOW THE 7(%2% CLAUSE WORKS #ONCEPTUALLY 31, GOES
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31, QUERIES THAT RETRIEVE ALL ROWS OF A TABLE ARE USEFUL FOR DATABASE BROWSING AND REPORTS BUT FOR LITTLE ELSE 5SUALLY YOULL WANT TO SELECT ONLY SOME OF THE ROWS IN A TABLE AND INCLUDE ONLY THESE ROWS IN THE QUERY RESULTS 4HE 7(%2% CLAUSE IS USED TO SPECIFY THE ROWS YOU WANT TO RETRIEVE (ERE ARE SOME EXAMPLES OF SIMPLE QUERIES THAT USE THE 7(%2% CLAUSE
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THROUGH EACH ROW OF THE 3!,%32%03 TABLE ONE BY ONE AND APPLIES THE SEARCH CONDITION TO THE ROW 7HEN A COLUMN NAME APPEARS IN THE SEARCH CONDITION SUCH AS THE -!.!'%2 COLUMN IN THIS EXAMPLE 31, USES THE VALUE OF THE COLUMN IN THE CURRENT ROW &OR EACH ROW THE SEARCH CONDITION CAN PRODUCE ONE OF THREE RESULTS s )F THE SEARCH CONDITION IS 425% THE ROW IS INCLUDED IN THE QUERY RESULTS &OR EXAMPLE THE ROW FOR "ILL !DAMS HAS THE CORRECT -!.!'%2 VALUE AND IS INCLUDED s )F THE SEARCH CONDITION IS &!,3% THE ROW IS EXCLUDED FROM THE QUERY RESULTS &OR EXAMPLE THE ROW FOR 3UE 3MITH HAS THE WRONG -!.!'%2 VALUE AND IS EXCLUDED s )F THE SEARCH CONDITION HAS A .5,, UNKNOWN VALUE THE ROW IS EXCLUDED FROM THE QUERY RESULTS &OR EXAMPLE THE ROW FOR 3AM #LARK HAS A .5,, VALUE FOR THE -!.!'%2 COLUMN AND IS EXCLUDED &IGURE SHOWS ANOTHER WAY TO THINK ABOUT THE ROLE OF THE SEARCH CONDITION IN THE 7(%2% CLAUSE "ASICALLY THE SEARCH CONDITION ACTS AS A FILTER FOR ROWS OF THE TABLE 2OWS THAT SATISFY THE SEARCH CONDITION PASS THROUGH THE FILTER AND BECOME PART OF THE QUERY RESULTS 2OWS THAT DO NOT SATISFY THE SEARCH CONDITION ARE TRAPPED BY THE FILTER AND EXCLUDED FROM THE QUERY RESULTS
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#HAPTERçç
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3EARCHõ#ONDITIONS 31, OFFERS A RICH SET OF SEARCH CONDITIONS THAT ALLOWS YOU TO SPECIFY MANY DIFFERENT KINDS OF QUERIES EFFICIENTLY AND NATURALLY &IVE BASIC SEARCH CONDITIONS CALLED PREDICATES IN THE !.3) )3/ STANDARD ARE SUMMARIZED HERE AND ARE DESCRIBED IN THE SECTIONS THAT FOLLOW s #OMPARISON TEST #OMPARES THE VALUE OF ONE EXPRESSION WITH THE VALUE OF ANOTHER EXPRESSION 5SE THIS TEST TO SELECT OFFICES IN THE %ASTERN REGION OR SALESPEOPLE WHOSE SALES ARE ABOVE THEIR QUOTAS
s 3ET MEMBERSHIP TEST #HECKS WHETHER THE VALUE OF AN EXPRESSION MATCHES ONE OF A SET OF VALUES 5SE THIS TEST TO SELECT OFFICES LOCATED IN .EW 9ORK #HICAGO OR ,OS !NGELES s 0ATTERN MATCHING TEST #HECKS WHETHER THE VALUE OF A COLUMN CONTAINING STRING DATA MATCHES A SPECIFIED PATTERN 5SE THIS TEST TO SELECT CUSTOMERS WHOSE NAMES START WITH THE LETTER % s .ULL VALUE TEST #HECKS WHETHER A COLUMN HAS A .5,, UNKNOWN VALUE 5SE THIS TEST TO FIND THE SALESPEOPLE WHO HAVE NOT YET BEEN ASSIGNED TO A MANAGER
4HEõ#OMPARISONõ4ESTõ õ õ õ õ õ 4HE MOST COMMON SEARCH CONDITION USED IN A 31, QUERY IS A COMPARISON TEST )N A COMPARISON TEST 31, COMPUTES AND COMPARES THE VALUES OF TWO 31, EXPRESSIONS FOR EACH ROW OF DATA 4HE EXPRESSIONS CAN BE AS SIMPLE AS A COLUMN NAME OR A CONSTANT OR THEY CAN BE MORE COMPLEX ARITHMETIC EXPRESSIONS 31, OFFERS SIX DIFFERENT WAYS OF COMPARING THE TWO EXPRESSIONS AS SHOWN IN &IGURE
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s 2ANGE TEST 4ESTS WHETHER THE VALUE OF AN EXPRESSION FALLS WITHIN A SPECIFIED RANGE OF VALUES 5SE THIS TEST TO FIND SALESPEOPLE WHOSE SALES ARE BETWEEN AND
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3OME EXAMPLES OF TYPICAL COMPARISON TESTS FOLLOW &IND SALESPEOPLE HIRED BEFORE 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% ()2%?$!4% g g .!-%
3UE 3MITH "OB 3MITH $AN 2OBERTS 0AUL #RUZ
.OTE THAT 31, PRODUCTS DO NOT HANDLE DATES IN THE SAME WAY BECAUSE VENDORS WERE PRESSED TO SUPPORT A DATE DATA TYPE BEFORE THE 31, STANDARD WAS WRITTEN 4HE 9999 -- $$ FORMAT SHOWN IN THE PRECEDING EXAMPLE WORKS FOR MOST 31, PRODUCTS BUT YOU MAY HAVE TO CHANGE IT FOR SOME PRODUCTS &OR EXAMPLE FOR /RACLE YOU EITHER NEED TO CHANGE THE DATE TO THE DEFAULT /RACLE FORMAT g *!. g OR YOU NEED TO CHANGE THE DEFAULT DATE FORMAT FOR YOUR SESSION USING THE COMMAND !,4%2 3%33)/. 3%4 .,3?$!4%?&/2-!4 g9999 -- $$g ,IST THE OFFICES WHOSE SALES FALL BELOW PERCENT OF TARGET 3%,%#4 #)49 3!,%3 4!2'%4 &2/- /&&)#%3 7(%2% 3!,%3 4!2'%4 #)49 3!,%3 4!2'%4
$ENVER
,IST THE OFFICES NOT MANAGED BY EMPLOYEE NUMBER 3%,%#4 #)49 -'2 &2/- /&&)#%3 7(%2% -'2 #)49 -'2
.EW 9ORK #HICAGO !TLANTA
!S SHOWN IN &IGURE THE INEQUALITY COMPARISON TEST IS WRITTEN AS ! " ACCORDING TO THE !.3))3/ 31, SPECIFICATION 3EVERAL 31, IMPLEMENTATIONS SUPPORT ALTERNATE NOTATIONS SUCH AS ! " SUPPORTED BY 31, 3ERVER $" /RACLE AND -Y31, )N SOME CASES THESE ARE ALTERNATIVE FORMS IN OTHERS THEY ARE THE ONLY ACCEPTABLE FORM OF THE INEQUALITY TEST
#HAPTERçç
3IMPLEç1UERIESç
7HEN 31, COMPARES THE VALUES OF THE TWO EXPRESSIONS IN THE COMPARISON TEST THREE RESULTS CAN OCCUR s )F THE COMPARISON IS TRUE THE TEST YIELDS A 425% RESULT s )F THE COMPARISON IS FALSE THE TEST YIELDS A &!,3% RESULT s )F EITHER OF THE TWO EXPRESSIONS PRODUCES A .5,, IE UNKNOWN OR MISSING VALUE THE COMPARISON YIELDS A .5,, RESULT
3INGLE 2OWõ2ETRIEVAL
2ETRIEVE THE NAME AND CREDIT LIMIT OF CUSTOMER NUMBER 3%,%#4 #/-0!.9 #2%$)4?,)-)4 &2/- #534/-%23 7(%2% #534?.5- #/-0!.9 #2%$)4?,)-)4
!CE )NTERNATIONAL
4HIS TYPE OF QUERY IS THE FOUNDATION OF FORMS BASED DATABASE RETRIEVAL ON WEB PAGES 4HE USER ENTERS A CUSTOMER NUMBER INTO THE FORM AND THE PROGRAM BEHIND THE PAGE USES THE NUMBER TO CONSTRUCT AND EXECUTE A QUERY )T THEN DISPLAYS THE RETRIEVED DATA IN THE FORM .OTE THAT THE 31, STATEMENTS FOR RETRIEVING A SPECIFIC CUSTOMER BY NUMBER AS IN THIS EXAMPLE AND RETRIEVING ALL CUSTOMERS WITH A CERTAIN CHARACTERISTIC SUCH AS THOSE WITH CREDIT LIMITS OVER BOTH HAVE EXACTLY THE SAME FORMAT
.5,,õ6ALUEõ#ONSIDERATIONS 4HE BEHAVIOR OF .5,, VALUES IN COMPARISON TESTS CAN REVEAL SOME hOBVIOUSLY TRUEv NOTIONS ABOUT 31, QUERIES TO BE IN FACT NOT NECESSARILY TRUE &OR EXAMPLE IT WOULD SEEM THAT EVERY ROW OF THE 3!,%32%03 TABLE WOULD APPEAR IN THE RESULTS OF ONE OF THESE TWO QUERIES AND NOT IN THE OTHER ,IST SALESPEOPLE WHO ARE OVER QUOTA 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 3!,%3 15/4! .!-%
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK $AN 2OBERTS ,ARRY &ITCH 0AUL #RUZ
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4HE MOST COMMON COMPARISON TEST IS ONE THAT CHECKS WHETHER A COLUMNS VALUE IS EQUAL TO SOME CONSTANT 7HEN THE COLUMN IS A PRIMARY KEY THE TEST ISOLATES A SINGLE ROW OF THE TABLE PRODUCING A SINGLE ROW OF QUERY RESULTS AS IN THIS EXAMPLE
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,IST SALESPEOPLE WHO ARE UNDER OR AT QUOTA 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 3!,%3 15/4! .!-%
"OB 3MITH .ANCY !NGELLI
(OWEVER THE QUERIES PRODUCE SEVEN AND TWO ROWS RESPECTIVELY FOR A TOTAL OF NINE ROWS WHILE THERE ARE TEN ROWS IN THE 3!,%32%03 TABLE 4OM 3NYDERS ROW HAS A .5,, VALUE IN THE 15/4! COLUMN BECAUSE HE HAS NOT YET BEEN ASSIGNED A QUOTA 4HIS ROW IS NOT LISTED BY EITHER QUERY IT hVANISHESv IN THE COMPARISON TEST ,OGICALLY THE DATABASE CANNOT DETERMINE WHETHER THE UNKNOWN 3!,%3 VALUE IS OVER UNDER OR EQUAL TO THE KNOWN 15/4! VALUE SO THE ROW IS ABSENT FROM BOTH QUERY RESULTS !S THIS EXAMPLE SHOWS YOU NEED TO THINK ABOUT .5,, VALUE HANDLING WHEN YOU SPECIFY A SEARCH CONDITION )N 31,S THREE VALUED LOGIC A SEARCH CONDITION CAN YIELD A 425% &!,3% OR .5,, RESULT /NLY ROWS WHERE THE SEARCH CONDITION YIELDS A 425% RESULT ARE INCLUDED IN THE QUERY RESULTS 4HE HANDLING OF .5,, VALUES IS DISCUSSED A LITTLE LATER IN THIS CHAPTER
4HEõ2ANGEõ4ESTõ"%47%%. 31, PROVIDES A DIFFERENT FORM OF SEARCH CONDITION WITH THE RANGE TEST "%47%%. SHOWN IN &IGURE 4HE RANGE TEST CHECKS WHETHER A DATA VALUE LIES BETWEEN TWO SPECIFIED VALUES )T INVOLVES THREE 31, EXPRESSIONS 4HE FIRST EXPRESSION DEFINES THE VALUE TO BE TESTED THE SECOND AND THIRD EXPRESSIONS DEFINE THE LOW AND HIGH ENDS OF THE RANGE TO BE CHECKED 4HE DATA TYPES OF THE THREE EXPRESSIONS MUST BE COMPARABLE 4HIS EXAMPLE SHOWS A TYPICAL RANGE TEST &IND ORDERS PLACED IN THE LAST QUARTER OF 3%,%#4 /2$%2?.5- /2$%2?$!4% -&2 02/$5#4 !-/5.4 &2/- /2$%23 7(%2% /2$%2?$!4% "%47%%. g g !.$ g g /2$%2?.5- /2$%2?$!4% -&2 02/$5#4 !-/5.4
2%) !, !#) !#) !#) !#) : !#) 2%) !' !#) 9
4HE "%47%%. TEST INCLUDES THE ENDPOINTS OF THE RANGE SO ORDERS PLACED ON /CTOBER OR $ECEMBER ARE INCLUDED IN THE QUERY RESULTS (ERE IS ANOTHER EXAMPLE OF A RANGE TEST
#HAPTERçç
3IMPLEç1UERIESç
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&IND THE ORDERS THAT FALL INTO VARIOUS AMOUNT RANGES
4HE NEGATED VERSION OF THE RANGE TEST ./4 "%47%%. CHECKS FOR VALUES THAT FALL OUTSIDE THE RANGE AS IN THIS EXAMPLE ,IST SALESPEOPLE WHOSE SALES ARE NOT BETWEEN PERCENT AND PERCENT OF QUOTA 3%,%#4 .!-% 3!,%3 15/4! &2/- 3!,%32%03 7(%2% 3!,%3 ./4 "%47%%. 15/4! !.$ 15/4! .!-% 3!,%3 15/4!
-ARY *ONES 3UE 3MITH "OB 3MITH .ANCY !NGELLI
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3%,%#4 /2$%2?.5- !-/5.4 &2/- /2$%23 7(%2% !-/5.4 "%47%%. !.$ /2$%2?.5- !-/5.4
3%,%#4 /2$%2?.5- !-/5.4 &2/- /2$%23 7(%2% !-/5.4 "%47%%. !.$ /2$%2?.5- !-/5.4
3%,%#4 /2$%2?.5- !-/5.4 &2/- /2$%23 7(%2% !-/5.4 "%47%%. !.$ /2$%2?.5- !-/5.4
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4HE TEST EXPRESSION SPECIFIED IN THE "%47%%. TEST CAN BE ANY VALID 31, EXPRESSION BUT IN PRACTICE ITS USUALLY JUST A COLUMN NAME AS IN THE PREVIOUS EXAMPLES 4HE !.3))3/ STANDARD DEFINES RELATIVELY COMPLEX RULES FOR THE HANDLING OF .5,, VALUES IN THE "%47%%. TEST s )F THE TEST EXPRESSION PRODUCES A .5,, VALUE OR IF BOTH EXPRESSIONS DEFINING THE RANGE PRODUCE .5,, VALUES THEN THE "%47%%. TEST RETURNS A .5,, RESULT s )F THE EXPRESSION DEFINING THE LOWER END OF THE RANGE PRODUCES A .5,, VALUE THEN THE "%47%%. TEST RETURNS &!,3% IF THE TEST VALUE IS GREATER THAN THE UPPER BOUND AND .5,, OTHERWISE s )F THE EXPRESSION DEFINING THE UPPER END OF THE RANGE PRODUCES A .5,, VALUE THEN THE "%47%%. TEST RETURNS &!,3% IF THE TEST VALUE IS LESS THAN THE LOWER BOUND AND .5,, OTHERWISE "EFORE RELYING ON THIS BEHAVIOR ITS A GOOD IDEA TO EXPERIMENT WITH YOUR $"-3 )TS WORTH NOTING THAT THE "%47%%. TEST DOESNT REALLY ADD TO THE EXPRESSIVE POWER OF 31, BECAUSE IT CAN BE EXPRESSED AS TWO COMPARISON TESTS 4HE RANGE TEST ! "%47%%. " !.$ #
IS COMPLETELY EQUIVALENT TO ! " !.$ ! #
(OWEVER THE "%47%%. TEST IS A SIMPLER WAY TO EXPRESS A SEARCH CONDITION WHEN YOURE THINKING OF IT IN TERMS OF A RANGE OF VALUES
4HEõ3ETõ-EMBERSHIPõ4ESTõ). !NOTHER COMMON SEARCH CONDITION IS THE SET MEMBERSHIP TEST ). SHOWN IN &IGURE )T TESTS WHETHER A DATA VALUE MATCHES ONE OF A LIST OF TARGET VALUES (ERE ARE SEVERAL QUERIES THAT USE THE SET MEMBERSHIP TEST ,IST THE SALESPEOPLE WHO WORK IN .EW 9ORK !TLANTA OR $ENVER 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). .!-% 15/4! 3!,%3
"ILL !DAMS -ARY *ONES 3AM #LARK .ANCY !NGELLI
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#HAPTERçç
3IMPLEç1UERIESç
&IND ALL ORDERS PLACED ON A &RIDAY IN *ANUARY 3%,%#4 /2$%2?.5- /2$%2?$!4% !-/5.4 &2/- /2$%23 7(%2% /2$%2?$!4% ). g g g g g g g g /2$%2?.5- /2$%2?$!4% !-/5.4
3%,%#4 /2$%2?.5- 2%0 !-/5.4 &2/- /2$%23 7(%2% 2%0 ). /2$%2?.5- 2%0 !-/5.4
9OU CAN CHECK WHETHER THE DATA VALUE DOES NOT MATCH ANY OF THE TARGET VALUES BY USING THE ./4 ). FORM OF THE SET MEMBERSHIP TEST 4HE TEST EXPRESSION IN AN ). TEST CAN BE ANY 31, EXPRESSION BUT ITS USUALLY JUST A COLUMN NAME AS IN THE PRECEDING EXAMPLES )F THE TEST EXPRESSION PRODUCES A .5,, VALUE THE ). TEST RETURNS .5,, !LL OF THE ITEMS IN THE LIST OF TARGET VALUES MUST HAVE THE SAME DATA TYPE AND THAT TYPE MUST BE COMPARABLE TO THE DATA TYPE OF THE TEST EXPRESSION ,IKE THE "%47%%. TEST THE ). TEST DOESNT ADD TO THE EXPRESSIVE POWER OF 31, BECAUSE THE SEARCH CONDITION 8 ). ! " #
IS COMPLETELY EQUIVALENT TO 8 ! /2 8 " /2 8 #
(OWEVER THE ). TEST OFFERS A MUCH MORE EFFICIENT WAY OF EXPRESSING THE SEARCH CONDITION ESPECIALLY IF THE SET CONTAINS MORE THAN A FEW VALUES 4HE !.3))3/ 31, STANDARD DOESNT SPECIFY A MAXIMUM LIMIT TO THE NUMBER OF ITEMS THAT CAN APPEAR IN THE VALUE LIST AND MOST
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&IND ALL ORDERS PLACED WITH FOUR SPECIFIC SALESPEOPLE
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COMMERCIAL IMPLEMENTATIONS DO NOT STATE AN EXPLICIT UPPER LIMIT EITHER &OR PORTABILITY REASONS ITS GENERALLY A GOOD IDEA TO AVOID LISTS WITH ONLY A SINGLE ITEM SUCH AS THIS ONE #)49 ). g.EW 9ORKg
AND REPLACE THEM WITH A SIMPLE COMPARISON TEST #)49 g.EW 9ORKg
4HEõ0ATTERNõ-ATCHINGõ4ESTõ,)+% 9OU CAN USE A SIMPLE COMPARISON TEST TO RETRIEVE ROWS WHERE THE CONTENTS OF A TEXT COLUMN MATCH SOME PARTICULAR TEXT &OR EXAMPLE THIS QUERY RETRIEVES A ROW OF THE #534/-%23 TABLE BY NAME 3HOW THE CREDIT LIMIT FOR 3MITHSON #ORP 3%,%#4 #/-0!.9 #2%$)4?,)-)4 &2/- #534/-%23 7(%2% #/-0!.9 g3MITHSON #ORPg
(OWEVER YOU MIGHT EASILY FORGET WHETHER THE COMPANYS NAME WAS h3MITH v h3MITHSON v OR h3MITHSONIANv 9OU CAN USE 31,S PATTERN MATCHING TEST TO RETRIEVE THE DATA BASED ON A PARTIAL MATCH OF THE CUSTOMERS NAME 4HE PATTERN MATCHING TEST ,)+% SHOWN IN &IGURE CHECKS TO SEE WHETHER THE DATA VALUE IN A COLUMN MATCHES A SPECIFIED PATTERN 4HE PATTERN IS A STRING THAT MAY INCLUDE ONE OR MORE WILDCARD CHARACTERS 4HESE CHARACTERS ARE INTERPRETED IN A SPECIAL WAY
7ILDCARDõ#HARACTERS 4HE PERCENT SIGN WILDCARD CHARACTER MATCHES ANY SEQUENCE OF ZERO OR MORE CHARACTERS (ERES A MODIFIED VERSION OF THE PREVIOUS QUERY THAT USES THE PERCENT SIGN FOR PATTERN MATCHING 3%,%#4 #/-0!.9 #2%$)4?,)-)4 &2/- #534/-%23 7(%2% #/-0!.9 ,)+% g3MITH #ORPg
4HE ,)+% KEYWORD TELLS 31, TO COMPARE THE .!-% COLUMN TO THE PATTERN 3MITH #ORP !NY OF THE FOLLOWING NAMES WOULD MATCH THE PATTERN 3MITH #ORP 3MITHSON #ORP 3MITHSEN #ORP 3MITHSONIAN #ORP
BUT THESE NAMES WOULD NOT 3MITH#ORP 3MITHSON )NC
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#HAPTERçç
3IMPLEç1UERIESç
4HE UNDERSCORE ? WILDCARD CHARACTER MATCHES ANY SINGLE CHARACTER )F YOU ARE SURE THAT THE COMPANYS NAME IS EITHER h3MITHSONv OR h3MITHSEN v FOR EXAMPLE YOU CAN USE THIS QUERY 3%,%#4 #/-0!.9 #2%$)4?,)-)4 &2/- #534/-%23 7(%2% #/-0!.9 ,)+% g3MITHS?N #ORPg
)N THIS CASE ANY OF THESE NAMES WILL MATCH THE PATTERN 3MITHSON #ORP 3MITHSEN #ORP 3MITHSUN #ORP
3MITHSOON #ORP 3MITHSN #ORP
7ILDCARD CHARACTERS CAN APPEAR ANYWHERE IN THE PATTERN STRING AND SEVERAL WILDCARD CHARACTERS CAN BE WITHIN A SINGLE STRING 4HIS QUERY ALLOWS EITHER THE h3MITHSONv OR h3MITHSENv SPELLING AND WILL ALSO ACCEPT h#ORP v h)NC v OR ANY OTHER ENDING ON THE COMPANY NAME 3%,%#4 #/-0!.9 #2%$)4?,)-)4 &2/- #534/-%23 7(%2% #/-0!.9 ,)+% g3MITHS?N g
9OU CAN LOCATE STRINGS THAT DO NOT MATCH A PATTERN BY USING THE ./4 ,)+% FORM OF THE PATTERN MATCHING TEST 4HE ,)+% TEST MUST BE APPLIED TO A COLUMN WITH A STRING DATA TYPE )F THE DATA VALUE IN THE COLUMN IS .5,, THE ,)+% TEST RETURNS A .5,, RESULT )F YOU HAVE USED COMPUTERS THROUGH A COMMAND LINE INTERFACE SUCH AS THE 5.)8 SHELL YOUVE PROBABLY SEEN STRING PATTERN MATCHING BEFORE &REQUENTLY THE ASTERISK IS USED INSTEAD OF THE 31, PERCENT SIGN AND THE QUESTION MARK IS USED INSTEAD OF THE 31, UNDERSCORE ? BUT THE PATTERN MATCHING CAPABILITIES THEMSELVES ARE SIMILAR IN MOST SITUATIONS WHERE A COMPUTER APPLICATION OFFERS THE CAPABILITY TO MATCH SELECTED PARTS OF A WORD OR TEXT
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/NE OF THE PROBLEMS WITH STRING PATTERN MATCHING IS HOW TO MATCH THE WILDCARD CHARACTERS THEMSELVES AS LITERAL CHARACTERS 4O TEST FOR THE PRESENCE OF A PERCENT SIGN CHARACTER IN A COLUMN OF TEXT DATA FOR EXAMPLE YOU CANT SIMPLY INCLUDE THE PERCENT SIGN IN THE PATTERN BECAUSE 31, WILL TREAT IT AS A WILDCARD 7ITH SOME SIMPLER 31, PRODUCTS YOU CANNOT LITERALLY MATCH THE TWO WILDCARD CHARACTERS 4HIS USUALLY DOESNT POSE SERIOUS PROBLEMS BECAUSE THE WILDCARD CHARACTERS DONT FREQUENTLY APPEAR IN NAMES PRODUCT NUMBERS AND OTHER TEXT DATA OF THE SORT THAT IS USUALLY STORED IN A DATABASE 4HE !.3))3/ 31, STANDARD DOES SPECIFY A WAY TO LITERALLY MATCH WILDCARD CHARACTERS USING A SPECIAL ESCAPE CHARACTER 7HEN THE ESCAPE CHARACTER APPEARS IN THE PATTERN THE CHARACTER IMMEDIATELY FOLLOWING IT IS TREATED AS A LITERAL CHARACTER RATHER THAN AS A WILDCARD CHARACTER 4HE LATTER CHARACTER IS SAID TO BE ESCAPED 4HE ESCAPED CHARACTER CAN BE EITHER OF THE TWO WILDCARD CHARACTERS OR THE ESCAPE CHARACTER ITSELF WHICH HAS NOW TAKEN ON A SPECIAL MEANING WITHIN THE PATTERN
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4HE ESCAPE CHARACTER IS SPECIFIED AS A ONE CHARACTER CONSTANT STRING IN THE %3#!0% CLAUSE OF THE SEARCH CONDITION AS SHOWN IN &IGURE (ERE IS AN EXAMPLE USING A DOLLAR SIGN AS THE ESCAPE CHARACTER &IND PRODUCTS WHOSE PRODUCT )$S START WITH THE FOUR LETTERS h!"#v 3%,%#4 /2$%2?.5- 02/$5#4 &2/- /2$%23 7(%2% 02/$5#4 ,)+% g!"#g %3#!0% gg
4HE FIRST PERCENT SIGN IN THE PATTERN WHICH FOLLOWS AN ESCAPE CHARACTER IS TREATED AS A LITERAL PERCENT SIGN THE SECOND FUNCTIONS AS A WILDCARD 4HE USE OF ESCAPE CHARACTERS IS VERY COMMON IN PATTERN MATCHING APPLICATIONS WHICH IS WHY THE !.3))3/ STANDARD SPECIFIED IT (OWEVER IT WAS NOT A PART OF THE EARLY 31, IMPLEMENTATIONS AND SOME DATABASE SYSTEMS HAVE IMPLEMENTED OTHER PATTERN MATCHING SCHEMES 4O ENSURE PORTABILITY THE %3#!0% CLAUSE SHOULD BE AVOIDED
4HEõ.ULLõ6ALUEõ4ESTõ)3õ.5,, .5,, VALUES CREATE A THREE VALUED LOGIC FOR 31, SEARCH CONDITIONS &OR ANY GIVEN ROW THE RESULT OF A SEARCH CONDITION MAY BE 425% OR &!,3% OR IT MAY BE .5,, BECAUSE ONE OF THE COLUMNS USED IN EVALUATING THE SEARCH CONDITION CONTAINS A .5,, VALUE 3OMETIMES ITS USEFUL TO CHECK EXPLICITLY FOR .5,, VALUES IN A SEARCH CONDITION AND HANDLE THEM DIRECTLY 31, PROVIDES A SPECIAL .5,, VALUE TEST )3 .5,, SHOWN IN &IGURE TO HANDLE THIS TASK 4HIS QUERY USES THE .5,, VALUE TEST TO FIND THE SALESPERSON IN THE SAMPLE DATABASE WHO HAS NOT YET BEEN ASSIGNED TO AN OFFICE &IND THE SALESPERSON NOT YET ASSIGNED TO AN OFFICE 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 2%0?/&&)#% )3 .5,, .!-%
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4HE NEGATED FORM OF THE .5,, VALUE TEST )3 ./4 .5,, FINDS ROWS THAT DO NOT CONTAIN A .5,, VALUE ,IST THE SALESPEOPLE WHO HAVE BEEN ASSIGNED TO AN OFFICE 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 2%0?/&&)#% )3 ./4 .5,,
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"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH $AN 2OBERTS ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI
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4HE .5,, KEYWORD CANT BE USED HERE BECAUSE IT ISNT REALLY A VALUE ITS JUST A SIGNAL THAT THE VALUE IS UNKNOWN %VEN IF THE COMPARISON TEST 2%0?/&&)#% .5,,
WERE LEGAL THE RULES FOR HANDLING .5,, VALUES IN COMPARISONS WOULD CAUSE IT TO BEHAVE DIFFERENTLY FROM WHAT YOU MIGHT EXPECT 7HEN 31, ENCOUNTERED A ROW WHERE THE 2%0? /&&)#% COLUMN WAS .5,, THE SEARCH CONDITION WOULD TEST .5,, .5,,
)S THE RESULT 425% OR &!,3% "ECAUSE THE VALUES ON BOTH SIDES OF THE EQUAL SIGN ARE UNKNOWN 31, CANT TELL SO THE RULES OF 31, LOGIC SAY THAT THE SEARCH CONDITION ITSELF MUST YIELD A .5,, RESULT "ECAUSE THE SEARCH CONDITION DOESNT PRODUCE A TRUE RESULT THE ROW IS EXCLUDED FROM THE QUERY RESULTSPRECISELY THE OPPOSITE OF WHAT YOU WANTED TO HAPPEN !S A RESULT OF THE WAY 31, HANDLES .5,,S IN COMPARISONS YOU MUST EXPLICITLY USE THE .5,, VALUE TEST TO CHECK FOR .5,, VALUES
#OMPOUNDõ3EARCHõ#ONDITIONSõ!.$ õ/2 õANDõ./4 4HE SIMPLE SEARCH CONDITIONS DESCRIBED IN THE PRECEDING SECTIONS RETURN A VALUE OF 425% &!,3% OR .5,, WHEN APPLIED TO A ROW OF DATA 5SING THE RULES OF LOGIC YOU CAN COMBINE THESE SIMPLE 31, SEARCH CONDITIONS TO FORM MORE COMPLEX ONES AS SHOWN IN &IGURE
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5NLIKE THE PREVIOUSLY DESCRIBED SEARCH CONDITIONS THE .5,, VALUE TEST CANNOT YIELD A .5,, RESULT )T IS ALWAYS EITHER 425% OR &!,3% )T MAY SEEM STRANGE THAT YOU CANT JUST TEST FOR A .5,, VALUE USING A SIMPLE COMPARISON SEARCH CONDITION SUCH AS THIS
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.OTE THAT THE SEARCH CONDITIONS COMBINED WITH !.$ /2 AND ./4 MAY THEMSELVES BE COMPOUND SEARCH CONDITIONS 4HE KEYWORD /2 IS USED TO COMBINE TWO SEARCH CONDITIONS WHEN ONE OR THE OTHER OR BOTH MUST BE TRUE &IND SALESPEOPLE WHO ARE UNDER QUOTA OR WITH SALES UNDER 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% 3!,%3 15/4! /2 3!,%3 .!-% 15/4! 3!,%3
3AM #LARK "OB 3MITH 4OM 3NYDER .5,, 0AUL #RUZ .ANCY !NGELLI
9OU CAN ALSO USE THE KEYWORD !.$ TO COMBINE TWO SEARCH CONDITIONS THAT MUST BOTH BE TRUE &IND SALESPEOPLE WHO ARE UNDER QUOTA AND WITH SALES UNDER 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% 3!,%3 15/4! !.$ 3!,%3 .!-% 15/4! 3!,%3
"OB 3MITH .ANCY !NGELLI
&INALLY YOU CAN USE THE KEYWORD ./4 TO SELECT ROWS WHERE A SEARCH CONDITION IS FALSE &IND ALL SALESPEOPLE WHO ARE UNDER QUOTA BUT WHOSE SALES ARE NOT UNDER 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% 3!,%3 15/4! !.$ ./4 3!,%3 .!-% 15/4! 3!,%3
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5SING THE LOGICAL !.$ /2 AND ./4 KEYWORDS AND PARENTHESES TO GROUP THE SEARCH CRITERIA YOU CAN BUILD VERY COMPLEX SEARCH CRITERIA SUCH AS THE ONE IN THIS QUERY &IND ALL SALESPEOPLE WHO A WORK IN $ENVER .EW 9ORK OR #HICAGO OR B HAVE NO MANAGER AND WERE HIRED SINCE *UNE OR C ARE OVER QUOTA BUT HAVE SALES OF OR LESS
#HAPTERçç
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%XACTLY WHY YOU MIGHT WANT TO SEE THIS PARTICULAR LIST OF NAMES IS A MYSTERY BUT THE EXAMPLE DOES ILLUSTRATE A REASONABLY COMPLEX QUERY !S WITH SIMPLE SEARCH CONDITIONS .5,, VALUES INFLUENCE THE OUTCOME OF COMPOUND SEARCH CONDITIONS AND THE RESULTS ARE SUBTLE )N PARTICULAR THE RESULT OF .5,, /2 425% IS 425% NOT .5,, AS YOU MIGHT EXPECT 4ABLES AND SPECIFY TRUTH TABLES FOR !.$ /2 AND ./4 RESPECTIVELY AND SHOW THE IMPACT OF .5,, VALUES 7HEN MORE THAN TWO SEARCH CONDITIONS ARE COMBINED WITH !.$ /2 AND ./4 THE !.3) )3/ STANDARD SPECIFIES THAT ./4 HAS THE HIGHEST PRECEDENCE FOLLOWED BY !.$ AND THEN /2 4O ENSURE PORTABILITY ITS ALWAYS A GOOD IDEA TO USE PARENTHESES AND REMOVE ANY POSSIBLE AMBIGUITY 4HE 31, ALSO KNOWN AS 31, AND 31, STANDARD ADDED ANOTHER LOGICAL SEARCH CONDITION THE )3 TEST TO THE LOGIC PROVIDED BY !.$ /2 AND ./4 &IGURE SHOWS THE SYNTAX OF THE )3 TEST WHICH CHECKS TO SEE WHETHER THE LOGICAL VALUE OF AN EXPRESSION OR COMPARISON TEST IS 425% &!,3% OR 5.+./7. .5,, &OR EXAMPLE THE )3 TEST
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CAN BE USED TO FIND ROWS WHERE THE COMPARISON CANNOT BE DONE BECAUSE EITHER 3!,%3 OR 15/4! HAS A .5,, VALUE 3IMILARLY THE )3 TEST 3!,%3 15/4! )3 &!,3%
WILL SELECT ROWS WHERE 3!,%3 ARE NOT SIGNIFICANTLY ABOVE 15/4! !S THIS EXAMPLE SHOWS THE )3 TEST DOESNT REALLY ADD TO THE EXPRESSIVE POWER OF 31, SINCE THE TEST COULD JUST AS EASILY HAVE BEEN WRITTEN ./4 3!,%3 15/4!
!LTHOUGH THE )3 TEST HAS BEEN INCLUDED IN THE 31, 3TANDARD SINCE VERY FEW 31, PRODUCTS PROVIDE SUPPORT FOR IT 4HEREFORE FOR MAXIMUM PORTABILITY ITS A GOOD IDEA TO AVOID THE TEST AND TO WRITE THE EXPRESSIONS USING ONLY !.$ /2 AND ./4 (OWEVER ITS NOT ALWAYS POSSIBLE TO AVOID THE )3 5.+./7. FORM OF THE TEST
3ORTINGõ1UERYõ2ESULTSõ/2$%2õ"9õ#LAUSE ,IKE THE ROWS OF A TABLE IN THE DATABASE THE ROWS OF QUERY RESULTS ARE NOT ARRANGED IN ANY PARTICULAR ORDER 9OU CAN ASK 31, TO SORT THE RESULTS OF A QUERY BY INCLUDING THE /2$%2 "9 CLAUSE IN THE 3%,%#4 STATEMENT 4HE /2$%2 "9 CLAUSE SHOWN IN &IGURE CONSISTS OF THE KEYWORDS /2$%2 "9 FOLLOWED BY A LIST OF SORT SPECIFICATIONS SEPARATED BY COMMAS &OR EXAMPLE THE RESULTS OF THIS QUERY ARE SORTED ON TWO COLUMNS 2%')/. AND #)49 3HOW THE SALES FOR EACH OFFICE SORTED IN ALPHABETICAL ORDER BY REGION AND WITHIN EACH REGION BY CITY 3%,%#4 #)49 2%')/. 3!,%3 &2/- /&&)#%3 /2$%2 "9 2%')/. #)49 #)49 2%')/. 3!,%3
!TLANTA %ASTERN #HICAGO %ASTERN .EW 9ORK %ASTERN $ENVER 7ESTERN ,OS !NGELES 7ESTERN
4HE FIRST SORT SPECIFICATION 2%')/. IS THE MAJOR SORT KEY THOSE THAT FOLLOW #)49 IN THIS CASE ARE PROGRESSIVELY MORE MINOR SORT KEYS USED AS hTIE BREAKERSv WHEN TWO ROWS OF QUERY RESULTS HAVE THE SAME VALUES FOR THE MORE MAJOR KEYS 5SING THE /2$%2 "9 CLAUSE
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,IST THE OFFICES SORTED IN DESCENDING ORDER BY SALES SO THAT THE OFFICES WITH THE LARGEST SALES APPEAR FIRST 3%,%#4 #)49 2%')/. 3!,%3 &2/- /&&)#%3 /2$%2 "9 3!,%3 $%3# #)49 2%')/. 3!,%3
,OS !NGELES 7ESTERN #HICAGO %ASTERN .EW 9ORK %ASTERN !TLANTA %ASTERN $ENVER 7ESTERN
!S INDICATED IN &IGURE YOU CAN ALSO USE THE KEYWORD !3# TO SPECIFY AN ASCENDING SORT BUT BECAUSE THATS THE DEFAULT SORTING SEQUENCE THE KEYWORD IS USUALLY OMITTED )F THE COLUMN OF QUERY RESULTS TO BE USED FOR SORTING IS A CALCULATED COLUMN IT HAS NO COLUMN NAME TO BE USED IN A SORT SPECIFICATION )N THIS CASE YOU MUST EITHER SPECIFY A COLUMN NUMBER INSTEAD OF A COLUMN NAME OR REPEAT THE COLUMN EXPRESSION IN THE /2$%2 "9 CLAUSE AS IN THE FOLLOWING EXAMPLE .OTE THAT THE USE OF COLUMN NUMBERS IS AN OLDER WAY OF WRITING 31, AND IT IS NO LONGER RECOMMENDED BECAUSE IT IS MORE PRONE TO ERROR WHEN SOMEONE SUBSEQUENTLY CHANGES THE COLUMN ORDER IN THE 3%,%#4 CLAUSE NOT NOTICING THE COLUMN NUMBER REFERENCES IN THE /2$%2 "9 CLAUSE ,IST THE OFFICES SORTED IN DESCENDING ORDER BY SALES PERFORMANCE SO THAT THE OFFICES WITH THE BEST PERFORMANCE APPEAR FIRST 3%,%#4 #)49 2%')/. 3!,%3 4!2'%4 &2/- /&&)#%3 /2$%2 "9 $%3#
OR 3%,%#4 #)49 2%')/. 3!,%3 n 4!2'%4 &2/- /&&)#%3 /2$%2 "9 3!,%3 n 4!2'%4 $%3#
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YOU CAN REQUEST SORTING IN AN ASCENDING OR DESCENDING SEQUENCE AND YOU CAN SORT ON ANY ITEM IN THE SELECT LIST OF THE QUERY "Y DEFAULT 31, SORTS DATA IN ASCENDING SEQUENCE 4O REQUEST SORTING IN DESCENDING SEQUENCE THE KEYWORD $%3# IS INCLUDED IN THE SORT SPECIFICATION AS IN THE NEXT EXAMPLE
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4HESE QUERY RESULTS ARE SORTED ON THE THIRD COLUMN WHICH IS THE CALCULATED DIFFERENCE BETWEEN THE 3!,%3 AND 4!2'%4 FOR EACH OFFICE "Y COMBINING COLUMN NUMBERS COLUMN NAMES ASCENDING SORTS AND DESCENDING SORTS YOU CAN SPECIFY QUITE COMPLEX SORTING OF THE QUERY RESULTS AS IN THE FOLLOWING FINAL EXAMPLE ,IST THE OFFICES SORTED IN ALPHABETICAL ORDER BY REGION AND WITHIN EACH REGION IN DESCENDING ORDER BY SALES PERFORMANCE 3%,%#4 #)49 2%')/. 3!,%3 4!2'%4 &2/- /&&)#%3 /2$%2 "9 2%')/. !3# $%3# #)49 2%')/. 3!,%3 4!2'%4
.EW 9ORK %ASTERN !TLANTA %ASTERN #HICAGO %ASTERN n ,OS !NGELES 7ESTERN $ENVER 7ESTERN n
4HE 31, STANDARD ALLOWS YOU TO CONTROL THE SORTING ORDER OF THE INDIVIDUAL CHARACTERS WITHIN A CHARACTER SET OFTEN CALLED THE COLLATING SEQUENCE OF THE CHARACTERS 4HIS CAN BE IMPORTANT WHEN WORKING WITH INTERNATIONAL CHARACTER SETS FOR EXAMPLE TO SPECIFY HOW DIACRITICAL MARKS SUCH AS ACCENTS OR UMLAUTS OR COMPOUND LETTERS SHOULD BE SORTED OR TO ENSURE PORTABILITY BETWEEN !3#)) AND %"#$)# CHARACTER SET SYSTEMS (OWEVER THIS AREA OF THE 31, STANDARD IS QUITE COMPLEX AND IN PRACTICE MANY 31, IMPLEMENTATIONS EITHER IGNORE SORTING SEQUENCE ISSUES OR USE THEIR OWN PROPRIETARY SCHEME FOR USER CONTROL OF THE SORTING SEQUENCE
2ULESõFORõ3INGLE 4ABLEõ1UERYõ0ROCESSING 3INGLE TABLE QUERIES ARE GENERALLY SIMPLE AND ITS USUALLY EASY TO UNDERSTAND THE MEANING OF A QUERY JUST BY READING THE 3%,%#4 STATEMENT !S QUERIES BECOME MORE COMPLEX HOWEVER ITS IMPORTANT TO HAVE A MORE PRECISE hDEFINITIONv OF THE QUERY RESULTS THAT WILL BE PRODUCED BY A GIVEN 3%,%#4 STATEMENT 4HE FOLLOWING STEPS DESCRIBE THE PROCEDURE FOR GENERATING THE RESULTS OF A 31, QUERY THAT INCLUDES THE CLAUSES DESCRIBED IN THIS CHAPTER !S THESE STEPS SHOW THE QUERY RESULTS PRODUCED BY A 3%,%#4 STATEMENT ARE SPECIFIED BY APPLYING EACH OF ITS CLAUSES ONE BY ONE 4HE &2/- CLAUSE IS APPLIED FIRST SELECTING THE TABLE OR VIEW CONTAINING DATA TO BE RETRIEVED 4HE 7(%2% CLAUSE IS APPLIED NEXT SELECTING SPECIFIC ROWS FROM THE TABLE 4HE 3%,%#4 CLAUSE IS APPLIED NEXT GENERATING THE SPECIFIC COLUMNS OF QUERY RESULTS AND ELIMINATING DUPLICATE ROWS IF REQUESTED &INALLY THE /2$%2 "9 CLAUSE IS APPLIED TO SORT THE QUERY RESULTS
#HAPTERçç
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4O GENERATE THE QUERY RESULTS FOR A SINGLE TABLE 3%,%#4 STATEMENT FOLLOW THESE STEPS 3TART WITH THE TABLE NAMED IN THE &2/- CLAUSE
)F THERE IS A 7(%2% CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW OF THE TABLE RETAINING THOSE ROWS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE ROWS FOR WHICH IT IS &!,3% OR .5,,
&OR EACH REMAINING ROW CALCULATE THE VALUE OF EACH ITEM IN THE SELECT LIST TO PRODUCE A SINGLE ROW OF QUERY RESULTS &OR EACH COLUMN REFERENCE USE THE VALUE OF THE COLUMN IN THE CURRENT ROW
)F 3%,%#4 $)34).#4 IS SPECIFIED ELIMINATE ANY DUPLICATE ROWS OF QUERY RESULTS THAT WERE PRODUCED
)F THERE IS AN /2$%2 "9 CLAUSE SORT THE QUERY RESULTS AS SPECIFIED
4HE ROWS GENERATED BY THIS PROCEDURE COMPRISE THE QUERY RESULTS 4HESE hRULESv FOR 31, QUERY PROCESSING WILL BE EXPANDED SEVERAL TIMES IN THE NEXT THREE CHAPTERS TO INCLUDE THE REMAINING CLAUSES OF THE 3%,%#4 STATEMENT
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/CCASIONALLY ITS CONVENIENT TO COMBINE THE RESULTS OF TWO OR MORE QUERIES INTO A SINGLE TABLE OF QUERY RESULTS 31, SUPPORTS THIS CAPABILITY THROUGH THE 5.)/. FEATURE OF THE 3%,%#4 STATEMENT &IGURE ILLUSTRATES HOW TO USE THE 5.)/. OPERATION TO SATISFY THE FOLLOWING REQUEST ,IST ALL THE PRODUCTS WHERE THE PRICE OF THE PRODUCT EXCEEDS OR WHERE MORE THAN OF THE PRODUCT HAS BEEN ORDERED IN A SINGLE ORDER
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4HE FIRST PART OF THE REQUEST CAN BE SATISFIED WITH THE TOP QUERY IN THE FIGURE ,IST ALL THE PRODUCTS WHOSE PRICE EXCEEDS 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% -&2?)$ 02/$5#4?)$
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3IMILARLY THE SECOND PART OF THE REQUEST CAN BE SATISFIED WITH THE BOTTOM QUERY IN THE FIGURE ,IST ALL THE PRODUCTS WHERE MORE THAN OF THE PRODUCT HAS BEEN ORDERED IN A SINGLE ORDER 3%,%#4 $)34).#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 -&2 02/$5#4
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!S SHOWN IN &IGURE THE 5.)/. OPERATION PRODUCES A SINGLE TABLE OF QUERY RESULTS THAT COMBINES THE ROWS OF THE TOP QUERY RESULTS WITH THE ROWS OF THE BOTTOM QUERY RESULTS 4HE 3%,%#4 STATEMENT THAT SPECIFIES THE 5.)/. OPERATION LOOKS LIKE THIS ,IST ALL THE PRODUCTS WHERE THE PRICE OF THE PRODUCT EXCEEDS OR WHERE MORE THAN OF THE PRODUCT HAS BEEN ORDERED IN A SINGLE ORDER 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 5.)/. 3%,%#4 $)34).#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 !#) 9 !#) : )-- # 2%) !, 2%) !2
4HERE ARE SEVERE RESTRICTIONS ON THE TABLES THAT CAN BE COMBINED BY A 5.)/. OPERATION s 4HE TWO 3%,%#4 CLAUSES MUST CONTAIN THE SAME NUMBER OF COLUMNS
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s 4HE DATA TYPE OF EACH COLUMN SELECTED FROM THE FIRST TABLE MUST BE THE SAME AS THE DATA TYPE OF THE CORRESPONDING COLUMN SELECTED FROM THE SECOND TABLE s .EITHER OF THE TWO TABLES CAN BE SORTED WITH THE /2$%2 "9 CLAUSE (OWEVER THE COMBINED QUERY RESULTS CAN BE SORTED AS DESCRIBED IN THE FOLLOWING SECTION
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"ECAUSE THE 5.)/. OPERATION COMBINES THE ROWS FROM TWO SETS OF QUERY RESULTS IT WOULD TEND TO PRODUCE QUERY RESULTS CONTAINING DUPLICATE ROWS &OR EXAMPLE IN THE QUERY OF &IGURE PRODUCT 2%) !, SELLS FOR SO IT APPEARS IN THE TOP SET OF QUERY RESULTS 4HERE IS ALSO AN ORDER FOR WORTH OF THIS PRODUCT IN THE /2$%23 TABLE SO IT ALSO APPEARS IN THE BOTTOM SET OF QUERY RESULTS "Y DEFAULT THE 5.)/. OPERATION ELIMINATES DUPLICATE ROWS AS PART OF ITS PROCESSING 4HUS THE COMBINED SET OF QUERY RESULTS CONTAINS ONLY ONE ROW FOR PRODUCT 2%) !, )F YOU WANT TO RETAIN DUPLICATE ROWS IN A 5.)/. OPERATION YOU CAN SPECIFY THE !,, KEYWORD IMMEDIATELY FOLLOWING THE WORD 5.)/. 4HIS FORM OF THE QUERY PRODUCES TWO DUPLICATE ROWS FOR PRODUCT 2%) !, ,IST ALL THE PRODUCTS WHERE THE PRICE OF THE PRODUCT EXCEEDS OR WHERE MORE THAN OF THE PRODUCT HAS BEEN ORDERED IN A SINGLE ORDER 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 5.)/. !,, 3%,%#4 $)34).#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 !#) 9 2%) !, !#) : 2%) !2 )-- # 2%) !, 2%) !2
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.OTE THAT THE COLUMN NAMES OF THE TWO QUERIES COMBINED BY 5.)/. DO NOT HAVE TO BE IDENTICAL )N THE PRECEDING EXAMPLE THE FIRST TABLE OF QUERY RESULTS HAS COLUMNS NAMED -&2? )$ AND 02/$5#4?)$ WHILE THE SECOND TABLE OF QUERY RESULTS HAS COLUMNS NAMED -&2 AND 02/$5#4 "ECAUSE THE COLUMNS IN THE TWO TABLES CAN HAVE DIFFERENT NAMES THE COLUMNS OF QUERY RESULTS PRODUCED BY THE 5.)/. OPERATION ARE UNNAMED 4HE ORIGINAL !.3))3/ 31, STANDARD SPECIFIED A FURTHER RESTRICTION ON A 3%,%#4 STATEMENT THAT PARTICIPATES IN A 5.)/. OPERATION )T PERMITS ONLY COLUMN NAMES OR AN ALL COLUMNS SPECIFICATION 3%,%#4 IN THE SELECT LIST AND PROHIBITS EXPRESSIONS IN THE SELECT LIST -OST COMMERCIAL 31, IMPLEMENTATIONS RELAX THIS RESTRICTION AND PERMIT SIMPLE EXPRESSIONS IN THE SELECT LIST (OWEVER MANY 31, IMPLEMENTATIONS DO NOT ALLOW THE 3%,%#4 STATEMENTS TO INCLUDE THE '2/50 "9 OR (!6).' CLAUSES AND SOME DO NOT ALLOW COLUMN FUNCTIONS IN THE SELECT LIST PROHIBITING SUMMARY QUERIES AS DESCRIBED IN #HAPTER )N FACT SOME SIMPLE 31, IMPLEMENTATIONS DO NOT SUPPORT THE 5.)/. OPERATION AT ALL
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.OTE THAT THE DEFAULT DUPLICATE ROW HANDLING FOR THE 5.)/. OPERATION AND FOR THE SIMPLE 3%,%#4 STATEMENT IS EXACTLY OPPOSITE &OR THE 3%,%#4 STATEMENT 3%,%#4 !,, DUPLICATES RETAINED IS THE DEFAULT 4O ELIMINATE DUPLICATE ROWS YOU MUST EXPLICITLY SPECIFY 3%,%#4 $)34).#4 &OR THE 5.)/. OPERATION 5.)/. DUPLICATES ELIMINATED IS THE DEFAULT 4O RETAIN DUPLICATE ROWS YOU MUST EXPLICITLY SPECIFY 5.)/. !,, $ATABASE EXPERTS HAVE CRITICIZED THE HANDLING OF DUPLICATE ROWS IN 31, AND POINT TO THIS INCONSISTENCY AS AN EXAMPLE OF THE PROBLEMS 4HE REASON FOR THE INCONSISTENCY IS THAT THE 31, DEFAULTS WERE CHOSEN TO PRODUCE THE CORRECT BEHAVIOR MOST OF THE TIME s )N PRACTICE MOST SIMPLE 3%,%#4 STATEMENTS DO NOT PRODUCE DUPLICATE ROWS SO THE DEFAULT IS NO DUPLICATE ELIMINATION s )N PRACTICE MOST 5.)/. OPERATIONS WOULD PRODUCE UNWANTED DUPLICATE ROWS SO THE DEFAULT IS DUPLICATE ELIMINATION %LIMINATING DUPLICATE ROWS FROM QUERY RESULTS IS A VERY TIME CONSUMING PROCESS ESPECIALLY IF THE QUERY RESULTS CONTAIN A LARGE NUMBER OF ROWS )F YOU KNOW BASED ON THE INDIVIDUAL QUERIES INVOLVED THAT A 5.)/. OPERATION CANNOT PRODUCE DUPLICATE ROWS YOU SHOULD SPECIFICALLY USE THE 5.)/. !,, OPERATION BECAUSE THE QUERY WILL EXECUTE MUCH MORE QUICKLY
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4HE /2$%2 "9 CLAUSE CANNOT APPEAR IN EITHER OF THE TWO 3%,%#4 STATEMENTS COMBINED BY A 5.)/. OPERATION )T WOULDNT MAKE MUCH SENSE TO SORT THE TWO SETS OF QUERY RESULTS ANYWAY BECAUSE THEY ARE FED DIRECTLY INTO THE 5.)/. OPERATION AND ARE NEVER VISIBLE TO THE USER (OWEVER THE COMBINED SET OF QUERY RESULTS PRODUCED BY THE 5.)/. OPERATION CAN BE SORTED BY SPECIFYING AN /2$%2 "9 CLAUSE AFTER THE SECOND 3%,%#4 STATEMENT 3INCE THE COLUMNS PRODUCED BY THE 5.)/. OPERATION ARE NOT NAMED THE /2$%2 "9 CLAUSE SPECIFIES THE COLUMNS BY COLUMN NUMBER (OWEVER MANY 31, PRODUCTS INCLUDING /RACLE 31, 3ERVER AND -Y31, USE THE COLUMN NAMES FROM THE FIRST 3%,%#4 STATEMENT AND THEREFORE ALLOW YOU TO USE THOSE COLUMN NAMES IN THE /2$%2 "9 CLAUSE (ERE IS THE SAME PRODUCTS QUERY AS THAT SHOWN IN &IGURE WITH THE QUERY RESULTS SORTED BY MANUFACTURER AND PRODUCT NUMBER ,IST ALL THE PRODUCTS WHERE THE PRICE OF THE PRODUCT EXCEEDS OR WHERE MORE THAN OF THE PRODUCT HAS BEEN ORDERED IN A SINGLE ORDER SORTED BY MANUFACTURER AND PRODUCT NUMBER 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 5.)/. 3%,%#4 $)34).#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 /2$%2 "9 !#) 9 !#) : )-- # 2%) !, 2%) !2
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9OU CAN USE THE 5.)/. OPERATION REPEATEDLY TO COMBINE THREE OR MORE SETS OF QUERY RESULTS AS SHOWN IN &IGURE 4HE UNION OF 4ABLE " AND 4ABLE # IN THE FIGURE PRODUCES A SINGLE COMBINED TABLE 4HIS TABLE IS THEN COMBINED WITH 4ABLE ! IN ANOTHER 5.)/. OPERATION 4HE QUERY IN THE FIGURE IS WRITTEN THIS WAY
4HE PARENTHESES IN THE QUERY INDICATE WHICH 5.)/. OPERATION SHOULD BE PERFORMED FIRST )N FACT IF ALL OF THE 5.)/.S IN THE STATEMENT ELIMINATE DUPLICATE ROWS OR IF ALL OF THEM RETAIN DUPLICATE ROWS THE ORDER IN WHICH THEY ARE PERFORMED IS UNIMPORTANT 4HESE THREE EXPRESSIONS ARE COMPLETELY EQUIVALENT ! 5.)/. " 5.)/. # ! 5.)/. " 5.)/. # ! 5.)/. # 5.)/. "
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AND PRODUCE SEVEN ROWS OF QUERY RESULTS 3IMILARLY THE FOLLOWING THREE EXPRESSIONS ARE COMPLETELY EQUIVALENT AND PRODUCE ROWS OF QUERY RESULTS BECAUSE THE DUPLICATES ARE RETAINED ! 5.)/. !,, " 5.)/. !,, # ! 5.)/. !,, " 5.)/. !,, # ! 5.)/. !,, # 5.)/. !,, "
(OWEVER IF THE 5.)/.S INVOLVE A MIXTURE OF 5.)/. AND 5.)/. !,, THE ORDER OF EVALUATION MATTERS )F THIS EXPRESSION ! 5.)/. !,, " 5.)/. #
IS INTERPRETED AS ! 5.)/. !,, " 5.)/. #
THEN IT PRODUCES TEN ROWS OF QUERY RESULTS SIX FROM THE INNER 5.)/. PLUS FOUR ROWS FROM 4ABLE ! (OWEVER IF IT IS INTERPRETED AS ! 5.)/. !,, " 5.)/. #
THEN IT PRODUCES ONLY FOUR ROWS BECAUSE THE OUTER 5.)/. ELIMINATES ALL DUPLICATE ROWS &OR THIS REASON ITS ALWAYS A GOOD IDEA TO USE PARENTHESES IN 5.)/.S OF THREE OR MORE TABLES TO SPECIFY THE ORDER OF EVALUATION INTENDED
3UMMARY 4HIS CHAPTER IS THE FIRST OF FOUR CHAPTERS ABOUT 31, QUERIES )T DESCRIBED THE FOLLOWING QUERY FEATURES s 4HE 3%,%#4 STATEMENT IS USED TO EXPRESS A 31, QUERY %VERY 3%,%#4 STATEMENT PRODUCES A TABLE OF QUERY RESULTS CONTAINING ONE OR MORE COLUMNS AND ZERO OR MORE ROWS s 4HE &2/- CLAUSE SPECIFIES THE TABLES CONTAINING THE DATA TO BE RETRIEVED BY A QUERY s 4HE 3%,%#4 CLAUSE SPECIFIES THE COLUMNS OF DATA TO BE INCLUDED IN THE QUERY RESULTS WHICH CAN BE COLUMNS OF DATA FROM THE DATABASE OR CALCULATED COLUMNS s 4HE 7(%2% CLAUSE SELECTS THE ROWS TO BE INCLUDED IN THE QUERY RESULTS BY APPLYING A SEARCH CONDITION TO ROWS OF THE DATABASE s ! SEARCH CONDITION CAN SELECT ROWS BY COMPARING VALUES BY CHECKING A VALUE AGAINST A RANGE OR SET OF VALUES BY MATCHING A STRING PATTERN AND BY CHECKING FOR .5,, VALUES s 3IMPLE SEARCH CONDITIONS CAN BE COMBINED WITH !.$ /2 AND ./4 TO FORM MORE COMPLEX SEARCH CONDITIONS s 4HE /2$%2 "9 CLAUSE SPECIFIES THAT THE QUERY RESULTS SHOULD BE SORTED IN ASCENDING OR DESCENDING ORDER BASED ON THE VALUES OF ONE OR MORE COLUMNS s 4HE 5.)/. OPERATION CAN BE USED WITHIN A 3%,%#4 STATEMENT TO COMBINE TWO OR MORE SETS OF QUERY RESULTS INTO A SINGLE SET
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OST USEFUL QUERIES REQUEST DATA FROM TWO OR MORE TABLES IN A DATABASE &OR EXAMPLE THESE REQUESTS FOR DATA IN THE SAMPLE DATABASE DRAW DATA FROM TWO THREE AND FOUR TABLES RESPECTIVELY
s ,IST THE SALESPEOPLE AND THE OFFICES WHERE THEY WORK 3!,%32%03 AND /&&)#%3 TABLES s ,IST EACH ORDER PLACED LAST WEEK SHOWING THE ORDER AMOUNT THE NAME OF THE CUSTOMER WHO PLACED IT AND THE NAME OF THE PRODUCT ORDERED /2$%23 #534/-%23 AND 02/$5#43 TABLES s 3HOW ALL ORDERS TAKEN BY SALESPEOPLE IN THE %ASTERN REGION SHOWING THE PRODUCT DESCRIPTION AND SALESPERSON /2$%23 3!,%32%03 /&&)#%3 AND 02/$5#43 TABLES 31, ALLOWS YOU TO RETRIEVE DATA THAT ANSWERS THESE REQUESTS THROUGH MULTITABLE QUERIES THAT JOIN DATA FROM TWO OR MORE TABLES 4HESE QUERIES AND THE 31, JOIN FACILITY ARE DESCRIBED IN THIS CHAPTER 7E BEGIN WITH THE JOIN CAPABILITIES THAT HAVE BEEN A PART OF 31, FROM THE EARLIEST DAYS AND ARE FOUND IN ALL 31, PRODUCTS TODAY 4HE LATER SECTIONS DESCRIBE ADDITIONAL JOIN CAPABILITIES THAT FIRST APPEARED IN 31, STANDARD AND ARE FOUND IN MOST MAINSTREAM PRODUCTS
!õ4WO 4ABLEõ1UERYõ%XAMPLE 4HE BEST WAY TO UNDERSTAND THE FACILITIES THAT 31, PROVIDES FOR MULTITABLE QUERIES IS TO START WITH A SIMPLE REQUEST THAT COMBINES DATA FROM TWO DIFFERENT TABLES h,IST ALL ORDERS SHOWING THE ORDER NUMBER AND AMOUNT AND THE NAME AND CREDIT LIMIT OF THE CUSTOMER WHO PLACED ITv 4HE FOUR SPECIFIC DATA ITEMS REQUESTED ARE CLEARLY STORED IN TWO DIFFERENT TABLES AS SHOWN IN &IGURE s 4HE /2$%23 TABLE CONTAINS THE ORDER NUMBER AND AMOUNT OF EACH ORDER BUT DOESNT HAVE CUSTOMER NAMES OR CREDIT LIMITS s 4HE #534/-%23 TABLE CONTAINS THE CUSTOMER NAMES AND CREDIT LIMITS BUT IT LACKS ANY INFORMATION ABOUT ORDERS
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4HERE IS A LINK BETWEEN THESE TWO TABLES HOWEVER )N EACH ROW OF THE /2$%23 TABLE THE #534 COLUMN CONTAINS THE CUSTOMER NUMBER OF THE CUSTOMER WHO PLACED THE ORDER WHICH MATCHES THE VALUE IN THE #534?.5- COLUMN IN ONE OF THE ROWS IN THE #534/-%23 TABLE #LEARLY THE 3%,%#4 STATEMENT THAT HANDLES THE REQUEST MUST SOMEHOW USE THIS LINK BETWEEN THE TABLES TO GENERATE ITS QUERY RESULTS "EFORE EXAMINING THE 3%,%#4 STATEMENT FOR THE QUERY ITS INSTRUCTIVE TO THINK ABOUT HOW YOU WOULD MANUALLY HANDLE THE REQUEST USING PAPER AND PENCIL &IGURE SHOWS WHAT YOU WOULD PROBABLY DO
3TART BY WRITING DOWN THE FOUR COLUMN NAMES FOR THE QUERY RESULTS 4HEN MOVE TO THE /2$%23 TABLE AND START WITH THE FIRST ORDER
,OOK ACROSS THE ROW TO FIND THE ORDER NUMBER AND THE ORDER AMOUNT AND COPY BOTH VALUES TO THE FIRST ROW OF QUERY RESULTS
,OOK ACROSS THE ROW TO FIND THE NUMBER OF THE CUSTOMER WHO PLACED THE ORDER AND MOVE TO THE #534/-%23 TABLE TO FIND CUSTOMER NUMBER BY SEARCHING THE #534?.5- COLUMN
-OVE ACROSS THE ROW OF THE #534/-%23 TABLE TO FIND THE CUSTOMERS NAME h*0 3INCLAIRv AND CREDIT LIMIT AND COPY THEM TO THE QUERY RESULTS TABLE
9OUVE GENERATED A ROW OF QUERY RESULTS -OVE BACK TO THE /2$%23 TABLE AND GO TO THE NEXT ROW 2EPEAT THE PROCESS STARTING WITH 3TEP UNTIL YOU RUN OUT OF ORDERS
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/F COURSE THIS ISNT THE ONLY WAY TO GENERATE THE QUERY RESULTS BUT REGARDLESS OF HOW YOU DO IT TWO THINGS WILL BE TRUE s %ACH ROW OF QUERY RESULTS DRAWS ITS DATA FROM A SPECIFIC PAIR OF ROWS ONE FROM THE /2$%23 TABLE AND ONE FROM THE #534/-%23 TABLE s 4HE PAIRS OF ROWS ARE FOUND BY MATCHING THE DATA VALUES IN CORRESPONDING COLUMNS FROM THE TABLES
3IMPLEõ*OINSõ%QUI *OINS 4HE PROCESS OF FORMING PAIRS OF ROWS BY MATCHING THE CONTENTS OF RELATED COLUMNS IS CALLED JOINING THE TABLES 4HE RESULTING TABLE CONTAINING DATA FROM BOTH OF THE ORIGINAL TABLES IS CALLED A JOIN BETWEEN THE TWO TABLES ! JOIN BASED ON AN EXACT MATCH BETWEEN TWO COLUMNS IS MORE PRECISELY CALLED AN EQUI JOIN *OINS CAN ALSO BE BASED ON OTHER KINDS OF COLUMN COMPARISONS AS DESCRIBED LATER IN THIS CHAPTER
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*OINS ARE THE FOUNDATION OF MULTITABLE QUERY PROCESSING IN 31, !LL OF THE DATA IN A RELATIONAL DATABASE IS STORED IN ITS COLUMNS AS EXPLICIT DATA VALUES SO ALL POSSIBLE RELATIONSHIPS BETWEEN TABLES CAN BE FORMED BY MATCHING THE CONTENTS OF RELATED COLUMNS *OINS THUS PROVIDE A POWERFUL FACILITY FOR EXERCISING THE DATA RELATIONSHIPS IN A DATABASE )N FACT BECAUSE RELATIONAL DATABASES DO NOT CONTAIN POINTERS OR OTHER MECHANISMS FOR RELATING ROWS TO ONE ANOTHER JOINS ARE THE ONLY MECHANISM FOR EXERCISING CROSS TABLE DATA RELATIONSHIPS "ECAUSE 31, HANDLES MULTITABLE QUERIES BY MATCHING COLUMNS IT SHOULD COME AS NO SURPRISE THAT THE 3%,%#4 STATEMENT FOR A MULTITABLE QUERY CONTAINS A SEARCH CONDITION THAT SPECIFIES THE COLUMN MATCH (ERE IS A 3%,%#4 STATEMENT FOR THE QUERY THAT WAS PERFORMED MANUALLY IN &IGURE ,IST ALL ORDERS SHOWING ORDER NUMBER AMOUNT CUSTOMER NAME hCOMPANYv AND THE CUSTOMERS CREDIT LIMIT 3%,%#4 /2$%2?.5- !-/5.4 #/-0!.9 #2%$)4?,)-)4 &2/- /2$%23 #534/-%23 7(%2% #534 #534?.5- /2$%2?.5- !-/5.4 #/-0!.9 #2%$)4?,)-)4
*ONES -FG &IRST #ORP !CME -FG !CME -FG !CME -FG !CME -FG &RED ,EWIS #ORP &RED ,EWIS #ORP !CE )NTERNATIONAL !CE )NTERNATIONAL (OLM ,ANDIS (OLM ,ANDIS (OLM ,ANDIS
2ECALL THAT DIFFERENT 31, TOOLS FORMAT RESULTS IN DIFFERENT WAYS SO YOUR RESULTS MAY VARY PARTICULARLY FOR THE DOLLAR AMOUNTS SHOWN IN THE EXAMPLE 4HIS QUERY LOOKS JUST LIKE THE QUERIES FROM THE PREVIOUS CHAPTER WITH TWO NEW FEATURES &IRST THE &2/- CLAUSE LISTS TWO TABLES INSTEAD OF JUST ONE 3ECOND THE SEARCH CONDITION #534 #534?.5-
COMPARES COLUMNS FROM TWO DIFFERENT TABLES 7E CALL THESE TWO COLUMNS THE MATCHING COLUMNS FOR THE TWO TABLES ,IKE ALL SEARCH CONDITIONS THIS ONE RESTRICTS THE ROWS THAT APPEAR IN THE QUERY RESULTS "ECAUSE THIS IS A TWO TABLE QUERY THE SEARCH CONDITION RESTRICTS THE PAIRS OF ROWS THAT GENERATE THE QUERY RESULTS )N FACT THE SEARCH CONDITION SPECIFIES THE SAME MATCHING COLUMNS YOU USED IN THE PAPER AND PENCIL QUERY PROCESSING )T ACTUALLY CAPTURES THE SPIRIT OF THE MANUAL COLUMN MATCHING VERY WELL SAYING
#HAPTERçç
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h'ENERATE QUERY RESULTS ONLY FOR PAIRS OF ROWS WHERE THE CUSTOMER NUMBER #534 IN THE /2$%23 TABLE MATCHES THE CUSTOMER NUMBER #534?.5- IN THE #534/-%23 TABLEv .OTICE THAT THE 3%,%#4 STATEMENT DOESNT SAY ANYTHING ABOUT HOW THE $"-3 SHOULD EXECUTE THE QUERY 4HERE IS NO MENTION OF hSTARTING WITH ORDERSv OR hSTARTING WITH CUSTOMERSv )NSTEAD THE QUERY TELLS THE $"-3 WHAT THE QUERY RESULTS SHOULD LOOK LIKE AND LEAVES IT UP TO THE $"-3 TO DECIDE HOW TO GENERATE THEM
0ARENT#HILDõ1UERIES
,IST EACH SALESPERSON AND THE CITY AND REGION WHERE THEY WORK 3%,%#4 .!-% #)49 2%')/. &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#% .!-% #)49 2%')/.
-ARY *ONES .EW 9ORK %ASTERN 3AM #LARK .EW 9ORK %ASTERN "OB 3MITH #HICAGO %ASTERN 0AUL #RUZ #HICAGO %ASTERN $AN 2OBERTS #HICAGO %ASTERN "ILL !DAMS !TLANTA %ASTERN 3UE 3MITH ,OS !NGELES 7ESTERN ,ARRY &ITCH ,OS !NGELES 7ESTERN .ANCY !NGELLI $ENVER 7ESTERN
4HE 3!,%32%03 CHILD TABLE CONTAINS 2%0?/&&)#% A FOREIGN KEY FOR THE /&&)#%3 PARENT TABLE 4HIS RELATIONSHIP IS USED TO FIND THE CORRECT /&&)#%3 ROW FOR EACH SALESPERSON SO THAT THE CORRECT CITY AND REGION CAN BE INCLUDED IN THE QUERY RESULTS (ERES ANOTHER QUERY INVOLVING THE SAME TWO TABLES BUT WITH THE PARENT AND CHILD ROLES REVERSED AS SHOWN IN &IGURE
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4HE MOST COMMON MULTITABLE QUERIES INVOLVE TWO TABLES THAT HAVE A NATURAL PARENTCHILD RELATIONSHIP 4HE QUERY ABOUT ORDERS AND CUSTOMERS IN THE PRECEDING SECTION IS AN EXAMPLE OF SUCH A QUERY %ACH ORDER CHILD HAS AN ASSOCIATED CUSTOMER PARENT AND EACH CUSTOMER PARENT CAN HAVE MANY ASSOCIATED ORDERS CHILDREN 4HE PAIRS OF ROWS THAT GENERATE THE QUERY RESULTS ARE PARENTCHILD ROW COMBINATIONS 9OU MAY RECALL FROM #HAPTER THAT FOREIGN KEYS AND PRIMARY KEYS CREATE THE PARENT CHILD RELATIONSHIP IN A 31, DATABASE 4HE TABLE CONTAINING THE FOREIGN KEY IS THE CHILD IN THE RELATIONSHIP THE TABLE WITH THE PRIMARY KEY IS THE PARENT 4O EXERCISE THE PARENTCHILD RELATIONSHIP IN A QUERY YOU SPECIFY A SEARCH CONDITION THAT COMPARES THE FOREIGN KEY AND THE PRIMARY KEY (ERE IS ANOTHER EXAMPLE OF A QUERY THAT EXERCISES A PARENTCHILD RELATIONSHIP SHOWN IN &IGURE
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,IST THE OFFICES AND THE NAMES AND TITLES OF THEIR MANAGERS
4HE /&&)#%3 CHILD TABLE CONTAINS -'2 A FOREIGN KEY FOR THE 3!,%32%03 PARENT TABLE 4HIS RELATIONSHIP IS USED TO FIND THE CORRECT 3!,%32%03 ROW FOR EACH SALESPERSON SO THAT THE CORRECT NAME AND TITLE OF THE MANAGER CAN BE INCLUDED IN THE QUERY RESULTS 31, DOES NOT REQUIRE THAT THE MATCHING COLUMNS BE INCLUDED IN THE RESULTS OF A MULTITABLE QUERY 4HEY ARE OFTEN OMITTED IN PRACTICE AS IN THE TWO PRECEDING EXAMPLES 4HATS BECAUSE PRIMARY KEYS AND FOREIGN KEYS ARE OFTEN )$ NUMBERS SUCH AS THE OFFICE NUMBERS AND EMPLOYEE NUMBERS IN THE EXAMPLES WHICH HUMANS FIND HARD TO REMEMBER WHILE THE ASSOCIATED NAMES CITIES REGIONS NAMES TITLES ARE EASIER TO UNDERSTAND )TS QUITE COMMON FOR )$ NUMBERS TO BE USED IN THE 7(%2% CLAUSE TO JOIN TWO TABLES AND FOR MORE DESCRIPTIVE NAMES TO BE SPECIFIED IN THE 3%,%#4 CLAUSE TO GENERATE COLUMNS OF QUERY RESULTS
!Nõ!LTERNATIVEõ7AYõTOõ3PECIFYõ*OINS 4HE SIMPLEST WAY TO SPECIFY THE TABLES TO BE JOINED IN A MULTITABLE QUERY IS TO NAME THEM IN A COMMA SEPARATED LIST IN THE &2/- CLAUSE OF THE 3%,%#4 STATEMENT AS SHOWN IN THE PREVIOUS EXAMPLES 4HIS METHOD FOR SPECIFYING JOINED TABLES APPEARED IN THE EARLIEST )"- 31, IMPLEMENTATIONS )T WAS INCLUDED IN THE ORIGINAL 31, STANDARD AND IS SUPPORTED BY ALL 31, BASED DATABASES 3UBSEQUENT VERSIONS OF THE STANDARD SIGNIFICANTLY EXPANDED THE JOIN CAPABILITY AND ADDED NEW OPTIONS TO THE &2/- CLAUSE 5SING THE NEWER FORM THE PREVIOUS TWO QUERY EXAMPLES COULD ALSO BE WRITTEN LIKE THIS ,IST EACH SALESPERSON AND THE CITY AND REGION WHERE THEY WORK 3%,%#4 .!-% #)49 2%')/. &2/- 3!,%32%03 */). /&&)#%3 /. 2%0?/&&)#% /&&)#% .!-% #)49 2%')/.
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,IST THE OFFICES AND THE NAMES AND TITLES OF THEIR MANAGERS 3%,%#4 #)49 .!-% 4)4,% &2/- /&&)#%3 */). 3!,%32%03 /. -'2 %-0,?.5- #)49 .!-% 4)4,%
#HICAGO "OB 3MITH 3ALES -GR !TLANTA "ILL !DAMS 3ALES 2EP .EW 9ORK 3AM #LARK 60 3ALES $ENVER ,ARRY &ITCH 3ALES -GR ,OS !NGELES ,ARRY &ITCH 3ALES -GR
)NSTEAD OF A COMMA SEPARATED LIST OF TABLE NAMES THE &2/- CLAUSE IN THESE EXAMPLES USES THE */). KEYWORD TO SPECIFICALLY DESCRIBE THE JOIN OPERATION !LSO THE MATCHING COLUMNS TO BE USED IN THE JOIN ARE SPECIFIED IN THE /. CLAUSE WHICH OCCURS AT THE END OF THE &2/- CLAUSE &OR THESE SIMPLE EXAMPLES THE EXPANDED STANDARD 31, SYNTAX ADDS VERY LITTLE TO THE OLDER FORM OF THE 3%,%#4 STATEMENT "UT THE RANGE OF JOINS THAT CAN BE EXPRESSED USING THE EXPANDED FORM IS MUCH BROADER AS DESCRIBED IN LATER SECTIONS OF THIS CHAPTER -ANY OF THE MAJOR $"-3 VENDORS ARE ENCOURAGING THE USE OF THIS NEW */). CLAUSE FOR THAT REASON
*OINSõWITHõ2OWõ3ELECTIONõ#RITERIA 4HE SEARCH CONDITION THAT SPECIFIES THE MATCHING COLUMNS IN A MULTITABLE QUERY CAN BE COMBINED WITH OTHER SEARCH CONDITIONS TO FURTHER RESTRICT THE CONTENTS OF THE QUERY RESULTS 3UPPOSE YOU WANT TO RERUN THE PRECEDING QUERY SHOWING ONLY OFFICES WITH LARGE SALES TARGETS ,IST THE OFFICES WITH A TARGET OVER AND THEIR MANAGER INFORMATION 3%,%#4 #)49 .!-% 4)4,% &2/- /&&)#%3 3!,%32%03 7(%2% -'2 %-0,?.5- !.$ 4!2'%4 #)49 .!-% 4)4,%
#HICAGO "OB 3MITH 3ALES -GR ,OS !NGELES ,ARRY &ITCH 3ALES -GR
7ITH THE ADDITIONAL SEARCH CONDITION THE ROWS THAT APPEAR IN THE QUERY RESULTS ARE FURTHER RESTRICTED 4HE FIRST TEST -'2 %-0,?.5- SELECTS ONLY PAIRS OF /&&)#%3 AND 3!,%32%03 ROWS THAT HAVE THE PROPER PARENTCHILD RELATIONSHIP THE SECOND TEST FURTHER SELECTS ONLY THOSE PAIRS OF ROWS WHERE THE OFFICE TARGET IS ABOVE )N THIS FORM OF THE QUERY THE MATCHING CONDITION FOR THE JOIN AND THE SEARCH CONDITION THAT RESTRICTS WHICH OFFICES ARE SELECTED BOTH APPEAR IN THE 7(%2% CLAUSE 5SING THE NEWER STANDARD 31, SYNTAX THE MATCHING CONDITION APPEARS IN THE /. CLAUSE AND THE SEARCH CONDITION APPEARS IN THE 7(%2% CLAUSE WHICH MAKES THE QUERY SLIGHTLY EASIER TO UNDERSTAND
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,IST THE OFFICES WITH A TARGET OVER AND THEIR MANAGER INFORMATION 3%,%#4 #)49 .!-% 4)4,% &2/- /&&)#%3 */). 3!,%32%03 /. -'2 %-0,?.5- 7(%2% 4!2'%4 #)49 .!-% 4)4,%
#HICAGO "OB 3MITH 3ALES -GR ,OS !NGELES ,ARRY &ITCH 3ALES -GR
4HE /2$%23 TABLE AND THE 02/$5#43 TABLE IN THE SAMPLE DATABASE ARE RELATED BY A COMPOSITE FOREIGN KEYPRIMARY KEY PAIR 4HE -&2 AND 02/$5#4 COLUMNS OF THE /2$%23 TABLE TOGETHER FORM A FOREIGN KEY FOR THE 02/$5#43 TABLE MATCHING ITS -&2?)$ AND 02/$5#4?)$ COLUMNS RESPECTIVELY 4O JOIN THE TABLES BASED ON THIS PARENTCHILD RELATIONSHIP YOU MUST SPECIFY BOTH PAIRS OF MATCHING COLUMNS AS SHOWN IN THIS EXAMPLE ,IST ALL THE ORDERS SHOWING AMOUNTS AND PRODUCT DESCRIPTIONS 3%,%#4 /2$%2?.5- !-/5.4 $%3#2)04)/. &2/- /2$%23 02/$5#43 7(%2% -&2 -&2?)$ !.$ 02/$5#4 02/$5#4?)$ /2$%2?.5- !-/5.4 $%3#2)04)/.
3IZE 7IDGET 3IZE 7IDGET 3IZE 7IDGET 3IZE 7IDGET 3IZE 7IDGET 3IZE 7IDGET 7IDGET !DJUSTER 7IDGET !DJUSTER
4HE SEARCH CONDITION IN THE QUERY TELLS 31, THAT THE RELATED PAIRS OF ROWS FROM THE /2$%23 AND 02/$5#43 TABLES ARE THOSE WHERE BOTH PAIRS OF MATCHING COLUMNS CONTAIN THE SAME VALUES 4HE ALTERNATIVE FORM OF THE QUERY SPECIFIES THE MATCHING COLUMNS IN THE SAME WAY 3%,%#4 /2$%2?.5- !-/5.4 $%3#2)04)/. &2/- /2$%23 */). 02/$5#43 /. -&2 -&2?)$ !.$ 02/$5#4 02/$5#4?)$
-ULTICOLUMN JOINS ARE USUALLY FOUND IN QUERIES INVOLVING COMPOUND FOREIGN KEYS SUCH AS THIS ONE 4HERE IS NO 31, RESTRICTION ON THE NUMBER OF COLUMNS THAT ARE INVOLVED IN THE MATCHING CONDITION BUT JOINS NORMALLY MIRROR THE REAL WORLD RELATIONSHIPS BETWEEN ENTITIES REPRESENTED IN THE DATABASE TABLES AND THOSE RELATIONSHIPS ARE USUALLY EMBODIED IN ONE OR JUST A FEW COLUMNS OF THE TABLES
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.ATURALõ*OINS /FTEN THE MATCHING COLUMN OR COLUMNS THAT WILL BE USED TO JOIN TWO TABLES HAVE THE SAME NAME IN BOTH TABLES 4HIS ISNT TRUE IN THE SAMPLE DATABASE WHERE THE PRIMARY KEYS AND RELATED FOREIGN KEYS HAVE BEEN GIVEN SLIGHTLY DIFFERENT NAMES SO THAT THEY CAN BE EASILY DISTINGUISHED IN OUR EXAMPLES "UT IN PRACTICE A DATABASE CREATOR WILL OFTEN USE THE SAME NAME FOR A COLUMN THAT CONTAINS A CUSTOMER )$ OR AN EMPLOYEE NUMBER ACROSS ALL OF THE TABLES THAT CONTAIN SUCH DATA 3UPPOSE THAT THE MANUFACTURER )$ AND PRODUCT )$ WERE CALLED -&2 AND 02/$5#4 IN BOTH THE /2$%23 TABLE AND THE 02/$5#43 TABLE IN THE SAMPLE DATABASE )F THAT WERE TRUE THEN THE MOST NATURAL JOIN BETWEEN THE TWO TABLES WOULD BE AN EQUI JOIN BASED ON ALL OF THE COLUMN NAMES THAT APPEAR IN BOTH TABLES 3UCH A JOIN IS IN FACT CALLED A NATURAL JOIN IN 31, STANDARD 4HE STANDARD JOIN SYNTAX ALLOWS YOU TO EASILY INDICATE THAT YOU WANT A NATURAL JOIN 3%,%#4 /2$%2?.5- !-/5.4 $%3#2)04)/. &2/- /2$%23 .!452!, */). 02/$5#43
4HIS STATEMENT TELLS THE $"-3 TO JOIN THE /2$%23 AND 02/$5#43 TABLES ON ALL OF THE COLUMNS THAT HAVE THE SAME NAMES IN BOTH TABLES )N THIS EXAMPLE THAT WOULD BE THE -&2 AND 02/$5#4 COLUMNS 9OU CAN ALSO EXPLICITLY NAME THE COLUMNS TO BE MATCHED IN THIS SITUATION WITH THIS ALTERNATIVE FORM OF THE JOIN SPECIFICATION 3%,%#4 /2$%2?.5- !-/5.4 $%3#2)04)/. &2/- /2$%23 */). 02/$5#43 53).' -&2 02/$5#4
4HE COLUMNS TO BE MATCHED FOR THE JOIN WHICH HAVE THE SAME NAME IN BOTH TABLES ARE LISTED ENCLOSED IN PARENTHESES IN THE 53).' CLAUSE .OTE THAT THE 53).' CLAUSE IS A MORE COMPACT ALTERNATIVE TO THE /. CLAUSE BUT THE PRECEDING QUERY WOULD BE COMPLETELY EQUIVALENT TO THIS ONE STILL ASSUMING THAT THE COLUMNS HAVE THE SAME NAMES IN BOTH TABLES 3%,%#4 /2$%2?.5- !-/5.4 $%3#2)04)/. &2/- /2$%23 */). 02/$5#43 /. /2$%23-&2 02/$5#43-&2 !.$ /2$%2302/$5#4 02/$5#4302/$5#4
)N MANY CASES THE FORM OF THE JOIN WITH THE 53).' CLAUSE IS PREFERABLE TO SPECIFYING AN EXPLICIT .!452!, */). )F TWO DIFFERENT ADMINISTRATORS ARE RESPONSIBLE FOR MAINTAINING THE /2$%23 AND 02/$5#43 TABLE FOR EXAMPLE COMPLETELY PLAUSIBLE IN A LARGE PRODUCTION DATABASE ITS POSSIBLE THAT THEY MIGHT BOTH ACCIDENTALLY CHOOSE THE SAME NAME FOR A NEW COLUMN TO BE ADDED TO THEIR TABLE EVEN THOUGH THE COLUMNS HAVE NOTHING TO DO WITH ONE ANOTHER )N THIS SITUATION THE .!452!, */). FORM OF THE STATEMENT WOULD PICK UP THE NEW COLUMNS WITH MATCHING NAMES AND ATTEMPT TO USE THEM WHEN JOINING THE TABLES PROBABLY RESULTING IN AN ERROR 4HE 53).' CLAUSE INSULATES THE QUERY FROM THIS TYPE OF ACCIDENTAL CONSEQUENCE OF DATABASE STRUCTURE CHANGES )N ADDITION THE 53).' CLAUSE ALLOWS YOU TO SELECT WHICH INDIVIDUAL COLUMNS ARE USED TO JOIN THE TABLES WHILE THE .!452!, */). AUTOMATICALLY USES ALL COLUMNS WITH MATCHING NAMES &INALLY IF THERE ARE NO MATCHING COLUMN NAMES A QUERY USING THE .!452!, */). MIGHT RETURN A #ARTESIAN PRODUCT DESCRIBED LATER IN THIS CHAPTER OR IT MIGHT RETURN AN ERROR DEPENDING ON THE $"-3 HOWEVER A QUERY FORMED WITH THE 53).' CLAUSE WILL ALWAYS RETURN AN ERROR IF THE NAMED COLUMNS DO NOT APPEAR IN BOTH TABLES
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
1UERIESõWITHõ4HREEõORõ-OREõ4ABLES 31, CAN COMBINE DATA FROM THREE OR MORE TABLES USING THE SAME BASIC TECHNIQUES USED FOR TWO TABLE QUERIES (ERE IS A SIMPLE EXAMPLE OF A THREE TABLE JOIN ,IST ORDERS OVER INCLUDING THE NAME OF THE SALESPERSON WHO TOOK THE ORDER AND THE NAME OF THE CUSTOMER WHO PLACED IT
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4HIS QUERY USES TWO FOREIGN KEYS IN THE /2$%23 TABLE AS SHOWN IN &IGURE 4HE #534 COLUMN IS A FOREIGN KEY FOR THE #534/-%23 TABLE LINKING EACH ORDER TO THE CUSTOMER WHO PLACED IT 4HE 2%0 COLUMN IS A FOREIGN KEY FOR THE 3!,%32%03 TABLE LINKING EACH ORDER TO THE SALESPERSON WHO TOOK IT )NFORMALLY SPEAKING THE QUERY LINKS EACH ORDER TO ITS ASSOCIATED CUSTOMER AND SALESPERSON 4HE ALTERNATIVE FORM OF THIS QUERY SPECIFIES EACH JOIN AND ITS MATCHING COLUMNS MORE EXPLICITLY 3%,%#4 /2$%2?.5- !-/5.4 #/-0!.9 .!-% &2/- /2$%23 */). #534/-%23 /. #534 #534?.5- */). 3!,%32%03 /. 2%0 %-0,?.5- 7(%2% !-/5.4
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(ERE IS ANOTHER THREE TABLE QUERY THAT USES A DIFFERENT ARRANGEMENT OF PARENTCHILD RELATIONSHIPS ,IST THE ORDERS OVER SHOWING THE NAME OF THE CUSTOMER WHO PLACED THE ORDER AND THE NAME OF THE SALESPERSON ASSIGNED TO THAT CUSTOMER 3%,%#4 /2$%2?.5- !-/5.4 #/-0!.9 .!-% &2/- /2$%23 #534/-%23 3!,%32%03 7(%2% #534 #534?.5- !.$ #534?2%0 %-0,?.5- !.$ !-/5.4 /2$%2?.5- !-/5.4 #/-0!.9 .!-%
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&IGURE SHOWS THE RELATIONSHIPS EXERCISED BY THIS QUERY 4HE FIRST RELATIONSHIP AGAIN USES THE #534 COLUMN FROM THE /2$%23 TABLE AS A FOREIGN KEY TO THE #534/-%23 TABLE
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-ULTITABLEç1UERIESç*OINS ç
,IST THE ORDERS OVER SHOWING THE NAME OF THE CUSTOMER WHO PLACED THE ORDER THE CUSTOMERS SALESPERSON AND THE OFFICE WHERE THE SALESPERSON WORKS 3%,%#4 /2$%2?.5- !-/5.4 #/-0!.9 .!-% #)49 &2/- /2$%23 #534/-%23 3!,%32%03 /&&)#%3 7(%2% #534 #534?.5- !.$ #534?2%0 %-0,?.5- !.$ 2%0?/&&)#% /&&)#% !.$ !-/5.4 /2$%2?.5- !-/5.4 #/-0!.9 .!-% #)49
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&IGURE SHOWS THE PARENTCHILD RELATIONSHIPS IN THIS QUERY ,OGICALLY IT EXTENDS THE JOIN SEQUENCE OF THE PREVIOUS EXAMPLE ONE MORE STEP LINKING AN ORDER TO ITS CUSTOMER THE CUSTOMER TO THEIR SALESPERSON AND THE SALESPERSON TO THEIR OFFICE
/THERõ%QUI *OINS 4HE VAST MAJORITY OF MULTITABLE QUERIES ARE BASED ON PARENTCHILD RELATIONSHIPS BUT 31, DOES NOT REQUIRE THAT THE MATCHING COLUMNS BE RELATED AS A FOREIGN KEY AND PRIMARY KEY !NY PAIR OF COLUMNS FROM TWO TABLES CAN SERVE AS MATCHING COLUMNS PROVIDED THEY HAVE
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4HE SECOND USES THE #534?2%0 COLUMN FROM THE #534/-%23 TABLE AS A FOREIGN KEY TO THE 3!,%32%03 TABLE )NFORMALLY SPEAKING THIS QUERY LINKS EACH ORDER TO ITS CUSTOMER AND EACH CUSTOMER TO THEIR SALESPERSON .OTE THAT THE ORDER OF THE JOINS IN THESE MULTITABLE QUERIES DOESNT MATTER 4HE $"-3 CAN JOIN THE /2$%23 TABLE TO THE #534/-%23 TABLE AND THEN JOIN THE RESULT TO THE 3!,%32%03 TABLE !LTERNATIVELY IT CAN JOIN THE #534/-%23 TABLE TO THE 3!,%32%03 TABLE FIRST AND THEN JOIN THE RESULT TO THE /2$%23 TABLE %ITHER WAY THE RESULTS WILL BE EXACTLY THE SAME SO THE $"-3 CAN PERFORM THE JOINS IN THE ORDER THAT IS MOST EFFICIENT (OWEVER SOME OF THE MORE ADVANCED JOINS DESCRIBED LATER IN THIS CHAPTER ARE SENSITIVE TO THE SEQUENCE OF THE INDIVIDUAL JOINS /NE OF THE ADVANTAGES OF THE NEWER STANDARD 31, JOIN SYNTAX IS THAT IT ALLOWS YOU TO SPECIFY THE JOIN ORDER IN THESE CASES )TS NOT UNCOMMON TO FIND QUERIES THAT JOIN THREE OR MORE TABLES IN PRODUCTION 31, APPLICATIONS AND BUSINESS INTELLIGENCE QUERIES AGAINST A LARGE DATA WAREHOUSE CAN EASILY GROW TO INVOLVE AT LEAST A DOZEN TABLES %VEN WITHIN THE CONFINES OF THE SMALL FIVE TABLE SAMPLE DATABASE ITS NOT TOO HARD TO FIND A FOUR TABLE QUERY THAT MAKES SENSE
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COMPARABLE DATA TYPES OR DATA TYPES THAT CAN BE CONVERTED TO COMPATIBLE TYPES 4HIS EXAMPLE SHOWS A QUERY THAT USES A PAIR OF DATES AS MATCHING COLUMNS &IND ALL ORDERS RECEIVED ON A DAY WHEN A NEW SALESPERSON WAS HIRED 3%,%#4 /2$%2?.5- !-/5.4 /2$%2?$!4% .!-% &2/- /2$%23 3!,%32%03 7(%2% /2$%2?$!4% ()2%?$!4% /2$%2?.5- !-/5.4 /2$%2?$!4% .!-%
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4HE RESULTS OF THIS QUERY COME FROM PAIRS OF ROWS IN THE /2$%23 AND 3!,%32%03 TABLES WHERE THE /2$%2?$!4% HAPPENS TO MATCH THE ()2%?$!4% FOR THE SALESPERSON AS SHOWN IN &IGURE .EITHER OF THESE COLUMNS IS A FOREIGN KEY OR A PRIMARY KEY AND THE RELATIONSHIP BETWEEN THE PAIRS OF ROWS IS ADMITTEDLY A STRANGE ONETHE ONLY THING THE MATCHED ORDERS AND SALESPEOPLE HAVE IN COMMON IS THAT THEY HAPPEN TO HAVE THE SAME DATES (OWEVER 31, HAPPILY JOINS THE TABLES ANYWAY -ATCHING COLUMNS LIKE THE ONES IN THIS EXAMPLE GENERATE A MANY TO MANY RELATIONSHIP BETWEEN THE TWO TABLES -ANY ORDERS CAN SHARE A SINGLE SALESPERSONS HIRE DATE AND MORE THAN ONE SALESPERSON MAY HAVE BEEN HIRED ON THE SAME DATE &OR EXAMPLE NOTE THAT THREE DIFFERENT ORDERS AND WERE RECEIVED ON /CTOBER AND TWO DIFFERENT SALESPEOPLE ,ARRY &ITCH AND -ARY *ONES WERE HIRED THAT SAME DAY 4HE THREE ORDERS EACH MATCHED TO BOTH OF THE TWO SALESPEOPLE PRODUCE SIX ROWS OF QUERY RESULTS 4HIS MANY TO MANY RELATIONSHIP IS DIFFERENT FROM THE ONE TO MANY RELATIONSHIP CREATED BY PRIMARY KEYFOREIGN KEY MATCHING COLUMNS 4HE SITUATION CAN BE SUMMARIZED AS FOLLOWS s *OINS THAT MATCH PRIMARY KEYS TO FOREIGN KEYS ALWAYS CREATE ONE TO MANY PARENT CHILD RELATIONSHIPS s /THER JOINS MAY ALSO GENERATE ONE TO MANY RELATIONSHIPS IF THE MATCHING COLUMN IN AT LEAST ONE OF THE TABLES HAS UNIQUE VALUES FOR ALL ROWS OF THE TABLE s )N GENERAL JOINS ON ARBITRARY MATCHING COLUMNS GENERATE MANY TO MANY RELATIONSHIPS .OTE THAT THESE THREE DIFFERENT SITUATIONS HAVE NOTHING TO DO WITH HOW YOU WRITE THE 3%,%#4 STATEMENT THAT EXPRESSES THE JOIN !LL THREE TYPES OF JOINS ARE WRITTEN THE SAME WAYBY INCLUDING A COMPARISON TEST FOR THE MATCHING COLUMN PAIRS IN THE 7(%2% CLAUSE OR IN THE /. CLAUSE .ONETHELESS ITS USEFUL TO THINK ABOUT JOINS IN THIS WAY TO UNDERSTAND HOW TO TURN AN %NGLISH LANGUAGE REQUEST INTO THE CORRECT 3%,%#4 STATEMENT
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.ON %QUI *OINS 4HE TERM JOIN APPLIES TO ANY QUERY THAT COMBINES DATA FROM TWO TABLES BY COMPARING THE VALUES IN A PAIR OF COLUMNS FROM THE TABLES !LTHOUGH JOINS BASED ON EQUALITY BETWEEN MATCHING COLUMNS EQUI JOINS ARE BY FAR THE MOST COMMON JOINS 31, ALSO ALLOWS YOU TO JOIN TABLES BASED ON OTHER COMPARISON OPERATORS (ERES AN EXAMPLE WHERE A GREATER THAN COMPARISON TEST IS USED AS THE BASIS FOR A JOIN ,IST ALL COMBINATIONS OF SALESPEOPLE AND OFFICES WHERE THE SALESPERSONS QUOTA IS MORE THAN THAT OFFICES TARGET REGARDLESS OF WHETHER THE SALESPERSON WORKS THERE 3%,%#4 .!-% 15/4! #)49 4!2'%4 &2/- 3!,%32%03 /&&)#%3 7(%2% 15/4! 4!2'%4 .!-% 15/4! #)49 4!2'%4
"ILL !DAMS $ENVER 3UE 3MITH $ENVER ,ARRY &ITCH $ENVER
!S IN ALL TWO TABLE QUERIES EACH ROW OF THE QUERY RESULTS COMES FROM A PAIR OF ROWS IN THIS CASE FROM THE 3!,%32%03 AND /&&)#%3 TABLES 4HE SEARCH CONDITION 15/4! 4!2'%4
SELECTS PAIRS OF ROWS WHERE THE 15/4! COLUMN FROM THE 3!,%32%03 ROW EXCEEDS THE 4!2'%4 COLUMN FROM THE /&&)#%3 ROW .OTE THAT THE PAIRS OF 3!,%32%03 AND /&&)#%3 ROWS SELECTED ARE RELATED ONLY IN THIS WAY IT IS SPECIFICALLY NOT REQUIRED THAT THE 3!,%32%03 ROW REPRESENT SOMEONE WHO WORKS IN THE OFFICE REPRESENTED BY THE /&&)#%3 ROW !DMITTEDLY THE EXAMPLE IS A BIT FARFETCHED AND IT ILLUSTRATES WHY JOINS BASED ON INEQUALITIES ARE NOT VERY COMMON (OWEVER THEY CAN BE USEFUL IN DECISION SUPPORT APPLICATIONS AND OTHER APPLICATIONS THAT EXPLORE MORE COMPLEX INTERRELATIONSHIPS IN THE DATABASE
31,õ#ONSIDERATIONSõFORõ-ULTITABLEõ1UERIES 4HE MULTITABLE QUERIES DESCRIBED THUS FAR HAVE NOT REQUIRED ANY SPECIAL 31, SYNTAX OR LANGUAGE FEATURES BEYOND THOSE DESCRIBED FOR SINGLE TABLE QUERIES (OWEVER SOME MULTITABLE QUERIES CANNOT BE EXPRESSED WITHOUT SOME ADDITIONAL 31, FEATURES 3PECIFICALLY s 1UALIFIED COLUMN NAMES ARE SOMETIMES NEEDED IN MULTITABLE QUERIES TO ELIMINATE AMBIGUOUS COLUMN REFERENCES s !LL COLUMN SELECTIONS 3%,%#4 HAVE A SPECIAL MEANING FOR MULTITABLE QUERIES s 3ELF JOINS CAN BE USED TO CREATE A MULTITABLE QUERY THAT RELATES A TABLE TO ITSELF s 4ABLE ALIASES CAN BE USED IN THE &2/- CLAUSE TO SIMPLIFY QUALIFIED COLUMN NAMES AND TO ALLOW UNAMBIGUOUS COLUMN REFERENCES IN SELF JOINS
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
1UALIFIEDõ#OLUMNõ.AMES 4HE SAMPLE DATABASE INCLUDES SEVERAL INSTANCES WHERE TWO TABLES CONTAIN COLUMNS WITH THE SAME NAME 4HE /&&)#%3 TABLE AND THE 3!,%32%03 TABLE FOR EXAMPLE BOTH HAVE A COLUMN NAMED 3!,%3 4HE COLUMN IN THE /&&)#%3 TABLE CONTAINS YEAR TO DATE SALES FOR EACH OFFICE THE ONE IN THE 3!,%32%03 TABLE CONTAINS YEAR TO DATE SALES FOR EACH SALESPERSON .ORMALLY THERE IS NO CONFUSION BETWEEN THE TWO COLUMNS BECAUSE THE &2/- CLAUSE DETERMINES WHICH OF THEM IS APPROPRIATE IN ANY GIVEN QUERY AS IN THESE EXAMPLES 3HOW THE CITIES WHERE SALES EXCEED TARGET
3HOW ALL SALESPEOPLE WITH SALES OVER 3%,%#4 .!-% 3!,%3 &2/- 3!,%32%03 7(%2% 3!,%3
(OWEVER HERE IS A QUERY WHERE THE DUPLICATE NAMES CAUSE A PROBLEM 3HOW THE NAME SALES AND OFFICE FOR EACH SALESPERSON 3%,%#4 .!-% 3!,%3 #)49 &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#% %RROR !MBIGUOUS COLUMN NAME 3!,%3
!LTHOUGH THE %NGLISH DESCRIPTION OF THE QUERY IMPLIES THAT YOU WANT THE 3!,%3 COLUMN IN THE 3!,%32%03 TABLE THE 31, QUERY IS AMBIGUOUS 4HE $"-3 HAS NO WAY OF KNOWING WHETHER YOU WANT THE 3!,%3 COLUMN FROM THE 3!,%32%03 TABLE OR THE ONE FROM THE /&&)#%3 TABLE SINCE BOTH TABLES ARE CONTRIBUTING DATA TO THE QUERY RESULTS 4O ELIMINATE THE AMBIGUITY YOU MUST USE A QUALIFIED COLUMN NAME TO IDENTIFY THE COLUMN 2ECALL FROM #HAPTER THAT A QUALIFIED COLUMN NAME SPECIFIES THE NAME OF A COLUMN AND THE TABLE CONTAINING THE COLUMN 4HE QUALIFIED NAMES OF THE TWO 3!,%3 COLUMNS IN THE SAMPLE DATABASE ARE /&&)#%33!,%3 AND 3!,%32%033!,%3
! QUALIFIED COLUMN NAME CAN BE USED IN A 3%,%#4 STATEMENT ANYWHERE THAT A COLUMN NAME IS PERMITTED 4HE TABLE SPECIFIED IN THE QUALIFIED COLUMN NAME MUST OF COURSE MATCH ONE OF THE TABLES SPECIFIED IN THE &2/- LIST (ERE IS A CORRECTED VERSION OF THE PREVIOUS QUERY THAT USES A QUALIFIED COLUMN NAME
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3%,%#4 #)49 3!,%3 &2/- /&&)#%3 7(%2% 3!,%3 4!2'%4
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3HOW THE NAME SALES AND OFFICE FOR EACH SALESPERSON 3%,%#4 .!-% 3!,%32%033!,%3 #)49 &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#% .!-% 3!,%32%033!,%3 #)49
-ARY *ONES .EW 9ORK 3AM #LARK .EW 9ORK "OB 3MITH #HICAGO 0AUL #RUZ #HICAGO $AN 2OBERTS #HICAGO "ILL !DAMS !TLANTA 3UE 3MITH ,OS !NGELES ,ARRY &ITCH ,OS !NGELES .ANCY !NGELLI $ENVER
5SING QUALIFIED COLUMN NAMES IN A MULTITABLE QUERY IS ALWAYS A GOOD IDEA 4HE DISADVANTAGE OF COURSE IS THAT THEY MAKE THE QUERY TEXT LONGER 7HEN USING INTERACTIVE 31, YOU MAY WANT TO FIRST TRY A QUERY WITH UNQUALIFIED COLUMN NAMES AND LET 31, FIND ANY AMBIGUOUS COLUMNS )F 31, REPORTS AN ERROR YOU CAN EDIT YOUR QUERY TO QUALIFY THE AMBIGUOUS COLUMNS
!LL #OLUMNõ3ELECTIONS !S DISCUSSED IN #HAPTER 3%,%#4 CAN BE USED TO SELECT ALL COLUMNS OF THE TABLE NAMED IN THE &2/- CLAUSE )N A MULTITABLE QUERY THE ASTERISK SELECTS ALL COLUMNS OF ALL TABLES IN THE &2/- CLAUSE 4HE FOLLOWING QUERY FOR EXAMPLE WOULD PRODUCE COLUMNS OF QUERY RESULTSTHE NINE COLUMNS FROM THE 3!,%32%03 TABLE FOLLOWED BY THE SIX COLUMNS FROM THE /&&)#%3 TABLE 4ELL ME ALL ABOUT SALESPEOPLE AND THE OFFICES WHERE THEY WORK 3%,%#4 &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#%
/BVIOUSLY THE 3%,%#4 FORM OF A QUERY BECOMES MUCH LESS PRACTICAL WHEN THERE ARE TWO THREE OR MORE TABLES IN THE &2/- CLAUSE -ANY 31, DIALECTS TREAT THE ASTERISK AS A SPECIAL KIND OF WILDCARD COLUMN NAME THAT IS EXPANDED INTO A LIST OF COLUMNS )N THESE DIALECTS THE ASTERISK CAN BE QUALIFIED WITH A TABLE NAME JUST LIKE A QUALIFIED COLUMN REFERENCE )N THE FOLLOWING QUERY THE SELECT ITEM 3!,%32%03 IS EXPANDED INTO A LIST CONTAINING ONLY THE COLUMNS FOUND IN THE 3!,%32%03 TABLE 4ELL ME ALL ABOUT SALESPEOPLE AND THE PLACES WHERE THEY WORK 3%,%#4 3!,%32%03 #)49 2%')/. &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#%
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
4HE QUERY WOULD PRODUCE COLUMNS OF QUERY RESULTSTHE NINE COLUMNS OF THE 3!,%32%03 TABLE FOLLOWED BY THE TWO OTHER COLUMNS EXPLICITLY REQUESTED FROM THE /&&)#%3 TABLE 4HIS TYPE OF hQUALIFIED ALL COLUMNSv SELECT ITEM WAS INTRODUCED IN THE 31, VERSION OF THE !.3))3/ STANDARD )T IS SUPPORTED IN THE MAINSTREAM 31, PRODUCTS BUT NOT IN SOME LOW END SYSTEMS
3ELF *OINS
3%,%#4 .!-% .!-% &2/- 3!,%32%03 3!,%32%03 7(%2% -!.!'%2 %-0,?.5-
4HIS 3%,%#4 STATEMENT IS ILLEGAL BECAUSE OF THE DUPLICATE REFERENCE TO THE 3!,%32%03 TABLE IN THE &2/- CLAUSE 9OU MIGHT ALSO TRY ELIMINATING THE SECOND REFERENCE TO THE 3!,%32%03 TABLE 3%,%#4 .!-% .!-% &2/- 3!,%32%03 7(%2% -!.!'%2 %-0,?.5-
4HIS QUERY IS LEGAL BUT IT WONT DO WHAT YOU WANT IT TO DO )TS A SINGLE TABLE QUERY SO 31, GOES THROUGH THE 3!,%32%03 TABLE ONE ROW AT A TIME APPLYING THE SEARCH CONDITION -!.!'%2 %-0,?.5-
4HE ROWS THAT SATISFY THIS CONDITION ARE THOSE WHERE THE TWO COLUMNS HAVE THE SAME VALUETHAT IS ROWS WHERE A SALESPERSON IS THEIR OWN MANAGER 4HERE ARE NO SUCH ROWS SO THE QUERY WOULD PRODUCE NO RESULTSWHICH IS QUITE DIFFERENT FROM THE DATA THAT THE %NGLISH LANGUAGE STATEMENT OF THE QUERY REQUESTED 4O UNDERSTAND HOW 31, SOLVES THIS PROBLEM IMAGINE THERE WERE TWO IDENTICAL COPIES OF THE 3!,%32%03 TABLE ONE NAMED %-03 CONTAINING EMPLOYEES AND ONE NAMED -'23 CONTAINING MANAGERS AS SHOWN IN &IGURE 4HE -!.!'%2 COLUMN OF THE %-03 TABLE WOULD THEN BE A FOREIGN KEY FOR THE -'23 TABLE AND THE FOLLOWING QUERY WOULD WORK ,IST THE NAMES OF SALESPEOPLE AND THEIR MANAGERS 3%,%#4 %-03.!-% -'23.!-% &2/- %-03 -'23 7(%2% %-03-!.!'%2 -'23%-0,?.5-
"ECAUSE THE COLUMNS IN THE TWO TABLES HAVE IDENTICAL NAMES ALL OF THE COLUMN REFERENCES ARE QUALIFIED /THERWISE THIS LOOKS LIKE AN ORDINARY TWO TABLE QUERY
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3OME MULTITABLE QUERIES INVOLVE A RELATIONSHIP THAT A TABLE HAS WITH ITSELF &OR EXAMPLE SUPPOSE YOU WANT TO LIST THE NAMES OF ALL SALESPEOPLE AND THEIR MANAGERS %ACH SALESPERSON APPEARS AS A ROW IN THE 3!,%32%03 TABLE AND THE -!.!'%2 COLUMN CONTAINS THE EMPLOYEE NUMBER OF THE SALESPERSONS MANAGER )T WOULD APPEAR THAT THE -!.!'%2 COLUMN SHOULD BE A FOREIGN KEY FOR THE TABLE THAT HOLDS DATA ABOUT MANAGERS )N FACT IT ISITS A FOREIGN KEY FOR THE 3!,%32%03 TABLE ITSELF )F YOU TRIED TO EXPRESS THIS QUERY LIKE ANY OTHER TWO TABLE QUERY INVOLVING A FOREIGN KEYPRIMARY KEY MATCH IT WOULD LOOK LIKE THIS
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31, USES EXACTLY THIS hIMAGINARY DUPLICATE TABLEv APPROACH TO JOIN A TABLE TO ITSELF )NSTEAD OF ACTUALLY DUPLICATING THE CONTENTS OF THE TABLE 31, LETS YOU SIMPLY REFER TO IT BY A DIFFERENT NAME CALLED A TABLE ALIAS (ERES THE SAME QUERY WRITTEN USING THE ALIASES %-03 AND -'23 FOR THE 3!,%32%03 TABLE ,IST THE NAMES OF SALESPEOPLE AND THEIR MANAGERS 3%,%#4 %-03.!-% -'23.!-% &2/- 3!,%32%03 %-03 3!,%32%03 -'23 7(%2% %-03-!.!'%2 -'23%-0,?.5- %-03.!-% -'23.!-%
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#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
4HE &2/- CLAUSE ASSIGNS A DIFFERENT ALIAS TO EACH OF THE TWO hVIRTUAL COPIESv OF THE 3!,%32%03 TABLE THAT ARE INVOLVED IN THE QUERY BY SPECIFYING THE ALIAS NAME IMMEDIATELY AFTER THE ACTUAL TABLE NAME !S THE EXAMPLE SHOWS WHEN A &2/- CLAUSE CONTAINS A TABLE ALIAS THE ALIAS MUST BE USED TO IDENTIFY THE TABLE IN QUALIFIED COLUMN REFERENCES /F COURSE ITS REALLY ONLY NECESSARY TO USE AN ALIAS FOR ONE OF THE TWO TABLE OCCURRENCES IN THIS QUERY )T COULD JUST AS EASILY HAVE BEEN WRITTEN 3%,%#4 3!,%32%03.!-% -'23.!-% &2/- 3!,%32%03 3!,%32%03 -'23 7(%2% 3!,%32%03-!.!'%2 -'23%-0,?.5-
,IST SALESPEOPLE WITH A HIGHER QUOTA THAN THEIR MANAGER 3%,%#4 3!,%32%03.!-% 3!,%32%0315/4! -'2315/4! &2/- 3!,%32%03 3!,%32%03 -'23 7(%2% 3!,%32%03-!.!'%2 -'23%-0,?.5- !.$ 3!,%32%0315/4! -'2315/4! 3!,%32%03.!-% 3!,%32%0315/4! -'2315/4!
"ILL !DAMS $AN 2OBERTS 0AUL #RUZ -ARY *ONES ,ARRY &ITCH
,IST SALESPEOPLE WHO WORK IN DIFFERENT OFFICES THAN THEIR MANAGER SHOWING THE NAME AND OFFICE WHERE EACH WORKS 3%,%#4 %-03.!-% %-0?/&&)#%#)49 -'23.!-% -'2?/&&)#%#)49 &2/- 3!,%32%03 %-03 3!,%32%03 -'23 /&&)#%3 %-0?/&&)#% /&&)#%3 -'2?/&&)#% 7(%2% %-032%0?/&&)#% %-0?/&&)#%/&&)#% !.$ -'232%0?/&&)#% -'2?/&&)#%/&&)#% !.$ %-03-!.!'%2 -'23%-0,?.5- !.$ %-032%0?/&&)#% -'232%0?/&&)#% %-03.!-% %-0?/&&)#%#)49 -'23.!-% -'2?/&&)#%#)49
"OB 3MITH #HICAGO 3AM #LARK .EW 9ORK "ILL !DAMS !TLANTA "OB 3MITH #HICAGO ,ARRY &ITCH ,OS !NGELES 3AM #LARK .EW 9ORK .ANCY !NGELLI $ENVER ,ARRY &ITCH ,OS !NGELES
4ABLEõ!LIASES !S DESCRIBED IN THE PREVIOUS SECTION TABLE ALIASES ARE REQUIRED IN QUERIES INVOLVING SELF JOINS (OWEVER YOU CAN USE AN ALIAS IN ANY QUERY &OR EXAMPLE IF A QUERY REFERS TO ANOTHER USERS TABLE OR IF THE NAME OF A TABLE IS VERY LONG THE TABLE NAME CAN BECOME TEDIOUS TO TYPE AS A
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(ERE THE ALIAS -'23 IS ASSIGNED TO ONE hVIRTUAL COPYv OF THE TABLE WHILE THE TABLES OWN NAME IS USED FOR THE OTHER COPY (ERE ARE SOME ADDITIONAL EXAMPLES OF SELF JOINS
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COLUMN QUALIFIER 4HIS QUERY WHICH REFERENCES THE ")24($!93 TABLE OWNED BY THE USER NAMED 3!- ,IST NAMES QUOTAS AND BIRTHDAYS OF SALESPEOPLE 3%,%#4 3!,%32%03.!-% 15/4! 3!-")24($!93")24(?$!4% &2/- 3!,%32%03 3!-")24($!93 7(%2% 3!,%32%03.!-% 3!-")24($!93.!-%
BECOMES EASIER TO READ AND TYPE WHEN THE ALIASES 3 AND " ARE USED FOR THE TWO TABLES ,IST NAMES QUOTAS AND BIRTHDAYS OF SALESPEOPLE 3%,%#4 3.!-% 315/4! "")24(?$!4% &2/- 3!,%32%03 3 3!-")24($!93 " 7(%2% 3.!-% ".!-%
&IGURE SHOWS THE BASIC FORM OF THE &2/- CLAUSE FOR A MULTITABLE 3%,%#4 STATEMENT COMPLETE WITH TABLE ALIASES 4HE CLAUSE HAS TWO IMPORTANT FUNCTIONS s 4HE &2/- CLAUSE IDENTIFIES ALL OF THE TABLES THAT CONTRIBUTE DATA TO THE QUERY RESULTS !NY COLUMNS REFERENCED IN THE 3%,%#4 STATEMENT MUST COME FROM ONE OF THE TABLES NAMED IN THE &2/- CLAUSE 4HERE IS AN EXCEPTION FOR OUTER REFERENCES CONTAINED IN A SUBQUERY AS DESCRIBED IN #HAPTER s 4HE &2/- CLAUSE SPECIFIES THE TAG THAT IS USED TO IDENTIFY THE TABLE IN QUALIFIED COLUMN REFERENCES WITHIN THE 3%,%#4 STATEMENT )F A TABLE ALIAS IS SPECIFIED IT BECOMES THE TABLE TAG OTHERWISE THE TABLES NAME EXACTLY AS IT APPEARS IN THE &2/- CLAUSE BECOMES THE TAG 4HE ONLY REQUIREMENT FOR TABLE TAGS IN THE &2/- CLAUSE IS THAT ALL OF THE TABLE TAGS IN A GIVEN &2/- CLAUSE MUST BE DISTINCT FROM EACH OTHER %VEN IF YOU DONT USE TABLE ALIASES IN 31, QUERIES THAT YOU WRITE YOU ARE LIKELY TO ENCOUNTER THEM IF YOU EXAMINE THE 31, GENERATED BY REPORT WRITING OR BUSINESS ANALYSIS TOOLS 4HESE TOOLS TYPICALLY PRESENT A GRAPHICAL INTERFACE THAT ALLOWS YOU TO EASILY CHOOSE THE COLUMNS TABLES MATCHING COLUMNS SEARCH CONDITIONS AND OTHER ELEMENTS OF YOUR QUERY AND THEY AUTOMATICALLY GENERATE THE CORRESPONDING 31, STATEMENTS THAT ARE PASSED TO THE $"-3 4HE TOOL WILL ALMOST ALWAYS USE TABLE TAGS TYPICALLY USING TAGS LIKE 4 4 4 ETC IN THE &2/- CLAUSE OF THE GENERATED 31, ALLOWING IT TO EASILY AND UNAMBIGUOUSLY SPECIFY THE REST OF THE QUERY REGARDLESS OF THE ACTUAL NAMES OF THE TABLES COLUMNS AND OTHER DATABASE ELEMENTS 4HE 31, STANDARD OPTIONALLY ALLOWS THE KEYWORD !3 TO APPEAR BETWEEN A TABLE NAME AND TABLE ALIAS )T ALSO USES THE TERM CORRELATION NAME TO REFER TO WHAT WE HAVE CALLED A TABLE ALIAS 4HE FUNCTION AND MEANING OF A CORRELATION NAME ARE EXACTLY AS DESCRIBED HERE
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#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
MANY 31, PRODUCTS USE THE TERM ALIAS AND IT IS MORE DESCRIPTIVE OF THE FUNCTION THAT A TABLE ALIAS PERFORMS 4HE 31, STANDARD SPECIFIES A SIMILAR TECHNIQUE FOR DESIGNATING ALTERNATE COLUMN NAMES AND IN THAT SITUATION THE COLUMN ALIAS NAME IS ACTUALLY CALLED AN ALIAS IN THE STANDARD
-ULTITABLEõ1UERYõ0ERFORMANCE
s 4HE USER ENTERS A CUSTOMER NUMBER INTO A FORM AND THE $"-3 RETRIEVES THE CUSTOMERS CREDIT LIMIT ACCOUNT BALANCE AND OTHER DATA A SINGLE TABLE QUERY s ! CASH REGISTER SCANS A PRODUCT NUMBER FROM A PACKAGE AND RETRIEVES THE PRODUCTS NAME AND PRICE FROM THE DATABASE A SINGLE TABLE QUERY s 4HE USER ENTERS A SALESPERSONS NAME AND THE PROGRAM LISTS THE CURRENT ORDERS FOR THAT SALESPERSON A TWO TABLE INQUIRY )N DECISION SUPPORT APPLICATIONS BY CONTRAST ITS COMMON FOR A QUERY TO INVOLVE MANY DIFFERENT TABLES AND TO EXERCISE COMPLEX RELATIONSHIPS IN THE DATABASE )N THESE APPLICATIONS THE QUERY RESULTS ARE OFTEN USED TO HELP MAKE EXPENSIVE DECISIONS SO A QUERY THAT REQUIRES SEVERAL MINUTES OR EVEN MANY HOURS TO COMPLETE IS PERFECTLY ACCEPTABLE (ERE ARE SOME TYPICAL DECISION SUPPORT QUERIES FOR THE SAMPLE DATABASE s 4HE USER ENTERS AN OFFICE NAME AND THE PROGRAM LISTS THE LARGEST ORDERS TAKEN BY SALESPEOPLE IN THAT OFFICE A THREE TABLE QUERY s ! REPORT SUMMARIZES SALES BY PRODUCT TYPE FOR EACH SALESPERSON SHOWING WHICH SALESPEOPLE ARE SELLING WHICH PRODUCTS A THREE TABLE QUERY s ! MANAGER CONSIDERS OPENING A NEW 3EATTLE SALES OFFICE AND RUNS A QUERY ANALYZING THE IMPACT ON ORDERS PRODUCTS CUSTOMERS AND THE SALESPEOPLE WHO CALL ON THEM A FOUR TABLE QUERY )N THE SMALL TABLES OF THE SAMPLE DATABASE EVEN THESE QUERIES WOULD REQUIRE ONLY SECONDS TO COMPLETE ON LOW COST COMPUTER HARDWARE "UT IF THE TABLES CONTAINED TENS OF MILLIONS OF ROWS THE TIME TO EXECUTE THE QUERIES WOULD LIKELY BE MUCH LONGER 4HE PERFORMANCE OF MULTITABLE JOINS CAN BE HIGHLY DEPENDENT ON THE INDEX STRUCTURES AND OTHER INTERNAL DATA STRUCTURES THAT THE $"-3 USES TO ORGANIZE THE DATA THAT IT STORES )N GENERAL QUERIES THAT EXERCISE PRIMARYFOREIGN KEY RELATIONSHIPS WILL PERFORM FAIRLY WELL BECAUSE THE $"-3 TENDS TO OPTIMIZE FOR THOSE
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!S THE NUMBER OF TABLES IN A QUERY GROWS THE AMOUNT OF EFFORT REQUIRED TO CARRY OUT THE QUERY INCREASES RAPIDLY 4HE 31, ITSELF PLACES NO LIMIT ON THE NUMBER OF TABLES JOINED BY A QUERY 3OME LOW END AND EMBEDDED 31, PRODUCTS DO LIMIT THE NUMBER OF TABLES WITH A LIMIT OF ABOUT EIGHT TABLES BEING FAIRLY COMMON 4HE HIGH PROCESSING COST OF QUERIES THAT JOIN MANY TABLES IMPOSES AN EVEN LOWER PRACTICAL LIMIT IN MANY APPLICATIONS )N ONLINE TRANSACTION PROCESSING /,40 APPLICATIONS ITS COMMON FOR A QUERY TO INVOLVE ONLY ONE OR TWO TABLES )N THESE APPLICATIONS RESPONSE TIME IS CRITICALTHE USER TYPICALLY ENTERS ONE OR TWO ITEMS OF DATA AND NEEDS A RESPONSE FROM THE DATABASE WITHIN A SECOND OR TWO (ERE ARE SOME TYPICAL /,40 QUERIES FOR THE SAMPLE DATABASE
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4HEõ3TRUCTUREõOFõAõ*OIN &OR SIMPLE JOINS ITS FAIRLY EASY TO WRITE THE CORRECT 3%,%#4 STATEMENT BASED ON AN %NGLISH LANGUAGE REQUEST OR TO LOOK AT A 3%,%#4 STATEMENT AND FIGURE OUT WHAT IT DOES 7HEN MANY TABLES ARE JOINED OR WHEN THE SEARCH CONDITIONS BECOME COMPLEX HOWEVER IT BECOMES VERY DIFFICULT JUST TO LOOK AT A 3%,%#4 STATEMENT AND FIGURE OUT WHAT IT MEANS &OR THIS REASON ITS IMPORTANT TO DEFINE MORE CAREFULLY AND JUST A BIT MORE FORMALLY WHAT A JOIN IS WHAT QUERY RESULTS ARE PRODUCED BY A GIVEN 3%,%#4 STATEMENT AND TO UNDERSTAND JUST A LITTLE BIT OF THE THEORY OF RELATIONAL DATABASE OPERATION THAT UNDERLIES JOINS
4ABLEõ-ULTIPLICATION ! JOIN IS A SPECIAL CASE OF A MORE GENERAL COMBINATION OF DATA FROM TWO TABLES KNOWN AS THE #ARTESIAN PRODUCT OR JUST THE PRODUCT OF TWO TABLES 4HE PRODUCT OF TWO TABLES IS ANOTHER TABLE THE PRODUCT TABLE WHICH CONSISTS OF ALL POSSIBLE PAIRS OF ROWS FROM THE TWO TABLES 4HE COLUMNS OF THE PRODUCT TABLE ARE ALL THE COLUMNS OF THE FIRST TABLE FOLLOWED BY ALL THE COLUMNS OF THE SECOND TABLE &IGURE SHOWS TWO SMALL SAMPLE TABLES AND THEIR PRODUCT )F YOU SPECIFY A TWO TABLE QUERY WITHOUT A 7(%2% CLAUSE 31, PRODUCES THE PRODUCT OF THE TWO TABLES AS THE QUERY RESULT &OR EXAMPLE THIS QUERY 3HOW ALL POSSIBLE COMBINATIONS OF SALESPEOPLE AND CITIES 3%,%#4 .!-% #)49 &2/- 3!,%32%03 /&&)#%3
WOULD PRODUCE THE PRODUCT OF THE 3!,%32%03 AND /&&)#%3 TABLES SHOWING ALL POSSIBLE SALESPERSONCITY PAIRS 4HERE WOULD BE ROWS OF QUERY RESULTS OFFICES ¾ SALESPEOPLE COMBINATIONS .OTICE THAT THE PRECEDING 3%,%#4 STATEMENT IS EXACTLY THE SAME AS THE FOLLOWING ONE YOU WOULD NATURALLY USE TO JOIN THE TWO TABLES BUT WITHOUT THE SPECIFICATION OF THE MATCHING COLUMNS 3HOW ALL SALESPEOPLE AND THE CITIES WHERE THEY WORK 3%,%#4 .!-% #)49 &2/- 3!,%32%03 */). /&&)#%3 /. 2%0?/&&)#% /&&)#%
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#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
4HESE TWO QUERIES POINT OUT AN IMPORTANT RELATIONSHIP BETWEEN JOINS AND PRODUCTS ! JOIN BETWEEN TWO TABLES IS JUST THE PRODUCT OF THE TWO TABLES WITH SOME OF THE ROWS REMOVED 4HE REMOVED ROWS ARE PRECISELY THOSE THAT DO NOT MEET THE MATCHING COLUMN CONDITION FOR THE JOIN 0RODUCTS ARE IMPORTANT BECAUSE THEY ARE PART OF THE FORMAL DEFINITION OF HOW 31, PROCESSES A MULTITABLE QUERY DESCRIBED IN THE NEXT SECTION
2ULESõFORõ-ULTITABLEõ1UERYõ0ROCESSING
,IST THE COMPANY NAME AND ALL ORDERS FOR CUSTOMER NUMBER 3%,%#4 #/-0!.9 /2$%2?.5- !-/5.4 &2/- #534/-%23 */). /2$%23 /. #534?.5- #534 7(%2% #534?.5- /2$%2 "9 /2$%2?.5- #/-0!.9 /2$%2?.5- !-/5.4
!CME -FG !CME -FG !CME -FG !CME -FG
4O GENERATE THE QUERY RESULTS FOR A 3%,%#4 STATEMENT
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS APPLY 3TEPS THROUGH TO EACH OF THE STATEMENTS TO GENERATE THEIR INDIVIDUAL QUERY RESULTS
&ORM THE PRODUCT OF THE TABLES NAMED IN THE &2/- CLAUSE )F THE &2/- CLAUSE NAMES A SINGLE TABLE THE PRODUCT IS THAT TABLE
)F THERE IS AN /. CLAUSE APPLY ITS MATCHING COLUMN CONDITION TO EACH ROW OF THE PRODUCT TABLE RETAINING THOSE ROWS FOR WHICH THE CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
)F THERE IS A 7(%2% CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW OF THE RESULTING TABLE RETAINING THOSE ROWS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
&OR EACH REMAINING ROW CALCULATE THE VALUE OF EACH ITEM IN THE SELECT LIST TO PRODUCE A SINGLE ROW OF QUERY RESULTS &OR EACH COLUMN REFERENCE USE THE VALUE OF THE COLUMN IN THE CURRENT ROW
)F 3%,%#4 $)34).#4 IS SPECIFIED ELIMINATE ANY DUPLICATE ROWS OF QUERY RESULTS THAT WERE PRODUCED
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4HE STEPS AFTER THE CODE THAT FOLLOWS RESTATE THE RULES FOR 31, QUERY PROCESSING ORIGINALLY INTRODUCED IN THE 2ULES FOR 3INGLE 4ABLE 1UERY 0ROCESSING TOPIC IN #HAPTER AND EXPANDS THEM TO INCLUDE MULTITABLE QUERIES 4HE RULES DEFINE THE MEANING OF ANY MULTITABLE 3%,%#4 STATEMENT BY SPECIFYING A PROCEDURE THAT ALWAYS GENERATES THE CORRECT SET OF QUERY RESULTS 4O SEE HOW THE PROCEDURE WORKS CONSIDER THIS QUERY
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)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS MERGE THE QUERY RESULTS FOR THE INDIVIDUAL STATEMENTS INTO A SINGLE TABLE OF QUERY RESULTS %LIMINATE DUPLICATE ROWS UNLESS 5.)/. !,, IS SPECIFIED
)F THERE IS AN /2$%2 "9 CLAUSE SORT THE QUERY RESULTS AS SPECIFIED 4HE ROWS GENERATED BY THIS PROCEDURE COMPRISE THE QUERY RESULTS &OLLOWING THE PREVIOUS STEPS
4HE &2/- CLAUSE GENERATES ALL POSSIBLE COMBINATIONS OF ROWS FROM THE #534/-%23 TABLE ROWS AND THE /2$%23 TABLE ROWS PRODUCING A PRODUCT TABLE OF ROWS
4HE /. CLAUSE SELECTS ONLY THOSE ROWS OF THE PRODUCT TABLE WHERE THE CUSTOMER NUMBERS MATCH #534?.5- #534 REDUCING THE ROWS TO ONLY ONE FOR EACH ORDER
4HE 7(%2% CLAUSE SELECTS ONLY THOSE ROWS OF THE RESULTING TABLE WHERE THE CUSTOMER NUMBER IS THE ONE SPECIFIED #534?.5- /NLY FOUR ROWS ARE SELECTED THE OTHER ROWS ARE ELIMINATED
4HE 3%,%#4 CLAUSE EXTRACTS THE THREE REQUESTED COLUMNS #/-0!.9 /2$%2? .5- AND !-/5.4 FROM EACH REMAINING ROW OF THE RESULTING TABLE TO GENERATE FOUR ROWS OF DETAILED QUERY RESULTS
4HE /2$%2 "9 CLAUSE SORTS THE FOUR ROWS ON THE /2$%2?.5- COLUMN TO GENERATE THE FINAL QUERY RESULTS
/BVIOUSLY NO 31, BASED $"-3 WOULD ACTUALLY CARRY OUT THE QUERY THIS WAY BUT THE PURPOSE OF THE PREVIOUS DEFINITION IS NOT TO DESCRIBE HOW THE QUERY IS CARRIED OUT BY A $"-3 )NSTEAD IT CONSTITUTES A DEFINITION OF HOW TO FIGURE OUT EXACTLY WHAT A PARTICULAR MULTITABLE QUERY hMEANSvTHAT IS THE SET OF QUERY RESULTS THAT IT SHOULD PRODUCE
/UTERõ*OINS 4HE 31, JOIN OPERATION COMBINES INFORMATION FROM TWO TABLES BY FORMING PAIRS OF RELATED ROWS FROM THE TWO TABLES WHERE THE MATCHING COLUMNS IN EACH OF THE TABLES HAVE THE SAME VALUES )F ONE OF THE ROWS OF A TABLE IS UNMATCHED IN THIS PROCESS THE JOIN CAN PRODUCE UNEXPECTED RESULTS AS ILLUSTRATED BY THESE QUERIES ,IST THE SALESPEOPLE AND THE OFFICES WHERE THEY WORK 3%,%#4 .!-% 2%0?/&&)#% &2/- 3!,%32%03 .!-% 2%0?/&&)#%
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH $AN 2OBERTS 4OM 3NYDER .5,,
#HAPTERçç
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,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI
2ECALL THAT NOT ALL 31, TOOLS DISPLAY .5,, VALUES IN THE MANNER SHOWN ,IST THE SALESPEOPLE AND THE CITIES WHERE THEY WORK
"ASED ON THE %NGLISH LANGUAGE DESCRIPTIONS OF THESE TWO QUERIES YOU WOULD PROBABLY EXPECT THEM TO PRODUCE TEN ROWS ONE FOR EACH SALESPERSON 4HE FIRST QUERY INDEED PRODUCES TEN ROWS BUT THE SECOND QUERY PRODUCES ONLY NINE ROWS 7HY "ECAUSE 4OM 3NYDER IS CURRENTLY NOT ASSIGNED TO AN OFFICE (IS ROW HAS A .5,, VALUE IN THE 2%0?/&&)#% COLUMN WHICH IS THE MATCHING COLUMN FOR THE JOIN 4HIS .5,, VALUE DOESNT MATCH ANY OF THE OFFICE NUMBERS IN THE /&&)#%3 TABLE SO 4OMS ROW IN THE 3!,%32%03 TABLE IS UNMATCHED !S A RESULT IT hVANISHESv IN THE JOIN WHETHER THE JOIN IS SPECIFIED USING THE /. CLAUSE OR THE 7(%2% CLAUSE 4HE STANDARD 31, JOIN THUS HAS THE POTENTIAL TO LOSE INFORMATION IF THE TABLES BEING JOINED CONTAIN UNMATCHED ROWS "ASED ON THE %NGLISH LANGUAGE VERSION OF THE REQUEST YOU WOULD PROBABLY EXPECT THE SECOND QUERY TO PRODUCE RESULTS LIKE THESE ,IST THE SALESPEOPLE AND THE CITIES WHERE THEY WORK 3%,%#4 .!-% #)49 &2/- 3!,%32%03 ,%&4 /54%2 */). /&&)#%3 /. 2%0?/&&)#% /&&)#% .!-% #)49
4OM 3NYDER .5,, -ARY *ONES .EW 9ORK 3AM #LARK .EW 9ORK "OB 3MITH #HICAGO 0AUL #RUZ #HICAGO $AN 2OBERTS #HICAGO "ILL !DAMS !TLANTA 3UE 3MITH ,OS !NGELES ,ARRY &ITCH ,OS !NGELES .ANCY !NGELLI $ENVER
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3%,%#4 .!-% #)49 &2/- 3!,%32%03 */). /&&)#%3 /. 2%0?/&&)#% /&&)#% .!-% #)49
-ARY *ONES .EW 9ORK 3AM #LARK .EW 9ORK "OB 3MITH #HICAGO 0AUL #RUZ #HICAGO $AN 2OBERTS #HICAGO "ILL !DAMS !TLANTA 3UE 3MITH ,OS !NGELES ,ARRY &ITCH ,OS !NGELES .ANCY !NGELLI $ENVER
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4HESE QUERY RESULTS ARE GENERATED BY A DIFFERENT TYPE OF JOIN OPERATION CALLED AN OUTER JOIN AS INDICATED BY THE ADDITIONAL KEYWORDS IN THE &2/- CLAUSE 4HE OUTER JOIN IS AN EXTENSION OF THE STANDARD JOIN DESCRIBED EARLIER IN THIS CHAPTER WHICH IS TECHNICALLY CALLED AN INNER JOIN 4HE ORIGINAL 31, STANDARD SPECIFIED ONLY THE INNER JOIN AND THE EARLY )"- 31, PRODUCTS ALSO SUPPORTED ONLY THE INNER JOIN (OWEVER THE OUTER JOIN IS A WELL UNDERSTOOD USEFUL AND INCREASINGLY IMPORTANT PART OF THE RELATIONAL DATABASE MODEL )T WAS IMPLEMENTED IN MANY NON )"- 31, PRODUCTS INCLUDING THE FLAGSHIP DATABASE PRODUCTS FROM -ICROSOFT 3YBASE AND /RACLE /UTER JOINS WERE INCLUDED IN THE 31, STANDARD STARTING WITH 31, AND ARE NOW BROADLY SUPPORTED IN MAINSTREAM PRODUCTS ALTHOUGH MANY ENTRY LEVEL 31, IMPLEMENTATIONS SUCH AS THOSE FOR EMBEDDED DEVICE APPLICATIONS STILL SUPPORT ONLY INNER JOINS 4O UNDERSTAND THE OUTER JOIN WELL ITS USEFUL TO MOVE AWAY FROM THE SAMPLE DATABASE AND CONSIDER THE TWO SIMPLE TABLES AT THE TOP OF &IGURE ! SCRIPT TO CREATE THESE TABLES AND INSERT THE SAMPLE ROWS CAN BE FOUND ON THE DOWNLOAD SITE AS DESCRIBED IN !PPENDIX ! 4HE ')2,3 TABLE LISTS FIVE GIRLS AND THE CITIES WHERE THEY LIVE THE "/93 TABLE LISTS FIVE BOYS AND THE CITIES WHERE THEY LIVE 4O FIND THE GIRLBOY PAIRS WHO LIVE IN THE SAME CITY YOU COULD USE THIS QUERY WHICH FORMS THE INNER JOIN OF THE TWO TABLES ,IST THE GIRLS AND BOYS WHO LIVE IN THE SAME CITY 3%,%#4 &2/- ')2,3 )..%2 */). "/93 /. ')2,3#)49 "/93#)49 ')2,3.!-% ')2,3#)49 "/93.!-% "/93#)49
-ARY "OSTON *OHN "OSTON -ARY "OSTON (ENRY "OSTON 3USAN #HICAGO 3AM #HICAGO "ETTY #HICAGO 3AM #HICAGO
4HIS QUERY EXPLICITLY REQUESTS THE INNER JOIN OF THE TWO TABLES AND PRODUCES FOUR ROWS OF QUERY RESULTS 4HE INNER JOIN IS THE DEFAULT SO EXACTLY THE SAME RESULTS WOULD BE PRODUCED IF THE OPTIONAL KEYWORD )..%2 HAD BEEN OMITTED FROM THE &2/- CLAUSE .OTICE THAT TWO OF THE GIRLS !NNE AND .ANCY AND TWO OF THE BOYS *AMES AND 'EORGE ARE NOT REPRESENTED IN THE QUERY RESULTS 4HESE ROWS CANNOT BE PAIRED WITH ANY ROW FROM THE OTHER TABLE AND SO THEY ARE MISSING FROM THE INNER JOIN RESULTS 4WO OF THE UNMATCHED ROWS !NNE AND *AMES HAVE VALID VALUES IN THEIR #)49 COLUMNS BUT THEY DONT MATCH ANY CITIES IN THE OPPOSITE TABLE 4HE OTHER TWO UNMATCHED ROWS .ANCY AND 'EORGE HAVE .5,, VALUES IN THEIR #)49 COLUMNS AND BY THE RULES OF 31, .5,, HANDLING THE .5,, VALUE DOESNT MATCH ANY OTHER VALUE EVEN ANOTHER .5,, VALUE 3UPPOSE YOU WANTED TO LIST THE GIRLBOY PAIRS WHO SHARE THE SAME CITIES AND INCLUDE THE UNMATCHED GIRLS AND BOYS IN THE LIST 4HE FULL OUTER JOIN OF THE ')2,3 AND "/93 TABLES PRODUCES EXACTLY THIS RESULT 4HE FOLLOWING LIST SHOWS THE PROCEDURE FOR CONSTRUCTING THE FULL OUTER JOIN AND THE PROCESS IS SHOWN GRAPHICALLY IN &IGURE
"EGIN WITH THE INNER JOIN OF THE TWO TABLES USING MATCHING COLUMNS IN THE NORMAL WAY 4HIS PRODUCES THE FIRST FOUR ROWS OF THE RESULTS TABLE IN THE FIGURE
&OR EACH ROW OF THE FIRST TABLE THAT IS NOT MATCHED BY ANY ROW IN THE SECOND TABLE ADD ONE ROW TO THE QUERY RESULTS USING THE VALUES OF THE COLUMNS IN THE FIRST TABLE AND ASSUMING A .5,, VALUE FOR ALL COLUMNS OF THE SECOND TABLE 4HIS PRODUCES THE FIFTH AND SIXTH ROWS OF RESULTS IN THE FIGURE
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&OR EACH ROW OF THE SECOND TABLE THAT IS NOT MATCHED BY ANY ROW IN THE FIRST TABLE ADD ONE ROW TO THE QUERY RESULTS USING THE VALUES OF THE COLUMNS IN THE SECOND TABLE AND ASSUMING A .5,, VALUE FOR ALL COLUMNS OF THE FIRST TABLE 4HIS PRODUCES THE SEVENTH AND EIGHTH ROWS OF RESULTS IN THE FIGURE
4HE RESULTING TABLE IS THE OUTER JOIN OF THE TWO TABLES !LL EIGHT ROWS OF QUERY RESULTS IN THE FIGURE (ERE IS THE 31, STATEMENT THAT PRODUCES THE OUTER JOIN
,IST GIRLS AND BOYS IN THE SAME CITY INCLUDING ANY UNMATCHED GIRLS OR BOYS 3%,%#4 &2/- ')2,3 &5,, /54%2 */). "/93 /. ')2,3#)49 "/93#)49 ')2,3.!-% ')2,3#)49 "/93.!-% "/93#)49
-ARY "OSTON *OHN "OSTON -ARY "OSTON (ENRY "OSTON 3USAN #HICAGO 3AM #HICAGO "ETTY #HICAGO 3AM #HICAGO !NNE $ENVER .5,, .5,, .ANCY .5,, .5,, .5,, .5,, .5,, *AMES $ALLAS .5,, .5,, 'EORGE .5,,
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!S THIS EXAMPLE SHOWS THE FULL OUTER JOIN IS AN hINFORMATION PRESERVINGv JOIN 3OME $"-3 PRODUCTS SUCH AS -Y31, DO NOT YET SUPPORT FULL OUTER JOINS %VERY ROW OF THE "/93 TABLE IS REPRESENTED IN THE QUERY RESULTS SOME MORE THAN ONCE 3IMILARLY EVERY ROW OF THE ')2,3 TABLE IS REPRESENTED IN THE QUERY RESULTS AGAIN SOME MORE THAN ONCE
,EFTõANDõ2IGHTõ/UTERõ*OINS 4HE FULL OUTER JOIN OF TWO TABLES ILLUSTRATED IN THE PREVIOUS QUERY TREATS BOTH OF THE JOINED TABLES SYMMETRICALLY 4WO OTHER USEFUL AND WELL DEFINED OUTER JOINS DO NOT 4HE LEFT OUTER JOIN BETWEEN TWO TABLES IS PRODUCED BY FOLLOWING 3TEP AND 3TEP IN THE PREVIOUS NUMBERED LIST BUT OMITTING 3TEP 4HE LEFT OUTER JOIN THUS INCLUDES .5,, EXTENDED COPIES OF THE UNMATCHED ROWS FROM THE FIRST LEFT TABLE BUT DOES NOT INCLUDE ANY UNMATCHED ROWS FROM THE SECOND RIGHT TABLE (ERE IS A LEFT OUTER JOIN BETWEEN THE ')2,3 AND "/93 TABLES ,IST GIRLS AND BOYS IN THE SAME CITY AND ANY UNMATCHED GIRLS 3%,%#4 &2/- ')2,3 ,%&4 /54%2 */). "/93 /. ')2,3#)49 "/93#)49 ')2,3.!-% ')2,3#)49 "/93.!-% "/93#)49
-ARY "OSTON *OHN "OSTON -ARY "OSTON (ENRY "OSTON 3USAN #HICAGO 3AM #HICAGO "ETTY #HICAGO 3AM #HICAGO !NNE $ENVER .5,, .5,, .ANCY .5,, .5,, .5,,
4HE QUERY PRODUCES SIX ROWS OF QUERY RESULTS SHOWING THE MATCHED GIRLBOY PAIRS AND THE UNMATCHED GIRLS 4HE UNMATCHED BOYS ARE MISSING FROM THE RESULTS 3IMILARLY THE RIGHT OUTER JOIN BETWEEN TWO TABLES IS PRODUCED BY FOLLOWING 3TEP AND 3TEP IN THE PREVIOUS NUMBERED LIST BUT OMITTING 3TEP 4HE RIGHT OUTER JOIN THUS INCLUDES .5,, EXTENDED COPIES OF THE UNMATCHED ROWS FROM THE SECOND RIGHT TABLE BUT DOES NOT INCLUDE THE UNMATCHED ROWS OF THE FIRST LEFT TABLE (ERE IS A RIGHT OUTER JOIN BETWEEN THE ')2,3 AND "/93 TABLES ,IST GIRLS AND BOYS IN THE SAME CITY AND ANY UNMATCHED BOYS 3%,%#4 &2/- ')2,3 2)'(4 /54%2 */). "/93 /. ')2,3#)49 "/93#)49 ')2,3.!-% ')2,3#)49 "/93.!-% "/93#)49
-ARY "OSTON *OHN "OSTON -ARY "OSTON (ENRY "OSTON 3USAN #HICAGO 3AM #HICAGO "ETTY #HICAGO 3AM #HICAGO .5,, .5,, *AMES $ALLAS .5,, .5,, 'EORGE .5,,
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
,IST THE SALESPEOPLE AND THE CITIES WHERE THEY WORK 3%,%#4 .!-% #)49 &2/- 3!,%32%03 ,%&4 /54%2 */). /&&)#%3 /. 2%0?/&&)#% /&&)#% .!-% #)49
4OM 3NYDER .5,, -ARY *ONES .EW 9ORK 3AM #LARK .EW 9ORK "OB 3MITH #HICAGO 0AUL #RUZ #HICAGO $AN 2OBERTS #HICAGO "ILL !DAMS !TLANTA 3UE 3MITH ,OS !NGELES ,ARRY &ITCH ,OS !NGELES .ANCY !NGELLI $ENVER
.OTE IN THIS CASE A LEFT OUTER JOIN THE hCHILDv TABLE 3!,%32%03 THE TABLE WITH THE FOREIGN KEY IS THE MAJOR TABLE AND THE hPARENTv TABLE /&&)#%3 IS THE MINOR TABLE 4HE OBJECTIVE IS TO RETAIN ROWS CONTAINING .5,, FOREIGN KEY VALUES LIKE 4OM 3NYDERS FROM THE CHILD TABLE IN THE QUERY RESULTS SO THE CHILD TABLE BECOMES THE MAJOR TABLE )T DOESNT MATTER
0!24ç))
4HIS QUERY ALSO PRODUCES SIX ROWS OF QUERY RESULTS SHOWING THE MATCHED GIRLBOY PAIRS AND THE UNMATCHED BOYS 4HIS TIME THE UNMATCHED GIRLS ARE MISSING FROM THE RESULTS !S NOTED BEFORE THE LEFT AND RIGHT OUTER JOINS DO NOT TREAT THE TWO JOINED TABLES SYMMETRICALLY )T IS OFTEN USEFUL TO THINK ABOUT ONE OF THE TABLES BEING THE hMAJORv TABLE THE ONE WHOSE ROWS ARE ALL REPRESENTED IN THE QUERY RESULTS AND THE OTHER TABLE BEING THE hMINORv TABLE THE ONE WHOSE COLUMNS CONTAIN .5,, VALUES IN THE JOINED QUERY RESULTS )N A LEFT OUTER JOIN THE LEFT FIRST MENTIONED TABLE IS THE MAJOR TABLE AND THE RIGHT LATER NAMED TABLE IS THE MINOR TABLE 4HE ROLES ARE REVERSED IN A RIGHT OUTER JOIN THE RIGHT TABLE IS MAJOR THE LEFT TABLE IS MINOR )N PRACTICE THE LEFT AND RIGHT OUTER JOINS ARE MORE USEFUL THAN THE FULL OUTER JOIN ESPECIALLY WHEN JOINING DATA FROM TWO TABLES USING A PARENTCHILD PRIMARY KEYFOREIGN KEY RELATIONSHIP 7E HAVE ALREADY SEEN ONE EXAMPLE INVOLVING THE 3!,%32%03 AND /&&)#%3 TABLE IN THE SAMPLE DATABASE 4HE 2%0?/&&)#% COLUMN IN THE 3!,%32%03 TABLE IS A FOREIGN KEY TO THE /&&)#%3 TABLE IT TELLS THE OFFICE WHERE EACH SALESPERSON WORKS AND IT IS ALLOWED TO HAVE A .5,, VALUE FOR A NEW SALESPERSON WHO HAS NOT YET BEEN ASSIGNED TO AN OFFICE SUCH AS 4OM 3NYDER !NY JOIN THAT EXERCISES THIS 3!,%32%03 TO /&&)#%3 RELATIONSHIP AND EXPECTS TO INCLUDE DATA FOR 4OM 3NYDER MUST BE AN OUTER JOIN WITH THE 3!,%32%03 TABLE AS THE MAJOR TABLE (ERE IS THE EXAMPLE USED EARLIER
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0ARTç))ç
2ETRIEVINGç$ATA
WHETHER THE QUERY IS ACTUALLY EXPRESSED AS A LEFT OUTER JOIN AS JUST SHOWN OR IF IT IS FLIPPED TO BECOME A RIGHT OUTER JOIN LIKE THIS ,IST THE SALESPEOPLE AND THE CITIES WHERE THEY WORK 3%,%#4 .!-% #)49 &2/- /&&)#%3 2)'(4 /54%2 */). 3!,%32%03 /. /&&)#% 2%0?/&&)#% .!-% #)49
4OM 3NYDER .5,, -ARY *ONES .EW 9ORK 3AM #LARK .EW 9ORK "OB 3MITH #HICAGO 0AUL #RUZ #HICAGO $AN 2OBERTS #HICAGO "ILL !DAMS !TLANTA 3UE 3MITH ,OS !NGELES ,ARRY &ITCH ,OS !NGELES .ANCY !NGELLI $ENVER
7HAT MATTERS IS THAT THE CHILD TABLE IS THE MAJOR TABLE IN THE OUTER JOIN 4HERE ARE ALSO USEFUL JOINED QUERIES WHERE THE PARENT IS THE MAJOR TABLE AND THE CHILD TABLE IS THE MINOR TABLE &OR EXAMPLE SUPPOSE THE COMPANY IN THE SAMPLE DATABASE OPENS A NEW SALES OFFICE IN $ALLAS BUT INITIALLY THE OFFICE HAS NO SALESPEOPLE ASSIGNED TO IT )F YOU WANT TO GENERATE A REPORT LISTING ALL OF THE OFFICES AND THE NAMES OF THE SALESPEOPLE WHO WORK THERE YOU MIGHT WANT TO INCLUDE A ROW REPRESENTING THE $ALLAS OFFICE (ERE IS THE OUTER JOIN QUERY THAT PRODUCES THOSE RESULTS ,IST THE OFFICES AND THE SALESPEOPLE WHO WORK IN EACH ONE 3%,%#4 #)49 .!-% &2/- /&&)#%3 ,%&4 /54%2 */). 3!,%32%03 /. /&&)#% 2%0?/&&)#% #)49 .!-%
.EW 9ORK -ARY *ONES .EW 9ORK 3AM #LARK #HICAGO "OB 3MITH #HICAGO 0AUL #RUZ #HICAGO $AN 2OBERTS !TLANTA "ILL !DAMS ,OS !NGELES 3UE 3MITH ,OS !NGELES ,ARRY &ITCH $ENVER .ANCY !NGELLI $ALLAS .5,,
)N THIS CASE THE PARENT TABLE /&&)#%3 IS THE MAJOR TABLE IN THE OUTER JOIN AND THE CHILD TABLE 3!,%32%03 IS THE MINOR TABLE 4HE OBJECTIVE IS TO ENSURE THAT ALL ROWS FROM THE /&&)#%3 TABLE ARE REPRESENTED IN THE QUERY RESULTS SO IT PLAYS THE ROLE OF MAJOR TABLE 4HE ROLES OF THE TWO TABLES ARE PRECISELY REVERSED FROM THE PREVIOUS EXAMPLE /F COURSE THE ROW FOR 4OM 3NYDER WHICH WAS INCLUDED IN THE QUERY RESULTS FOR THE EARLIER EXAMPLE
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
WHEN 3!,%32%03 WAS THE MAJOR TABLE IS MISSING FROM THIS SET OF QUERY RESULTS BECAUSE 3!,%32%03 IS NOW THE MINOR TABLE
/LDERõ/UTERõ*OINõ.OTATION
,IST GIRLS AND BOYS IN THE SAME CITY INCLUDING ANY UNMATCHED GIRLS OR BOYS 3%,%#4 &2/- ')2,3 &5,, /54%2 */). "/93 /. ')2,3#)49 "/93#)49
BECOMES THIS QUERY USING THE 31, 3ERVER NOTATION 3%,%#4 &2/- ')2,3 "/93 7(%2% ')2,3#)49 "/93#)49
4O INDICATE THE FULL OUTER JOIN BETWEEN THE TWO TABLES AN ASTERISK IS PLACED BEFORE AND AFTER THE EQUAL SIGN THAT DEFINES THE JOIN 4O INDICATE A LEFT OUTER JOIN ONLY THE LEADING ASTERISK IS SPECIFIED PRODUCING THIS QUERY 3%,%#4 &2/- ')2,3 "/93 7(%2% ')2,3#)49 "/93#)49
WHICH IS EQUIVALENT TO THIS STANDARDS BASED FORM 3%,%#4 &2/- ')2,3 ,%&4 /54%2 */). "/93 /. ')2,3#)49 "/93#)49
3IMILARLY A RIGHT OUTER JOIN IS INDICATED BY AN ASTERISK FOLLOWING THE EQUAL SIGN 3%,%#4 &2/- ')2,3 "/93 7(%2% ')2,3#)49 "/93#)49
0!24ç))
"ECAUSE THE OUTER JOIN WAS NOT PART OF THE ORIGINAL 31, STANDARD AND WAS NOT IMPLEMENTED IN EARLY )"- 31, PRODUCTS THE $"-3 VENDORS WHO PIONEERED SUPPORT FOR THE OUTER JOIN EACH INVENTED THEIR OWN NOTATION FOR EXPRESSING OUTER JOINS 5SERS OF THESE PRODUCTS BEGAN TO DEVELOP PROGRAMS THAT USED THESE PROPRIETARY OUTER JOIN CAPABILITIES CREATING AN INSTALLED BASE OF USER WRITTEN PROGRAMS THAT DEPENDED ON THE SPECIFIC /RACLE OR 31, 3ERVER NOTATION 4HE WRITERS OF THE 31, STANDARD WANTED TO ADD OUTER JOIN SUPPORT IN A WAY THAT WOULD NOT hBREAKv THESE EXISTING PROGRAMS SO THEY COULD COEXIST WITH NEW STANDARDS BASED PROGRAMS !LL OF THE MAJOR VENDORS NOW SUPPORT SOME OR ALL OF THE 31, STANDARD OUTER JOIN NOTATION AND THEY ENCOURAGE ITS USE (OWEVER YOU MAY ENCOUNTER OLDER PROGRAMS THAT USE THE OLDER PROPRIETARY FORMS SO THEY ARE DESCRIBED HERE 31, 3ERVER SUPPORTED OUTER JOINS IN ITS EARLY IMPLEMENTATIONS FROM 3YBASE AND CONTINUED TO SUPPORT OUTER JOINS AFTER IT WAS ADOPTED BY -ICROSOFT 4HE 31, 3ERVER NOTATION APPENDS AN ASTERISK TO THE EQUAL SIGN IN THE COMPARISON TEST IN THE 7(%2% CLAUSE THAT DEFINES THE JOIN CONDITION 3O THIS FULL OUTER JOIN BETWEEN THE ')2,3 AND "/93 TABLES EXPRESSED USING THE 31, STANDARD NOTATION
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2ETRIEVINGç$ATA
4HE ASTERISK MAY ALSO BE USED IN CONJUNCTION WITH OTHER COMPARISON OPERATORS SUCH AS THE GREATER THAN OR LESS THAN SIGNS TO SPECIFY OUTER NON EQUI JOINS 4HIS OLDER 31, 3ERVER NOTATION IS STILL SUPPORTED BY CURRENT VERSIONS OF THE PRODUCT IF THE APPROPRIATE COMPATIBILITY LEVEL IS SET BUT AS OF 31, 3ERVER IT IS CONSIDERED A DEPRECATED FEATURE )T MAY ALSO BE FOUND IN STORED PROCEDURES WRITTEN USING 31, 3ERVERS 4RANSACT 31, LANGUAGE /RACLE ALSO PROVIDED EARLY SUPPORT FOR OUTER JOINS BUT USES A DIFFERENT NOTATION FROM 31, 3ERVER 4HIS NOTATION INDICATES THE OUTER JOIN IN THE 7(%2% CLAUSE BY INCLUDING A PARENTHESIZED PLUS SIGN FOLLOWING THE COLUMN WHOSE TABLE IS TO HAVE THE IMAGINARY .5,, ROW ADDED THAT IS THE MINOR TABLE IN THE OUTER JOIN 4HE LEFT OUTER JOIN OF THE ')2,3 AND "/93 TABLES PRODUCES AN /RACLE QUERY THAT LOOKS LIKE THIS 3%,%#4 &2/- ')2,3 "/93 7(%2% ')2,3#)49 "/93#)49
WHICH IS ONCE AGAIN EQUIVALENT TO THIS STANDARDS BASED FORM 3%,%#4 &2/- ')2,3 ,%&4 /54%2 */). "/93 /. ')2,3#)49 "/93#)49
.OTE THAT THE PLUS SIGN APPEARS ON THE OPPOSITE SIDE OF THE COMPARISON FROM WHERE THE ASTERISK APPEARS IN THE 31, 3ERVER NOTATION 3IMILARLY A RIGHT OUTER JOIN IS INDICATED ON THE OPPOSITE SIDE OF THE EQUAL SIGN 3%,%#4 &2/- ')2,3 "/93 7(%2% ')2,3#)49 "/93#)49
/RACLE DID NOT SUPPORT A PROPRIETARY FORM OF THE FULL OUTER JOIN BUT AS NOTED EARLIER THIS DID NOT DIMINISH THE PRACTICAL USEFULNESS OF /RACLES OUTER JOINS AND YOU WILL FIND THE OLDER NOTATION IN EXISTING PROGRAMS WRITTEN FOR USE WITH /RACLE "OTH 31, 3ERVER AND /RACLE NOTATIONS HAVE SOME SIGNIFICANT LIMITATIONS COMPARED WITH THE STANDARD FORM &OR EXAMPLE WHEN THREE OR MORE TABLES ARE COMBINED USING AN OUTER JOIN THE ORDER IN WHICH THE TABLES ARE JOINED AFFECTS THE QUERY RESULTS 4HE RESULTS OF 4", /54%2 */). 4", /54%2 */). 4",
WILL IN GENERAL BE DIFFERENT FROM THE RESULTS OF 4", /54%2 */). 4", /54%2 */). 4",
5SING EITHER THE 31, 3ERVER OR /RACLE NOTATIONS ITS IMPOSSIBLE TO SPECIFY THE EVALUATION ORDER OF THE OUTER JOINS "ECAUSE OF THIS THE RESULTS PRODUCED BY THE OUTER JOIN OF THREE OR MORE TABLES DEPEND UPON THE SPECIFICS OF THE $"-3 IMPLEMENTATION &OR THIS AND OTHER REASONS YOU SHOULD ALWAYS WRITE NEW PROGRAMS USING THE 31, STANDARD OUTER JOIN NOTATION )TS ALSO USUALLY A GOOD IDEA TO CONVERT EXISTING PROGRAMS TO THE STANDARD NOTATION WHEN THEY ARE BEING REVISED
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
*OINSõANDõTHEõ31,õ3TANDARD
)NNERõ*OINSõINõ3TANDARDõ31, &IGURE SHOWS A SIMPLIFIED FORM OF THE EXTENDED STANDARD 31, SYNTAX FOR THE &2/- CLAUSE )TS EASIEST TO UNDERSTAND ALL OF THE OPTIONS PROVIDED BY CONSIDERING EACH TYPE OF JOIN ONE BY ONE STARTING WITH THE BASIC INNER JOIN AND THEN MOVING TO THE VARIOUS FORMS OF OUTER JOIN 4HE STANDARD INNER JOIN OF THE ')2,3 AND "/93 TABLES EXPRESSED IN THE ORIGINAL 31, NOTATION 3%,%#4 &2/- ')2,3 "/93 7(%2% ')2,3#)49 "/93#)49
IS STILL AN ACCEPTABLE STATEMENT IN THE LATEST VERSION OF THE STANDARD 4HE STANDARD WRITERS REALLY COULDNT HAVE MADE IT ILLEGAL WITHOUT hBREAKINGv ALL OF THE MILLIONS OF MULTITABLE 31, QUERIES THAT HAD ALREADY BEEN WRITTEN BY THE EARLY S "UT THE MODERN 31, STANDARD ALLOWS THESE ALTERNATIVE WAYS OF EXPRESSING AN INNER JOIN WHICH WE HAVE ALREADY SEEN IN EARLIER EXAMPLES 3%,%#4 &2/- ')2,3 )..%2 */). "/93 /. ')2,3#)49 "/93#)49 3%,%#4 &2/- ')2,3 )..%2 */). "/93 53).' #)49 3%,%#4 &2/- ')2,3 .!452!, )..%2 */). "/93
4HE )..%2 KEYWORD IS OPTIONAL AN INNER JOIN IS THE DEFAULT 4HE .!452!, */). FORM OF THE STATEMENT CAN BE USED IF ALL OF THE IDENTICALLY NAMED COLUMNS IN THE TWO TABLES ARE MATCHING COLUMNS OTHERWISE THE 53).' CLAUSE MUST BE USED TO INDICATE SPECIFIC MATCHING COLUMNS )N THIS CASE THE MATCHING COLUMNS ARE .!-% AND #)49 AND SINCE NONE OF THE BOYS HAS THE SAME NAME AS ONE OF THE GIRLS THAT .!452!, */). FORM OF THE QUERY RETURNS NO ROWS )F THE MATCHING COLUMNS DO NOT HAVE IDENTICAL NAMES IN THE TWO TABLES OR IF A NON EQUI JOIN IS NEEDED THEN THE FULL /. CLAUSE OR 7(%2% CLAUSE MUST BE USED TO SPECIFY THE MATCHING COLUMN CONDITIONS 4HE /. AND 7(%2% CLAUSES ARE ALSO MORE WIDELY SUPPORTED THAN THE .!452!, AND 53).' VARIATIONS
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4HE 31, REVISION DRAMATICALLY EXPANDED THE SUPPORT FOR JOINS IN THE !.3))3/ 31, STANDARD THROUGH A NEW EXPANDED FORM OF THE &2/- CLAUSE THAT CAN EXPRESS EVEN THE MOST COMPLEX OF JOINS !T THIS WRITING ALL OF THE MAJOR 31, PRODUCTS HAVE SUPPORT FOR ALL OR NEARLY ALL OF THE 31, EXPANDED JOIN CAPABILITY 4HE EXPANDED JOIN SUPPORT COMES AT THE EXPENSE OF SOME SIGNIFICANT ADDED COMPLEXITY FOR WHAT HAD PREVIOUSLY BEEN ONE OF THE SIMPLER PARTS OF 31, )N FACT THE EXPANDED JOIN SUPPORT IS PART OF A MUCH LARGER EXPANSION OF QUERY CAPABILITIES IN 31, AND SUBSEQUENT VERSIONS OF THE 31, STANDARD WHICH ADD EVEN MORE CAPABILITY AND COMPLEXITY 4HE OTHER EXPANDED FEATURES INCLUDE SET OPERATIONS ON QUERY RESULTS UNION INTERSECTION AND DIFFERENCES OF TABLES AND MUCH RICHER QUERY EXPRESSIONS THAT MANIPULATE ROWS AND TABLES AND ALLOW THEM TO BE USED IN SUBQUERIES 4HESE CAPABILITIES ARE DESCRIBED IN THE NEXT CHAPTER AFTER THE DISCUSSION OF BASIC SUBQUERIES
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7E HAVE ALREADY SEEN HOW THE EXPANDED 31, STANDARD SUPPORTS OUTER JOINS SUCH AS THE FULL LEFT AND RIGHT OUTER JOINS SPECIFIED BY THESE QUERIES 3%,%#4 &2/- ')2,3 &5,, /54%2 */). "/93 /. ')2,3#)49 "/93#)49 3%,%#4 &2/- ')2,3 ,%&4 /54%2 */). "/93 /. ')2,3#)49 "/93#)49
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
3%,%#4 &2/- ')2,3 2)'(4 /54%2 */). "/93 /. ')2,3#)49 "/93#)49
#ROSSõ*OINSõINõ3TANDARDõ31,
4HE SUPPORT FOR EXTENDED JOINS INCLUDES TWO OTHER METHODS FOR COMBINING DATA FROM TWO TABLES ! CROSS JOIN IS ANOTHER NAME FOR THE #ARTESIAN PRODUCT OF TWO TABLES AS DESCRIBED EARLIER IN THIS CHAPTER (ERE IS A QUERY THAT GENERATES THE COMPLETE PRODUCT OF THE ')2,3 AND "/93 TABLES 3%,%#4 &2/- ')2,3 #2/33 */). "/93
"Y DEFINITION THE #ARTESIAN PRODUCT ALSO SOMETIMES CALLED THE CROSS PRODUCT HENCE THE NAME h#2/33 */).v CONTAINS EVERY POSSIBLE PAIR OF ROWS FROM THE TWO TABLES )T hMULTIPLIESv THE TWO TABLES TURNING TABLES OF FOR EXAMPLE THREE GIRLS AND TWO BOYS INTO A TABLE OF SIX ¾ BOYGIRL PAIRS .O hMATCHING COLUMNSv OR hSELECTION CRITERIAv ARE ASSOCIATED WITH THE CROSS PRODUCTS SO THE /. CLAUSE AND THE 53).' CLAUSE ARE NOT ALLOWED .OTE THAT THE CROSS JOIN REALLY DOESNT ADD ANY NEW CAPABILITIES TO THE 31, LANGUAGE %XACTLY THE SAME QUERY RESULTS CAN BE GENERATED WITH AN INNER JOIN THAT SPECIFIES NO MATCHING COLUMNS 3O THE PRECEDING QUERY COULD JUST AS WELL HAVE BEEN WRITTEN AS 3%,%#4 &2/- ')2,3 "/93
4HE USE OF THE KEYWORDS #2/33 */). IN THE &2/- CLAUSE SIMPLY MAKES THE CROSS JOIN MORE EXPLICIT )N MOST DATABASES THE CROSS JOIN OF TWO TABLES BY ITSELF IS OF VERY LITTLE PRACTICAL USE )TS USEFULNESS REALLY COMES AS A BUILDING BLOCK FOR MORE COMPLEX QUERY EXPRESSIONS THAT START WITH THE CROSS PRODUCT OF TWO TABLES AND THEN USE SUMMARY QUERY CAPABILITIES DESCRIBED IN THE NEXT CHAPTER OR SET OPERATIONS TO FURTHER MANIPULATE THE RESULTS !T THIS WRITING $" DOES NOT SUPPORT THE CROSS JOIN SYNTAX BUT THE SAME EFFECT CAN BE ACHIEVED WITH THE OLDER 31, SYNTAX 4HE UNION JOIN COMBINES SOME OF THE FEATURES OF THE 5.)/. OPERATION DESCRIBED IN THE PREVIOUS CHAPTER WITH SOME OF THE FEATURES OF THE JOIN OPERATIONS DESCRIBED IN THIS CHAPTER (OWEVER THE 5.)/. */). WAS DEPRECATED IN THE 31, STANDARD AND REMOVED ENTIRELY FROM THE 31, STANDARD 3O IF YOU ARE USING A $"-3 THAT SUPPORTS A NEWER VERSION OF THE STANDARD ITS LIKELY THAT IT HAS NO SUPPORT FOR THE 5.)/. */). SYNTAX )N FACT NONE OF THE CURRENT VERSIONS OF /RACLE 31, 3ERVER -Y31, AND $" SUPPORTS IT
0!24ç))
4HE USE OF THE /54%2 KEYWORD IS OPTIONAL THE $"-3 CAN INFER FROM THE KEYWORD &5,, ,%&4 OR 2)'(4 THAT AN OUTER JOIN IS REQUIRED 4HE RESULTS OF THE EXAMPLES SHOWN WILL ALL BE DIFFERENTTHE &5,, /54%2 */). WILL RETURN ALL THE ROWS FROM BOTH TABLES THE ,%&4 /54%2 */). WILL RETURN ALL THE ROWS FROM THE LEFT ')2,3 TABLE PLUS MATCHING ROWS FROM THE RIGHT TABLE "/93 AND THE 2)'(4 /54%2 */). WILL RETURN ALL THE ROWS FROM THE RIGHT "/93 TABLE PLUS MATCHING ROWS FROM THE LEFT ')2,3 TABLE !S FOR )..%2 JOINS A NATURAL JOIN CAN BE SPECIFIED WITH THE .!452!, KEYWORD ELIMINATING THE NEED TO EXPLICITLY NAME THE MATCHING COLUMNS 3IMILARLY THE MATCHING COLUMNS CAN BE NAMED IN A 53).' CLAUSE
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2ETRIEVINGç$ATA
2ECALL THAT THE 5.)/. OPERATION EFFECTIVELY COMBINES THE ROWS OF TWO TABLES WHICH MUST HAVE THE SAME NUMBER OF COLUMNS AND THE COMPATIBLE DATA TYPES FOR EACH CORRESPONDING COLUMN 4HIS QUERY WHICH USES A SIMPLE 5.)/. OPERATION 3%,%#4 &2/- ')2,3 5.)/. !,, 3%,%#4 &2/- "/93
WHEN APPLIED TO A FIVE ROW TABLE OF GIRLS AND A FIVE ROW TABLE OF BOYS YIELDS A TEN ROW TABLE OF QUERY RESULTS %ACH ROW OF QUERY RESULTS CORRESPONDS PRECISELY TO EITHER A ROW OF THE ')2,3 TABLE OR A ROW OF THE "/93 TABLE FROM WHICH IT WAS DERIVED 4HE QUERY RESULTS HAVE TWO COLUMNS .!-% AND #)49 BECAUSE THE ')2,3 AND "/93 TABLES EACH HAVE THESE TWO COLUMNS 4HE UNION JOIN OF THE ')2,3 AND "/93 TABLES IS SPECIFIED BY THIS QUERY 3%,%#4 &2/- ')2,3 5.)/. */). "/93
4HE QUERY RESULTS AGAIN HAVE FIVE ROWS AND AGAIN EACH ROW OF RESULTS IS CONTRIBUTED BY EXACTLY ONE OF THE ROWS IN THE ')2,3 TABLE OR THE "/93 TABLE "UT UNLIKE THE SIMPLE UNION THESE QUERY RESULTS HAVE FOUR COLUMNSALL OF THE COLUMNS OF THE FIRST TABLE PLUS ALL OF THE COLUMNS OF THE SECOND TABLE )N THIS ASPECT THE UNION JOIN IS LIKE ALL OF THE OTHER JOINS &OR EACH ROW OF QUERY RESULTS CONTRIBUTED BY THE ')2,3 TABLE THE COLUMNS THAT COME FROM THE ')2,3 TABLE RECEIVE THE CORRESPONDING DATA VALUES THE OTHER COLUMNS THOSE THAT COME FROM THE "/93 TABLE HAVE .5,, VALUES 3IMILARLY FOR EACH ROW OF QUERY RESULTS CONTRIBUTED BY THE "/93 TABLE THE COLUMNS THAT COME FROM THE "/93 TABLE RECEIVE THE CORRESPONDING DATA VALUES THE OTHER COLUMNS THIS TIME THOSE THAT COME FROM THE ')2,3 TABLE HAVE .5,, VALUES !NOTHER WAY OF LOOKING AT THE RESULTS OF THE UNION JOIN IS TO COMPARE THEM TO THE RESULTS OF A FULL OUTER JOIN OF THE ')2,3 AND "/93 TABLES 4HE UNION JOIN RESULTS INCLUDE THE .5,, EXTENDED ROWS OF DATA FROM THE ')2,3 TABLE AND THE .5,, EXTENDED ROWS OF DATA FROM THE "/93 TABLE BUT THEY DO NOT INCLUDE ANY OF THE ROWS GENERATED BY MATCHING COLUMNS 2EFERRING BACK TO THE DEFINITION OF AN OUTER JOIN IN &IGURE THE UNION JOIN IS PRODUCED BY OMITTING 3TEP AND FOLLOWING 3TEPS AND &INALLY ITS USEFUL TO EXAMINE THE RELATIONSHIPS BETWEEN THE SETS OF ROWS PRODUCED BY THE CROSS JOIN THE VARIOUS TYPES OF OUTER JOINS AND THE INNER JOIN SHOWN IN &IGURE 7HEN JOINING TWO TABLES 4", WITH M ROWS AND 4", WITH N ROWS THE FIGURE SHOWS THAT s 4HE CROSS JOIN WILL CONTAIN M¾N ROWS CONSISTING OF ALL POSSIBLE ROW PAIRS FROM THE TWO TABLES s 4", )..%2 */). 4", WILL CONTAIN SOME NUMBER OF ROWS R WHICH IS LESS THAN M¾N 4HE INNER JOIN IS STRICTLY A SUBSET OF THE CROSS JOIN )T IS FORMED BY ELIMINATING THOSE ROWS FROM THE CROSS JOIN THAT DO NOT SATISFY THE MATCHING CONDITION FOR THE INNER JOIN s 4HE LEFT OUTER JOIN CONTAINS ALL OF THE ROWS FROM THE INNER JOIN PLUS EACH UNMATCHED ROW FROM 4", .5,, EXTENDED s 4HE RIGHT OUTER JOIN ALSO CONTAINS ALL OF THE ROWS FROM THE INNER JOIN PLUS EACH UNMATCHED ROW FROM 4", .5,, EXTENDED
#HAPTERçç
-ULTITABLEç1UERIESç*OINS ç
s 4HE FULL OUTER JOIN CONTAINS ALL OF THE ROWS FROM THE INNER JOIN PLUS EACH UNMATCHED ROW FROM 4", .5,, EXTENDED PLUS EACH UNMATCHED ROW FROM 4", .5,, EXTENDED 2OUGHLY SPEAKING ITS QUERY RESULTS ARE EQUAL TO THE LEFT OUTER JOIN hPLUSv THE RIGHT OUTER JOIN s 4HE UNION JOIN CONTAINS ALL OF THE ROWS OF 4", .5,, EXTENDED PLUS ALL OF THE ROWS OF 4", .5,, EXTENDED 2OUGHLY SPEAKING ITS QUERY RESULTS ARE THE FULL OUTER JOIN hMINUSv THE INNER JOIN
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!N IMPORTANT ADVANTAGE OF THE STANDARD 31, NOTATION IS THAT IT ALLOWS VERY CLEAR SPECIFICATION OF THREE TABLE OR FOUR TABLE JOINS 4O BUILD THESE MORE COMPLEX JOINS ANY OF THE JOIN EXPRESSIONS SHOWN IN &IGURE AND DESCRIBED IN THE PRECEDING SECTIONS CAN BE ENCLOSED IN PARENTHESES 4HE RESULTING JOIN EXPRESSION CAN ITSELF BE USED IN ANOTHER JOIN EXPRESSION AS IF IT WERE A SIMPLE TABLE *UST AS 31, ALLOWS YOU TO COMBINE MATHEMATICAL OPERATIONS AND WITH PARENTHESES AND BUILD MORE COMPLEX EXPRESSIONS THE 31, STANDARD ALLOWS YOU TO BUILD MORE COMPLEX JOIN EXPRESSIONS IN THE SAME WAY 4O ILLUSTRATE MULTITABLE JOINS ASSUME THAT A NEW 0!2%.43 TABLE HAS BEEN ADDED TO THE DATABASE CONTAINING THE ')2,3 AND "/93 EXAMPLE WE HAVE BEEN USING 4HE 0!2%.43 TABLE HAS THREE COLUMNS
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2ETRIEVINGç$ATA
! ROW IN THE ')2,3 OR "/93 TABLE CAN HAVE TWO MATCHING ROWS IN THE 0!2%.43 TABLE ONE SPECIFYING A -/4(%2 AND ONE A &!4(%2 OR IT CAN HAVE ONLY ONE OF THESE ROWS OR IT CAN HAVE NO MATCHING ROWS IF NO DATA ON THE CHILDS PARENTS IS AVAILABLE 4HE ')2,3 "/93 AND 0!2%.43 TABLES TOGETHER PROVIDE A RICH SET OF DATA FOR SOME MULTITABLE JOIN EXAMPLES 3UPPOSE YOU WANTED TO MAKE A LIST OF ALL OF THE GIRLS ALONG WITH THE NAMES OF THEIR MOTHERS AND THE NAMES OF THE BOYS WHO LIVE IN THE SAME CITY (ERE IS ONE QUERY THAT PRODUCES THE LIST 3%,%#4 ')2,3.!-% 0.!-% "/93.!-% &2/- ')2,3 */). 0!2%.43 /. 0!2%.43#(),$ .!-% */). "/93 /. ')2,3#)49 "/93#)49 7(%2% 490% g-/4(%2g
"ECAUSE BOTH OF THESE JOINS ARE INNER JOINS ANY GIRL WHO DOES NOT HAVE A BOY LIVING IN THE SAME CITY OR ANY GIRL WHO DOES NOT HAVE A MOTHER IN THE DATABASE WILL NOT SHOW UP IN THE QUERY RESULTS 4HIS MAY OR MAY NOT BE THE DESIRED RESULT 4O INCLUDE THOSE GIRLS WITHOUT A MATCHING MOTHER IN THE DATABASE YOU WOULD CHANGE THE JOIN BETWEEN THE ')2,3 AND THE 0!2%.43 TABLE TO A LEFT OUTER JOIN LIKE THIS 3%,%#4 ')2,3.!-% 0.!-% "/93.!-% &2/- ')2,3 ,%&4 */). 0!2%.43 /. 0!2%.43#(),$ .!-% */). "/93 /. ')2,3#)49 "/93#)49 7(%2% 490% g-/4(%2g /2 490% )3 .5,,
4HIS QUERY WILL INCLUDE ALL OF THE GIRLBOY PAIRS REGARDLESS OF WHETHER THE GIRLS HAVE A MOTHER IN THE DATABASE BUT IT WILL STILL OMIT GIRLS WHO DO NOT LIVE IN A CITY WITH ANY OF THE BOYS 4O INCLUDE THESE GIRLS AS WELL THE SECOND JOIN MUST ALSO BE CONVERTED TO A LEFT OUTER JOIN 3%,%#4 ')2,3.!-% 0.!-% "/93.!-% &2/- ')2,3 ,%&4 */). 0!2%.43 /. 0!2%.43#(),$ .!-% ,%&4 */). "/93 /. ')2,3#)49 "/93#)49 7(%2% 490% g-/4(%2g /2 490% )3 .5,,
.OTE THAT THE .5,, EXTENSION OF THE ')2,3 ROWS BY THE OUTER JOIN WITH THEIR MOTHERS ALSO CREATES SOME ADDITIONAL COMPLICATION IN THE 7(%2% CLAUSE 4HE GIRLS WITHOUT MATCHING MOTHERS WILL GENERATE ROWS WITH NOT ONLY A .5,, MOTHERS NAME 0.!-% COLUMN BUT ALSO A .5,, VALUE IN THE 490% COLUMN 4HE SIMPLE SELECTION CRITERION 7(%2% 490% g-/4(%2g
WOULD GENERATE AN hUNKNOWNv RESULT FOR THESE ROWS AND THEY WILL NOT BE INCLUDED IN THE QUERY RESULTS "UT THE ENTIRE REASON FOR USING THE LEFT OUTER JOIN WAS TO MAKE CERTAIN THEY WERE INCLUDED 4O SOLVE THIS PROBLEM THE 7(%2% CLAUSE IS EXPANDED TO ALSO TEST FOR AND ALLOW ROWS WHERE THE PARENT TYPE IS .5,,
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4HIS QUERY SOLVES THE 7(%2% CLAUSE TEST PROBLEM IN A DIFFERENT WAYBY MOVING THE TEST FOR THE 490% OF PARENT INTO THE /. CLAUSE OF THE JOIN SPECIFICATION )N THIS POSITION THE TEST FOR APPROPRIATE 490% OF PARENT WILL BE PERFORMED WHEN THE $"-3 FINDS MATCHING COLUMNS TO CONSTRUCT THE JOIN BEFORE THE .5,, EXTENDED ROWS ARE ADDED TO THE OUTER JOIN RESULTS "ECAUSE THE 0!2%.43 TABLE IS BEING USED TWICE IN THE &2/- CLAUSE IN TWO DIFFERENT ROLES ITS NECESSARY TO GIVE IT TWO DIFFERENT TABLE ALIASES SO THAT THE CORRECT NAMES CAN BE SPECIFIED IN THE SELECT LIST !S THIS EXAMPLE SHOWS EVEN A FOUR JOIN QUERY LIKE THIS ONE CAN BECOME QUITE COMPLEX WITH THE EXPANDED STANDARD 31, JOIN SYNTAX 3YNTAX CAN VARY ACROSS 31, IMPLEMENTATIONS &OR EXAMPLE /RACLE DOESNT ACCEPT THE !3 KEYWORD BETWEEN THE TABLE NAME AND ALIAS IN THE */). CLAUSE (OWEVER DESPITE THE COMPLEXITY THE QUERY DOES SPECIFY PRECISELY THE QUERY THAT THE $"-3 IS TO CARRY OUT 4HERE IS NO AMBIGUITY ABOUT THE ORDER IN WHICH THE TABLES ARE JOINED OR ABOUT WHICH JOINS ARE INNER OR OUTER JOINS /VERALL THE ADDED CAPABILITY IS WELL WORTH THE ADDED COMPLEXITY INTRODUCED BY THE EXTENDED STANDARD 31, &2/- CLAUSE !LTHOUGH NONE OF THE QUERY EXAMPLES INCLUDED IN THIS SECTION HAD 7(%2% OR /2$%2 "9 CLAUSES THEY CAN BE FREELY USED WITH THE EXTENDED JOIN SUPPORT 4HE RELATIONSHIP AMONG THE CLAUSES IS SIMPLE AND REMAINS AS DESCRIBED EARLIER IN THIS CHAPTER 4HE PROCESSING SPECIFIED IN THE &2/- CLAUSES GENERALLY OCCURS FIRST INCLUDING ANY JOINS OR UNIONS 4HE JOIN CRITERIA SPECIFIED IN A 53).' OR /. CLAUSE ARE APPLIED AS A PART OF THE PARTICULAR JOIN SPECIFICATION WHERE THEY APPEAR 7HEN PROCESSING OF THE &2/- CLASS IS COMPLETE THE RESULTING TABLE IS USED TO APPLY THE SELECTION CRITERIA IN THE 7(%2% CLAUSE 4HUS THE /. CLAUSE SPECIFIES SEARCH CRITERIA THAT APPLY TO SPECIFIC JOINS THE 7(%2% CLAUSE SPECIFIES SEARCH CRITERIA THAT APPLY TO THE ENTIRE TABLE RESULTING FROM THESE JOINS 4ABLE SUMMARIZES 31, JOIN SYNTAX SHOWING BOTH OLD AND NEW 31, STANDARD VARIANTS USING MANY OF THE EXAMPLES FROM THIS CHAPTER
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!S ONE FINAL EXAMPLE SUPPOSE YOU WANT TO GENERATE A GIRLBOY LISTING AGAIN BUT THIS TIME YOU WANT TO INCLUDE THE NAME OF THE BOYS FATHER AND THE GIRLS MOTHER IN THE QUERY RESULTS 4HIS QUERY REQUIRES A FOUR TABLE JOIN "/93 ')2,3 AND TWO COPIES OF THE 0!2%.43 TABLE ONE FOR JOINING TO THE BOYS INFORMATION TO GET FATHER NAMES AND ONE FOR JOINING TO THE GIRLS INFORMATION TO OBTAIN MOTHER NAMES !GAIN THE POTENTIAL FOR UNMATCHED ROWS IN THE JOINS MEANS THERE ARE SEVERAL POSSIBLE hRIGHTv ANSWERS TO THE QUERY 3UPPOSE AS BEFORE THAT YOU WANT TO INCLUDE ALL GIRLS AND BOYS IN THE BOYGIRL PAIRING EVEN IF THE BOY OR GIRL DOES NOT HAVE A MATCHING ROW IN THE 0!2%.43 TABLE 9OU NEED TO USE OUTER JOINS FOR THE "/93 JOIN 0!2%.43 AND ')2,3 JOIN 0!2%.43 PARTS OF THE QUERY BUT AN INNER JOIN FOR THE "/93 JOIN ')2,3 PART OF THE QUERY 4HIS QUERY YIELDS THE DESIRED RESULTS
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3UMMARY 4HIS CHAPTER DESCRIBED HOW 31, HANDLES QUERIES THAT COMBINE DATA FROM TWO OR MORE TABLES s )N A MULTITABLE QUERY A JOIN THE TABLES CONTAINING THE DATA ARE NAMED IN THE &2/- CLAUSE s %ACH ROW OF QUERY RESULTS IS A COMBINATION OF DATA FROM A SINGLE ROW IN EACH OF THE TABLES AND IT IS THE ONLY ROW THAT DRAWS ITS DATA FROM THAT PARTICULAR COMBINATION s 4HE MOST COMMON MULTITABLE QUERIES USE THE PARENTCHILD RELATIONSHIPS CREATED BY PRIMARY KEYS AND FOREIGN KEYS s )N GENERAL JOINS CAN BE BUILT BY COMPARING ANY PAIRS OF COLUMNS FROM THE TWO JOINED TABLES USING EITHER A TEST FOR EQUALITY OR ANY OTHER COMPARISON TEST s ! JOIN CAN BE THOUGHT OF AS THE PRODUCT OF TWO TABLES FROM WHICH SOME OF THE ROWS HAVE BEEN REMOVED s ! TABLE CAN BE JOINED TO ITSELF SELF JOINS REQUIRE THE USE OF A TABLE ALIAS s /UTER JOINS EXTEND THE STANDARD INNER JOIN BY RETAINING UNMATCHED ROWS OF ONE OR BOTH OF THE JOINED TABLES IN THE QUERY RESULTS AND USING .5,, VALUES FOR DATA FROM THE OTHER TABLE s 4HE 31, STANDARD PROVIDES COMPREHENSIVE SUPPORT FOR INNER AND OUTER JOINS AND FOR COMBINING THE RESULTS OF JOINS WITH OTHER MULTITABLE OPERATIONS SUCH AS UNIONS INTERSECTIONS AND DIFFERENCES
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ANY REQUESTS FOR INFORMATION DONT REQUIRE THE LEVEL OF DETAIL PROVIDED BY THE 31, QUERIES DESCRIBED IN THE LAST TWO CHAPTERS &OR EXAMPLE EACH OF THE FOLLOWING REQUESTS ASKS FOR A SINGLE VALUE OR A SMALL NUMBER OF VALUES THAT SUMMARIZES THE CONTENTS OF THE DATABASE s 7HAT IS THE TOTAL QUOTA FOR ALL SALESPEOPLE s 7HAT ARE THE SMALLEST AND LARGEST ASSIGNED QUOTAS s (OW MANY SALESPEOPLE HAVE EXCEEDED THEIR QUOTA s 7HAT IS THE SIZE OF THE AVERAGE ORDER s 7HAT IS THE SIZE OF THE AVERAGE ORDER FOR EACH SALES OFFICE s (OW MANY SALESPEOPLE ARE ASSIGNED TO EACH SALES OFFICE 31, SUPPORTS THESE REQUESTS FOR SUMMARY DATA THROUGH COLUMN FUNCTIONS AND THE '2/50 "9 AND (!6).' CLAUSES OF THE 3%,%#4 STATEMENT WHICH ARE DESCRIBED IN THIS CHAPTER
#OLUMNõ&UNCTIONS 31, LETS YOU SUMMARIZE DATA FROM THE DATABASE THROUGH A SET OF COLUMN FUNCTIONS ! 31, COLUMN FUNCTION TAKES AN ENTIRE COLUMN OF DATA AS ITS ARGUMENT AND PRODUCES A SINGLE DATA ITEM THAT SUMMARIZES THE COLUMN &OR EXAMPLE THE !6' COLUMN FUNCTION TAKES A COLUMN OF DATA AND COMPUTES ITS AVERAGE (ERE IS A QUERY THAT USES THE !6' COLUMN FUNCTION TO COMPUTE THE AVERAGE VALUE OF TWO COLUMNS FROM THE 3!,%32%03 TABLE 7HAT ARE THE AVERAGE QUOTA AND AVERAGE SALES OF OUR SALESPEOPLE 3%,%#4 !6'15/4! !6'3!,%3 &2/- 3!,%32%03 !6'15/4! !6'3!,%3
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&IGURE GRAPHICALLY SHOWS HOW THE QUERY RESULTS ARE PRODUCED 4HE FIRST COLUMN FUNCTION IN THE QUERY TAKES VALUES IN THE 15/4! COLUMN AND COMPUTES THEIR AVERAGE THE SECOND ONE AVERAGES THE VALUES IN THE 3!,%3 COLUMN 4HE QUERY PRODUCES A SINGLE ROW OF QUERY RESULTS SUMMARIZING THE DATA IN THE 3!,%32%03 TABLE 4HE 31, STANDARD SPECIFIES A NUMBER OF COLUMN FUNCTIONS AND $"-3 VENDORS HAVE ADDED MANY MORE TO THEIR PRODUCTS 4HE SIX MOST COMMONLY SUPPORTED COLUMN FUNCTIONS ARE SHOWN IN &IGURE 4HESE COLUMN FUNCTIONS OFFER DIFFERENT KINDS OF SUMMARY DATA s 35- COMPUTES THE TOTAL OF A COLUMN s !6' COMPUTES THE AVERAGE VALUE IN A COLUMN s -). FINDS THE SMALLEST VALUE IN A COLUMN s -!8 FINDS THE LARGEST VALUE IN A COLUMN s #/5.4 COUNTS THE NUMBER OF VALUES IN A COLUMN .5,, VALUES ARE NOT COUNTED s #/5.4 COUNTS ROWS OF QUERY RESULTS 4HIS IS ACTUALLY AN ALTERNATE FORM OF THE #/5.4 FUNCTION 4HE ARGUMENT TO A COLUMN FUNCTION CAN BE A SIMPLE COLUMN NAME AS IN THE PREVIOUS EXAMPLE OR IT CAN BE A 31, EXPRESSION AS SHOWN HERE 7HAT IS THE AVERAGE SALES PERFORMANCE ACROSS ALL OF OUR SALESPEOPLE 3%,%#4 !6' 3!,%315/4! &2/- 3!,%32%03 !6' 3!,%315/4!
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4O PROCESS THIS QUERY 31, CONSTRUCTS A TEMPORARY COLUMN CONTAINING THE VALUE OF THE EXPRESSION 3!,%315/4! FOR EACH ROW OF THE 3!,%32%03 TABLE AND THEN COMPUTES THE AVERAGES OF THE TEMPORARY COLUMN
#OMPUTINGõAõ#OLUMNõ4OTALõ35- 4HE 35- COLUMN FUNCTION COMPUTES THE SUM OF A COLUMN OF DATA VALUES 4HE DATA IN THE COLUMN MUST HAVE A NUMERIC TYPE SUCH AS INTEGER DECIMAL FLOATING POINT OR MONEY 4HE RESULT OF THE 35- FUNCTION HAS THE SAME BASIC DATA TYPE AS THE DATA IN THE COLUMN BUT THE RESULT MAY HAVE A HIGHER PRECISION &OR EXAMPLE IF YOU APPLY THE 35- FUNCTION TO A COLUMN OF BIT INTEGERS IT MAY PRODUCE A BIT INTEGER AS ITS RESULT (ERE ARE SOME EXAMPLES THAT USE THE 35- COLUMN FUNCTION 7HAT ARE THE TOTAL QUOTAS AND SALES FOR ALL SALESPEOPLE 3%,%#4 35-15/4! 35-3!,%3 &2/- 3!,%32%03 35-15/4! 35-3!,%3
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7HAT IS THE TOTAL OF THE ORDERS TAKEN BY "ILL !DAMS 3%,%#4 35-!-/5.4 &2/- /2$%23 3!,%32%03 7(%2% .!-% g"ILL !DAMSg !.$ 2%0 %-0,?.5- 35-!-/5.4
#OMPUTINGõAõ#OLUMNõ!VERAGEõ!6' 4HE !6' COLUMN FUNCTION COMPUTES THE AVERAGE OF A COLUMN OF DATA VALUES !S WITH THE 35- FUNCTION THE DATA IN THE COLUMN MUST HAVE A NUMERIC TYPE "ECAUSE THE !6' FUNCTION ADDS THE VALUES IN THE COLUMN AND THEN DIVIDES BY THE NUMBER OF VALUES ITS RESULT MAY HAVE A DIFFERENT DATA TYPE THAN THAT OF THE VALUES IN THE COLUMN &OR EXAMPLE IF YOU APPLY THE !6' FUNCTION TO A COLUMN OF INTEGERS THE RESULT WILL BE EITHER A DECIMAL OR A FLOATING POINT NUMBER DEPENDING ON THE BRAND OF $"-3 YOU ARE USING (ERE ARE SOME EXAMPLES OF THE !6' COLUMN FUNCTION #ALCULATE THE AVERAGE PRICE OF PRODUCTS FROM MANUFACTURER !#) 3%,%#4 !6'02)#% &2/- 02/$5#43 7(%2% -&2?)$ g!#)g !6'02)#%
#ALCULATE THE AVERAGE SIZE OF AN ORDER PLACED BY !CME -FG CUSTOMER NUMBER 3%,%#4 !6'!-/5.4 &2/- /2$%23 7(%2% #534 !6'!-/5.4
&INDINGõ%XTREMEõ6ALUESõ-).õANDõ-!8 4HE -). AND -!8 COLUMN FUNCTIONS FIND THE SMALLEST AND LARGEST VALUES IN A COLUMN RESPECTIVELY 4HE DATA IN THE COLUMN CAN CONTAIN NUMERIC STRING OR DATETIME INFORMATION 4HE RESULT OF THE -). OR -!8 FUNCTION HAS EXACTLY THE SAME DATA TYPE AS THE DATA IN THE COLUMN (ERE ARE SOME EXAMPLES THAT SHOW THE USE OF THESE COLUMN FUNCTIONS 7HAT ARE THE SMALLEST AND LARGEST ASSIGNED QUOTAS 3%,%#4 -).15/4! -!815/4! &2/- 3!,%32%03
#HAPTERçç
3UMMARYç1UERIESç
-).15/4! -!815/4!
7HAT IS THE EARLIEST ORDER DATE IN THE DATABASE 3%,%#4 -)./2$%2?$!4% &2/- /2$%23 -)./2$%2?$!4%
3%,%#4 -!8 3!,%315/4! &2/- 3!,%32%03 -!8 3!,%315/4!
7HEN THE -). AND -!8 COLUMN FUNCTIONS ARE APPLIED TO NUMERIC DATA 31, COMPARES THE NUMBERS IN ALGEBRAIC ORDER LARGE NEGATIVE NUMBERS ARE LESS THAN SMALL NEGATIVE NUMBERS WHICH ARE LESS THAN ZERO WHICH IS LESS THAN ALL POSITIVE NUMBERS $ATES ARE COMPARED SEQUENTIALLY %ARLIER DATES ARE SMALLER THAN LATER ONES $URATIONS ARE COMPARED BASED ON THEIR LENGTH 3HORTER DURATIONS ARE SMALLER THAN LONGER ONES 7HEN USING -). AND -!8 WITH STRING DATA THE COMPARISON OF TWO STRINGS DEPENDS ON THE CHARACTER SET BEING USED /N A PERSONAL COMPUTER OR A TYPICAL SERVER BOTH OF WHICH USE THE !3#)) CHARACTER SET DIGITS COME BEFORE THE LETTERS IN THE SORTING SEQUENCE AND ALL OF THE UPPERCASE CHARACTERS COME BEFORE ALL OF THE LOWERCASE CHARACTERS /N MAINFRAMES WHICH USE THE %"#$)# CHARACTER SET THE LOWERCASE CHARACTERS PRECEDE THE UPPERCASE CHARACTERS AND DIGITS COME AFTER THE LETTERS (ERE IS A COMPARISON OF THE !3#)) AND %"#$)# COLLATING SEQUENCES OF A LIST OF STRINGS FROM SMALLEST TO LARGEST - Ê !"# !"# !#-% -&'° !CME -FG° :%4! #/20° :ETA #ORP° ACME MFG° ZETA CORP°
ACME MFG° ZETA CORP° !CME -FG° !#-% -&'° :ETA #ORP° :%4! #/20° !"# !"#
4HE DIFFERENCE IN THE COLLATING SEQUENCES MEANS THAT A QUERY WITH AN /2$%2 "9 CLAUSE CAN PRODUCE DIFFERENT RESULTS ON TWO DIFFERENT SYSTEMS
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7HAT IS THE BEST SALES PERFORMANCE OF ANY SALESPERSON
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)NTERNATIONAL CHARACTERS FOR EXAMPLE ACCENTED CHARACTERS IN &RENCH 'ERMAN 3PANISH OR )TALIAN OR THE #YRILLIC ALPHABET LETTERS USED IN 'REEK OR 2USSIAN OR THE +ANJI SYMBOLS USED IN *APANESE POSE ADDITIONAL PROBLEMS 3OME BRANDS OF $"-3 USE SPECIAL INTERNATIONAL SORTING ALGORITHMS TO SORT THESE CHARACTERS INTO THEIR CORRECT POSITION FOR EACH LANGUAGE /THERS SIMPLY SORT THEM ACCORDING TO THE NUMERIC VALUE OF THE CODE ASSIGNED TO THE CHARACTER 4O ADDRESS THESE ISSUES THE 31, STANDARD INCLUDES ELABORATE SUPPORT FOR NATIONAL CHARACTER SETS USER DEFINED CHARACTER SETS AND ALTERNATE COLLATING SEQUENCES 5NFORTUNATELY SUPPORT FOR THESE 31, FEATURES VARIES WIDELY AMONG POPULAR $"-3 PRODUCTS )F YOUR APPLICATION INVOLVES INTERNATIONAL TEXT YOU WILL WANT TO EXPERIMENT WITH YOUR PARTICULAR $"-3 TO FIND OUT HOW IT HANDLES THESE CHARACTERS
#OUNTINGõ$ATAõ6ALUESõ#/5.4 4HE #/5.4 COLUMN FUNCTION COUNTS THE NUMBER OF DATA VALUES IN A COLUMN 4HE DATA IN THE COLUMN CAN BE OF ANY TYPE 4HE #/5.4 FUNCTION ALWAYS RETURNS AN INTEGER REGARDLESS OF THE DATA TYPE OF THE COLUMN (ERE ARE SOME EXAMPLES OF QUERIES THAT USE THE #/5.4 COLUMN FUNCTION (OW MANY CUSTOMERS ARE THERE 3%,%#4 #/5.4#534?.5- &2/- #534/-%23 #/5.4#534?.5-
(OW MANY SALESPEOPLE ARE OVER QUOTA 3%,%#4 #/5.4.!-% &2/- 3!,%32%03 7(%2% 3!,%3 15/4! #/5.4.!-%
(OW MANY ORDERS FOR MORE THAN ARE ON THE BOOKS 3%,%#4 #/5.4!-/5.4 &2/- /2$%23 7(%2% !-/5.4 #/5.4!-/5.4
.OTE THAT THE #/5.4 FUNCTION THAT INCLUDES A COLUMN NAME DOES NOT COUNT .5,, VALUES IN THAT COLUMN BUT #/5.4 COUNTS ALL ROWS REGARDLESS OF COLUMN VALUES !SIDE FROM .5,, VALUES HOWEVER #/5.4 IGNORES THE VALUES OF THE DATA ITEMS IN THE COLUMN IT SIMPLY COUNTS HOW MANY DATA ITEMS THERE ARE !S A RESULT IT DOESNT REALLY MATTER WHICH
#HAPTERçç
3UMMARYç1UERIESç
COLUMN YOU SPECIFY AS THE ARGUMENT OF THE #/5.4 FUNCTION 4HE LAST EXAMPLE COULD JUST AS WELL HAVE BEEN WRITTEN THIS WAY 3%,%#4 #/5.4/2$%2?.5- &2/- /2$%23 7(%2% !-/5.4 #/5.4/2$%2?.5-
3%,%#4 #/5.4 &2/- /2$%23 7(%2% !-/5.4 #/5.4
)F YOU THINK OF THE #/5.4 FUNCTION AS A hROWCOUNTv FUNCTION IT MAKES THE QUERY EASIER TO READ )N PRACTICE THE #/5.4 FUNCTION IS ALMOST ALWAYS USED INSTEAD OF THE #/5.4 FUNCTION TO COUNT ROWS
#OLUMNõ&UNCTIONSõINõTHEõ3ELECTõ,IST 3IMPLE QUERIES WITH A COLUMN FUNCTION IN THEIR SELECT LIST ARE FAIRLY EASY TO UNDERSTAND (OWEVER WHEN THE SELECT LIST INCLUDES SEVERAL COLUMN FUNCTIONS OR WHEN THE ARGUMENT TO A COLUMN FUNCTION IS A COMPLEX EXPRESSION THE QUERY CAN BE HARDER TO READ AND UNDERSTAND 4HE FOLLOWING STEPS SHOW THE RULES FOR 31, QUERY PROCESSING EXPANDED ONCE MORE TO DESCRIBE HOW COLUMN FUNCTIONS ARE HANDLED !S BEFORE THE RULES ARE INTENDED TO PROVIDE A PRECISE DEFINITION OF WHAT A QUERY MEANS NOT A DESCRIPTION OF HOW THE $"-3 ACTUALLY GOES ABOUT PRODUCING THE QUERY RESULTS 4O GENERATE THE QUERY RESULTS FOR A 3%,%#4 STATEMENT
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS APPLY 3TEPS THROUGH TO EACH OF THE STATEMENTS TO GENERATE THEIR INDIVIDUAL QUERY RESULTS
&ORM THE PRODUCT OF THE TABLES NAMED IN THE &2/- CLAUSE )F THE &2/- CLAUSE NAMES A SINGLE TABLE THE PRODUCT IS THAT TABLE
)F THERE IS A 7(%2% CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW OF THE PRODUCT TABLE RETAINING THOSE ROWS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
&OR EACH REMAINING ROW CALCULATE THE VALUE OF EACH ITEM IN THE SELECT LIST TO PRODUCE A SINGLE ROW OF QUERY RESULTS &OR A SIMPLE COLUMN REFERENCE USE THE VALUE OF THE COLUMN IN THE CURRENT ROW &OR A COLUMN FUNCTION USE THE ENTIRE SET OF ROWS AS ITS ARGUMENT
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)N FACT ITS AWKWARD TO THINK OF THE QUERY AS hCOUNTING HOW MANY ORDER AMOUNTSv OR hCOUNTING HOW MANY ORDER NUMBERSv ITS MUCH EASIER TO THINK ABOUT hCOUNTING HOW MANY ORDERSv &OR THIS REASON 31, SUPPORTS A SPECIAL #/5.4 COLUMN FUNCTION WHICH COUNTS ROWS RATHER THAN DATA VALUES (ERE IS THE SAME QUERY REWRITTEN ONCE AGAIN TO USE THE #/5.4 FUNCTION
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)F 3%,%#4 $)34).#4 IS SPECIFIED ELIMINATE ANY DUPLICATE ROWS OF QUERY RESULTS THAT WERE PRODUCED
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS MERGE THE QUERY RESULTS FOR THE INDIVIDUAL STATEMENTS INTO A SINGLE TABLE OF QUERY RESULTS %LIMINATE DUPLICATE ROWS UNLESS 5.)/. !,, IS SPECIFIED
)F THERE IS AN /2$%2 "9 CLAUSE SORT THE QUERY RESULTS AS SPECIFIED
4HE ROWS GENERATED BY THIS PROCEDURE COMPRISE THE QUERY RESULTS /NE OF THE BEST WAYS TO THINK ABOUT SUMMARY QUERIES AND COLUMN FUNCTIONS IS TO IMAGINE THE QUERY PROCESSING BROKEN DOWN INTO TWO STEPS &IRST YOU SHOULD IMAGINE HOW THE QUERY WOULD WORK WITHOUT THE COLUMN FUNCTIONS PRODUCING MANY ROWS OF DETAILED QUERY RESULTS 4HEN YOU SHOULD IMAGINE 31, APPLYING THE COLUMN FUNCTIONS TO THE DETAILED QUERY RESULTS PRODUCING A SINGLE SUMMARY ROW &OR EXAMPLE CONSIDER THE FOLLOWING COMPLEX QUERY &IND THE AVERAGE ORDER AMOUNT TOTAL ORDER AMOUNT AVERAGE ORDER AMOUNT AS A PERCENTAGE OF THE CUSTOMERS CREDIT LIMIT AND AVERAGE ORDER AMOUNT AS A PERCENTAGE OF THE SALESPERSONS QUOTA 3%,%#4 !6'!-/5.4 35-!-/5.4 !6'!-/5.4#2%$)4?,)-)4 !6'!-/5.415/4! &2/- /2$%23 #534/-%23 3!,%32%03 7(%2% #534 #534?.5- !.$ 2%0 %-0,?.5- !6'!-/5.4 35-!-/5.4 !6'!-/5.4#2%$)4?,)-)4
!6'!-/5.415/4!
.OTE THAT THE ROW SIZE IN THE QUERY RESULTS IS RATHER LARGE BECAUSE OF THE VERY LONG COLUMN HEADINGS )F YOU ARE USING AN 31, CLIENT THAT RESTRICTS QUERY RESULT ROWS TO CHARACTERS OR LESS EACH ROW WILL WRAP TO MULTIPLE LINES AND IT WONT BE NEARLY AS READABLE AS WHAT IS SHOWN HERE 9OU WILL LATER LEARN HOW TO ADD A COLUMN ALIAS TO THE QUERY RESULTS TO ELIMINATE THE LONG COLUMN HEADINGS GENERATED BY THE $"-3 WHEN COLUMN FUNCTIONS ARE USED 7ITHOUT THE COLUMN FUNCTIONS IT WOULD LOOK LIKE THIS 3%,%#4 !-/5.4 !-/5.4 !-/5.4#2%$)4?,)-)4 !-/5.415/4! &2/- /2$%23 #534/-%23 3!,%32%03 7(%2% #534 #534?.5- !.$ !.$ 2%0 %-0,?.5-
AND WOULD PRODUCE ONE ROW OF DETAILED QUERY RESULTS FOR EACH ORDER 4HE COLUMN FUNCTIONS USE THE COLUMNS OF THIS DETAILED QUERY RESULTS TABLE TO GENERATE A SINGLE ROW TABLE OF SUMMARY QUERY RESULTS ! COLUMN FUNCTION CAN APPEAR IN A 31, STATEMENT ANYWHERE THAT A COLUMN NAME CAN APPEAR )T CAN FOR EXAMPLE BE PART OF AN EXPRESSION THAT ADDS OR SUBTRACTS THE VALUES OF TWO COLUMN FUNCTIONS (OWEVER IN SOME 31, IMPLEMENTATIONS PARTICULARLY OLDER ONES BASED ON THE 31, STANDARD THE ARGUMENT OF A COLUMN FUNCTION CANNOT CONTAIN ANOTHER
#HAPTERçç
3UMMARYç1UERIESç
COLUMN FUNCTION BECAUSE THE RESULTING EXPRESSION DOESNT MAKE SENSE 4HIS RULE IS SOMETIMES SUMMARIZED AS hITS ILLEGAL TO NEST COLUMN FUNCTIONSv )TS ALSO ILLEGAL TO MIX COLUMN FUNCTIONS AND ORDINARY COLUMN NAMES IN A SELECT LIST EXCEPT IN GROUPED QUERIES AND SUBQUERIES AS DESCRIBED IN THE h'ROUPED 1UERIESv SECTION LATER IN THIS CHAPTER AGAIN BECAUSE THE RESULTING QUERY DOESNT MAKE SENSE &OR EXAMPLE CONSIDER THIS QUERY 3%,%#4 .!-% 35-3!,%3 &2/- 3!,%32%03
.5,,õ6ALUESõANDõ#OLUMNõ&UNCTIONS 4HE 35- !6' -). -!8 AND #/5.4 COLUMN FUNCTIONS EACH TAKE A COLUMN OF DATA VALUES AS THEIR ARGUMENT AND PRODUCE A SINGLE DATA VALUE AS A RESULT 7HAT HAPPENS IF ONE OR MORE OF THE DATA VALUES IN THE COLUMN IS A .5,, VALUE 4HE !.3))3/ 31, STANDARD SPECIFIES THAT .5,, VALUES IN THE COLUMN ARE IGNORED BY THE COLUMN FUNCTIONS 4HIS QUERY SHOWS HOW THE #/5.4 COLUMN FUNCTION IGNORES ANY .5,, VALUES IN A COLUMN 3%,%#4 #/5.4 #/5.43!,%3 #/5.415/4! &2/- 3!,%32%03 #/5.4 #/5.43!,%3 #/5.415/4!
4HE 3!,%32%03 TABLE CONTAINS TEN ROWS SO #/5.4 RETURNS A COUNT OF TEN 4HE 3!,%3 COLUMN CONTAINS TEN NON .5,, VALUES SO THE FUNCTION #/5.43!,%3 ALSO RETURNS A COUNT OF TEN 4HE 15/4! COLUMN IS .5,, FOR THE NEWEST SALESPERSON 4HE #/5.415/4! FUNCTION IGNORES THIS .5,, VALUE AND RETURNS A COUNT OF NINE "ECAUSE OF THESE ANOMALIES THE #/5.4 FUNCTION IS ALMOST ALWAYS USED INSTEAD OF THE #/5.4 FUNCTION UNLESS YOU SPECIFICALLY WANT TO EXCLUDE .5,, VALUES IN A PARTICULAR COLUMN FROM THE TOTAL )GNORING .5,, VALUES HAS LITTLE IMPACT ON THE -). AND -!8 COLUMN FUNCTIONS (OWEVER IT CAN CAUSE SUBTLE PROBLEMS FOR THE 35- AND !6' COLUMN FUNCTIONS AS ILLUSTRATED BY THIS QUERY 3%,%#4 35-3!,%3 35-15/4! 35-3!,%3 35-15/4! 35-3!,%3 15/4! &2/- 3!,%32%03 35-3!,%3 35-15/4! 35-3!,%3 35-15/4! 35-3!,%3 15/4!
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4HE FIRST SELECT ITEM ASKS 31, TO GENERATE A MULTIROW TABLE OF DETAILED QUERY RESULTSONE ROW FOR EACH SALESPERSON 4HE SECOND SELECT ITEM ASKS 31, TO GENERATE A ONE ROW COLUMN OF SUMMARY QUERY RESULTS CONTAINING THE TOTAL OF THE 3!,%3 COLUMN 4HE TWO 3%,%#4 ITEMS CONTRADICT EACH OTHER PRODUCING AN ERROR &OR THIS REASON EITHER ALL COLUMN REFERENCES IN THE SELECT LIST MUST APPEAR WITHIN THE ARGUMENT OF A COLUMN FUNCTION PRODUCING A SUMMARY QUERY OR THE SELECT LIST MUST NOT CONTAIN ANY COLUMN FUNCTIONS PRODUCING A DETAILED QUERY EXCEPT AS DESCRIBED IN THE h'ROUPED 1UERIESv SECTION LATER IN THIS CHAPTER
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9OU WOULD EXPECT THE TWO EXPRESSIONS 35-3!,%3 35-15/4! !.$ 35-3!,%3 15/4!
IN THE SELECT LIST TO PRODUCE IDENTICAL RESULTS BUT THE EXAMPLE SHOWS THAT THEY DO NOT 4HE SALESPERSON WITH A .5,, VALUE IN THE 15/4! COLUMN IS AGAIN THE REASON 4HE EXPRESSION 35-3!,%3
TOTALS THE SALES FOR ALL TEN SALESPEOPLE WHILE THE EXPRESSION 35-15/4!
TOTALS ONLY THE NINE NON .5,, QUOTA VALUES 4HE EXPRESSION 35-3!,%3 35-15/4!
COMPUTES THE DIFFERENCE OF THESE TWO AMOUNTS (OWEVER THE COLUMN FUNCTION 35-3!,%3 15/4!
HAS A NON .5,, ARGUMENT VALUE FOR ONLY NINE OF THE TEN SALESPEOPLE )N THE ROW WITH A .5,, QUOTA VALUE THE SUBTRACTION PRODUCES A .5,, WHICH IS IGNORED BY THE 35- FUNCTION 4HUS THE SALES FOR THE SALESPERSON WITHOUT A QUOTA WHICH ARE INCLUDED IN THE PREVIOUS CALCULATION ARE EXCLUDED FROM THIS CALCULATION 7HICH IS THE hCORRECTv ANSWER "OTH ARE 4HE FIRST EXPRESSION CALCULATES EXACTLY WHAT IT SAYS hTHE SUM OF 3!,%3 LESS THE SUM OF 15/4!v 4HE SECOND EXPRESSION ALSO CALCULATES EXACTLY WHAT IT SAYS hTHE SUM OF 3!,%3 n 15/4! v 7HEN .5,, VALUES OCCUR HOWEVER THE TWO CALCULATIONS ARE NOT QUITE THE SAME 4HE !.3))3/ 31, STANDARD SPECIFIES THESE PRECISE RULES FOR HANDLING .5,, VALUES IN COLUMN FUNCTIONS s )F ANY OF THE DATA VALUES IN A COLUMN ARE .5,, THEY ARE IGNORED FOR THE PURPOSE OF COMPUTING THE COLUMN FUNCTIONS VALUE s )F EVERY DATA ITEM IN THE COLUMN IS .5,, THEN THE 35- !6' -). AND -!8 COLUMN FUNCTIONS RETURN A .5,, VALUE THE #/5.4 FUNCTION RETURNS A VALUE OF ZERO s )F NO DATA ITEMS ARE IN THE COLUMN THAT IS THE COLUMN IS EMPTY THEN THE 35- !6' -). AND -!8 COLUMN FUNCTIONS RETURN A .5,, VALUE THE #/5.4 FUNCTION RETURNS A VALUE OF ZERO s 4HE #/5.4 COUNTS ROWS AND DOES NOT DEPEND ON THE PRESENCE OR ABSENCE OF .5,, VALUES IN A COLUMN )F THERE ARE NO ROWS IT RETURNS A VALUE OF ZERO !LTHOUGH THE STANDARD IS VERY CLEAR IN THIS AREA COMMERCIAL 31, PRODUCTS MAY PRODUCE RESULTS DIFFERENT FROM THE STANDARD ESPECIALLY IF ALL OF THE DATA VALUES IN A COLUMN ARE .5,, OR WHEN A COLUMN FUNCTION IS APPLIED TO AN EMPTY TABLE "EFORE ASSUMING IT WILL BEHAVE AS SPECIFIED BY THE STANDARD YOU SHOULD TEST YOUR PARTICULAR $"-3
#HAPTERçç
3UMMARYç1UERIESç
$UPLICATEõ2OWõ%LIMINATIONõ$)34).#4 2ECALL FROM #HAPTER THAT YOU CAN SPECIFY THE $)34).#4 KEYWORD AT THE BEGINNING OF THE SELECT LIST TO ELIMINATE DUPLICATE ROWS OF QUERY RESULTS 9OU CAN ALSO ASK 31, TO ELIMINATE DUPLICATE VALUES FROM A COLUMN BEFORE APPLYING A COLUMN FUNCTION TO IT 4O ELIMINATE DUPLICATE VALUES THE KEYWORD $)34).#4 IS INCLUDED BEFORE THE COLUMN FUNCTION ARGUMENT IMMEDIATELY AFTER THE OPENING PARENTHESIS (ERE ARE TWO QUERIES THAT ILLUSTRATE DUPLICATE ROW ELIMINATION FOR COLUMN FUNCTIONS (OW MANY DIFFERENT TITLES ARE HELD BY SALESPEOPLE
(OW MANY SALES OFFICES HAVE SALESPEOPLE WHO ARE OVER QUOTA 3%,%#4 #/5.4$)34).#4 2%0?/&&)#% &2/- 3!,%32%03 7(%2% 3!,%3 15/4! #/5.4$)34).#4 2%0?/&&)#%
4HE $)34).#4 KEYWORD CAN BE SPECIFIED ONLY ONCE IN A QUERY )F IT APPEARS IN THE ARGUMENT OF ONE COLUMN FUNCTION IT CANT APPEAR IN ANY OTHER )F IT IS SPECIFIED BEFORE THE SELECT LIST IT CANT APPEAR IN ANY COLUMN FUNCTIONS 4HE ONLY EXCEPTION IS THAT $)34).#4 MAY BE SPECIFIED A SECOND TIME INSIDE A SUBQUERY CONTAINED WITHIN THE QUERY 3UBQUERIES ARE DESCRIBED IN #HAPTER
'ROUPEDõ1UERIESõ'2/50õ"9õ#LAUSE 4HE SUMMARY QUERIES DESCRIBED THUS FAR ARE LIKE THE TOTALS AT THE BOTTOM OF A REPORT 4HEY CONDENSE ALL OF THE DETAILED DATA IN THE REPORT INTO A SINGLE SUMMARY ROW OF DATA *UST AS SUBTOTALS ARE USEFUL IN PRINTED REPORTS ITS OFTEN CONVENIENT TO SUMMARIZE QUERY RESULTS AT A hSUBTOTALv LEVEL 4HE '2/50 "9 CLAUSE OF THE 3%,%#4 STATEMENT PROVIDES THIS CAPABILITY 4HE FUNCTION OF THE '2/50 "9 CLAUSE IS MOST EASILY UNDERSTOOD BY EXAMPLE #ONSIDER THESE TWO QUERIES 7HAT IS THE AVERAGE ORDER SIZE 3%,%#4 !6'!-/5.4 &2/- /2$%23 !6'!-/5.4
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7HAT IS THE AVERAGE ORDER SIZE FOR EACH SALESPERSON 3%,%#4 2%0 !6'!-/5.4 &2/- /2$%23 '2/50 "9 2%0 2%0 !6'!-/5.4
4HE FIRST QUERY IS A SIMPLE SUMMARY QUERY LIKE THE PREVIOUS EXAMPLES IN THIS CHAPTER 4HE SECOND QUERY PRODUCES SEVERAL SUMMARY ROWSONE ROW FOR EACH GROUP SUMMARIZING THE ORDERS TAKEN BY A SINGLE SALESPERSON &IGURE SHOWS HOW THE SECOND QUERY WORKS #ONCEPTUALLY 31, CARRIES OUT THE QUERY AS FOLLOWS
31, DIVIDES THE ORDERS INTO GROUPS OF ORDERS WITH ONE GROUP FOR EACH SALESPERSON 7ITHIN EACH GROUP ALL OF THE ORDERS HAVE THE SAME VALUE IN THE 2%0 COLUMN
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#HAPTERçç
3UMMARYç1UERIESç
&OR EACH GROUP 31, COMPUTES THE AVERAGE VALUE OF THE !-/5.4 COLUMN FOR ALL OF THE ROWS IN THE GROUP AND GENERATES A SINGLE SUMMARY ROW OF QUERY RESULTS 4HE ROW CONTAINS THE VALUE OF THE 2%0 COLUMN FOR THE GROUP AND THE CALCULATED AVERAGE ORDER SIZE
! QUERY THAT INCLUDES THE '2/50 "9 CLAUSE IS CALLED A GROUPED QUERY BECAUSE IT GROUPS THE DATA FROM ITS SOURCE TABLES AND PRODUCES A SINGLE SUMMARY ROW FOR EACH ROW GROUP 4HE COLUMNS NAMED IN THE '2/50 "9 CLAUSE ARE CALLED THE GROUPING COLUMNS OF THE QUERY BECAUSE THEY DETERMINE HOW THE ROWS ARE DIVIDED INTO GROUPS (ERE ARE SOME ADDITIONAL EXAMPLES OF GROUPED QUERIES
3%,%#4 2%0?/&&)#% -).15/4! -!815/4! &2/- 3!,%32%03 '2/50 "9 2%0?/&&)#% 2%0?/&&)#% -).15/4! -!815/4!
.5,, .5,, .5,,
(OW MANY SALESPEOPLE ARE ASSIGNED TO EACH OFFICE 3%,%#4 2%0?/&&)#% #/5.4 &2/- 3!,%32%03 '2/50 "9 2%0?/&&)#% 2%0?/&&)#% #/5.4
.5,,
(OW MANY DIFFERENT CUSTOMERS ARE SERVED BY EACH SALESPERSON 3%,%#4 #/5.4$)34).#4 #534?.5- gCUSTOMERS FOR SALESREPg #534?2%0 &2/- #534/-%23 '2/50 "9 #534?2%0 #/5.4$)34).#4 #534?.5- #534/-%23 &/2 3!,%32%0 #534?2%0
CUSTOMERS FOR SALESREP CUSTOMERS FOR SALESREP CUSTOMERS FOR SALESREP CUSTOMERS FOR SALESREP
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7HAT IS THE RANGE OF ASSIGNED QUOTAS IN EACH OFFICE
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CUSTOMERS FOR SALESREP CUSTOMERS FOR SALESREP
4HERE IS AN INTIMATE LINK BETWEEN THE 31, COLUMN FUNCTIONS AND THE '2/50 "9 CLAUSE 2EMEMBER THAT THE COLUMN FUNCTIONS TAKE A COLUMN OF DATA VALUES AND PRODUCE A SINGLE RESULT 7HEN THE '2/50 "9 CLAUSE IS PRESENT IT TELLS 31, TO DIVIDE THE DETAILED QUERY RESULTS INTO GROUPS AND TO APPLY THE COLUMN FUNCTION SEPARATELY TO EACH GROUP PRODUCING A SINGLE RESULT FOR EACH GROUP 4HE FOLLOWING STEPS SHOW THE RULES FOR 31, QUERY PROCESSING EXPANDED ONCE AGAIN FOR GROUPED QUERIES 4O GENERATE THE QUERY RESULTS FOR A 3%,%#4 STATEMENT
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS APPLY 3TEPS THROUGH TO EACH OF THE STATEMENTS TO GENERATE THEIR INDIVIDUAL QUERY RESULTS
&ORM THE PRODUCT OF THE TABLES NAMED IN THE &2/- CLAUSE )F THE &2/- CLAUSE NAMES A SINGLE TABLE THE PRODUCT IS THAT TABLE
)F THERE IS A 7(%2% CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW OF THE PRODUCT TABLE RETAINING THOSE ROWS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
)F THERE IS A '2/50 "9 CLAUSE ARRANGE THE REMAINING ROWS OF THE PRODUCT TABLE INTO ROW GROUPS SO THAT THE ROWS IN EACH GROUP HAVE IDENTICAL VALUES IN ALL OF THE GROUPING COLUMNS
)F THERE IS A (!6).' CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW GROUP RETAINING THOSE GROUPS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
&OR EACH REMAINING ROW OR ROW GROUP CALCULATE THE VALUE OF EACH ITEM IN THE SELECT LIST TO PRODUCE A SINGLE ROW OF QUERY RESULTS &OR A SIMPLE COLUMN REFERENCE USE THE VALUE OF THE COLUMN IN THE CURRENT ROW OR ROW GROUP &OR A COLUMN FUNCTION USE THE CURRENT ROW GROUP AS ITS ARGUMENT IF '2/50 "9 IS SPECIFIED OTHERWISE USE THE ENTIRE SET OF ROWS
)F 3%,%#4 $)34).#4 IS SPECIFIED ELIMINATE ANY DUPLICATE ROWS OF QUERY RESULTS THAT WERE PRODUCED
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS MERGE THE QUERY RESULTS FOR THE INDIVIDUAL STATEMENTS INTO A SINGLE TABLE OF QUERY RESULTS %LIMINATE DUPLICATE ROWS UNLESS 5.)/. !,, IS SPECIFIED
)F THERE IS AN /2$%2 "9 CLAUSE SORT THE QUERY RESULTS AS SPECIFIED 4HE ROWS GENERATED BY THIS PROCEDURE COMPRISE THE QUERY RESULTS
-ULTIPLEõ'ROUPINGõ#OLUMNS 31, CAN GROUP QUERY RESULTS BASED ON THE CONTENTS OF TWO OR MORE COLUMNS &OR EXAMPLE SUPPOSE YOU WANT TO GROUP THE ORDERS BY SALESPERSON AND BY CUSTOMER 4HIS QUERY GROUPS THE DATA BASED ON BOTH CRITERIA
#HAPTERçç
3UMMARYç1UERIESç
#ALCULATE THE TOTAL ORDERS FOR EACH CUSTOMER OF EACH SALESPERSON
%VEN WITH MULTIPLE GROUPING COLUMNS OLDER 31, VERSIONS PROVIDE ONLY A SINGLE LEVEL OF GROUPING 4HE QUERY PRODUCES A SEPARATE SUMMARY ROW FOR EACH SALESPERSONCUSTOMER PAIR 4O PRODUCE MORE THAN ONE LEVEL OF SUBTOTALS IN MORE MODERN 31, YOU CAN USE THE 7)4( 2/,,50 AND 7)4( #5"% OPERATORS IN COMBINATION WITH THE '2/50 "9 OPERATOR 7)4( 2/,,50 CAUSES THE '2/50 "9 OPERATION TO DISPLAY A SUBTOTAL FOR EACH LEVEL OF GROUPING WORKING LEFT TO RIGHT ACROSS THE LIST OF GROUPING COLUMNS 7)4( #5"% GOES FURTHER BY SHOWING SUBTOTALS FOR EVERY POSSIBLE COMBINATION OF GROUPING COLUMNS 7)4( #5"% AND 7)4( 2/,,50 ALSO PROVIDE A GRAND TOTAL IN THE RESULT SET BUT THE GRAND TOTAL MIGHT NOT ALWAYS APPEAR AT THE END OF THE RESULT SET /RACLES #5"% OPTION FOR EXAMPLE DISPLAYS THE GRAND TOTAL FIRST 9OU CAN SPOT THE SUBTOTAL ROWS BECAUSE GROUPING COLUMNS THAT DONT APPLY ARE .5,, 3IMILARLY THE GRAND TOTAL LINE WILL HAVE .5,, VALUES IN ALL OF THE GROUPING COLUMNS #ALCULATE THE TOTAL ORDERS FOR EACH CUSTOMER OF EACH SALESPERSON WITH SUBTOTALS FOR EACH SALESPERSON 3%,%#4 2%0 #534 35-!-/5.4 &2/- /2$%23 '2/50 "9 2%0 #534 7)4( 2/,,50 2%0 #534 35-!-/5.4
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3%,%#4 2%0 #534 35-!-/5.4 &2/- /2$%23 '2/50 "9 2%0 #534 2%0 #534 35-!-/5.4
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#ALCULATE THE TOTAL ORDERS FOR EACH CUSTOMER OF EACH SALESPERSON WITH SUBTOTALS FOR EACH SALESPERSON AND EACH CUSTOMER 3%,%#4 2%0 #534 35-!-/5.4 &2/- /2$%23 '2/50 "9 2%0 #534 7)4( #5"% 2%0 #534 35-!-/5.4
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3UMMARYç1UERIESç
#ALCULATE THE TOTAL ORDERS FOR EACH CUSTOMER OF EACH SALESPERSON SORTED BY CUSTOMER AND WITHIN EACH CUSTOMER BY SALESPERSON 3%,%#4 #534 2%0 35-!-/5.4 &2/- /2$%23 '2/50 "9 #534 2%0 /2$%2 "9 #534 2%0 #534 2%0 35-!-/5.4
2ESTRICTIONSõONõ'ROUPEDõ1UERIES 'ROUPED QUERIES ARE SUBJECT TO SOME RATHER STRICT LIMITATIONS 4HE GROUPING COLUMNS MUST BE ACTUAL COLUMNS OF THE TABLES NAMED IN THE &2/- CLAUSE OF THE QUERY (OWEVER SOME IMPLEMENTATIONS ALSO PERMIT COLUMN EXPRESSIONS AND EVEN ALLOW YOU TO GROUP ON EXPRESSIONS BY SIMPLY REPEATING THE COLUMN EXPRESSION IN THE '2/50 "9 CLAUSE 4HERE ARE ALSO RESTRICTIONS ON THE ITEMS THAT CAN APPEAR IN THE SELECT LIST OF A GROUPED QUERY !LL OF THE ITEMS IN THE SELECT LIST MUST HAVE A SINGLE VALUE FOR EACH GROUP OF ROWS "ASICALLY THIS MEANS THAT A SELECT ITEM IN A GROUPED QUERY CAN BE s ! COLUMN PROVIDED IT IS ONE OF THE GROUPING COLUMNS s ! CONSTANT s ! COLUMN FUNCTION WHICH PRODUCES A SINGLE VALUE SUMMARIZING THE ROWS IN THE GROUP
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4HE SYNTAX FOR 7)4( 2/,,50 AND 7)4( #5"% VARIES SOMEWHAT FROM ONE 31, PRODUCT TO ANOTHER SO CHECK YOUR VENDORS DOCUMENTATION 4HE 31, STANDARD SYNTAX WHICH IS SUPPORTED BY 31, 3ERVER $" 5NIVERSAL $ATABASE 5$" AND -Y31, IS SHOWN IN THE PRECEDING EXAMPLES (OWEVER AS OF VERSION -Y31, DOES NOT YET SUPPORT 7)4( #5"% /RACLE REQUIRES THE KEYWORDS '2/50 "9 2/,,50 OR '2/50 "9 #5"% FOLLOWED BY THE GROUPING COLUMN LIST WHICH MUST BE ENCLOSED IN PARENTHESES SUCH AS '2/50 "9 #5"% 2%0 #534 $" 5$" SUPPORTS BOTH THE STANDARD SYNTAX AND THE VARIATION REQUIRED BY /RACLE )F YOUR 31, IMPLEMENTATION DOES NOT SUPPORT 2/,,50 OR #5"% THE BEST YOU CAN DO IS SORT THE DATA SO THAT THE ROWS OF QUERY RESULTS APPEAR IN THE APPROPRIATE ORDER )N MANY 31, IMPLEMENTATIONS THE '2/50 "9 CLAUSE WILL AUTOMATICALLY HAVE THE SIDE EFFECT OF SORTING THE DATA BUT YOU CAN OVERRIDE THIS SORT WITH AN /2$%2 "9 CLAUSE AS SHOWN NEXT
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s ! GROUPING COLUMN WHICH BY DEFINITION HAS THE SAME VALUE IN EVERY ROW OF THE GROUP s !N EXPRESSION INVOLVING COMBINATIONS OF THESE )N PRACTICE A GROUPED QUERY WILL ALWAYS INCLUDE BOTH A GROUPING COLUMN AND A COLUMN FUNCTION IN ITS SELECT LIST )F NO COLUMN FUNCTION APPEARS THE QUERY CAN BE EXPRESSED MORE SIMPLY USING 3%,%#4 $)34).#4 WITHOUT '2/50 "9 #ONVERSELY IF YOU DONT INCLUDE A GROUPING COLUMN IN THE QUERY RESULTS YOU WONT BE ABLE TO TELL WHICH ROW OF QUERY RESULTS CAME FROM WHICH GROUP !NOTHER LIMITATION OF GROUPED QUERIES IS THAT 31, IGNORES INFORMATION ABOUT PRIMARY KEYS AND FOREIGN KEYS WHEN ANALYZING THE VALIDITY OF A GROUPED QUERY #ONSIDER THIS QUERY WHICH PRODUCES AN ERROR #ALCULATE THE TOTAL ORDERS FOR EACH SALESPERSON 3%,%#4 %-0,?.5- .!-% 35-!-/5.4 &2/- /2$%23 3!,%32%03 7(%2% 2%0 %-0,?.5- '2/50 "9 %-0,?.5- %RROR .!-% NOT A '2/50 "9 EXPRESSION
'IVEN THE NATURE OF THE DATA THE QUERY MAKES PERFECTLY GOOD SENSE BECAUSE GROUPING ON THE SALESPERSONS EMPLOYEE NUMBER IS IN EFFECT THE SAME AS GROUPING ON THE SALESPERSONS NAME -ORE PRECISELY %-0,?.5- THE GROUPING COLUMN IS THE PRIMARY KEY OF THE 3!,%32%03 TABLE SO THE .!-% COLUMN MUST BE SINGLE VALUED FOR EACH GROUP .ONETHELESS 31, REPORTS AN ERROR BECAUSE THE .!-% COLUMN IS NOT EXPLICITLY SPECIFIED AS A GROUPING COLUMN 4HE EXACT ERROR MESSAGE WILL VARY FROM ONE $"-3 PRODUCT TO ANOTHER 4O CORRECT THE PROBLEM YOU CAN SIMPLY INCLUDE THE .!-% COLUMN AS A SECOND REDUNDANT GROUPING COLUMN #ALCULATE THE TOTAL ORDERS FOR EACH SALESPERSON 3%,%#4 %-0,?.5- .!-% 35-!-/5.4 &2/- /2$%23 3!,%32%03 7(%2% 2%0 %-0,?.5- '2/50 "9 %-0,?.5- .!-% %-0,?.5- .!-% 35-!-/5.4
$AN 2OBERTS 3UE 3MITH 0AUL #RUZ "ILL !DAMS 3AM #LARK .ANCY !NGELLI ,ARRY &ITCH -ARY *ONES 4OM 3NYDER
/F COURSE IF THE SALESPERSONS EMPLOYEE NUMBER IS NOT NEEDED IN THE QUERY RESULTS YOU CAN ELIMINATE IT ENTIRELY FROM THE SELECT LIST
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3UMMARYç1UERIESç
#ALCULATE THE TOTAL ORDERS FOR EACH SALESPERSON
.5,,õ6ALUESõINõ'ROUPINGõ#OLUMNS ! .5,, VALUE POSES A SPECIAL PROBLEM WHEN IT OCCURS IN A GROUPING COLUMN )F THE VALUE OF THE COLUMN IS UNKNOWN INTO WHICH GROUP SHOULD THE ROW BE PLACED )N THE 7(%2% CLAUSE WHEN TWO DIFFERENT .5,, VALUES ARE COMPARED THE RESULT IS .5,, NOT 425% THAT IS THE TWO .5,, VALUES ARE NOT CONSIDERED TO BE EQUAL !PPLYING THE SAME CONVENTION TO THE '2/50 "9 CLAUSE WOULD FORCE 31, TO PLACE EACH ROW WITH A .5,, GROUPING COLUMN INTO A SEPARATE GROUP BY ITSELF )N PRACTICE THIS RULE PROVES TOO UNWIELDY )NSTEAD THE !.3))3/ 31, STANDARD CONSIDERS TWO .5,, VALUES TO BE EQUAL FOR PURPOSES OF THE '2/50 "9 CLAUSE )F TWO ROWS HAVE .5,,S IN THE SAME GROUPING COLUMNS AND IDENTICAL VALUES IN ALL OF THEIR NON .5,, GROUPING COLUMNS THEY ARE GROUPED TOGETHER INTO THE SAME ROW GROUP 4HE SMALL SAMPLE TABLE IN &IGURE ILLUSTRATES THE !.3))3/ HANDLING OF .5,, VALUES BY THE '2/50 "9 CLAUSE AS SHOWN IN THIS QUERY 3%,%#4 (!)2 %9%3 #/5.4 &2/- 0%/0,% '2/50 "9 (!)2 %9%3 (!)2 %9%3 #/5.4
"ROWN "LUE .5,, "LUE .5,, .5,, "ROWN .5,, "ROWN "ROWN "ROWN "ROWN
!LTHOUGH THIS BEHAVIOR OF .5,,S IN GROUPING COLUMNS IS CLEARLY SPECIFIED IN THE !.3) )3/ STANDARD IT IS NOT IMPLEMENTED IN ALL 31, DIALECTS )TS A GOOD IDEA TO BUILD A SMALL TEST TABLE AND CHECK THE BEHAVIOR OF YOUR $"-3 BRAND BEFORE COUNTING ON A SPECIFIC BEHAVIOR
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'ROUPõ3EARCHõ#ONDITIONSõ(!6).'õ#LAUSE *UST AS THE 7(%2% CLAUSE CAN BE USED TO SELECT AND REJECT THE INDIVIDUAL ROWS THAT PARTICIPATE IN A QUERY THE (!6).' CLAUSE CAN BE USED TO SELECT AND REJECT ROW GROUPS 4HE FORMAT OF THE (!6).' CLAUSE PARALLELS THAT OF THE 7(%2% CLAUSE CONSISTING OF THE KEYWORD (!6).' FOLLOWED BY A SEARCH CONDITION 4HE (!6).' CLAUSE THUS SPECIFIES A SEARCH CONDITION FOR GROUPS !N EXAMPLE PROVIDES THE BEST WAY TO UNDERSTAND THE ROLE OF THE (!6).' CLAUSE #ONSIDER THIS QUERY 7HAT IS THE AVERAGE ORDER SIZE FOR EACH SALESPERSON WHOSE ORDERS TOTAL MORE THAN 3%,%#4 2%0 !6'!-/5.4 &2/- /2$%23 '2/50 "9 2%0 (!6).' 35-!-/5.4 2%0 !6'!-/5.4
&IGURE SHOWS GRAPHICALLY HOW 31, CARRIES OUT THE QUERY 4HE '2/50 "9 CLAUSE FIRST ARRANGES THE ORDERS INTO GROUPS BY SALESPERSON 4HE (!6).' CLAUSE THEN ELIMINATES ANY GROUP WHERE THE TOTAL OF THE ORDERS IN THE GROUP DOES NOT EXCEED &INALLY THE 3%,%#4 CLAUSE CALCULATES THE AVERAGE ORDER SIZE FOR EACH OF THE REMAINING GROUPS AND GENERATES THE QUERY RESULTS 4HE SEARCH CONDITIONS YOU CAN SPECIFY IN THE (!6).' CLAUSE ARE THE SAME ONES USED IN THE 7(%2% CLAUSE AS DESCRIBED IN #HAPTERS AND (ERE IS ANOTHER EXAMPLE OF THE USE OF A GROUP SEARCH CONDITION
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&OR EACH OFFICE WITH TWO OR MORE PEOPLE COMPUTE THE TOTAL QUOTA AND TOTAL SALES FOR ALL SALESPEOPLE WHO WORK IN THE OFFICE 3%,%#4 #)49 35-15/4! 35-3!,%32%033!,%3 &2/- /&&)#%3 3!,%32%03 7(%2% /&&)#% 2%0?/&&)#% '2/50 "9 #)49 (!6).' #/5.4 #)49 35-15/4! 35-3!,%32%033!,%3
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4HE FOLLOWING STEPS SHOW THE RULES FOR 31, QUERY PROCESSING EXPANDED ONCE AGAIN TO INCLUDE GROUP SEARCH CONDITIONS 4O GENERATE THE QUERY RESULTS FOR A 3%,%#4 STATEMENT
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS APPLY 3TEPS THROUGH TO EACH OF THE STATEMENTS TO GENERATE THEIR INDIVIDUAL QUERY RESULTS
&ORM THE PRODUCT OF THE TABLES NAMED IN THE &2/- CLAUSE )F THE &2/- CLAUSE NAMES A SINGLE TABLE THE PRODUCT IS THAT TABLE
)F THERE IS A 7(%2% CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW OF THE PRODUCT TABLE RETAINING THOSE ROWS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
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)F THERE IS A '2/50 "9 CLAUSE ARRANGE THE REMAINING ROWS OF THE PRODUCT TABLE INTO ROW GROUPS SO THAT THE ROWS IN EACH GROUP HAVE IDENTICAL VALUES IN ALL OF THE GROUPING COLUMNS
)F THERE IS A (!6).' CLAUSE APPLY ITS SEARCH CONDITION TO EACH ROW GROUP RETAINING THOSE GROUPS FOR WHICH THE SEARCH CONDITION IS 425% AND DISCARDING THOSE FOR WHICH IT IS &!,3% OR .5,,
&OR EACH REMAINING ROW OR ROW GROUP CALCULATE THE VALUE OF EACH ITEM IN THE SELECT LIST TO PRODUCE A SINGLE ROW OF QUERY RESULTS &OR A SIMPLE COLUMN REFERENCE USE THE VALUE OF THE COLUMN IN THE CURRENT ROW OR ROW GROUP &OR A COLUMN FUNCTION USE THE CURRENT ROW GROUP AS ITS ARGUMENT IF '2/50 "9 IS SPECIFIED OTHERWISE USE THE ENTIRE SET OF ROWS
)F 3%,%#4 $)34).#4 IS SPECIFIED ELIMINATE ANY DUPLICATE ROWS OF QUERY RESULTS THAT WERE PRODUCED
)F THE STATEMENT IS A 5.)/. OF 3%,%#4 STATEMENTS MERGE THE QUERY RESULTS FOR THE INDIVIDUAL STATEMENTS INTO A SINGLE TABLE OF QUERY RESULTS %LIMINATE DUPLICATE ROWS UNLESS 5.)/. !,, IS SPECIFIED
)F THERE IS AN /2$%2 "9 CLAUSE SORT THE QUERY RESULTS AS SPECIFIED
4HE ROWS GENERATED BY THIS PROCEDURE COMPRISE THE QUERY RESULTS &OLLOWING THIS PROCEDURE 31, HANDLES THE QUERY IN THE PREVIOUS EXAMPLE AS FOLLOWS
*OINS THE /&&)#%3 AND 3!,%32%03 TABLES TO FIND THE CITY WHERE EACH SALESPERSON WORKS
'ROUPS THE RESULTING ROWS BY OFFICE
%LIMINATES GROUPS WITH TWO OR FEWER ROWSTHESE REPRESENT OFFICES THAT DONT MEET THE (!6).' CLAUSE CRITERION
#ALCULATES THE TOTAL QUOTA AND TOTAL SALES FOR EACH GROUP (ERE IS ONE MORE EXAMPLE WHICH USES ALL OF THE 3%,%#4 STATEMENT CLAUSES
3HOW THE PRICE QUANTITY ON HAND AND TOTAL QUANTITY ON ORDER FOR EACH PRODUCT WHERE THE TOTAL QUANTITY ON ORDER IS MORE THAN PERCENT OF THE QUANTITY ON HAND 3%,%#4 $%3#2)04)/. 02)#% 149?/.?(!.$ 35-149 &2/- 02/$5#43 /2$%23 7(%2% -&2 -&2?)$ !.$ 02/$5#4 02/$5#4?)$ '2/50 "9 -&2?)$ 02/$5#4?)$ $%3#2)04)/. 02)#% 149?/.?(!.$ (!6).' 35-149 149?/.?(!.$ /2$%2 "9 149?/.?(!.$ $%3# $%3#2)04)/. 02)#% 149?/.?(!.$ 35-149
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3UMMARYç1UERIESç
4O PROCESS THIS QUERY 31, CONCEPTUALLY PERFORMS THE FOLLOWING STEPS *OINS THE /2$%23 AND 02/$5#43 TABLES TO FIND THE DESCRIPTION PRICE AND QUANTITY ON HAND FOR EACH PRODUCT ORDERED
'ROUPS THE RESULTING ROWS BY MANUFACTURER AND PRODUCT )$
%LIMINATES GROUPS WHERE THE QUANTITY ORDERED THE TOTAL OF THE 149 COLUMN FOR ALL ORDERS IN THE GROUP IS LESS THAN PERCENT OF THE QUANTITY ON HAND
#ALCULATES THE TOTAL QUANTITY ORDERED FOR EACH GROUP
'ENERATES ONE SUMMARY ROW OF QUERY RESULTS FOR EACH GROUP
3ORTS THE QUERY RESULTS SO THAT PRODUCTS WITH THE LARGEST QUANTITY ON HAND APPEAR FIRST
!S DESCRIBED PREVIOUSLY $%3#2)04)/. 02)#% AND 149?/.?(!.$ MUST BE SPECIFIED AS GROUPING COLUMNS IN THIS QUERY SOLELY BECAUSE THEY APPEAR IN THE SELECT LIST 4HEY ACTUALLY CONTRIBUTE NOTHING TO THE GROUPING PROCESS BECAUSE THE -&2?)$ AND 02/$5#4?)$ COMPLETELY SPECIFY A SINGLE ROW OF THE 02/$5#43 TABLE AUTOMATICALLY MAKING THE OTHER THREE COLUMNS SINGLE VALUED PER GROUP
2ESTRICTIONSõONõ'ROUPõ3EARCHõ#ONDITIONS 4HE (!6).' CLAUSE IS USED TO INCLUDE OR EXCLUDE ROW GROUPS FROM THE QUERY RESULTS SO THE SEARCH CONDITION IT SPECIFIES MUST BE ONE THAT APPLIES TO THE GROUP AS A WHOLE RATHER THAN TO INDIVIDUAL ROWS 4HIS MEANS THAT AN ITEM APPEARING WITHIN THE SEARCH CONDITION IN A (!6).' CLAUSE CAN BE s ! CONSTANT s ! COLUMN FUNCTION WHICH PRODUCES A SINGLE VALUE SUMMARIZING THE ROWS IN THE GROUP s ! GROUPING COLUMN WHICH BY DEFINITION HAS THE SAME VALUE IN EVERY ROW OF THE GROUP s !N EXPRESSION INVOLVING COMBINATIONS OF THESE )N PRACTICE THE SEARCH CONDITION IN THE (!6).' CLAUSE WILL ALWAYS INCLUDE AT LEAST ONE COLUMN FUNCTION )F IT DID NOT THE SEARCH CONDITION COULD BE MOVED TO THE 7(%2% CLAUSE AND APPLIED TO INDIVIDUAL ROWS 4HE EASIEST WAY TO FIGURE OUT WHETHER A SEARCH CONDITION BELONGS IN THE 7(%2% CLAUSE OR IN THE (!6).' CLAUSE IS TO REMEMBER HOW THE TWO CLAUSES ARE APPLIED s 4HE 7(%2% CLAUSE IS APPLIED TO INDIVIDUAL ROWS SO THE EXPRESSIONS IT CONTAINS MUST BE COMPUTABLE FOR INDIVIDUAL ROWS s 4HE (!6).' CLAUSE IS APPLIED TO ROW GROUPS SO THE EXPRESSIONS IT CONTAINS MUST BE COMPUTABLE FOR A GROUP OF ROWS
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.5,,õ6ALUESõANDõ'ROUPõ3EARCHõ#ONDITIONS ,IKE THE SEARCH CONDITION IN THE 7(%2% CLAUSE THE (!6).' CLAUSE SEARCH CONDITION CAN PRODUCE ONE OF THREE RESULTS s )F THE SEARCH CONDITION IS 425% THE ROW GROUP IS RETAINED AND IT CONTRIBUTES A SUMMARY ROW TO THE QUERY RESULTS s )F THE SEARCH CONDITION IS &!,3% THE ROW GROUP IS DISCARDED AND IT DOES NOT CONTRIBUTE A SUMMARY ROW TO THE QUERY RESULTS s )F THE SEARCH CONDITION IS .5,, THE ROW GROUP IS DISCARDED AND IT DOES NOT CONTRIBUTE A SUMMARY ROW TO THE QUERY RESULTS 4HE ANOMALIES THAT CAN OCCUR WITH .5,, VALUES IN THE SEARCH CONDITION ARE THE SAME AS THOSE FOR THE 7(%2% CLAUSE AND HAVE BEEN DESCRIBED IN #HAPTER
(!6).'õ7ITHOUTõ'2/50õ"9 4HE (!6).' CLAUSE IS ALMOST ALWAYS USED IN CONJUNCTION WITH THE '2/50 "9 CLAUSE BUT THE SYNTAX OF THE 3%,%#4 STATEMENT DOES NOT REQUIRE IT )F A (!6).' CLAUSE APPEARS WITHOUT A '2/50 "9 CLAUSE 31, CONSIDERS THE ENTIRE SET OF DETAILED QUERY RESULTS TO BE A SINGLE GROUP )N OTHER WORDS THE COLUMN FUNCTIONS IN THE (!6).' CLAUSE ARE APPLIED TO ONE AND ONLY ONE GROUP TO DETERMINE WHETHER THE GROUP IS INCLUDED OR EXCLUDED FROM THE QUERY RESULTS AND THAT GROUP CONSISTS OF ALL THE ROWS 4HE USE OF A (!6).' CLAUSE WITHOUT A CORRESPONDING '2/50 "9 CLAUSE IS SELDOM SEEN IN PRACTICE
3UMMARY 4HIS CHAPTER DESCRIBED SUMMARY QUERIES WHICH SUMMARIZE DATA FROM THE DATABASE s 3UMMARY QUERIES USE 31, COLUMN FUNCTIONS TO COLLAPSE A COLUMN OF DATA VALUES INTO A SINGLE VALUE THAT SUMMARIZES THE COLUMN s #OLUMN FUNCTIONS CAN COMPUTE THE AVERAGE SUM MINIMUM AND MAXIMUM VALUES OF A COLUMN COUNT THE NUMBER OF DATA VALUES IN A COLUMN OR COUNT THE NUMBER OF ROWS OF QUERY RESULTS s ! SUMMARY QUERY WITHOUT A '2/50 "9 CLAUSE GENERATES A SINGLE ROW OF QUERY RESULTS SUMMARIZING ALL THE ROWS OF A TABLE OR A JOINED SET OF TABLES s ! SUMMARY QUERY WITH A '2/50 "9 CLAUSE GENERATES MULTIPLE ROWS OF QUERY RESULTS EACH SUMMARIZING THE ROWS IN A PARTICULAR GROUP s 4HE (!6).' CLAUSE ACTS AS A 7(%2% CLAUSE FOR GROUPS SELECTING THE ROW GROUPS THAT CONTRIBUTE TO THE SUMMARY QUERY RESULTS
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HE 31, SUBQUERY FEATURE LETS YOU USE THE RESULTS OF ONE QUERY AS PART OF ANOTHER QUERY 4HE ABILITY TO USE A QUERY WITHIN A QUERY WAS THE ORIGINAL REASON FOR THE WORD hSTRUCTUREDv IN THE NAME 3TRUCTURED 1UERY ,ANGUAGE 4HE SUBQUERY FEATURE IS LESS WELL KNOWN THAN 31,S JOIN FEATURE BUT IT PLAYS AN IMPORTANT ROLE IN 31, FOR THREE REASONS s ! 31, STATEMENT WITH A SUBQUERY IS OFTEN THE MOST NATURAL WAY TO EXPRESS A QUERY BECAUSE IT MOST CLOSELY PARALLELS THE %NGLISH LANGUAGE DESCRIPTION OF THE QUERY s 3UBQUERIES MAKE IT EASIER TO WRITE 3%,%#4 STATEMENTS BECAUSE THEY LET YOU BREAK A QUERY DOWN INTO PIECES THE QUERY AND ITS SUBQUERIES AND THEN PUT THE PIECES BACK TOGETHER s 3OME QUERIES CANNOT BE EXPRESSED IN 31, WITHOUT USING A SUBQUERY 4HE FIRST SEVERAL SECTIONS OF THIS CHAPTER DESCRIBE SUBQUERIES AND SHOW HOW THEY ARE USED IN THE 7(%2% AND (!6).' CLAUSES OF A 31, STATEMENT 4HE LATER SECTIONS OF THIS CHAPTER DESCRIBE THE ADVANCED QUERY EXPRESSION CAPABILITIES THAT HAVE BEEN ADDED TO THE 31, STANDARD WHICH SUBSTANTIALLY EXPANDS THE POWER OF 31, TO PERFORM EVEN THE MOST COMPLEX OF DATABASE OPERATIONS
5SINGõ3UBQUERIES ! SUBQUERY IS A QUERY WITHIN A QUERY 4HE RESULTS OF THE SUBQUERY ARE USED BY THE $"-3 TO DETERMINE THE RESULTS OF THE HIGHER LEVEL QUERY THAT CONTAINS THE SUBQUERY )N THE SIMPLEST FORMS OF A SUBQUERY THE SUBQUERY APPEARS WITHIN THE 7(%2% OR (!6).' CLAUSE OF ANOTHER 31, STATEMENT 3UBQUERIES PROVIDE AN EFFICIENT NATURAL WAY TO HANDLE QUERY REQUESTS THAT ARE THEMSELVES EXPRESSED IN TERMS OF THE RESULTS OF OTHER QUERIES (ERE IS AN EXAMPLE OF SUCH A REQUEST ,IST THE OFlCES WHERE THE SALES TARGET FOR THE OFlCE EXCEEDS THE SUM OF THE SALESPEOPLES QUOTAS
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4HE REQUEST ASKS FOR A LIST OF OFFICES FROM THE /&&)#%3 TABLE WHERE THE VALUE OF THE 4!2'%4 COLUMN MEETS SOME CONDITION )T SEEMS REASONABLE THAT THE 3%,%#4 STATEMENT THAT EXPRESSES THE QUERY SHOULD LOOK SOMETHING LIKE THIS 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 4!2'%4
4HE VALUE h v NEEDS TO BE FILLED IN AND SHOULD BE EQUAL TO THE SUM OF THE QUOTAS OF THE SALESPEOPLE ASSIGNED TO THE OFFICE IN QUESTION (OW CAN YOU SPECIFY THAT VALUE IN THE QUERY &ROM #HAPTER YOU KNOW THAT THE SUM OF THE QUOTAS FOR A SPECIFIC OFFICE SAY OFFICE NUMBER CAN BE OBTAINED WITH THIS QUERY 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#%
"UT IT WOULD BE INEFFICIENT TO HAVE TO TYPE IN THIS QUERY WRITE DOWN THE RESULTS AND THEN TYPE IN THE PREVIOUS QUERY WITH THE CORRECT AMOUNT (OW CAN YOU PUT THE RESULTS OF THIS QUERY INTO THE EARLIER QUERY IN PLACE OF THE QUESTION MARKS )T WOULD SEEM REASONABLE TO START WITH THE FIRST QUERY AND REPLACE THE h v WITH THE SECOND QUERY AS FOLLOWS 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 4!2'%4 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#%
)N FACT THIS IS A CORRECTLY FORMED 31, QUERY &OR EACH OFFICE THE INNER QUERY THE SUBQUERY CALCULATES THE SUM OF THE QUOTAS FOR THE SALESPEOPLE WORKING IN THAT OFFICE 4HE OUTER QUERY THE MAIN QUERY COMPARES THE OFFICES TARGET WITH THE CALCULATED TOTAL AND DECIDES WHETHER TO ADD THE OFFICE TO THE MAIN QUERY RESULTS 7ORKING TOGETHER THE MAIN QUERY AND THE SUBQUERY EXPRESS THE ORIGINAL REQUEST AND RETRIEVE THE REQUESTED DATA FROM THE DATABASE 31, SUBQUERIES TYPICALLY APPEAR AS PART OF THE 7(%2% CLAUSE OR THE (!6).' CLAUSE )N THE 7(%2% CLAUSE THEY HELP TO SELECT THE INDIVIDUAL ROWS THAT APPEAR IN THE QUERY RESULTS )N THE (!6).' CLAUSE THEY HELP TO SELECT THE ROW GROUPS THAT APPEAR IN THE QUERY RESULTS
7HATõ)SõAõ3UBQUERY &IGURE SHOWS THE FORM OF A 31, SUBQUERY 4HE SUBQUERY IS ENCLOSED IN PARENTHESES BUT OTHERWISE IT HAS THE FAMILIAR FORM OF A 3%,%#4 STATEMENT WITH A &2/- CLAUSE AND OPTIONAL 7(%2% '2/50 "9 (!6).' AND /2$%2 "9 CLAUSES 4HE FORM OF THESE CLAUSES IN A SUBQUERY IS IDENTICAL TO THAT IN A 3%,%#4 STATEMENT AND THEY PERFORM THEIR NORMAL FUNCTIONS WHEN USED WITHIN A SUBQUERY 4HERE ARE HOWEVER A FEW DIFFERENCES BETWEEN A SUBQUERY AND AN ACTUAL 3%,%#4 STATEMENT s )N THE MOST COMMON USES A SUBQUERY MUST PRODUCE A SINGLE COLUMN OF DATA AS ITS QUERY RESULTS 4HIS MEANS THAT A SUBQUERY ALMOST ALWAYS HAS A SINGLE SELECT ITEM IN ITS 3%,%#4 CLAUSE s 7HILE THE /2$%2 "9 CLAUSE CAN BE SPECIFIED IN A SUBQUERY IT IS RARELY USED THERE 4HE SUBQUERY RESULTS ARE USED INTERNALLY BY THE MAIN QUERY AND ARE NEVER VISIBLE
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TO THE USER SO IT MAKES LITTLE SENSE TO SORT THEM -OREOVER SORTING LARGE NUMBERS OF ROWS CAN ADVERSELY AFFECT PERFORMANCE s #OLUMN NAMES APPEARING IN A SUBQUERY MAY REFER TO COLUMNS OF TABLES IN THE MAIN QUERY 4HESE OUTER REFERENCES ARE DESCRIBED IN DETAIL LATER IN THE h/UTER 2EFERENCESv SECTION s )N MOST IMPLEMENTATIONS A SUBQUERY CANNOT BE THE 5.)/. OF SEVERAL DIFFERENT 3%,%#4 STATEMENTS ONLY A SINGLE 3%,%#4 IS ALLOWED 4HE 31, STANDARD ALLOWS MUCH MORE POWERFUL QUERY EXPRESSIONS AND RELAXES THIS RESTRICTION AS DESCRIBED LATER IN THE SECTION h!DVANCED 1UERIESv
3UBQUERIESõINõTHEõ7(%2%õ#LAUSE 3UBQUERIES ARE MOST FREQUENTLY USED IN THE 7(%2% CLAUSE OF A 31, STATEMENT 7HEN A SUBQUERY APPEARS IN THE 7(%2% CLAUSE IT WORKS AS PART OF THE ROW SELECTION PROCESS 4HE VERY SIMPLEST SUBQUERIES APPEAR WITHIN A SEARCH CONDITION AND PRODUCE A VALUE THAT IS USED TO TEST THE SEARCH CONDITION 4HE FOLLOWING IS AN EXAMPLE OF A SIMPLE SUBQUERY
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,IST THE SALESPEOPLE WHOSE QUOTA IS LESS THAN PERCENT OF THE COMPANYWIDE SALES TARGET 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 15/4! 3%,%#4 35-4!2'%4 &2/- /&&)#%3 .!-%
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)N THIS CASE THE SUBQUERY CALCULATES THE SUM OF THE SALES TARGETS FOR ALL OF THE OFFICES TO DETERMINE THE COMPANYWIDE TARGET WHICH IS MULTIPLIED BY PERCENT TO DETERMINE THE CUTOFF SALES QUOTA FOR THE QUERY 4HAT VALUE IS THEN USED IN THE SEARCH CONDITION TO CHECK EACH ROW OF THE 3!,%32%03 TABLE AND FIND THE REQUESTED NAMES )N THIS SIMPLE CASE THE SUBQUERY PRODUCES THE SAME VALUE FOR EVERY ROW OF THE 3!,%32%03 TABLE THE 15/4! VALUE FOR EACH SALESPERSON IS COMPARED WITH THE SAME COMPANYWIDE NUMBER /F COURSE THE QUERY COULD ALSO BE WRITTEN TO PERFORM THE MULTIPLICATION WITHIN THE SUBQUERY LIKE THIS 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 15/4! 3%,%#4 35-4!2'%4 &2/- /&&)#%3
)N THIS CASE ITS MORE CONVENIENT TO USE THE SUBQUERY BUT ITS NOT ESSENTIAL 7E COULD HAVE SIMPLY RUN THE QUERY CONTAINED IN THE SUBQUERY BY ITSELF TO RETURN THE CUTOFF QUOTA AMOUNT IN THE SAMPLE DATABASE AND THEN KEYED THAT AMOUNT INTO THE 7(%2% CLAUSE OF THE MAIN QUERY AS SHOWN HERE 3%,%#4 35-4!2'%4 &2/- /&&)#%3 35-4!2'%4
3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 15/4!
(OWEVER SUBQUERIES ARE USUALLY NOT THIS SIMPLE &OR EXAMPLE CONSIDER ONCE AGAIN THE QUERY FROM THE PREVIOUS SECTION ,IST THE OFlCES WHERE THE SALES TARGET FOR THE OFlCE EXCEEDS THE SUM OF THE SALESPEOPLES QUOTAS 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 4!2'%4 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#% #)49
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#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
/UTERõ2EFERENCES 7ITHIN THE BODY OF A SUBQUERY ITS OFTEN NECESSARY TO REFER TO THE VALUE OF A COLUMN IN THE CURRENT ROW OF THE MAIN QUERY #ONSIDER ONCE AGAIN THE QUERY FROM THE PREVIOUS SECTIONS ,IST THE OFlCES WHERE THE SALES TARGET FOR THE OFlCE EXCEEDS THE SUM OF THE SALESPEOPLES QUOTAS 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 4!2'%4 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#%
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)N THIS MORE TYPICAL CASE THE SUBQUERY CANNOT BE CALCULATED ONCE FOR THE ENTIRE QUERY 4HE SUBQUERY PRODUCES A DIFFERENT VALUE FOR EACH OFFICE BASED ON THE QUOTAS OF THE SALESPEOPLE IN THAT PARTICULAR OFFICE &IGURE SHOWS CONCEPTUALLY HOW 31, CARRIES OUT THE QUERY 4HE MAIN QUERY DRAWS ITS DATA FROM THE /&&)#%3 TABLE AND THE 7(%2% CLAUSE SELECTS WHICH OFFICES WILL BE INCLUDED IN THE QUERY RESULTS 31, GOES THROUGH THE ROWS OF THE /&&)#%3 TABLE ONE BY ONE APPLYING THE TEST STATED IN THE 7(%2% CLAUSE 4O TEST THE 4!2'%4 VALUE 31, CARRIES OUT THE SUBQUERY FINDING THE SUM OF THE QUOTAS FOR SALESPEOPLE IN THE CURRENT OFFICE 4HE SUBQUERY PRODUCES A SINGLE NUMBER AND THE 7(%2% CLAUSE COMPARES THE NUMBER WITH THE 4!2'%4 VALUE SELECTING OR REJECTING THE CURRENT OFFICE BASED ON THE COMPARISON !S THE FIGURE SHOWS 31, CARRIES OUT THE SUBQUERY REPEATEDLY ONCE FOR EACH ROW TESTED BY THE 7(%2% CLAUSE OF THE MAIN QUERY
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4HE ROLE OF THE SUBQUERY IN THIS 3%,%#4 STATEMENT IS TO CALCULATE THE TOTAL QUOTA FOR THOSE SALESPEOPLE WHO WORK IN A PARTICULAR OFFICESPECIFICALLY THE OFFICE CURRENTLY BEING TESTED BY THE 7(%2% CLAUSE OF THE MAIN QUERY 4HE SUBQUERY DOES THIS BY SCANNING THE 3!,%32%03 TABLE "UT NOTICE THAT THE /&&)#% COLUMN IN THE 7(%2% CLAUSE OF THE SUBQUERY DOESNT REFER TO A COLUMN OF THE 3!,%32%03 TABLE IT REFERS TO A COLUMN OF THE /&&)#%3 TABLE WHICH IS A PART OF THE MAIN QUERY !S 31, MOVES THROUGH EACH ROW OF THE /&&)#%3 TABLE IT USES THE /&&)#% VALUE FROM THE CURRENT ROW WHEN IT CARRIES OUT THE SUBQUERY 4HE /&&)#% COLUMN IN THIS SUBQUERY IS AN EXAMPLE OF AN OUTER REFERENCE WHICH IS A COLUMN NAME THAT DOES NOT REFER TO ANY OF THE TABLES NAMED IN THE &2/- CLAUSE OF THE SUBQUERY IN WHICH THE COLUMN NAME APPEARS )NSTEAD THE COLUMN NAME REFERS TO A COLUMN OF A TABLE SPECIFIED IN THE &2/- CLAUSE OF THE MAIN QUERY !S THE PREVIOUS EXAMPLE SHOWS WHEN THE $"-3 EXAMINES THE SEARCH CONDITION IN THE SUBQUERY THE VALUE OF THE COLUMN IN AN OUTER REFERENCE IS TAKEN FROM THE ROW CURRENTLY BEING TESTED BY THE MAIN QUERY
3UBQUERYõ3EARCHõ#ONDITIONS ! SUBQUERY USUALLY APPEARS AS PART OF A SEARCH CONDITION IN THE 7(%2% OR (!6).' CLAUSE #HAPTER DESCRIBED THE SIMPLE SEARCH CONDITIONS THAT CAN BE USED IN THESE CLAUSES )N ADDITION MOST 31, PRODUCTS OFFER THESE SUBQUERY SEARCH CONDITIONS s 3UBQUERY COMPARISON TEST #OMPARES THE VALUE OF AN EXPRESSION WITH A SINGLE VALUE PRODUCED BY A SUBQUERY 4HIS TEST RESEMBLES THE SIMPLE COMPARISON TEST s 3UBQUERY SET MEMBERSHIP TEST #HECKS WHETHER THE VALUE OF AN EXPRESSION MATCHES ONE OF THE SET OF VALUES PRODUCED BY A SUBQUERY 4HIS TEST RESEMBLES THE SIMPLE SET MEMBERSHIP TEST s %XISTENCE TEST 4ESTS WHETHER A SUBQUERY PRODUCES ANY ROWS OF QUERY RESULTS s 1UANTIFIED COMPARISON TEST #OMPARES THE VALUE OF AN EXPRESSION WITH EACH OF THE SETS OF VALUES PRODUCED BY A SUBQUERY
4HEõ3UBQUERYõ#OMPARISONõ4ESTõ õ õ õ õ õ 4HE SUBQUERY COMPARISON TEST IS A MODIFIED FORM OF THE SIMPLE COMPARISON TEST AS SHOWN IN &IGURE )T COMPARES THE VALUE OF AN EXPRESSION WITH THE VALUE PRODUCED BY A SUBQUERY
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AND RETURNS A 425% RESULT IF THE COMPARISON IS TRUE 9OU USE THIS TEST TO COMPARE A VALUE FROM THE ROW BEING TESTED WITH A SINGLE VALUE PRODUCED BY A SUBQUERY AS IN THIS EXAMPLE ,IST THE SALESPEOPLE WHOSE QUOTAS ARE EQUAL TO OR HIGHER THAN THE TARGET OF THE !TLANTA SALES OFlCE
4HE SUBQUERY IN THE EXAMPLE RETRIEVES THE SALES TARGET OF THE !TLANTA OFFICE 4HE VALUE IS THEN USED TO SELECT THE SALESPEOPLE WHOSE QUOTAS ARE HIGHER THAN THE RETRIEVED TARGET 4HE SUBQUERY COMPARISON TEST OFFERS THE SAME SIX COMPARISON OPERATORS AVAILABLE WITH THE SIMPLE COMPARISON TEST 4HE SUBQUERY SPECIFIED IN THIS TEST MUST PRODUCE A SINGLE VALUE OF THE APPROPRIATE DATA TYPETHAT IS IT MUST PRODUCE A SINGLE ROW OF QUERY RESULTS CONTAINING EXACTLY ONE COLUMN )F THE SUBQUERY PRODUCES MULTIPLE ROWS OR MULTIPLE COLUMNS THE COMPARISON DOES NOT MAKE SENSE AND 31, REPORTS AN ERROR CONDITION )F THE SUBQUERY PRODUCES NO ROWS OR PRODUCES A .5,, VALUE THE COMPARISON TEST RETURNS .5,, UNKNOWN (ERE ARE SOME ADDITIONAL EXAMPLES OF SUBQUERY COMPARISON TESTS ,IST ALL CUSTOMERS SERVED BY "ILL !DAMS 3%,%#4 #/-0!.9 &2/- #534/-%23 7(%2% #534?2%0 3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% .!-% g"ILL !DAMSg #/-0!.9
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,IST ALL PRODUCTS FROM MANUFACTURER !#) WHERE THE QUANTITY ON HAND IS ABOVE THE QUANTITY ON HAND OF PRODUCT !#) 3%,%#4 $%3#2)04)/. 149?/.?(!.$ &2/- 02/$5#43 7(%2% -&2?)$ g!#)g !.$ 149?/.?(!.$ 3%,%#4 149?/.?(!.$ &2/- 02/$5#43 7(%2% -&2?)$ g!#)g !.$ 02/$5#4?)$ gg
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4HE SUBQUERY COMPARISON TEST SPECIFIED BY THE ORIGINAL 31, STANDARD 31, AND SUPPORTED BY ALL OF THE LEADING $"-3 PRODUCTS ALLOWS A SUBQUERY ONLY ON THE RIGHT SIDE OF THE COMPARISON OPERATOR 4HIS COMPARISON ! SUBQUERY
IS ALLOWED BUT THIS COMPARISON SUBQUERY !
IS NOT PERMITTED 4HIS DOESNT LIMIT THE POWER OF THE COMPARISON TEST BECAUSE THE OPERATOR IN ANY UNEQUAL COMPARISON CAN ALWAYS BE TURNED AROUND SO THAT THE SUBQUERY IS PUT ON THE RIGHT SIDE OF THE INEQUALITY (OWEVER IT DOES MEAN THAT YOU MUST SOMETIMES TURN AROUND THE LOGIC OF AN %NGLISH LANGUAGE REQUEST TO GET A FORM OF THE REQUEST THAT CORRESPONDS TO A LEGAL 31, STATEMENT 3UBSEQUENT VERSIONS OF THE 31, STANDARD ELIMINATED THIS RESTRICTION AND ALLOW THE SUBQUERY TO APPEAR ON EITHER SIDE OF THE COMPARISON OPERATOR )N FACT THE CURRENT 31, STANDARD GOES CONSIDERABLY FURTHER AND ALLOWS A COMPARISON TEST TO BE APPLIED TO AN ENTIRE ROW OF VALUES INSTEAD OF TO A SINGLE VALUE 4HIS AND OTHER MORE ADVANCED QUERY EXPRESSION FEATURES OF THE 31, STANDARD ARE DESCRIBED IN THE LATTER SECTIONS OF THIS CHAPTER (OWEVER THEY ARE NOT UNIFORMLY SUPPORTED BY THE CURRENT VERSIONS OF THE MAJOR 31, PRODUCTS &OR PORTABILITY ITS BEST TO WRITE SUBQUERIES THAT CONFORM TO THE 31, RESTRICTIONS AS DESCRIBED PREVIOUSLY
4HEõ3ETõ-EMBERSHIPõ4ESTõ). 4HE SUBQUERY SET MEMBERSHIP TEST ). IS A MODIFIED FORM OF THE SIMPLE SET MEMBERSHIP TEST AS SHOWN IN &IGURE )T COMPARES A SINGLE DATA VALUE WITH A COLUMN OF DATA VALUES PRODUCED BY A SUBQUERY AND RETURNS A 425% RESULT IF THE DATA VALUE MATCHES ONE OF THE VALUES IN THE COLUMN 9OU USE THIS TEST WHEN YOU NEED TO COMPARE A VALUE FROM THE ROW BEING TESTED WITH A SET OF VALUES PRODUCED BY A SUBQUERY (ERE IS A SIMPLE EXAMPLE ,IST THE SALESPEOPLE WHO WORK IN OFlCES THAT ARE OVER TARGET 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% 3!,%3 4!2'%4 .!-%
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#HAPTERçç
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,IST THE SALESPEOPLE WHO DO NOT WORK IN OFlCES MANAGED BY ,ARRY &ITCH EMPLOYEE 3%,%#4 .!-% &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ./4 ). 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% -'2 .!-%
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,IST ALL OF THE CUSTOMERS WHO HAVE PLACED ORDERS FOR !#) 7IDGETS MANUFACTURER !#) PRODUCT NUMBERS STARTING WITH BETWEEN *ANUARY AND *UNE 3%,%#4 #/-0!.9 &2/- #534/-%23 7(%2% #534?.5- ). 3%,%#4 $)34).#4 #534 &2/- /2$%23 7(%2% -&2 g!#)g !.$ 02/$5#4 ,)+% gg !.$ /2$%2?$!4% "%47%%. g g !.$ g g #/-0!.9
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4HE SUBQUERY PRODUCES A SET OF OFFICE NUMBERS WHERE THE SALES ARE ABOVE TARGET )N THE SAMPLE DATABASE THERE ARE THREE SUCH OFFICES NUMBERED AND 4HE MAIN QUERY THEN CHECKS EACH ROW OF THE 3!,%32%03 TABLE TO DETERMINE WHETHER THAT PARTICULAR SALESPERSON WORKS IN AN OFFICE WITH ONE OF THESE NUMBERS (ERE ARE SOME OTHER EXAMPLES OF SUBQUERIES THAT TEST SET MEMBERSHIP
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.OTE THAT THE USE OF $)34).#4 IN THE SUBQUERY ISNT STRICTLY NECESSARY )F THE SAME CUSTOMER APPEARS MULTIPLE TIMES IN THE SUBQUERY RESULTS INSTEAD OF ONLY ONCE THE OUTER QUERY YIELDS THE SAME RESULTS /FTEN THERE IS A PERFORMANCE TRADE OFF BETWEEN THE OVERHEAD THE $"-3 REQUIRES TO ELIMINATE DUPLICATES USUALLY A SORT IS REQUIRED AND THE OVERHEAD OF PROCESSING ADDITIONAL ROWS IN THE SUBQUERY RESULTS WHEN PROCESSING THE 7(%2% CLAUSE OF THE MAIN QUERY 5SUALLY THE LARGER INTERMEDIATE RESULT SET IS A LOT MORE EFFICIENT THAN THE SORT REQUIRED TO ELIMINATE DUPLICATES !ND THERE ARE OFTEN OTHER CONSIDERATIONS &OR EXAMPLE IN /RACLE A '2/50 "9 IS USUALLY MORE EFFICIENT THAN A $)34).#4 !S YOU CAN SEE WRITING THE MOST EFFICIENT 31, POSSIBLE REQUIRES SOME DETAILED KNOWLEDGE ABOUT HOW THE PARTICULAR $"-3 BEING USED PROCESSES 31, STATEMENTS )N EACH OF THESE EXAMPLES THE SUBQUERY PRODUCES A COLUMN OF DATA VALUES AND THE 7(%2% CLAUSE OF THE MAIN QUERY CHECKS TO SEE WHETHER A VALUE FROM A ROW OF THE MAIN QUERY MATCHES ONE OF THE VALUES IN THE COLUMN 4HE SUBQUERY FORM OF THE ). TEST THUS WORKS EXACTLY LIKE THE SIMPLE ). TEST EXCEPT THAT THE SET OF VALUES IS PRODUCED BY A SUBQUERY INSTEAD OF BEING EXPLICITLY LISTED IN THE STATEMENT
4HEõ%XISTENCEõ4ESTõ%8)343 4HE EXISTENCE TEST %8)343 CHECKS WHETHER A SUBQUERY PRODUCES ANY ROWS OF QUERY RESULTS AS SHOWN IN &IGURE .O SIMPLE COMPARISON TEST RESEMBLES THE EXISTENCE TEST IT IS USED ONLY WITH SUBQUERIES (ERE IS AN EXAMPLE OF A REQUEST THAT CAN BE EXPRESSED NATURALLY USING AN EXISTENCE TEST ,IST THE PRODUCTS FOR WHICH AN ORDER OF OR MORE HAS BEEN RECEIVED 4HE REQUEST COULD EASILY BE REPHRASED AS ,IST THE PRODUCTS FOR WHICH THERE EXISTS AT LEAST ONE ORDER IN THE /2$%23 TABLE A THAT IS FOR THE PRODUCT IN QUESTION AND B THAT HAS AN AMOUNT OF AT LEAST 4HE 3%,%#4 STATEMENT USED TO RETRIEVE THE REQUESTED LIST OF PRODUCTS CLOSELY RESEMBLES THE REPHRASED REQUEST 3%,%#4 $)34).#4 $%3#2)04)/. &2/- 02/$5#43 7(%2% %8)343 3%,%#4 /2$%2?.5- &2/- /2$%23 7(%2% 02/$5#4 02/$5#4?)$ !.$ -&2 -&2?)$ !.$ !-/5.4 $%3#2)04)/.
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,IST THE PRODUCTS FOR WHICH AN ORDER OF OR MORE HAS BEEN RECEIVED 3%,%#4 $%3#2)04)/. &2/- 02/$5#43 7(%2% %8)343 3%,%#4 &2/- /2$%23 7(%2% 02/$5#4 02/$5#4?)$ !.$ -&2 -&2?)$ !.$ !-/5.4
)N PRACTICE THE SUBQUERY IN AN %8)343 TEST IS USUALLY WRITTEN USING THE 3%,%#4 NOTATION (ERE ARE SOME ADDITIONAL EXAMPLES OF QUERIES THAT USE %8)343 ,IST ANY CUSTOMERS ASSIGNED TO 3UE 3MITH WHO HAVE NOT PLACED AN ORDER FOR OVER 3%,%#4 #/-0!.9 &2/- #534/-%23 7(%2% #534?2%0 3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% .!-% g3UE 3MITHg !.$ ./4 %8)343 3%,%#4 &2/- /2$%23 7(%2% #534 #534?.5- !.$ !-/5.4 #/-0!.9
#ARTER 3ONS &RED ,EWIS #ORP
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#ONCEPTUALLY 31, PROCESSES THIS QUERY BY GOING THROUGH THE 02/$5#43 TABLE AND PERFORMING THE SUBQUERY FOR EACH PRODUCT 4HE SUBQUERY PRODUCES A COLUMN CONTAINING THE ORDER NUMBERS OF ANY ORDERS FOR THE hCURRENTv PRODUCT THAT ARE OVER )F THERE ARE ANY SUCH ORDERS THAT IS IF THE COLUMN IS NOT EMPTY THE %8)343 TEST IS 425% )F THE SUBQUERY PRODUCES NO ROWS THE %8)343 TEST IS &!,3% 4HE %8)343 TEST CANNOT PRODUCE A .5,, VALUE 9OU CAN REVERSE THE LOGIC OF THE %8)343 TEST USING THE ./4 %8)343 FORM )N THIS CASE THE TEST IS 425% IF THE SUBQUERY PRODUCES NO ROWS AND &!,3% OTHERWISE .OTICE THAT THE %8)343 SEARCH CONDITION DOESNT REALLY USE THE RESULTS OF THE SUBQUERY AT ALL )T MERELY TESTS TO SEE WHETHER THE SUBQUERY PRODUCES ANY RESULTS &OR THIS REASON 31, RELAXES THE RULE THAT hSUBQUERIES MUST RETURN A SINGLE COLUMN OF DATAv AND ALLOWS YOU TO USE THE 3%,%#4 FORM IN THE SUBQUERY OF AN %8)343 TEST 4HE PREVIOUS SUBQUERY COULD THUS HAVE BEEN WRITTEN AS
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,IST THE OFlCES WHERE THERE IS A SALESPERSON WHOSE QUOTA REPRESENTS MORE THAN PERCENT OF THE OFlCES TARGET 3%,%#4 #)49 &2/- /&&)#%3 7(%2% %8)343 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#% !.$ 15/4! 4!2'%4 #)49
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.OTE THAT IN EACH OF THESE EXAMPLES THE SUBQUERY INCLUDES AN OUTER REFERENCE TO A COLUMN OF THE TABLE IN THE MAIN QUERY )N PRACTICE THE SUBQUERY IN AN %8)343 TEST WILL ALWAYS CONTAIN AN OUTER REFERENCE THAT LINKS THE SUBQUERY TO THE ROW CURRENTLY BEING TESTED BY THE MAIN QUERY
1UANTIFIEDõ4ESTSõ!.9õANDõ!,,
4HE SUBQUERY VERSION OF THE ). TEST CHECKS WHETHER A DATA VALUE IS EQUAL TO SOME VALUE IN A COLUMN OF SUBQUERY RESULTS 31, PROVIDES TWO QUANTIFIED TESTS !.9 AND !,, THAT EXTEND THIS NOTION TO OTHER COMPARISON OPERATORS SUCH AS GREATER THAN AND LESS THAN "OTH OF THESE TESTS COMPARE A DATA VALUE WITH THE COLUMN OF DATA VALUES PRODUCED BY A SUBQUERY AS SHOWN IN &IGURE
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4HE !.9 TEST IS USED IN CONJUNCTION WITH ONE OF THE SIX 31, COMPARISON OPERATORS TO COMPARE A SINGLE TEST VALUE WITH A COLUMN OF DATA VALUES PRODUCED BY A SUBQUERY 4O PERFORM THE TEST 31, USES THE SPECIFIED COMPARISON OPERATOR TO COMPARE THE TEST VALUE WITH EACH DATA VALUE IN THE COLUMN ONE AT A TIME )F ANY OF THE INDIVIDUAL COMPARISONS YIELDS A 425% RESULT THE !.9 TEST RETURNS A 425% RESULT (ERE IS AN EXAMPLE OF A REQUEST THAT CAN BE HANDLED WITH THE !.9 TEST ,IST THE SALESPEOPLE WHO HAVE TAKEN AN ORDER THAT REPRESENTS MORE THAN PERCENT OF THEIR QUOTA
#ONCEPTUALLY THE MAIN QUERY TESTS EACH ROW OF THE 3!,%32%03 TABLE ONE BY ONE 4HE SUBQUERY FINDS ALL OF THE ORDERS TAKEN BY THE CURRENT SALESPERSON AND RETURNS A COLUMN CONTAINING THE ORDER AMOUNTS FOR THOSE ORDERS 4HE 7(%2% CLAUSE OF THE MAIN QUERY THEN COMPUTES PERCENT OF THE CURRENT SALESPERSONS QUOTA AND USES IT AS A TEST VALUE COMPARING IT WITH EVERY ORDER AMOUNT PRODUCED BY THE SUBQUERY )F ANY ORDER AMOUNT EXCEEDS THE CALCULATED TEST VALUE THE !.9 TEST RETURNS 425% AND THE SALESPERSON IS INCLUDED IN THE QUERY RESULTS )F NOT THE SALESPERSON IS NOT INCLUDED IN THE QUERY RESULTS 4HE KEYWORD 3/-% IS AN ALTERNATIVE FOR !.9 SPECIFIED BY THE !.3))3/ 31, STANDARD %ITHER KEYWORD GENERALLY CAN BE USED BUT SOME $"-3 BRANDS DO NOT SUPPORT 3/-% 4HE !.9 TEST CAN SOMETIMES BE DIFFICULT TO UNDERSTAND BECAUSE IT INVOLVES AN ENTIRE SET OF COMPARISONS NOT JUST ONE )T HELPS IF YOU READ THE TEST IN A SLIGHTLY DIFFERENT WAY THAN IT APPEARS IN THE STATEMENT )F THIS !.9 TEST APPEARS 7(%2% 8 !.9 3%,%#4 9 x
INSTEAD OF READING THE TEST LIKE THIS WHERE 8 IS LESS THAN ANY SELECT 9x
TRY READING IT LIKE THIS WHERE FOR SOME 9 8 IS LESS THAN 9
7HEN YOU USE THIS TRICK THE PRECEDING QUERY BECOMES 3ELECT THE SALESPEOPLE WHERE FOR SOME ORDER TAKEN BY THE SALESPERSON PERCENT OF THE SALESPERSONS QUOTA IS LESS THAN THE ORDER AMOUNT )F THE SUBQUERY IN AN !.9 TEST PRODUCES NO ROWS OF QUERY RESULTS OR IF THE QUERY RESULTS INCLUDE .5,, VALUES THE OPERATION OF THE !.9 TEST MAY VARY FROM ONE $"-3 TO ANOTHER
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4HE !.3))3/ 31, STANDARD SPECIFIES THESE DETAILED RULES DESCRIBING THE RESULTS OF THE !.9 TEST WHEN THE TEST VALUE IS COMPARED WITH THE COLUMN OF SUBQUERY RESULTS s )F THE SUBQUERY PRODUCES AN EMPTY COLUMN OF QUERY RESULTS THE !.9 TEST RETURNS &!,3%NO VALUE IS PRODUCED BY THE SUBQUERY FOR WHICH THE COMPARISON TEST HOLDS s )F THE COMPARISON TEST IS 425% FOR AT LEAST ONE OF THE DATA VALUES IN THE COLUMN THEN THE !.9 SEARCH CONDITION RETURNS 425%INDEED SOME VALUE IS PRODUCED BY THE SUBQUERY FOR WHICH THE COMPARISON TEST HOLDS s )F THE COMPARISON TEST IS &!,3% FOR EVERY DATA VALUE IN THE COLUMN THEN THE !.9 SEARCH CONDITION RETURNS &!,3% )N THIS CASE YOU CAN CONCLUSIVELY STATE THAT NO VALUE IS PRODUCED BY THE SUBQUERY FOR WHICH THE COMPARISON TEST HOLDS s )F THE COMPARISON TEST IS NOT 425% FOR ANY DATA VALUE IN THE COLUMN BUT IT IS .5,, UNKNOWN FOR ONE OR MORE OF THE DATA VALUES THEN THE !.9 SEARCH CONDITION RETURNS .5,, )N THIS SITUATION YOU CANNOT CONCLUSIVELY STATE WHETHER A VALUE IS PRODUCED BY THE SUBQUERY FOR WHICH THE COMPARISON TEST HOLDS IT MAY OR MAY NOT BE DEPENDING ON THE hACTUALv BUT CURRENTLY UNKNOWN VALUES FOR THE .5,, DATA 4HE !.9 COMPARISON OPERATOR CAN BE VERY TRICKY TO USE IN PRACTICE ESPECIALLY IN CONJUNCTION WITH THE INEQUALITY COMPARISON OPERATOR (ERE IS AN EXAMPLE THAT SHOWS THE PROBLEM ,IST THE NAMES AND AGES OF ALL THE PEOPLE IN THE SALES FORCE WHO DO NOT MANAGE AN OFlCE )TS TEMPTING TO EXPRESS THIS QUERY AS SHOWN IN THIS EXAMPLE 3%,%#4 .!-% !'% &2/- 3!,%32%03 7(%2% %-0,?.5- !.9 3%,%#4 -'2 &2/- /&&)#%3
4HE SUBQUERY 3%,%#4 -'2 &2/- /&&)#%3
OBVIOUSLY PRODUCES THE EMPLOYEE NUMBERS OF THE MANAGERS AND THEREFORE THE QUERY SEEMS TO BE SAYING &IND EACH SALESPERSON WHO IS NOT THE MANAGER OF ANY OFlCE "UT THATS NOT WHAT THE QUERY SAYS 7HAT IT DOES SAY IS THIS &IND EACH SALESPERSON WHO FOR SOME OFlCE IS NOT THE MANAGER OF THAT OFlCE /F COURSE FOR ANY GIVEN SALESPERSON ITS POSSIBLE TO FIND SOME OFFICE WHERE THAT SALESPERSON IS NOT THE MANAGER 4HE QUERY RESULTS WOULD INCLUDE ALL THE SALESPEOPLE AND THEREFORE FAIL TO ANSWER THE QUESTION THAT WAS POSED 4HE CORRECT QUERY IS 3%,%#4 .!-% !'% &2/- 3!,%32%03 7(%2% ./4 %-0,?.5- !.9 3%,%#4 -'2 &2/- /&&)#%3
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,IKE THE !.9 TEST THE !,, TEST IS USED IN CONJUNCTION WITH ONE OF THE SIX 31, COMPARISON OPERATORS TO COMPARE A SINGLE TEST VALUE WITH A COLUMN OF DATA VALUES PRODUCED BY A SUBQUERY 4O PERFORM THE TEST 31, USES THE SPECIFIED COMPARISON OPERATOR TO COMPARE THE TEST VALUE WITH EACH DATA VALUE IN THE COLUMN ONE AT A TIME )F ALL OF THE INDIVIDUAL COMPARISONS YIELD A 425% RESULT THE !,, TEST RETURNS A 425% RESULT (ERE IS AN EXAMPLE OF A REQUEST THAT CAN BE HANDLED WITH THE !,, TEST ,IST THE OFlCES AND THEIR TARGETS WHERE ALL OF THE SALESPEOPLE HAVE SALES THAT EXCEED PERCENT OF THE OFlCES TARGET 3%,%#4 #)49 4!2'%4 &2/- /&&)#%3 7(%2% 4!2'%4 !,, 3%,%#4 3!,%3 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#% #)49 4!2'%4
$ENVER .EW 9ORK !TLANTA
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9OU CAN ALWAYS TURN A QUERY WITH AN !.9 TEST INTO A QUERY WITH AN %8)343 TEST BY MOVING THE COMPARISON INSIDE THE SEARCH CONDITION OF THE SUBQUERY 4HIS IS USUALLY A VERY GOOD IDEA BECAUSE IT ELIMINATES ERRORS LIKE THE ONE JUST DESCRIBED (ERE IS AN ALTERNATIVE FORM OF THE QUERY USING THE %8)343 TEST
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#ONCEPTUALLY THE MAIN QUERY TESTS EACH ROW OF THE /&&)#%3 TABLE ONE BY ONE 4HE SUBQUERY FINDS ALL OF THE SALESPEOPLE WHO WORK IN THE CURRENT OFFICE AND RETURNS A COLUMN CONTAINING THE SALES FOR EACH SALESPERSON 4HE 7(%2% CLAUSE OF THE MAIN QUERY THEN COMPUTES PERCENT OF THE OFFICES TARGET AND USES IT AS A TEST VALUE COMPARING IT WITH EVERY SALES VALUE PRODUCED BY THE SUBQUERY )F ALL OF THE SALES VALUES EXCEED THE CALCULATED TEST VALUE THE !,, TEST RETURNS 425% AND THE OFFICE IS INCLUDED IN THE QUERY RESULTS )F NOT THE OFFICE IS NOT INCLUDED IN THE QUERY RESULTS ,IKE THE !.9 TEST THE !,, TEST CAN BE DIFFICULT TO UNDERSTAND BECAUSE IT INVOLVES AN ENTIRE SET OF COMPARISONS NOT JUST ONE !GAIN IT HELPS IF YOU READ THE TEST IN A SLIGHTLY DIFFERENT WAY THAN IT APPEARS IN THE STATEMENT )F THIS !,, TEST APPEARS 7(%2% 8 !,, 3%,%#4 9 x
INSTEAD OF READING IT LIKE THIS WHERE 8 IS LESS THAN ALL SELECT 9x
TRY READING THE TEST LIKE THIS WHERE FOR ALL 9 8 IS LESS THAN 9
7HEN YOU USE THIS TRICK THE PRECEDING QUERY BECOMES 3ELECT THE OFlCES WHERE FOR ALL SALESPEOPLE WHO WORK IN THE OFlCE PERCENT OF THE OFlCES TARGET IS LESS THAN THE SALESPERSONS SALES )F THE SUBQUERY IN AN !,, TEST PRODUCES NO ROWS OF QUERY RESULTS OR IF THE QUERY RESULTS INCLUDE .5,, VALUES THE OPERATION OF THE !,, TEST MAY VARY FROM ONE $"-3 TO ANOTHER 4HE !.3))3/ 31, STANDARD SPECIFIES THESE DETAILED RULES DESCRIBING THE RESULTS OF THE !,, TEST WHEN THE TEST VALUE IS COMPARED WITH THE COLUMN OF SUBQUERY RESULTS s )F THE SUBQUERY PRODUCES AN EMPTY COLUMN OF QUERY RESULTS THE !,, TEST RETURNS 425% 4HE COMPARISON TEST DOES HOLD FOR EVERY VALUE PRODUCED BY THE SUBQUERY THERE JUST ARENT ANY VALUES s )F THE COMPARISON TEST IS 425% FOR EVERY DATA VALUE IN THE COLUMN THEN THE !,, SEARCH CONDITION RETURNS 425% !GAIN THE COMPARISON TEST HOLDS TRUE FOR EVERY VALUE PRODUCED BY THE SUBQUERY s )F THE COMPARISON TEST IS &!,3% FOR ANY DATA VALUE IN THE COLUMN THEN THE !,, SEARCH CONDITION RETURNS &!,3% )N THIS CASE YOU CAN CONCLUSIVELY STATE THAT THE COMPARISON TEST DOES NOT HOLD TRUE FOR EVERY DATA VALUE PRODUCED BY THE QUERY s )F THE COMPARISON TEST IS NOT &!,3% FOR ANY DATA VALUE IN THE COLUMN BUT IT IS .5,, FOR ONE OR MORE OF THE DATA VALUES THEN THE !,, SEARCH CONDITION RETURNS .5,, )N THIS SITUATION YOU CANNOT CONCLUSIVELY STATE WHETHER A VALUE IS PRODUCED BY THE SUBQUERY FOR WHICH THE COMPARISON TEST DOES NOT HOLD TRUE THERE MAY OR MAY NOT BE DEPENDING ON THE hACTUALv BUT CURRENTLY UNKNOWN VALUES FOR THE .5,, DATA 4HE SUBTLE ERRORS THAT CAN OCCUR WHEN THE !.9 TEST IS COMBINED WITH THE INEQUALITY COMPARISON OPERATOR ALSO OCCUR WITH THE !,, TEST !S WITH THE !.9 TEST THE !,, TEST CAN ALWAYS BE CONVERTED INTO AN EQUIVALENT %8)343 TEST BY MOVING THE COMPARISON INSIDE THE SUBQUERY
#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
3UBQUERIESõANDõ*OINS 9OU MAY HAVE NOTICED AS YOU READ THROUGH THIS CHAPTER THAT MANY OF THE QUERIES THAT WERE WRITTEN USING SUBQUERIES COULD ALSO HAVE BEEN WRITTEN AS MULTITABLE QUERIES OR JOINS 4HIS IS OFTEN THE CASE AND 31, ALLOWS YOU TO WRITE THE QUERY EITHER WAY 4HIS EXAMPLE ILLUSTRATES THE POINT ,IST THE NAMES AND AGES OF SALESPEOPLE WHO WORK IN OFlCES IN THE 7ESTERN REGION
4HIS FORM OF THE QUERY CLOSELY PARALLELS THE STATED REQUEST 4HE SUBQUERY YIELDS A LIST OF OFFICES IN THE 7ESTERN REGION AND THE MAIN QUERY FINDS THE SALESPEOPLE WHO WORK IN ONE OF THE OFFICES IN THE LIST (ERE IS AN ALTERNATIVE FORM OF THE QUERY USING A TWO TABLE JOIN ,IST THE NAMES AND AGES OF SALESPEOPLE WHO WORK IN OFlCES IN THE 7ESTERN REGION 3%,%#4 .!-% !'% &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#% !.$ 2%')/. g7ESTERNg .!-% !'%
3UE 3MITH ,ARRY &ITCH .ANCY !NGELLI
4HIS FORM OF THE QUERY JOINS THE 3!,%32%03 TABLE TO THE /&&)#%3 TABLE TO FIND THE REGION WHERE EACH SALESPERSON WORKS AND THEN ELIMINATES THOSE WHO DO NOT WORK IN THE 7ESTERN REGION !NOTHER WAY TO WRITE THIS QUERY IS WITH THE %8)343 OPERATOR ,IST THE NAMES AND AGES OF SALESPEOPLE WHO WORK IN OFlCES IN THE 7ESTERN REGION 3%,%#4 .!-% !'% &2/- 3!,%32%03 7(%2% %8)343 3%,%#4 &2/- /&&)#%3 7(%2% 2%')/. g7ESTERNg !.$ 2%0?/&&)#% /&&)#% .!-% !'%
3UE 3MITH ,ARRY &ITCH .ANCY !NGELLI
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3%,%#4 .!-% !'% &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% 2%')/. g7ESTERNg .!-% !'%
3UE 3MITH ,ARRY &ITCH .ANCY !NGELLI
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!NY OF THE THREE QUERIES WILL FIND THE CORRECT SALESPEOPLE AND NONE OF THEM IS RIGHT OR WRONG -ANY PEOPLE WILL FIND THE FIRST FORM WITH THE SUBQUERY MORE NATURAL BECAUSE THE %NGLISH REQUEST DOESNT ASK FOR ANY INFORMATION ABOUT OFFICES AND BECAUSE IT SEEMS A LITTLE STRANGE TO JOIN THE 3!,%32%03 AND /&&)#%3 TABLES TO ANSWER THE REQUEST /F COURSE IF THE REQUEST IS CHANGED TO ASK FOR SOME INFORMATION FROM THE /&&)#%3 TABLE ,IST THE NAMES AND AGES OF THE SALESPEOPLE WHO WORK IN OFlCES IN THE 7ESTERN REGION AND THE CITIES WHERE THEY WORK THE SUBQUERY FORM WILL NO LONGER WORK AND THE TWO TABLE QUERY MUST BE USED #ONVERSELY MANY QUERIES WITH SUBQUERIES CANNOT BE TRANSLATED INTO AN EQUIVALENT JOIN (ERE IS A SIMPLE EXAMPLE ,IST THE NAMES AND AGES OF SALESPEOPLE WHO HAVE ABOVE AVERAGE QUOTAS 3%,%#4 .!-% !'% &2/- 3!,%32%03 7(%2% 15/4! 3%,%#4 !6'15/4! &2/- 3!,%32%03 .!-% !'%
"ILL !DAMS 3UE 3MITH ,ARRY &ITCH
)N THIS CASE THE INNER QUERY IS A SUMMARY QUERY AND THE OUTER QUERY IS NOT SO THERE IS NO WAY THE TWO QUERIES CAN BE COMBINED INTO A SINGLE JOIN
.ESTEDõ3UBQUERIES !LL OF THE QUERIES DESCRIBED THUS FAR IN THIS CHAPTER HAVE BEEN TWO LEVEL QUERIES INVOLVING A MAIN QUERY AND A SUBQUERY *UST AS YOU CAN USE A SUBQUERY INSIDE A MAIN QUERY YOU CAN USE A SUBQUERY INSIDE ANOTHER SUBQUERY (ERE IS AN EXAMPLE OF A REQUEST THAT IS NATURALLY REPRESENTED AS A THREE LEVEL QUERY WITH A MAIN QUERY A SUBQUERY AND A SUB SUBQUERY ,IST THE CUSTOMERS WHOSE SALESPEOPLE ARE ASSIGNED TO OFlCES IN THE %ASTERN SALES REGION 3%,%#4 #/-0!.9 &2/- #534/-%23 7(%2% #534?2%0 ). 3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% 2%')/. g%ASTERNg #/-0!.9
&IRST #ORP 3MITHSON #ORP !!! )NVESTMENTS *#0 )NC #HEN !SSOCIATES
#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
1-! !SSOC )AN 3CHMIDT !CME -FG
)N THIS EXAMPLE THE INNERMOST SUBQUERY 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% 2%')/. g%ASTERNg
3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). SUBQUERY
PRODUCES A COLUMN CONTAINING THE EMPLOYEE NUMBERS OF THE SALESPEOPLE WHO WORK IN ONE OF THE SELECTED OFFICES &INALLY THE OUTERMOST QUERY 3%,%#4 #/-0!.9 &2/- #534/-%23 7(%2% #534?2%0 ). SUBQUERY
FINDS THE CUSTOMERS WHOSE SALESPEOPLE HAVE ONE OF THE SELECTED EMPLOYEE NUMBERS 4HE SAME TECHNIQUE USED IN THIS THREE LEVEL QUERY CAN BE USED TO BUILD QUERIES WITH FOUR OR MORE LEVELS 4HE !.3))3/ 31, STANDARD DOES NOT SPECIFY A MAXIMUM NUMBER OF NESTING LEVELS BUT IN PRACTICE A QUERY BECOMES MUCH MORE TIME CONSUMING AS THE NUMBER OF LEVELS INCREASES 4HE QUERY ALSO BECOMES MORE DIFFICULT TO READ UNDERSTAND AND MAINTAIN WHEN IT INVOLVES MORE THAN ONE OR TWO LEVELS OF SUBQUERIES -ANY 31, IMPLEMENTATIONS RESTRICT THE NUMBER OF SUBQUERY LEVELS TO A RELATIVELY SMALL NUMBER
#ORRELATEDõ3UBQUERIES
)N CONCEPT 31, PERFORMS A SUBQUERY OVER AND OVER AGAINONCE FOR EACH ROW OF THE MAIN QUERY &OR MANY SUBQUERIES HOWEVER THE SUBQUERY PRODUCES THE SAME RESULTS FOR EVERY ROW OR ROW GROUP (ERE IS AN EXAMPLE ,IST THE SALES OFlCES WHOSE SALES ARE BELOW THE AVERAGE TARGET 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 3!,%3 3%,%#4 !6'4!2'%4 &2/- /&&)#%3 #)49
$ENVER !TLANTA
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PRODUCES A COLUMN CONTAINING THE OFFICE NUMBERS OF THE OFFICES IN THE %ASTERN REGION 4HE NEXT SUBQUERY
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)N THIS QUERY IT WOULD BE SILLY TO PERFORM THE SUBQUERY FIVE TIMES ONCE FOR EACH OFFICE 4HE AVERAGE TARGET DOESNT CHANGE WITH EACH OFFICE ITS COMPLETELY INDEPENDENT OF THE OFFICE CURRENTLY BEING TESTED !S A RESULT 31, CAN HANDLE THE QUERY BY FIRST PERFORMING THE SUBQUERY YIELDING THE AVERAGE TARGET AND THEN CONVERTING THE MAIN QUERY INTO 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 3!,%3
#OMMERCIAL 31, IMPLEMENTATIONS AUTOMATICALLY DETECT THIS SITUATION AND USE THIS SHORTCUT WHENEVER POSSIBLE TO REDUCE THE AMOUNT OF PROCESSING REQUIRED BY A SUBQUERY (OWEVER THE SHORTCUT CANNOT BE USED IF THE SUBQUERY CONTAINS AN OUTER REFERENCE AS IN THIS EXAMPLE ,IST ALL OF THE OFlCES WHOSE TARGETS EXCEED THE SUM OF THE QUOTAS OF THE SALESPEOPLE WHO WORK IN THEM 3%,%#4 #)49 &2/- /&&)#%3 7(%2% 4!2'%4 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#% #)49
#HICAGO ,OS !NGELES
&OR EACH ROW OF THE /&&)#%3 TABLE TO BE TESTED BY THE 7(%2% CLAUSE OF THE MAIN QUERY THE /&&)#% COLUMN WHICH APPEARS IN THE SUBQUERY AS AN OUTER REFERENCE HAS A DIFFERENT VALUE 4HUS 31, HAS NO CHOICE BUT TO CARRY OUT THIS SUBQUERY FIVE TIMESONCE FOR EACH ROW IN THE /&&)#%3 TABLE ! SUBQUERY CONTAINING AN OUTER REFERENCE IS CALLED A CORRELATED SUBQUERY BECAUSE ITS RESULTS ARE CORRELATED WITH EACH INDIVIDUAL ROW OF THE MAIN QUERY &OR THE SAME REASON AN OUTER REFERENCE IS SOMETIMES CALLED A CORRELATED REFERENCE ! SUBQUERY CAN CONTAIN AN OUTER REFERENCE TO A TABLE IN THE &2/- CLAUSE OF ANY QUERY THAT CONTAINS THE SUBQUERY NO MATTER HOW DEEPLY THE SUBQUERIES ARE NESTED ! COLUMN NAME IN A FOURTH LEVEL SUBQUERY FOR EXAMPLE MAY REFER TO ONE OF THE TABLES NAMED IN THE &2/- CLAUSE OF THE MAIN QUERY OR TO A TABLE NAMED IN THE &2/- CLAUSE OF THE SECOND LEVEL SUBQUERY OR THE THIRD LEVEL SUBQUERY THAT CONTAINS IT 2EGARDLESS OF THE LEVEL OF NESTING AN OUTER REFERENCE ALWAYS TAKES ON THE VALUE OF THE COLUMN IN THE CURRENT ROW OF THE TABLE BEING TESTED "ECAUSE A SUBQUERY CAN CONTAIN OUTER REFERENCES THERE IS EVEN MORE POTENTIAL FOR AMBIGUOUS COLUMN NAMES IN A SUBQUERY THAN IN A MAIN QUERY 7HEN AN UNQUALIFIED COLUMN NAME APPEARS WITHIN A SUBQUERY 31, MUST DETERMINE WHETHER IT REFERS TO A TABLE IN THE SUBQUERYS OWN &2/- CLAUSE OR TO A &2/- CLAUSE IN A QUERY CONTAINING THE SUBQUERY 4O MINIMIZE THE POSSIBILITY OF CONFUSION 31, ALWAYS INTERPRETS A COLUMN REFERENCE IN
#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
A SUBQUERY USING THE NEAREST &2/- CLAUSE POSSIBLE 4O ILLUSTRATE THIS POINT IN THIS EXAMPLE THE SAME TABLE IS USED IN THE QUERY AND IN THE SUBQUERY ,IST THE SALESPEOPLE WHO ARE OVER AND WHO MANAGE A SALESPERSON WHO IS OVER QUOTA
4HE -!.!'%2 15/4! AND 3!,%3 COLUMNS IN THE SUBQUERY ARE REFERENCES TO THE 3!,%32%03 TABLE IN THE SUBQUERYS OWN &2/- CLAUSE 31, DOES NOT INTERPRET THEM AS OUTER REFERENCES AND THE SUBQUERY IS NOT A CORRELATED SUBQUERY 31, CAN PERFORM THE SUBQUERY FIRST IN THIS CASE FINDING THE SALESPEOPLE WHO ARE OVER QUOTA AND GENERATING A LIST OF THE EMPLOYEE NUMBERS OF THEIR MANAGERS 31, CAN THEN TURN ITS ATTENTION TO THE MAIN QUERY SELECTING MANAGERS WHOSE EMPLOYEE NUMBERS APPEAR IN THE GENERATED LIST )F YOU WANT TO USE AN OUTER REFERENCE WITHIN A SUBQUERY LIKE THE ONE IN THE PREVIOUS EXAMPLE YOU MUST USE A TABLE ALIAS TO FORCE THE OUTER REFERENCE 4HIS REQUEST WHICH ADDS ONE MORE QUALIFYING CONDITION TO THE PREVIOUS ONE SHOWS HOW ,IST THE MANAGERS WHO ARE OVER AND WHO MANAGE A SALESPERSON WHO IS OVER QUOTA AND WHO DOES NOT WORK IN THE SAME SALES OFlCE AS THE MANAGER 3%,%#4 .!-% &2/- 3!,%32%03 -'23 7(%2% !'% !.$ -'23%-0,?.5- ). 3%,%#4 -!.!'%2 &2/- 3!,%32%03 %-03 7(%2% %-0315/4! %-033!,%3 !.$ %-032%0?/&&)#% -'232%0?/&&)#% .!-%
3AM #LARK ,ARRY &ITCH
4HE COPY OF THE 3!,%32%03 TABLE USED IN THE MAIN QUERY NOW HAS THE TAG -'23 AND THE COPY IN THE SUBQUERY HAS THE TAG %-03 4HE SUBQUERY CONTAINS ONE ADDITIONAL SEARCH CONDITION REQUIRING THAT THE EMPLOYEES OFFICE NUMBER DOES NOT MATCH THAT OF THE MANAGER 4HE QUALIFIED COLUMN NAME -'232%0?/&&)#% IN THE SUBQUERY IS AN OUTER REFERENCE AND THIS SUBQUERY IS A CORRELATED SUBQUERY
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3%,%#4 .!-% &2/- 3!,%32%03 7(%2% !'% !.$ %-0,?.5- ). 3%,%#4 -!.!'%2 &2/- 3!,%32%03 7(%2% 3!,%3 15/4! .!-%
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3UBQUERIESõINõTHEõ(!6).'õ#LAUSE
!LTHOUGH SUBQUERIES ARE MOST OFTEN FOUND IN THE 7(%2% CLAUSE THEY CAN ALSO BE USED IN THE (!6).' CLAUSE OF A QUERY 7HEN A SUBQUERY APPEARS IN THE (!6).' CLAUSE IT WORKS AS PART OF THE ROW GROUP SELECTION PERFORMED BY THE (!6).' CLAUSE #ONSIDER THIS QUERY WITH A SUBQUERY ,IST THE SALESPEOPLE WHOSE AVERAGE ORDER SIZE FOR PRODUCTS MANUFACTURED BY !#) IS HIGHER THAN THE OVERALL AVERAGE ORDER SIZE 3%,%#4 .!-% !6'!-/5.4 &2/- 3!,%32%03 /2$%23 7(%2% %-0,?.5- 2%0 !.$ -&2 g!#)g '2/50 "9 .!-% (!6).' !6'!-/5.4 3%,%#4 !6'!-/5.4 &2/- /2$%23 .!-% !6'!-/5.4
3UE 3MITH 4OM 3NYDER
&IGURE SHOWS CONCEPTUALLY HOW THIS QUERY WORKS 4HE SUBQUERY CALCULATES THE OVERALL AVERAGE ORDER SIZE )T IS A SIMPLE SUBQUERY AND CONTAINS NO OUTER REFERENCES SO 31, CAN CALCULATE THE AVERAGE ONCE AND THEN USE IT REPEATEDLY IN THE (!6).' CLAUSE 4HE MAIN QUERY GOES THROUGH !&'+) !&'+)
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#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
,IST THE SALESPEOPLE WHOSE AVERAGE ORDER SIZE FOR PRODUCTS MANUFACTURED BY !#) IS AT LEAST AS BIG AS THAT SALESPERSONS OVERALL AVERAGE ORDER SIZE 3%,%#4 .!-% !6'!-/5.4 &2/- 3!,%32%03 /2$%23 7(%2% %-0,?.5- 2%0 !.$ -&2 g!#)g '2/50 "9 .!-% %-0,?.5- (!6).' !6'!-/5.4 3%,%#4 !6'!-/5.4 &2/- /2$%23 7(%2% 2%0 %-0,?.5- .!-% !6'!-/5.4
"ILL !DAMS 3UE 3MITH 4OM 3NYDER
)N THIS NEW EXAMPLE THE SUBQUERY MUST PRODUCE THE OVERALL AVERAGE ORDER SIZE FOR THE SALESPERSON WHOSE ROW GROUP IS CURRENTLY BEING TESTED BY THE (!6).' CLAUSE 4HE SUBQUERY SELECTS ORDERS FOR THAT PARTICULAR SALESPERSON USING THE OUTER REFERENCE %-0,?.5- 4HE OUTER REFERENCE IS LEGAL BECAUSE %-0,?.5- HAS THE SAME VALUE IN ALL ROWS OF A GROUP PRODUCED BY THE MAIN QUERY
3UBQUERYõ3UMMARY 4HIS CHAPTER SO FAR HAS DESCRIBED SUBQUERIES WHICH ALLOW YOU TO USE THE RESULTS OF ONE QUERY TO HELP DEFINE ANOTHER QUERY "EFORE MOVING ON TO THE ADVANCED QUERY FACILITIES OF THE 31, SPECIFICATION LETS SUMMARIZE SUBQUERIES s ! SUBQUERY IS A hQUERY WITHIN A QUERYv 3UBQUERIES APPEAR WITHIN ONE OF THE SUBQUERY SEARCH CONDITIONS IN THE 7(%2% OR (!6).' CLAUSE s 7HEN A SUBQUERY APPEARS IN THE 7(%2% CLAUSE THE RESULTS OF THE SUBQUERY ARE USED TO SELECT THE INDIVIDUAL ROWS THAT CONTRIBUTE DATA TO THE QUERY RESULTS s 7HEN A SUBQUERY APPEARS IN THE (!6).' CLAUSE THE RESULTS OF THE SUBQUERY ARE USED TO SELECT THE ROW GROUPS THAT CONTRIBUTE DATA TO THE QUERY RESULTS s 3UBQUERIES CAN BE NESTED WITHIN OTHER SUBQUERIES
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THE /2$%23 TABLE FINDING ALL ORDERS FOR !#) PRODUCTS AND GROUPS THEM BY SALESPERSON 4HE (!6).' CLAUSE THEN CHECKS EACH ROW GROUP TO SEE WHETHER THE AVERAGE ORDER SIZE IN THAT GROUP IS BIGGER THAN THE AVERAGE FOR ALL ORDERS CALCULATED EARLIER )F SO THE ROW GROUP IS RETAINED IF NOT THE ROW GROUP IS DISCARDED &INALLY THE 3%,%#4 CLAUSE PRODUCES ONE SUMMARY ROW FOR EACH GROUP SHOWING THE NAME OF THE SALESPERSON AND THE AVERAGE ORDER SIZE FOR EACH 9OU CAN ALSO USE A CORRELATED SUBQUERY IN THE (!6).' CLAUSE "ECAUSE THE SUBQUERY IS EVALUATED ONCE FOR EACH ROW GROUP HOWEVER ALL OUTER REFERENCES IN THE CORRELATED SUBQUERY MUST BE SINGLE VALUED FOR EACH ROW GROUP %FFECTIVELY THIS MEANS THAT THE OUTER REFERENCE MUST EITHER BE A REFERENCE TO A GROUPING COLUMN OF THE OUTER QUERY OR BE CONTAINED WITHIN A COLUMN FUNCTION )N THE LATTER CASE THE VALUE OF THE COLUMN FUNCTION FOR THE ROW GROUP BEING TESTED IS CALCULATED AS PART OF THE SUBQUERY PROCESSING )F THE PREVIOUS REQUEST IS CHANGED SLIGHTLY THE SUBQUERY IN THE (!6).' CLAUSE BECOMES A CORRELATED SUBQUERY
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s 4HE SUBQUERY FORM OF THE COMPARISON TEST USES ONE OF THE SIMPLE COMPARISON OPERATORS TO COMPARE A TEST VALUE WITH THE SINGLE VALUE RETURNED BY A SUBQUERY s 4HE SUBQUERY FORM OF THE SET MEMBERSHIP TEST ). MATCHES A TEST VALUE TO THE SET OF VALUES RETURNED BY A SUBQUERY s 4HE EXISTENCE TEST %8)343 CHECKS WHETHER A SUBQUERY RETURNS ANY VALUES s 4HE QUANTIFIED TESTS !.9 AND !,, USE ONE OF THE SIMPLE COMPARISON OPERATORS TO COMPARE A TEST VALUE WITH ALL OF THE VALUES RETURNED BY A SUBQUERY CHECKING TO SEE WHETHER THE COMPARISON HOLDS FOR SOME OR ALL OF THE VALUES s ! SUBQUERY MAY INCLUDE AN OUTER REFERENCE TO A TABLE IN ANY OF THE QUERIES THAT CONTAINS IT LINKING THE SUBQUERY TO THE CURRENT ROW OF THAT QUERY &IGURE SHOWS THE FINAL VERSION OF THE RULES FOR 31, QUERY PROCESSING EXTENDED TO INCLUDE SUBQUERIES )T PROVIDES A COMPLETE DEFINITION OF THE QUERY RESULTS PRODUCED BY A 3%,%#4 STATEMENT " !%'' $(%+%&( '&"% &'' !'
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#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
!DVANCEDõ1UERIES
4HE 31, QUERIES DESCRIBED THUS FAR IN #HAPTERS THROUGH ARE THE MAINSTREAM CAPABILITIES PROVIDED BY MOST 31, IMPLEMENTATIONS 4HE COMBINATION OF FEATURES THEY REPRESENT COLUMN SELECTION IN THE 3%,%#4 CLAUSE ROW SELECTION CRITERIA IN THE 7(%2% CLAUSE MULTITABLE JOINS IN THE &2/- CLAUSE SUMMARY QUERIES IN THE '2/50 "9 AND (!6).' CLAUSES AND SUBQUERIES FOR MORE COMPLEX REQUESTSGIVE THE USER A POWERFUL SET OF DATA RETRIEVAL AND DATA ANALYSIS CAPABILITIES (OWEVER DATABASE EXPERTS HAVE POINTED OUT MANY LIMITATIONS OF THESE MAINSTREAM QUERY CAPABILITIES INCLUDING THESE
s ,IMITED USE OF SUBQUERIES 4HE SIMPLEST EXAMPLE OF THIS LIMITATION IS THE 31, RESTRICTION THAT A SUBQUERY CAN APPEAR ONLY ON THE RIGHT SIDE OF A COMPARISON TEST IN A 7(%2% CLAUSE 4HE DATABASE REQUEST h,IST THE OFFICES WHERE THE SUM OF THE SALESPEOPLES QUOTAS IS LESS THAN THE OFFICE TARGETv IS MOST DIRECTLY EXPRESSED AS THIS QUERY 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#% 4!2'%4
7HILE THIS ISNT A LEGAL 31, STATEMENT IT IS SUPPORTED IN SUBSEQUENT VERSIONS OF THE 31, STANDARD .ONETHELESS MOST PEOPLE UNDERSTAND IT MORE READILY IF YOU TURN THE INEQUALITY AROUND 3%,%#4 /&&)#% &2/- /&&)#%3 7(%2% 4!2'%4 3%,%#4 35-15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /&&)#%
)N THIS SIMPLE EXAMPLE IT ISNT HARD TO TURN THE LOGIC AROUND BUT THE RESTRICTION IS A NUISANCE AT BEST AND IT DOES PREVENT YOU FROM COMPARING THE RESULTS OF TWO SUBQUERIES FOR EXAMPLE
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s .O DECISION MAKING WITHIN QUERIES 3UPPOSE YOU WANTED TO GENERATE A TWO COLUMN REPORT FROM THE SAMPLE DATABASE SHOWING THE NAME OF EACH SALES OFFICE AND EITHER ITS ANNUAL SALES TARGET OR ITS YEAR TO DATE SALES WHICHEVER IS LARGER 7ITH THE MAINSTREAM 31, QUERY FEATURES THIS IS HARD TO DO /R SUPPOSE YOU HAD A DATABASE THAT KEPT TRACK OF SALES BY QUARTER FOUR COLUMNS OF DATA FOR EACH OFFICE AND WANTED TO WRITE A PROGRAM THAT DISPLAYED OFFICES AND THEIR SALES FOR A SPECIFIC USER SUPPLIED QUARTER !GAIN THIS PROGRAM IS MORE DIFFICULT TO WRITE USING MAINSTREAM 31, QUERIES 9OU MUST INCLUDE FOUR SEPARATE 31, QUERIES ONE FOR EACH QUARTER AND THE PROGRAM LOGIC MUST SELECT WHICH QUERY TO RUN BASED ON USER INPUT 4HIS SIMPLE CASE ISNT TOO DIFFICULT BUT IN A MORE GENERAL CASE THE PROGRAM COULD BECOME MUCH MORE COMPLEX
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s ,IMITED ROW EXPRESSIONS 3UPPOSE YOU WANTED TO LIST THE SUPPLIERS ITEM NUMBERS AND PRICES FOR A SET OF PRODUCTS THAT ARE SUBSTITUTES FOR ONE ANOTHER #ONCEPTUALLY THESE ARE A SET OF PRODUCTS WHOSE IDENTIFICATION A MANUFACTURER )$PRODUCT )$ PAIR MATCHES ONE OF A SET OF VALUES AND IT WOULD BE NATURAL TO WRITE THE QUERY USING A SET MEMBERSHIP TEST 3%,%#4 -&2?)$ 02/$5#4?)$ 02)#% &2/- 02/$5#43 7(%2% -&2?)$ 02/$5#4?)$ ). g!#)g g")#g x
4HE 31, STANDARD DOESNT PERMIT THIS KIND OF SET MEMBERSHIP TEST )NSTEAD YOU MUST CONSTRUCT THE QUERY AS A LONG SET OF INDIVIDUAL COMPARISONS CONNECTED BY !.$S AND /2S s ,IMITED TABLE EXPRESSIONS 31, ALLOWS YOU TO DEFINE A VIEW LIKE THIS ONE FOR LARGE ORDERS 3%,%#4 &2/- /2$%23 7(%2% !-/5.4
AND THEN TO USE THE VIEW AS IF IT WERE A REAL TABLE IN THE &2/- CLAUSE OF A QUERY TO FIND OUT WHICH PRODUCTS IN WHICH QUANTITIES WERE ORDERED IN THESE LARGE ORDERS 3%,%#4 -&2 02/$5#4 35-149 &2/- ")'/2$%23 '2/50 "9 -&2 02/$5#4
#ONCEPTUALLY 31, SHOULD LET YOU SUBSTITUTE THE VIEW DEFINITION RIGHT INTO THE QUERY LIKE THIS 3%,%#4 -&2 02/$5#4 35-149 &2/- 3%,%#4 &2/- /2$%23 7(%2% !-/5.4 ! '2/50 "9 -&2 02/$5#4
"UT THE 31, STANDARD DOESNT ALLOW A SUBQUERY IN THIS POSITION IN THE 7(%2% CLAUSE 9ET CLEARLY THE $"-3 SHOULD BE ABLE TO DETERMINE THE MEANING OF THIS QUERY SINCE IT MUST BASICALLY DO THE SAME PROCESSING TO INTERPRET THE ")'/2$%23 VIEW DEFINITION !S THESE EXAMPLES SHOW THE 31, STANDARD AND $"-3 PRODUCTS THAT IMPLEMENT TO THIS LEVEL OF THE STANDARD ARE RELATIVELY RESTRICTIVE IN THEIR PERMITTED USE OF EXPRESSIONS INVOLVING INDIVIDUAL DATA ITEMS SETS OF DATA ITEMS ROWS AND TABLES 3UBSEQUENT VERSIONS OF THE 31, STANDARD INCLUDE A NUMBER OF ADVANCED QUERY CAPABILITIES THAT ARE FOCUSED ON REMOVING THESE RESTRICTIONS AND MAKING THE 31, LANGUAGE MORE GENERAL 4HE SPIRIT OF THESE CAPABILITIES TENDS TO BE THAT A USER SHOULD BE ABLE TO WRITE A QUERY EXPRESSION THAT MAKES SENSE AND HAVE THE QUERY EXPRESSION BE A LEGAL 31, QUERY "ECAUSE THESE CAPABILITIES CONSTITUTE MAJOR EXPANSIONS OF THE LANGUAGE OVER THE ORIGINAL 31, STANDARD MOST OF THEM ARE REQUIRED ONLY AT A FULL LEVEL OF THE STANDARD
#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
3CALAR 6ALUEDõ%XPRESSIONS 4HE SIMPLEST EXTENDED QUERY CAPABILITIES IN 31, ARE THOSE THAT PROVIDE MORE DATA MANIPULATION AND CALCULATION POWER INVOLVING INDIVIDUAL DATA VALUES CALLED SCALARS IN THE 31, STANDARD 7ITHIN THE 31, LANGUAGE INDIVIDUAL DATA VALUES TEND TO HAVE THREE SOURCES s 4HE VALUE OF AN INDIVIDUAL COLUMN WITHIN AN INDIVIDUAL ROW OF A TABLE s ! LITERAL VALUE SUCH AS OR !"# s ! USER SUPPLIED DATA VALUE ENTERED INTO A PROGRAM )N THIS 31, QUERY
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3%,%#4 .!-% %-0,?.5- ()2%?$!4% 15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% /2 4)4,% g60 3ALESg
THE COLUMN NAMES .!-% %-0,?.5- ()2%?$!4% AND 15/4! GENERATE INDIVIDUAL DATA VALUES FOR EACH ROW OF QUERY RESULTS AS DO THE COLUMN NAMES 2%0?/&&)#% AND 4)4,% IN THE 7(%2% CLAUSE 4HE NUMBERS AND AND THE CHARACTER STRING h60 3ALESv SIMILARLY GENERATE INDIVIDUAL DATA VALUES )F THIS 31, STATEMENT WERE TO APPEAR WITHIN AN EMBEDDED 31, PROGRAM DESCRIBED IN #HAPTER THE PROGRAM VARIABLE OFFICE?NUM MIGHT CONTAIN AN INDIVIDUAL DATA VALUE AND THE QUERY MIGHT APPEAR AS 3%,%#4 .!-% %-0,?.5- ()2%?$!4% 15/4! &2/- 3!,%32%03 7(%2% 2%0?/&&)#% OFFICE?NUM /2 4)4,% g60 3!,%3g
!S THIS QUERY AND MANY PREVIOUS EXAMPLES HAVE SHOWN INDIVIDUAL DATA VALUES CAN BE COMBINED IN SIMPLE EXPRESSIONS LIKE THE CALCULATED VALUE 15/4! 4O THESE BASIC EXPRESSIONS THE 31, STANDARD ADDS THE #!34 OPERATOR FOR EXPLICIT DATA TYPE CONVERSION THE #!3% OPERATOR FOR DECISION MAKING THE #/!,%3#% OPERATOR FOR CONDITIONALLY CREATING NON .5,, VALUES AND THE .5,,)& OPERATION FOR CONDITIONALLY CREATING A .5,, VALUE
4HEõ#!34õ%XPRESSION 4HE 31, STANDARD HAS FAIRLY RESTRICTIVE RULES ABOUT COMBINING DATA OF DIFFERENT TYPES IN EXPRESSIONS )T SPECIFIES THAT THE $"-3 SHALL AUTOMATICALLY CONVERT AMONG VERY SIMILAR DATA TYPES SUCH AS BYTE AND BYTE INTEGERS (OWEVER IF YOU TRY TO COMPARE NUMBERS AND CHARACTER DATA FOR EXAMPLE THE STANDARD SAYS THAT THE $"-3 SHOULD GENERATE AN ERROR 4HE STANDARD CONSIDERS THIS AN ERROR CONDITION EVEN IF THE CHARACTER STRING CONTAINS NUMERIC DATA 9OU CAN HOWEVER EXPLICITLY ASK THE $"-3 TO CONVERT AMONG DATA TYPES USING THE #!34 EXPRESSION WHICH HAS THE SYNTAX SHOWN IN &IGURE
1, ÊÊ Ê #!34ÊiÝ«ÀiÃÃÊ ÃÞÌ>ÝÊ`>}À>
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4HE #!34 EXPRESSION TENDS TO BE OF LITTLE IMPORTANCE WHEN YOU ARE TYPING 31, STATEMENTS DIRECTLY INTO AN INTERACTIVE 31, INTERFACE (OWEVER IT CAN BE CRITICAL WHEN USING 31, FROM WITHIN A PROGRAMMING LANGUAGE WHERE DATA TYPES DONT MATCH THE DATA TYPES SUPPORTED BY THE 31, STANDARD &OR EXAMPLE THE #!34 EXPRESSION IN THE 3%,%#4 CLAUSE OF THIS QUERY CONVERTS THE VALUES FOR 2%0?/&&)#% INTEGERS IN THE SAMPLE DATABASE AND ()2%? $!4% A DATE IN THE SAMPLE DATABASE INTO CHARACTER STRINGS FOR THE RETURNED QUERY RESULTS 3%,%#4 .!-% #!34 2%0?/&&)#% !3 #(!2 #!34 ()2%?$!4% !3 #(!2 &2/- 3!,%32%03
3UPPORT FOR THE #!34 EXPRESSION VARIES ACROSS 31, IMPLEMENTATIONS &OR EXAMPLE /RACLE REQUIRES THAT #(!2 AND 6!2#(!2 DATA TYPES USED IN A #!34 EXPRESSION INCLUDE A LENGTH SPECIFICATION WHILE -Y31, AND $" 5$" DO NOT SUPPORT THE $!4% DATA TYPE IN A #!34 EXPRESSION 4HE #!34 EXPRESSION CAN GENERALLY APPEAR ANYWHERE THAT A SCALAR VALUED EXPRESSION CAN APPEAR WITHIN A 31, STATEMENT )N THIS EXAMPLE ITS USED IN THE 7(%2% CLAUSE TO CONVERT A CHARACTER STRING CUSTOMER NUMBER INTO AN INTEGER SO THAT IT CAN BE COMPARED WITH THE DATA IN THE DATABASE 3%,%#4 02/$5#4 149 !-/5.4 &2/- /2$%23 7(%2% #534 #!34 gg !3 ).4%'%2
)NSTEAD OF SPECIFYING A DATA TYPE IN THE #!34 EXPRESSION YOU CAN SPECIFY A DOMAIN $OMAINS ARE SPECIFIC COLLECTIONS OF LEGAL DATA VALUES THAT CAN BE DEFINED IN THE DATABASE 4HEY ARE FULLY DESCRIBED IN #HAPTER BECAUSE OF THE ROLE THEY PLAY IN 31, DATA INTEGRITY .OTE THAT YOU CAN ALSO GENERATE A .5,, VALUE OF THE APPROPRIATE DATA TYPE FOR USE IN 31, EXPRESSIONS USING THE #!34 EXPRESSION 4HE MOST COMMON USES FOR THE #!34 EXPRESSION ARE s 4O CONVERT DATA FROM WITHIN A DATABASE TABLE WHERE THE COLUMN IS DEFINED WITH THE WRONG DATA TYPE FOR EXAMPLE WHEN A COLUMN IS DEFINED AS A CHARACTER STRING BUT YOU KNOW IT ACTUALLY CONTAINS NUMBERS THAT IS STRINGS OF DIGITS OR DATES STRINGS THAT CAN BE INTERPRETED AS A CALENDAR DATE s 4O CONVERT DATA FROM DATA TYPES SUPPORTED BY THE $"-3 THAT ARE NOT SUPPORTED BY A HOST PROGRAMMING LANGUAGE &OR EXAMPLE MOST HOST PROGRAMMING LANGUAGES DO NOT HAVE EXPLICIT DATE AND TIME DATA TYPES AND REQUIRE THAT DATETIME VALUES BE CONVERTED INTO CHARACTER STRINGS FOR HANDLING BY A PROGRAM s 4O ELIMINATE DIFFERENCES BETWEEN DATA TYPES IN TWO DIFFERENT TABLES &OR EXAMPLE IF AN ORDER DATE IS STORED IN ONE TABLE AS $!4% DATA BUT A PRODUCT AVAILABILITY DATE IS STORED IN A DIFFERENT TABLE AS A CHARACTER STRING YOU CAN STILL COMPARE THE COLUMNS FROM THE TWO TABLES BY #!34ING ONE OF THE COLUMNS INTO THE DATA TYPE OF THE OTHER 3IMILARLY IF YOU WANT TO COMBINE DATA FROM TWO DIFFERENT TABLES WITH A 5.)/. OPERATION THEIR COLUMNS MUST HAVE IDENTICAL DATA TYPES 9OU CAN ACHIEVE THIS BY #!34ING THE COLUMNS OF ONE OF THE TABLES
#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
1, Ê£äÊ #!3%ÊiÝ«ÀiÃÃÊÃÞÌ>ÝÊ`>}À>
4HEõ#!3%õ%XPRESSION
3%,%#4 #/-0!.9 #!3% 7(%. #2%$)4?,)-)4 4(%. g!g 7(%. #2%$)4?,)-)4 4(%. g"g %,3% g#g %.$ !3 #2%$)4?2!4).' &2/- #534/-%23
&OR EACH ROW OF QUERY RESULTS THE $"-3 EVALUATES THE #!3% EXPRESSION BY FIRST COMPARING THE CREDIT LIMIT WITH AND IF THE COMPARISON IS 425% RETURNING AN ! IN THE SECOND COLUMN OF QUERY RESULTS )F THAT COMPARISON FAILS THE COMPARISON TO IS MADE AND A " IS RETURNED IF THIS SECOND COMPARISON IS 425% /THERWISE THE THIRD COLUMN OF QUERY RESULTS RETURNS A # 4HIS IS A VERY SIMPLE EXAMPLE OF A #!3% EXPRESSION 4HE RESULTS OF THE #!3% EXPRESSION ARE ALL LITERALS HERE BUT IN GENERAL THEY CAN BE ANY 31, EXPRESSION 3IMILARLY THERE IS NO REQUIREMENT THAT THE TESTS IN EACH 7(%. CLAUSE BE SIMILAR AS THEY ARE HERE 4HE #!3% EXPRESSION CAN ALSO APPEAR IN OTHER CLAUSES OF A QUERY PROVIDED THE 31, IMPLEMENTATION SUPPORTS SUCH USE (ERE IS AN EXAMPLE OF A QUERY WHERE THE #!3% EXPRESSION IS USEFUL IN THE 7(%2% CLAUSE 3UPPOSE YOU WANT TO FIND THE TOTAL OF THE SALESPEOPLES SALES BY OFFICE )F A SALESPERSON IS NOT YET ASSIGNED TO AN OFFICE THAT PERSON
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4HE #!3% EXPRESSION PROVIDES FOR LIMITED DECISION MAKING WITHIN 31, EXPRESSIONS )TS BASIC STRUCTURE SHOWN IN &IGURE IS SIMILAR TO THE )&x4(%.x%,3% STATEMENT FOUND IN MANY PROGRAMMING LANGUAGES 7HEN THE $"-3 ENCOUNTERS A #!3% EXPRESSION IT EVALUATES THE FIRST SEARCH CONDITION AND IF IT IS 425% THEN THE VALUE OF THE #!3% EXPRESSION IS THE VALUE OF THE FIRST RESULT EXPRESSION )F THE RESULT OF THE FIRST SEARCH CONDITION IS NOT 425% THE $"-3 PROCEEDS TO THE SECOND SEARCH CONDITION AND CHECKS WHETHER IT IS 425% )F SO THE VALUE OF THE #!3% EXPRESSION IS THE VALUE OF THE SECOND RESULT EXPRESSION AND SO ON (ERE IS A SIMPLE EXAMPLE OF THE USE OF THE #!3% EXPRESSION 3UPPOSE YOU WANT TO DO AN !"# ANALYSIS OF THE CUSTOMERS FROM THE SAMPLE DATABASE ACCORDING TO THEIR CREDIT LIMITS 4HE ! CUSTOMERS ARE THE ONES WITH CREDIT LIMITS OVER THE " CUSTOMERS ARE THOSE WITH LIMITS OVER AND THE # CUSTOMERS ARE THE OTHERS 7ITHOUT THE #!3% EXPRESSION YOU WOULD HAVE TO RETRIEVE CUSTOMER NAMES AND CREDIT LIMITS FROM THE DATABASE AND THEN RELY ON AN APPLICATION PROGRAM TO LOOK AT THE CREDIT LIMIT VALUES AND ASSIGN AN ! " OR # RATING 5SING A #!3% EXPRESSION YOU CAN HAVE THE $"-3 DO THE WORK FOR YOU
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SHOULD BE INCLUDED IN THE TOTAL FOR HIS OR HER MANAGERS OFFICE (ERE IS A QUERY THAT GENERATES THE APPROPRIATE OFFICE GROUPINGS 3%,%#4 #)49 35-3!,%32%033!,%3 &2/- /&&)#%3 3!,%32%03 7(%2% /&&)#% #!3% 7(%. 2%0?/&&)#% )3 ./4 .5,, 4(%. 2%0?/&&)#% %,3% 3%,%#4 2%0?/&&)#% &2/- 3!,%32%03 -'23 7(%2% -'23%-0,?.5- -!.!'%2 %.$ '2/50 "9 #)49
4HE 31, STANDARD PROVIDES A SHORTHAND VERSION OF THE #!3% EXPRESSION FOR THE COMMON SITUATION WHERE YOU WANT TO COMPARE A TEST VALUE OF SOME KIND WITH A SEQUENCE OF DATA VALUES USUALLY LITERALS 4HIS VERSION OF THE #!3% SYNTAX IS SHOWN IN &IGURE )NSTEAD OF REPEATING A SEARCH CONDITION OF THE FORM TEST?VALUE VALUE
IN EACH 7(%. CLAUSE IT LETS YOU SPECIFY THE TEST?VALUE CALCULATION ONCE &OR EXAMPLE SUPPOSE YOU WANTED TO GENERATE A LIST OF ALL OF THE OFFICES SHOWING THE NAMES OF THEIR MANAGERS AND THE CITIES AND STATES WHERE THEY ARE 4HE SAMPLE DATABASE DOESNT INCLUDE STATE NAMES SO THE QUERY MUST GENERATE THIS INFORMATION ITSELF (ERE IS A QUERY WITH A #!3% EXPRESSION IN THE 3%,%#4 LIST THAT DOES THE JOB 3%,%#4 .!-% #)49 #!3% /&&)#% 7(%. 4(%. g.EW 9ORKg 7(%. 4(%. g)LLINOISg 7(%. 4(%. g'EORGIAg 7(%. 4(%. g#ALIFORNIAg 7(%. 4(%. g#OLORADOg %.$ !3 34!4% &2/- /&&)#%3 3!,%32%03 7(%2% -'2 %-0,?.5-
4HEõ#/!,%3#%õ%XPRESSION /NE OF THE MOST COMMON USES FOR THE DECISION MAKING CAPABILITY OF THE #!3% EXPRESSION IS FOR HANDLING .5,, VALUES WITHIN THE DATABASE &OR EXAMPLE ITS FREQUENTLY DESIRABLE TO HAVE A .5,, VALUE FROM THE DATABASE REPRESENTED BY SOME LITERAL VALUE SUCH AS THE WORD hMISSINGv OR BY SOME DEFAULT VALUE WHEN USING 31, TO GENERATE A REPORT (ERE IS A REPORT THAT LISTS THE SALESPEOPLE AND THEIR QUOTAS )F A SALESPERSON HAS NOT YET BEEN ASSIGNED A QUOTA ASSUME THAT THE SALESPERSONS ACTUAL YEAR TO DATE SALES SHOULD BE LISTED INSTEAD )F FOR
1, Ê££Ê #!3%ÊiÝ«ÀiÃÃÊ>ÌiÀ>ÌiÊÃÞÌ>Ý
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#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
SOME REASON THE ACTUAL YEAR TO DATE SALES ARE ALSO .5,, UNKNOWN THEN A ZERO AMOUNT SHOULD BE LISTED 4HE #!3% STATEMENT GENERATES THE DESIRED )&x4(%.x%,3% LOGIC
4HIS TYPE OF .5,, HANDLING LOGIC IS NEEDED FREQUENTLY SO THE 31, STANDARD INCLUDES A SPECIALIZED FORM OF THE #!3% EXPRESSION THE #/!,%3#% EXPRESSION TO HANDLE IT 4HE SYNTAX FOR THE #/!,%3#% EXPRESSION IS SHOWN IN &IGURE 4HE PROCESSING RULES FOR THE #/!,%3#% EXPRESSION ARE VERY STRAIGHTFORWARD 4HE $"-3 EXAMINES THE FIRST VALUE IN THE LIST )F ITS VALUE IS NOT .5,, IT BECOMES THE VALUE OF THE #/!,%3#% EXPRESSION )F THE FIRST VALUE IS .5,, THE $"-3 MOVES TO THE SECOND VALUE AND CHECKS TO SEE WHETHER IT IS .5,, )F NOT IT BECOMES THE VALUE OF THE EXPRESSION /THERWISE THE $"-3 MOVES TO THE THIRD VALUE AND SO ON (ERE IS THE SAME EXAMPLE JUST GIVEN EXPRESSED WITH THE #/!,%3#% EXPRESSION INSTEAD OF A #!3% EXPRESSION 3%,%#4 .!-% #/!,%3#%15/4! 3!,%3 &2/- 3!,%32%03
!S YOU CAN SEE BY COMPARING THE TWO QUERIES THE SIMPLICITY OF THE #/!,%3#% SYNTAX MAKES IT EASIER TO SEE AT A GLANCE THE MEANING OF THE QUERY (OWEVER THE OPERATION OF THE TWO QUERIES IS IDENTICAL 4HE #/!,%3#% EXPRESSION ADDS SIMPLICITY BUT NO NEW CAPABILITY TO 31,
4HEõ.5,,)&õ%XPRESSION *UST AS THE #/!,%3#% EXPRESSION IS USED TO ELIMINATE .5,, VALUES WHEN THEY ARE NOT DESIRED FOR PROCESSING SOMETIMES YOU MAY NEED TO CREATE .5,, VALUES )N MANY DATA PROCESSING APPLICATIONS ESPECIALLY OLDER ONES THAT WERE DEVELOPED BEFORE RELATIONAL DATABASES WERE POPULAR MISSING DATA IS NOT REPRESENTED BY .5,, VALUES )NSTEAD SOME SPECIAL CODE VALUE THAT IS OTHERWISE INVALID IS USED TO INDICATE THAT THE DATA IS MISSING &OR EXAMPLE SUPPOSE THAT IN THE SAMPLE DATABASE THE SITUATION WHERE A SALESPERSON HAD NOT YET BEEN ASSIGNED A MANAGER WAS INDICATED BY A ZERO VALUE IN THE -!.!'%2 COLUMN INSTEAD OF A .5,, VALUE )N SOME CIRCUMSTANCES YOU WILL WANT TO DETECT THIS SITUATION WITHIN A 31, QUERY AND SUBSTITUTE THE .5,, VALUE FOR THE ZERO hCODEv 4HE .5,,)& EXPRESSION SHOWN IN &IGURE IS USED FOR THIS PURPOSE 7HEN THE $"-3 ENCOUNTERS A .5,,)& EXPRESSION IT EXAMINES THE FIRST VALUE USUALLY A COLUMN NAME AND COMPARES IT WITH THE 1, Ê£ÎÊ Ê .5,,)&Ê iÝ«ÀiÃÃÊÃÞÌ>ÝÊ `>}À>
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3%,%#4 .!-% #!3% 7(%. 15/4! )3 ./4 .5,, 4(%. 15/4! 7(%. 3!,%3 )3 ./4 .5,, 4(%. 3!,%3 %,3% %.$ !3 !$*534%$?15/4! &2/- 3!,%32%03
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SECOND VALUE USUALLY THE CODE VALUE USED TO INDICATE MISSING DATA )F THE TWO VALUES ARE EQUAL THE EXPRESSION GENERATES A .5,, VALUE /THERWISE THE EXPRESSION GENERATES THE FIRST VALUE (ERE IS A QUERY THAT HANDLES THE CASE WHERE MISSING OFFICE NUMBERS ARE REPRESENTED BY A ZERO 3%,%#4 #)49 35-3!,%32%033!,%3 &2/- /&&)#%3 3!,%32%03 7(%2% /&&)#% .5,,)&2%0?/&&)#% '2/50 "9 #)49
4OGETHER THE #!3% #/!,%3#% AND .5,,)& EXPRESSIONS PROVIDE A SOLID DECISION MAKING LOGIC CAPABILITY FOR USE WITHIN 31, STATEMENTS 4HEY FALL FAR SHORT OF THE COMPLETE LOGICAL FLOW CONSTRUCTS PROVIDED BY MOST PROGRAMMING LANGUAGES LOOPING BRANCHING AND SO ON BUT DO PROVIDE FOR MUCH GREATER FLEXIBILITY IN QUERY EXPRESSIONS 4HE NET RESULT IS THAT MORE PROCESSING WORK CAN BE DONE BY THE $"-3 AND REFLECTED IN QUERY RESULTS LEAVING LESS WORK TO BE DONE BY THE HUMAN USER OR THE APPLICATION PROGRAM
2OW 6ALUEDõ%XPRESSIONS !LTHOUGH COLUMNS AND THE SCALAR DATA VALUES THEY CONTAIN ARE THE ATOMIC BUILDING BLOCKS OF A RELATIONAL DATABASE THE STRUCTURING OF COLUMNS INTO ROWS THAT REPRESENT REAL WORLD ENTITIES SUCH AS INDIVIDUAL OFFICES OR CUSTOMERS OR ORDERS IS ONE OF THE MOST IMPORTANT FEATURES OF THE RELATIONAL MODEL 4HE 31, STANDARD AND MOST MAINSTREAM COMMERCIAL DATABASE PRODUCTS CERTAINLY REFLECT THIS ROWCOLUMN STRUCTURE BUT THEY PROVIDE VERY LIMITED CAPABILITY TO ACTUALLY MANIPULATE ROWS AND GROUPS OF ROWS "ASICALLY 31, OPERATIONS ALLOW YOU TO INSERT A ROW INTO A TABLE OR TO RETRIEVE UPDATE OR DELETE GROUPS OF ROWS FROM A DATABASE USING THE ).3%24 3%,%#4 50$!4% OR $%,%4% STATEMENTS .EWER VERSIONS OF THE 31, STANDARD GO WELL BEYOND THESE CAPABILITIES ALLOWING YOU TO GENERALLY USE ROWS IN 31, EXPRESSIONS IN MUCH THE SAME WAY THAT YOU CAN USE SCALAR VALUES 4HEY PROVIDE SYNTAX FOR CONSTRUCTING ROWS OF DATA 4HEY ALLOW ROW VALUED SUBQUERIES !ND THEY DEFINE ROW VALUED MEANINGS FOR THE 31, COMPARISON OPERATORS AND OTHER 31, STRUCTURES
4HEõ2OW 6ALUEõ#ONSTRUCTOR 31, ALLOWS YOU TO SPECIFY A ROW OF DATA VALUES BY USING A ROW VALUE CONSTRUCTOR EXPRESSION WHOSE SYNTAX IS SHOWN IN &IGURE )N ITS MOST COMMON FORM THE ROW CONSTRUCTOR IS A COMMA SEPARATED LIST OF LITERAL VALUES OR EXPRESSIONS &OR EXAMPLE HERE IS A ROW VALUE CONSTRUCTOR FOR A ROW OF DATA WHOSE STRUCTURE MATCHES THE /&&)#%3 TABLE IN THE SAMPLE DATABASE g3AN $IEGOg g7ESTERNg .5,, $%&!5,4 1, Ê£{Ê Ê ,ÜÛ>ÕiÊ VÃÌÀÕVÌÀÊÃÞÌ>ÝÊ `>}À>
#HAPTERçç
3UBQUERIESçANDç1UERYç%XPRESSIONSç
4HE RESULT OF THIS EXPRESSION IS A SINGLE ROW OF DATA WITH SIX COLUMNS 4HE .5,, KEYWORD IN THE FOURTH COLUMN POSITION INDICATES THAT THE FOURTH COLUMN IN THE CONSTRUCTED ROW SHOULD CONTAIN A .5,, UNKNOWN VALUE 4HE $%&!5,4 KEYWORD IN THE FIFTH COLUMN POSITION INDICATES THAT THE FIFTH COLUMN IN THE CONSTRUCTED ROW SHOULD CONTAIN THE DEFAULT VALUE FOR THE COLUMN 4HIS KEYWORD MAY APPEAR IN A ROW VALUE CONSTRUCTOR ONLY IN CERTAIN SITUATIONSFOR EXAMPLE WHEN THE ROW VALUE CONSTRUCTOR APPEARS IN AN ).3%24 STATEMENT TO ADD A NEW ROW TO A TABLE 7HEN A ROW CONSTRUCTOR IS USED IN THE 7(%2% CLAUSE OF A 31, STATEMENT COLUMN NAMES CAN ALSO APPEAR AS INDIVIDUAL DATA ITEMS WITHIN THE ROW CONSTRUCTOR OR AS PART OF AN EXPRESSION WITHIN THE ROW CONSTRUCTOR &OR EXAMPLE CONSIDER THIS QUERY
3%,%#4 /2$%2?.5- 149 !-/5.4 &2/- /2$%23 7(%2% -'2 02/$5#4 g!#)g gg
.OTE THAT WHILE THIS SYNTAX IS SPECIFIED IN THE 31, STANDARD VERY FEW 31, IMPLEMENTATIONS SUPPORT IT 5NDER THE NORMAL RULES OF 31, QUERY PROCESSING THE 7(%2% CLAUSE IS APPLIED TO EACH ROW OF THE /2$%23 TABLE ONE BY ONE 4HE FIRST ROW VALUE CONSTRUCTOR IN THE 7(%2% CLAUSE TO THE LEFT OF THE EQUAL SIGN GENERATES A TWO COLUMN ROW CONTAINING THE MANUFACTURER CODE AND THE PRODUCT NUMBER FOR THE CURRENT ORDER BEING CONSIDERED 4HE SECOND ROW VALUE CONSTRUCTOR TO THE RIGHT OF THE EQUAL SIGN GENERATES A TWO COLUMN ROW CONTAINING THE LITERAL MANUFACTURER CODE !#) AND PRODUCT NUMBER 4HE EQUAL SIGN IS NOW COMPARING TWO ROWS OF VALUES NOT TWO SCALAR VALUES 4HE 31, STANDARD DEFINES THIS TYPE OF ROW VALUED COMPARISON FOR EQUALITY WHICH IS PROCESSED BY COMPARING PAIRWISE EACH OF THE COLUMNS IN THE TWO ROWS 4HE RESULT OF THE COMPARISON IS 425% ONLY IF ALL OF THE PAIRWISE COLUMN COMPARISONS ARE 425% /F COURSE ITS POSSIBLE TO WRITE THE QUERY WITHOUT THE ROW VALUE CONSTRUCTORS LIKE THIS ,IST THE ORDER NUMBER QUANTITY AND AMOUNT OF ALL ORDERS FOR !#) WIDGETS 3%,%#4 /2$%2?.5- 149 !-/5.4 &2/- /2$%23 7(%2% -&2 g!#)g !.$ 02/$5#4 gg
AND IN THIS SIMPLE EXAMPLE THE MEANING OF THE QUERY IS PROBABLY EQUALLY CLEAR WITH EITHER FORM (OWEVER ROW VALUE CONSTRUCTORS CAN BE VERY USEFUL IN SIMPLIFYING THE APPEARANCE OF MORE COMPLEX QUERIES AND THEY BECOME EVEN MORE USEFUL WHEN COMBINED WITH ROW VALUED SUBQUERIES
2OW 6ALUEDõ3UBQUERIES !S DESCRIBED THROUGHOUT THE EARLIER PARTS OF THIS CHAPTER THE 31, STANDARD PROVIDES A SUBQUERY CAPABILITY FOR EXPRESSING MORE COMPLEX DATABASE QUERIES 4HE SUBQUERY TAKES THE SAME FORM AS A 31, QUERY THAT IS A 3%,%#4 STATEMENT BUT A 31, SUBQUERY MUST BE SCALAR VALUEDTHAT IS IT MUST PRODUCE A SINGLE DATA VALUE AS ITS QUERY RESULTS 4HE VALUE GENERATED BY THE SUBQUERY IS THEN USED AS PART OF AN EXPRESSION WITHIN THE MAIN 31, STATEMENT THAT CONTAINS THE SUBQUERY 4HIS USE OF SUBQUERIES IS SUPPORTED BY THE MAJOR ENTERPRISE CLASS RELATIONAL DATABASE SYSTEMS TODAY 3UBSEQUENT VERSIONS OF THE 31, STANDARD DRAMATICALLY EXPAND THE SUBQUERY FACILITY INCLUDING SUPPORT FOR ROW VALUED SUBQUERIES ! ROW VALUED SUBQUERY RETURNS NOT JUST A SINGLE DATA ITEM BUT A ROW OF DATA ITEMS WHICH CAN BE USED IN 31, EXPRESSIONS AND COMPARED
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,IST THE ORDER NUMBER QUANTITY AND AMOUNT OF ALL ORDERS FOR !#) WIDGETS
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WITH OTHER ROWS &OR EXAMPLE SUPPOSE YOU WANTED TO SHOW THE ORDER NUMBERS AND DATES FOR ALL OF THE ORDERS PLACED AGAINST THE HIGHEST PRICED PRODUCT IN THE SAMPLE DATABASE ! LOGICAL WAY TO START BUILDING THE APPROPRIATE 31, QUERY IS TO FIND AN EXPRESSION THAT WILL GIVE YOU THE IDENTITY MANUFACTURER )$ AND PRODUCT )$ OF THE HIGH PRICED PRODUCT IN QUESTION (ERE IS A QUERY THAT FINDS THE RIGHT PRODUCT &IND THE MANUFACTURER )$ AND PRODUCT )$ OF THE PRODUCT WITH THE HIGHEST UNIT PRICE 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 3%,%#4 -!802)#% &2/- 02/$5#43
)GNORING THE POSSIBILITY OF A TIE FOR THE MOST EXPENSIVE PRODUCT FOR A MOMENT THIS QUERY WILL GENERATE A SINGLE ROW OF QUERY RESULTS CONSISTING OF TWO COLUMNS 5SING 31,S ROW VALUED SUBQUERY CAPABILITY YOU CAN EMBED THIS ENTIRE QUERY AS A SUBQUERY WITHIN A 3%,%#4 STATEMENT TO RETRIEVE THE ORDER INFORMATION AS SHOWN IN THE NEXT EXAMPLE ,IST THE ORDER NUMBERS AND DATES OF ALL ORDERS PLACED FOR THE HIGHEST PRICED PRODUCT 3%,%#4 /2$%2?.5- /2$%2?$!4% &2/- /2$%23 7(%2% -&2 02/$5#4 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 3%,%#4 -!802)#% &2/- 02/$5#43
4HE TOP LEVEL 7(%2% CLAUSE IN THIS QUERY CONTAINS A ROW VALUED COMPARISON /N THE LEFT SIDE OF THE EQUAL SIGN IS A ROW VALUE CONSTRUCTOR CONSISTING OF TWO COLUMN NAMES %ACH TIME THE 7(%2% CLAUSE IS EXAMINED TO CARRY OUT THE TOP LEVEL QUERY THE VALUE OF THIS ROW VALUED EXPRESSION IS A MANUFACTURER )$PRODUCT )$ PAIR FROM A ROW OF THE /2$%23 TABLE /N THE RIGHT SIDE OF THE EQUAL SIGN IS THE SUBQUERY THAT GENERATES THE IDENTITY OF THE PRODUCT WITH THE HIGHEST DOLLAR VALUE 4HE RESULT OF THIS SUBQUERY IS AGAIN A ROW VALUE WITH TWO COLUMNS WHOSE DATA TYPES MATCH THOSE OF THE ROW VALUED EXPRESSION ON THE LEFT SIDE OF THE EQUAL SIGN )TS POSSIBLE TO EXPRESS THIS QUERY WITHOUT THE ROW VALUED SUBQUERY BUT THE RESULTING QUERY WILL BE MUCH LESS STRAIGHTFORWARD ,IST THE ORDER NUMBERS AND DATES OF ALL ORDERS PLACED FOR THE HIGHEST PRICED PRODUCTS 3%,%#4 /2$%2?.5- /2$%2?$!4% &2/- /2$%23 7(%2% -&2 ). 3%,%#4 -&2?)$ &2/- 02/$5#43 7(%2% 02)#% 3%,%#4 -!802)#% &2/- 02/$5#43 !.$ 02/$5#4 ). 3%,%#4 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 3%,%#4 -!802)#% &2/- 02/$5#43
)NSTEAD OF A SINGLE ROW VALUED COMPARISON IN THE 7(%2% CLAUSE THE RESULTING QUERY HAS TWO SEPARATE SCALAR VALUED COMPARISONS ONE FOR THE MANUFACTURER )$ AND ONE FOR THE PRODUCT )$ "ECAUSE THE COMPARISON MUST BE SPLIT THE LOWER LEVEL SUBQUERY TO FIND THE
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MAXIMUM PRICE MUST BE REPEATED TWICE AS WELL /VERALL THE FORM OF THE QUERY USING THE ROW VALUED EXPRESSION IS A MORE DIRECT TRANSLATION OF THE %NGLISH LANGUAGE REQUEST AND ITS EASIER TO READ AND UNDERSTAND
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g!#)g gg g2%)g g!2g BASED ON lRST COLUMN g!#)g gg g!#)g gg BASED ON SECOND COLUMN g!#)g gg g!#)g gg BASED ON THIRD COLUMN
4ABLE 6ALUEDõ%XPRESSIONS )N ADDITION TO ITS EXTENDED CAPABILITIES FOR EXPRESSIONS INVOLVING SIMPLE SCALAR DATA VALUES AND ROW VALUES THE 31, STANDARD DRAMATICALLY EXTENDS THE 31, CAPABILITIES FOR TABLE PROCESSING )T PROVIDES A MECHANISM FOR CONSTRUCTING A TABLE OF DATA VALUES IN PLACE WITHIN A 31, STATEMENT )T ALLOWS TABLE VALUED SUBQUERIES AND EXTENDS THE 31, SUBQUERY TESTS TO HANDLE THEM )T ALSO ALLOWS SUBQUERIES TO APPEAR IN MANY MORE PLACES WITHIN A 31, STATEMENTFOR EXAMPLE A SUBQUERY CAN APPEAR IN THE &2/- CLAUSE OF A 3%,%#4 STATEMENT AS ONE OR MORE OF ITS SOURCE TABLES &INALLY IT PROVIDES EXPANDED CAPABILITIES FOR COMBINING TABLES INCLUDING THE 5.)/. ).4%23%#4)/. AND $)&&%2%.#% OPERATIONS
4HEõ4ABLE 6ALUEõ#ONSTRUCTOR 31, ALLOWS YOU TO SPECIFY A TABLE OF DATA VALUES WITHIN A 31, STATEMENT BY USING A TABLE VALUE CONSTRUCTOR EXPRESSION WHOSE SYNTAX IS SHOWN IN &IGURE )N ITS SIMPLEST FORM THE TABLE VALUE CONSTRUCTOR IS A COMMA SEPARATED LIST OF ROW VALUE CONSTRUCTORS EACH OF WHICH CONTAINS A COMMA SEPARATED SET OF LITERALS THAT FORM INDIVIDUAL COLUMN VALUES &OR EXAMPLE THE 31, ).3%24 STATEMENT USES A TABLE VALUE CONSTRUCTOR AS THE SOURCE OF THE DATA TO BE INSERTED INTO A DATABASE 7HILE THE 31, ).3%24 STATEMENT DESCRIBED IN #HAPTER ALLOWS YOU TO INSERT ONLY A SINGLE ROW OF DATA THE 31, AND BEYOND STANDARD ).3%24
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4HE MOST COMMON USE OF ROW VALUED EXPRESSIONS IN THE 7(%2% OR (!6).' CLAUSE IS WITHIN A TEST FOR EQUALITY AS ILLUSTRATED BY THE LAST FEW EXAMPLES ! CONSTRUCTED ROW OFTEN CONSISTING OF COLUMN VALUES FROM A CANDIDATE ROW OF QUERY RESULTS IS COMPARED WITH ANOTHER CONSTRUCTED ROW PERHAPS A ROW OF SUBQUERY RESULTS OR A ROW OF LITERAL VALUES AND IF THE ROWS ARE EQUAL THE CANDIDATE ROW IS INCLUDED IN THE QUERY RESULTS 4HE 31, STANDARD ALSO PROVIDES FOR ROW VALUED FORMS OF THE INEQUALITY COMPARISON TESTS AND THE RANGE TEST 7HEN COMPARING TWO ROWS FOR INEQUALITY 31, USES THE SAME RULES THAT IT WOULD USE IF THE COLUMNS WERE BEING USED TO SORT THE ROWS )T COMPARES THE CONTENTS OF THE FIRST COLUMN IN THE TWO ROWS AND IF THEY ARE UNEQUAL USES THEM TO ORDER THE ROWS )F THEY ARE EQUAL THE COMPARISON MOVES TO THE SECOND COLUMN AND THEN THE THIRD AND SO ON (ERE ARE THE RESULTING COMPARISONS FOR SOME THREE COLUMN CONSTRUCTED ROWS DERIVED FROM THE /2$%23 TABLE
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STATEMENT INSERTS THREE ROWS INTO THE /&&)#%3 TABLE (OWEVER NOT ALL 31, IMPLEMENTATIONS SUPPORT THIS SYNTAX !DD THREE OFlCES TO THE /&&)#%3 TABLE ).3%24 ).4/ /&&)#%3 /&&)#% #)49 2%')/. -'2 3!,%3 6!,5%3 g3AN $IEGOg g7ESTERNg g3EATTLEg g7ESTERNg g"OSTONg g%ASTERNg .5,,
.OTE THAT THE INDIVIDUAL ROWS IN THE TABLE VALUE CONSTRUCTOR ARE NOT RESTRICTED TO CONTAIN ONLY LITERAL VALUES 4HE SOURCE OF A DATA VALUE CAN BE A SCALAR VALUED SUBQUERY OR AN ENTIRE ROW CAN BE THE RESULT OF A ROW VALUED SUBQUERY !LTHOUGH IT DOESNT MAKE MUCH SENSE IN THE SAMPLE DATABASE AND THE SYNTAX ISNT SUPPORTED BY ANY OF THE LEADING $"-3 BRANDS THIS IS A LEGAL 31, STANDARD ).3%24 STATEMENT THAT ILLUSTRATES THESE CAPABILITIES !DD THREE OFlCES TO THE /&&)#%3 TABLE ).3%24 ).4/ /&&)#%3 /&&)#% #)49 2%')/. -'2 3!,%3 6!,5%3 g3AN $IEGOg g7ESTERNg g3EATTLEg g7ESTERNg 3%,%#4 -!.!'%2 &2/- 3!,%32%03 7(%2% %-0,?.5- 3%,%#4 g"/34/.g 2%')/. -'2 &2/- /&&)#%3 7(%2% /&&)#%
!S IN THE PRECEDING EXAMPLE THE 6!,5%3 CLAUSE IN THIS ).3%24 STATEMENT GENERATES A THREE ROW TABLE TO BE INSERTED 4HE FIRST ROW IS SPECIFIED WITH LITERAL VALUES )N THE SECOND ROW THE FOURTH COLUMN IS SPECIFIED AS A SCALAR VALUED SUBQUERY THAT RETRIEVES THE MANAGER OF EMPLOYEE NUMBER )N THE THIRD ROW THE ENTIRE ROW IS GENERATED BY A ROW VALUED SUBQUERY )N THIS CASE THREE OF THE COLUMN VALUES IN THE SUBQUERYS 3%,%#4 CLAUSE ARE ACTUALLY LITERAL VALUES BUT THE THIRD AND FOURTH COLUMNS ARE PRODUCED BY THE SUBQUERY WHICH RETRIEVES THE MANAGER AND REGION FOR THE .EW 9ORK OFFICE NUMBER
4ABLE 6ALUEDõ3UBQUERIES *UST AS NEWER VERSIONS OF THE 31, STANDARD EXPAND THE USE OF SCALAR SUBQUERIES INTO ROW VALUED SUBQUERIES THEY ALSO EXTEND THE 31, SUBQUERY FACILITY TO SUPPORT TABLE VALUED SUBQUERIESTHAT IS SUBQUERIES THAT RETURN A FULL TABLE OF RESULTS .OTE THAT 31, 3ERVER DOES NOT SUPPORT THIS SYNTAX BUT /RACLE -Y31, AND $" 5$" DO /NE USEFUL ROLE FOR TABLE VALUED SUBQUERIES IS WITHIN THE 7(%2% OR (!6).' CLAUSE WHERE THE TABLE VALUED SUBQUERY IS COMBINED WITH EXTENDED FORMS OF THE SUBQUERY TESTS &OR EXAMPLE SUPPOSE YOU WANTED TO LIST THE DESCRIPTIONS AND PRICES OF ALL PRODUCTS WITH ORDERS EXCEEDING IN THE SAMPLE DATABASE 0ERHAPS THE MOST STRAIGHTFORWARD WAY TO EXPRESS THIS REQUEST IS IN THIS 31, STATEMENT THAT USES A TABLE VALUED SUBQUERY ,IST THE DESCRIPTION AND PRICE OF ALL PRODUCTS WITH INDIVIDUAL ORDERS OVER 3%,%#4 $%3#2)04)/. 02)#% &2/- 02/$5#43 7(%2% -&2?)$ 02/$5#4?)$ ). 3%,%#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4
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4HE TOP LEVEL QUERY IS A STRAIGHTFORWARD STATEMENT OF THE %NGLISH LANGUAGE REQUESTIT ASKS FOR THE DESCRIPTION AND PRICE OF THOSE PRODUCTS WHOSE IDENTIFICATION AS IN PREVIOUS EXAMPLES A MANUFACTURER )$PRODUCT )$ PAIR MATCHES SOME SET OF PRODUCTS 4HIS IS EXPRESSED AS A SUBQUERY SET MEMBERSHIP TEST IN THE 7(%2% CLAUSE 4HE SUBQUERY GENERATES A TWO COLUMN TABLE OF SUBQUERY RESULTS WHICH ARE THE IDENTIFICATIONS OF THE PRODUCTS THAT MEET THE STATED ORDER SIZE CRITERION )TS CERTAINLY POSSIBLE TO EXPRESS THIS QUERY IN OTHER WAYS &ROM THE DISCUSSION IN #HAPTER YOU PROBABLY RECOGNIZE THAT IT CAN BE STATED AS A JOIN OF THE 02/$5#43 AND /2$%23 TABLES WITH A COMPOUND SEARCH CONDITION
3%,%#4 $)34).#4 $%3#2)04)/. 02)#% &2/- 02/$5#43 /2$%23 7(%2% -&2?)$ -&2 !.$ 02/$5#4?)$ 02/$5#4 !.$ !-/5.4
.OTE THAT WE HAD TO ADD THE $)34).#4 KEYWORD BECAUSE THERE ARE TWO ORDERS OVER FOR THE h2IGHT (INGEv PRODUCT 4HIS IS AN EQUALLY VALID STATEMENT OF THE QUERY BUT ITS A LOT FURTHER REMOVED FROM THE %NGLISH LANGUAGE REQUEST AND THEREFORE MORE DIFFICULT TO UNDERSTAND FOR MOST PEOPLE !S QUERIES BECOME MORE COMPLEX THE ABILITY TO USE TABLE VALUED SUBQUERIES BECOMES EVEN MORE USEFUL TO SIMPLIFY AND CLARIFY 31, REQUESTS
4HEõ31,õ1UERYõ3PECIFICATION 4HE 31, STANDARD FORMALIZES THE DEFINITION OF WHAT WE HAVE LOOSELY BEEN CALLING A 3%,%#4 STATEMENT OR A QUERY IN THE LAST THREE CHAPTERS INTO A BASIC BUILDING BLOCK CALLED A QUERY SPECIFICATION &OR A COMPLETE UNDERSTANDING OF THE 31, TABLE EXPRESSION CAPABILITIES IN THE NEXT SECTION ITS USEFUL TO UNDERSTAND THIS FORMAL DEFINITION 4HE FORM OF A 31, QUERY SPECIFICATION IS SHOWN IN &IGURE )TS COMPONENTS SHOULD BE FAMILIAR FROM THE EARLIER CHAPTERS s ! SELECT LIST SPECIFIES THE COLUMNS OF QUERY RESULTS %ACH COLUMN IS SPECIFIED BY AN EXPRESSION THAT TELLS THE $"-3 HOW TO DETERMINE ITS VALUE 4HE COLUMN CAN BE ASSIGNED AN OPTIONAL ALIAS WITH THE !3 CLAUSE s 4HE KEYWORDS !,, OR $)34).#4 CONTROL DUPLICATE ROW ELIMINATION IN THE QUERY RESULTS s 4HE &2/- CLAUSE SPECIFIES THE TABLES THAT CONTRIBUTE TO THE QUERY RESULTS s 4HE 7(%2% CLAUSE DESCRIBES HOW THE $"-3 SHOULD DETERMINE WHICH ROWS ARE INCLUDED IN THE QUERY RESULTS AND WHICH SHOULD BE DISCARDED s 4HE '2/50 "9 AND (!6).' CLAUSES TOGETHER CONTROL THE GROUPING OF INDIVIDUAL QUERY RESULTS ROWS IN A GROUPED QUERY AND THE SELECTION OF ROW GROUPS FOR INCLUSION OR EXCLUSION IN THE FINAL RESULTS s 4HE /2$%2 "9 CLAUSE SPECIFIES THE DESIRED SEQUENCE OF THE ROWS IN THE QUERY RESULTS
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,IST THE DESCRIPTION AND PRICE OF ALL PRODUCTS WITH INDIVIDUAL ORDERS OVER
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4HE QUERY SPECIFICATION IS THE BASIC QUERY BUILDING BLOCK IN THE 31, STANDARD #ONCEPTUALLY IT DESCRIBES THE PROCESS OF COMBINING DATA FROM THE TABLES IN THE &2/- CLAUSE INTO A ROWCOLUMN TABLE OF QUERY RESULTS 4HE VALUE OF THE QUERY SPECIFICATION IS A TABLE OF DATA )N THE SIMPLEST CASE A 31, QUERY CONSISTS OF A SIMPLE QUERY SPECIFICATION )N A SLIGHTLY MORE COMPLEX CASE A QUERY SPECIFICATION IS USED TO DESCRIBE A SUBQUERY WHICH APPEARS WITHIN ANOTHER HIGHER LEVEL QUERY SPECIFICATION &INALLY QUERY SPECIFICATIONS CAN BE COMBINED USING TABLE VALUED OPERATIONS TO FORM GENERAL PURPOSE QUERY EXPRESSIONS AS DESCRIBED IN THE NEXT SECTION
1UERYõ%XPRESSIONS 4HE 31, STANDARD DEFINES A QUERY EXPRESSION AS THE FULL GENERAL PURPOSE WAY THAT YOU CAN SPECIFY A TABLE OF QUERY RESULTS IN 31, 4HE BASIC BUILDING BLOCKS YOU CAN USE TO CREATE A QUERY EXPRESSION ARE THE FOLLOWING s ! QUERY SPECIFICATION AS DESCRIBED IN THE PRECEDING SECTION 3%,%#4x&2/-x )TS VALUE IS A TABLE OF QUERY RESULTS s ! TABLE VALUE CONSTRUCTOR AS PREVIOUSLY DESCRIBED 6!,5%3 x )TS VALUE IS A TABLE OF CONSTRUCTED VALUES s !N EXPLICIT TABLE REFERENCE 4!",% TBLNAME )TS VALUE IS THE CONTENTS OF THE NAMED TABLE
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5SING THESE BUILDING BLOCKS 31, LETS YOU COMBINE THEIR TABLE VALUES USING THE FOLLOWING OPERATIONS s */). 31, PROVIDES EXPLICIT SUPPORT FOR FULL CROSS PRODUCT JOINS CROSS JOINS NATURAL JOINS INNER JOINS AND ALL TYPES OF OUTER JOINS LEFT RIGHT AND FULL AS DESCRIBED IN #HAPTER ! */). OPERATION TAKES TWO TABLES AS ITS INPUT AND PRODUCES A TABLE OF COMBINED QUERY RESULTS ACCORDING TO THE JOIN SPECIFICATION
s %8#%04 4HE 31, %8#%04 OPERATION TAKES TWO TABLES AS ITS INPUT AND PRODUCES AS ITS OUTPUT A TABLE CONTAINING THE ROWS THAT APPEAR IN THE FIRST TABLE BUT THAT DO NOT APPEAR IN ANOTHER TABLETHAT IS THE ROWS THAT ARE MISSING FROM THE SECOND TABLE #ONCEPTUALLY THE %8#%04 OPERATION IS LIKE TABLE SUBTRACTION 4HE ROWS OF THE SECOND TABLE ARE TAKEN AWAY FROM THE ROWS OF THE FIRST TABLE AND THE ANSWER IS THE REMAINING ROWS OF THE FIRST TABLE s ).4%23%#4 4HE 31, ).4%23%#4 OPERATION TAKES TWO TABLES AS ITS INPUT AND PRODUCES AS ITS OUTPUT A TABLE CONTAINING THE ROWS THAT APPEAR IN BOTH INPUT TABLES
5.)/. õ).4%23%#4 õANDõ%8#%04õ/PERATIONS 4HE 5.)/. ).4%23%#4 AND %8#%04 OPERATIONS PROVIDE SET OPERATIONS FOR COMBINING TWO INPUT TABLES TO FORM AN OUTPUT TABLE .EARLY ALL VENDORS SUPPORT 5.)/. BUT SUPPORT FOR ).4%23%#4 AND %8#%04 IS INCONSISTENT ACROSS VENDORS &OR EXAMPLE /RACLE USES THE KEYWORD -).53 INSTEAD OF %8#%04 !LL THREE OF THE OPERATIONS REQUIRE THAT THE TWO INPUT TABLES BE UNION COMPATIBLETHEY MUST HAVE THE SAME NUMBER OF COLUMNS AND THE CORRESPONDING COLUMNS OF EACH TABLE MUST HAVE IDENTICAL DATA TYPES (ERE ARE SOME SIMPLE EXAMPLES OF 31, QUERY EXPRESSIONS INVOLVING 5.)/. ).4%23%#4 AND %8#%04 OPERATIONS BASED ON THE SAMPLE DATABASE 3HOW ALL PRODUCTS FOR WHICH THERE IS AN ORDER OVER OR MORE THAN WORTH OF INVENTORY ON HAND 3%,%#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 5.)/. 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 149?/.?(!.$
3HOW ALL PRODUCTS FOR WHICH THERE IS AN ORDER OVER AND MORE THAN WORTH OF INVENTORY ON HAND 3%,%#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 ).4%23%#4 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#% 149?/.?(!.$
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s 5.)/. 4HE 31, 5.)/. OPERATION PROVIDES EXPLICIT SUPPORT FOR MERGING THE ROWS OF TWO COMPATIBLE TABLES THAT IS TWO TABLES HAVING THE SAME NUMBER OF COLUMNS AND WITH CORRESPONDING COLUMNS HAVING THE SAME DATA TYPES 4HE 5.)/. OPERATION TAKES TWO TABLES AS ITS INPUT AND PRODUCES A SINGLE MERGED TABLE OF QUERY RESULTS
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3HOW ALL PRODUCTS FOR WHICH THERE IS AN ORDER OVER EXCEPT FOR THOSE PRODUCTS THAT SELL FOR UNDER 3%,%#4 -&2 02/$5#4 &2/- /2$%23 7(%2% !-/5.4 %8#%04 3%,%#4 -&2?)$ 02/$5#4?)$ &2/- 02/$5#43 7(%2% 02)#%
"Y DEFAULT THE 5.)/. ).4%23%#4 AND %8#%04 OPERATIONS ELIMINATE DUPLICATE ROWS DURING THEIR PROCESSING 4HIS IS USUALLY THE DESIRED RESULT AS IT IS IN THESE EXAMPLES BUT OCCASIONALLY YOU MAY NEED TO SUPPRESS THE ELIMINATION OF DUPLICATE ROWS 9OU CAN DO THIS BY SPECIFYING THE 5.)/. !,, ).4%23%#4 !,, OR %8#%04 !,, FORMS OF THE OPERATIONS .OTE EACH OF THESE EXAMPLES PRODUCES A TWO COLUMN TABLE OF QUERY RESULTS 4HE RESULTS COME FROM TWO DIFFERENT SOURCE TABLES WITHIN THE DATABASETHE /2$%23 TABLE AND THE 02/$5#43 TABLE (OWEVER THE COLUMNS SELECTED FROM THESE TABLES HAVE THE SAME CORRESPONDING DATA TYPES SO THEY CAN BE COMBINED USING THESE OPERATIONS )N THE SAMPLE DATABASE THE CORRESPONDING COLUMNS HAVE DIFFERENT NAMES IN THE TWO TABLES 4HE MANUFACTURER )$ COLUMN IS NAMED -&2 IN THE /2$%23 TABLE BUT NAMED -&2?)$ IN THE 02/$5#43 TABLE
1UERYõ%XPRESSIONSõINõTHEõ&2/-õ#LAUSE 31, QUERY EXPRESSIONS PROVIDE A MUCH MORE POWERFUL AND FLEXIBLE METHOD FOR GENERATING AND COMBINING TABLES OF QUERY RESULTS THAN THE SIMPLE SUBQUERY AND 5.)/. OPERATIONS PROVIDED BY THE 31, STANDARD 4O MAKE QUERY EXPRESSIONS EVEN MORE USEFUL AND MORE GENERAL PURPOSE THE 31, STANDARD NOW ALLOWS THEM TO APPEAR ALMOST ANYWHERE THAT A TABLE REFERENCE COULD APPEAR IN A 31, QUERY )N PARTICULAR A QUERY EXPRESSION CAN APPEAR IN PLACE OF A TABLE NAME IN THE &2/- CLAUSE (ERE IS A SIMPLE EXAMPLE OF A QUERY FOR THE SAMPLE DATABASE THAT USES THIS FEATURE 3HOW THE NAMES AND TOTAL OUTSTANDING ORDERS OF ALL CUSTOMERS WITH CREDIT LIMITS OVER 3%,%#4 #/-0!.9 4/4?/2$%23 &2/- #534/-%23 3%,%#4 #534 35-!-/5.4 !3 4/4?/2$%23 &2/- /2$%23 '2/50 "9 #534 ! 7(%2% #2%$)4?,)-)4 !.$ #534?.5- #534
4HE SECOND hTABLE NAMEv IN THE &2/- CLAUSE OF THE MAIN QUERY IS NOT A TABLE NAME AT ALL BUT A FULL BLOWN QUERY EXPRESSION )N FACT THE EXPRESSION COULD HAVE BEEN MUCH MORE COMPLEX INVOLVING 5.)/. OR */). OPERATIONS 7HEN A QUERY EXPRESSION APPEARS IN THE &2/- CLAUSE AS IT DOES HERE THE $"-3 CONCEPTUALLY CARRIES IT OUT FIRST BEFORE ANY OTHER PROCESSING OF THE QUERY AND CREATES A TEMPORARY TABLE OF THE QUERY RESULTS GENERATED BY THE QUERY EXPRESSION )N THIS CASE THIS TEMPORARY TABLE CONSISTS OF TWO COLUMNS LISTING EACH CUSTOMER NUMBER AND THE TOTAL OF ORDERS FOR THAT CUSTOMER NUMBER 4HIS TEMPORARY TABLE THEN ACTS AS ONE OF THE SOURCE TABLES FOR THE MAIN QUERY )N THIS EXAMPLE ITS CONTENTS ARE JOINED TO THE #534/-%2 TABLE TO OBTAIN THE COMPANY NAME AND GENERATE THE ANSWER TO THE MAIN QUESTION
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3UBQUERIESçANDç1UERYç%XPRESSIONSç
31,õ1UERIESõ!õ&INALõ3UMMARY 4HIS CONCLUDES THE DISCUSSION OF THE 31, QUERIES AND THE 3%,%#4 STATEMENT THAT BEGAN IN #HAPTER !S DESCRIBED IN #HAPTERS THROUGH THE CLAUSES OF THE 3%,%#4 STATEMENT PROVIDE A POWERFUL FLEXIBLE SET OF CAPABILITIES FOR RETRIEVING DATA FROM THE DATABASE %ACH CLAUSE PLAYS A SPECIFIC ROLE IN DATA RETRIEVAL s 4HE &2/- CLAUSE SPECIFIES THE SOURCE TABLES THAT CONTRIBUTE DATA TO THE QUERY RESULTS %VERY COLUMN NAME IN THE BODY OF THE 3%,%#4 STATEMENT MUST UNAMBIGUOUSLY IDENTIFY A COLUMN FROM ONE OF THESE TABLES OR IT MUST BE AN OUTER REFERENCE TO A COLUMN FROM A SOURCE TABLE OF AN OUTER QUERY s 4HE 7(%2% CLAUSE IF PRESENT SELECTS INDIVIDUAL COMBINATIONS OF ROWS FROM THE SOURCE TABLES TO PARTICIPATE IN THE QUERY RESULTS 3UBQUERIES IN THE 7(%2% CLAUSE ARE EVALUATED FOR EACH INDIVIDUAL ROW s 4HE '2/50 "9 CLAUSE IF PRESENT GROUPS THE INDIVIDUAL ROWS SELECTED BY THE 7(%2% CLAUSE INTO ROW GROUPS s 4HE (!6).' CLAUSE IF PRESENT SELECTS ROW GROUPS TO PARTICIPATE IN THE QUERY RESULTS 3UBQUERIES IN THE (!6).' CLAUSE ARE EVALUATED FOR EACH ROW GROUP s 4HE 3%,%#4 CLAUSE DETERMINES WHICH DATA VALUES ACTUALLY APPEAR AS COLUMNS IN THE FINAL QUERY RESULTS s 4HE $)34).#4 KEYWORD IF PRESENT ELIMINATES DUPLICATE ROWS OF QUERY RESULTS s 4HE 5.)/. OPERATOR IF PRESENT MERGES THE QUERY RESULTS PRODUCED BY INDIVIDUAL 3%,%#4 STATEMENTS INTO A SINGLE SET OF QUERY RESULTS s 4HE /2$%2 "9 CLAUSE IF PRESENT SORTS THE FINAL QUERY RESULTS BASED ON ONE OR MORE COLUMNS s 4HE 31, QUERY EXPRESSION CAPABILITIES ADD ROW VALUED AND TABLE VALUED EXPRESSIONS AND ).4%23%#4 AND %8#%04 OPERATIONS TO THE 31, CAPABILITIES 4HE FUNDAMENTAL FLOW OF QUERY PROCESSING IS NOT CHANGED BUT THE CAPABILITY TO EXPRESS QUERIES WITHIN QUERIES IS GREATLY ENHANCED
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4HERE ARE MANY OTHER WAYS IN WHICH THIS QUERY COULD BE WRITTEN 4HE ENTIRE QUERY COULD BE WRITTEN AS ONE TOP LEVEL GROUPED QUERY THAT JOINS THE #534/-%2 AND /2$%23 TABLE 4HE JOIN OPERATION COULD BE MADE EXPLICIT WITH A */). OPERATOR AND THEN THE RESULTS OF THE JOIN COULD BE GROUPED IN THE TOP LEVEL QUERY !S THIS EXAMPLE SHOWS ONE OF THE BENEFITS OF THE 31, QUERY EXPRESSION CAPABILITIES IS THAT THEY TYPICALLY PROVIDE SEVERAL DIFFERENT WAYS TO OBTAIN THE SAME QUERY RESULTS 4HE GENERAL PHILOSOPHY BEHIND THE CAPABILITIES IN THIS AREA IS THAT 31, SHOULD PROVIDE THE FLEXIBILITY TO EXPRESS A QUERY IN THE MOST NATURAL FORM 4HE UNDERLYING $"-3 MUST BE ABLE TO TAKE THE QUERY HOWEVER EXPRESSED BREAK IT DOWN INTO ITS FUNDAMENTALS AND THEN DETERMINE THE MOST EFFICIENT WAY TO CARRY OUT THE QUERY 4HIS INTERNAL QUERY EXECUTION PLAN MAY BE QUITE DIFFERENT FROM THE APPARENT PLAN CALLED FOR BY THE ACTUAL 31, STATEMENT BUT AS LONG AS IT PRODUCES THE SAME QUERY RESULTS THE NET EFFECT IS TO SHIFT THE OPTIMIZATION WORKLOAD FROM THE HUMAN USER OR PROGRAMMER TO THE $"-3
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1, IS NOT ONLY A QUERY LANGUAGE BUT ITS ALSO A COMPLETE LANGUAGE FOR RETRIEVING AND MODIFYING DATA IN A DATABASE #HAPTERS n FOCUS ON DATABASE UPDATES #HAPTER DESCRIBES 31, STATEMENTS THAT ADD DATA TO A DATABASE REMOVE DATA FROM A DATABASE AND MODIFY EXISTING DATABASE DATA #HAPTER DESCRIBES HOW 31, MAINTAINS THE INTEGRITY OF STORED DATA WHEN THE DATA IS MODIFIED #HAPTER DESCRIBES THE 31, TRANSACTION PROCESSING FEATURES THAT SUPPORT CONCURRENT DATABASE UPDATES BY MANY DIFFERENT USERS
#(!04%2ç $ATABASE 5PDATES #(!04%2ç $ATA )NTEGRITY #(!04%2ç 4RANSACTION 0ROCESSING
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1, IS A COMPLETE DATA MANIPULATION LANGUAGE THAT IS USED NOT ONLY FOR DATABASE QUERIES BUT ALSO TO MODIFY AND UPDATE DATA IN THE DATABASE #OMPARED WITH THE COMPLEXITY OF THE 3%,%#4 STATEMENT WHICH SUPPORTS 31, QUERIES THE 31, STATEMENTS THAT MODIFY DATABASE CONTENTS ARE EXTREMELY SIMPLE (OWEVER DATABASE UPDATES POSE SOME CHALLENGES FOR A $"-3 BEYOND THOSE PRESENTED BY DATABASE QUERIES 4HE $"-3 MUST PROTECT THE INTEGRITY OF STORED DATA DURING CHANGES ENSURING THAT ONLY VALID DATA IS INTRODUCED INTO THE DATABASE AND THAT THE DATABASE REMAINS SELF CONSISTENT EVEN IN THE EVENT OF SYSTEM FAILURES 4HE $"-3 MUST ALSO COORDINATE SIMULTANEOUS UPDATES BY MULTIPLE USERS ENSURING THAT THE USERS AND THEIR CHANGES DO NOT INTERFERE WITH ONE ANOTHER 4HIS CHAPTER DESCRIBES THE THREE 31, STATEMENTS THAT ARE USED TO MODIFY THE CONTENTS OF A DATABASE s ).3%24 !DDS NEW ROWS OF DATA TO A TABLE s $%,%4% 2EMOVES ROWS OF DATA FROM A TABLE s 50$!4% -ODIFIES EXISTING DATA IN THE DATABASE )N #HAPTER 31, FACILITIES FOR MAINTAINING DATA INTEGRITY ARE DESCRIBED #HAPTER COVERS 31, SUPPORT FOR MULTIUSER CONCURRENCY
!DDINGõ$ATAõTOõTHEõ$ATABASE ! NEW ROW OF DATA IS TYPICALLY ADDED TO A RELATIONAL DATABASE WHEN A NEW ENTITY REPRESENTED BY THE ROW APPEARS IN THE OUTSIDE WORLD &OR EXAMPLE IN THE SAMPLE DATABASE s 7HEN YOU HIRE A NEW SALESPERSON A NEW ROW MUST BE ADDED TO THE 3!,%32%03 TABLE TO STORE THE SALESPERSONS DATA s 7HEN A SALESPERSON SIGNS A NEW CUSTOMER A NEW ROW MUST BE ADDED TO THE #534/-%23 TABLE REPRESENTING THE NEW CUSTOMER s 7HEN A CUSTOMER PLACES AN ORDER A NEW ROW MUST BE ADDED TO THE /2$%23 TABLE TO CONTAIN THE ORDER DATA
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)N EACH CASE THE NEW ROW IS ADDED TO MAINTAIN THE DATABASE AS AN ACCURATE MODEL OF THE REAL WORLD 4HE SMALLEST UNIT OF DATA THAT CAN BE ADDED TO A RELATIONAL DATABASE IS A SINGLE ROW )N GENERAL A 31, BASED $"-3 PROVIDES THREE WAYS TO ADD NEW ROWS OF DATA TO A DATABASE s 3INGLE ROW ).3%24 ! SINGLE ROW ).3%24 STATEMENT ADDS A SINGLE NEW ROW OF DATA TO A TABLE )T IS COMMONLY USED IN DAILY APPLICATIONSFOR EXAMPLE DATA ENTRY PROGRAMS s -ULTIROW ).3%24 ! MULTIROW ).3%24 STATEMENT EXTRACTS ROWS OF DATA FROM ANOTHER PART OF THE DATABASE AND ADDS THEM TO A TABLE )T IS COMMONLY USED FOR EXAMPLE IN END OF MONTH PROCESSING WHEN OLD ROWS OF A TABLE ARE MOVED TO AN INACTIVE TABLE OR WHEN MONTHLY RESULTS ARE SUMMARIZED INTO A TABLE THAT HAS BEEN SET UP TO HOLD THEM s "ULK LOAD ! BULK LOAD UTILITY ADDS DATA TO A TABLE FROM A FILE THAT IS OUTSIDE OF THE DATABASE )T IS COMMONLY USED TO INITIALLY LOAD THE DATABASE OR TO INCORPORATE DATA DOWNLOADED FROM ANOTHER COMPUTER SYSTEM OR COLLECTED FROM MANY SITES
4HEõ3INGLE 2OWõ).3%24õ3TATEMENT 4HE SINGLE ROW ).3%24 STATEMENT SHOWN IN &IGURE ADDS A NEW ROW TO A TABLE 4HE ).4/ CLAUSE SPECIFIES THE TABLE THAT RECEIVES THE NEW ROW THE TARGET TABLE AND THE 6!,5%3 CLAUSE SPECIFIES THE DATA VALUES THAT THE NEW ROW WILL CONTAIN 4HE COLUMN LIST INDICATES WHICH DATA VALUE GOES INTO WHICH COLUMN OF THE NEW ROW 3UPPOSE YOU JUST HIRED A NEW SALESPERSON (ENRY *ACOBSEN WITH THE FOLLOWING PERSONAL DATA >i\
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#HAPTERçç
$ATABASEç5PDATESç
(ERE IS THE ).3%24 STATEMENT THAT ADDS -R *ACOBSEN TO THE SAMPLE DATABASE !DD (ENRY *ACOBSEN AS A NEW SALESPERSON ).3%24 ).4/ 3!,%32%03 .!-% !'% %-0,?.5- 3!,%3 4)4,% ()2%?$!4% 2%0?/&&)#% 6!,5%3 g(ENRY *ACOBSENg g3ALES -GRg g g ROW INSERTED
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&IGURE GRAPHICALLY ILLUSTRATES HOW 31, CARRIES OUT THIS ).3%24 STATEMENT #ONCEPTUALLY THE ).3%24 STATEMENT BUILDS A SINGLE ROW OF DATA THAT MATCHES THE COLUMN STRUCTURE OF THE TABLE FILLS IT WITH THE DATA FROM THE 6!,5%3 CLAUSE AND THEN ADDS THE NEW ROW TO THE TABLE 4HE ROWS OF A TABLE ARE UNORDERED SO THERE IS NO NOTION OF INSERTING THE ROW AT THE TOP AT THE BOTTOM OR BETWEEN TWO ROWS OF THE TABLE !FTER THE ).3%24 STATEMENT THE NEW ROW IS SIMPLY A PART OF THE TABLE ! SUBSEQUENT QUERY AGAINST THE 3!,%32%03 TABLE WILL INCLUDE THE NEW ROW BUT IT MAY APPEAR ANYWHERE AMONG THE ROWS OF QUERY RESULTS 3UPPOSE -R *ACOBSEN NOW RECEIVES HIS FIRST ORDER FROM )NTER#ORP A NEW CUSTOMER WHO IS ASSIGNED CUSTOMER NUMBER 4HE ORDER IS FOR !#) WIDGETS FOR A TOTAL
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5PDATINGç$ATA
PRICE OF AND HAS BEEN ASSIGNED ORDER NUMBER (ERE ARE THE ).3%24 STATEMENTS THAT ADD THE NEW CUSTOMER AND THE ORDER TO THE DATABASE )NSERT A NEW CUSTOMER AND ORDER FOR -R *ACOBSEN ).3%24 ).4/ #534/-%23 #/-0!.9 #534?.5- #2%$)4?,)-)4 #534?2%0 6!,5%3 g)NTER#ORPg ROW INSERTED ).3%24 ).4/ /2$%23 !-/5.4 -&2 02/$5#4 149 /2$%2?$!4% /2$%2?.5- #534 2%0 6!,5%3 g!#)g gg #522%.4?$!4% ROW INSERTED
!S THIS EXAMPLE SHOWS THE ).3%24 STATEMENT CAN BECOME LENGTHY IF THERE ARE MANY COLUMNS OF DATA BUT ITS FORMAT IS STILL VERY STRAIGHTFORWARD 4HE SECOND ).3%24 STATEMENT USES THE SYSTEM CONSTANT #522%.4 $!4% IN ITS 6!,5%3 CLAUSE CAUSING THE CURRENT DATE TO BE INSERTED AS THE ORDER DATE 4HIS SYSTEM CONSTANT IS SPECIFIED IN THE 31, STANDARD AND IS SUPPORTED BY MANY OF THE POPULAR 31, PRODUCTS INCLUDING /RACLE AND -Y31, /THER BRANDS OF $"-3 SUCH AS 31, 3ERVER AND $" 5$" PROVIDE OTHER SYSTEM CONSTANTS OR BUILT IN FUNCTIONS TO OBTAIN THE CURRENT DATE AND TIME 9OU CAN USE THE ).3%24 STATEMENT WITH INTERACTIVE 31, TO ADD ROWS TO A TABLE THAT GROWS VERY RARELY SUCH AS THE /&&)#%3 TABLE )N PRACTICE HOWEVER DATA ABOUT A NEW CUSTOMER ORDER OR SALESPERSON IS ALMOST ALWAYS ADDED TO A DATABASE THROUGH A DATA ENTRY PROGRAM THAT PRESENTS A FORM TO THE USER TO COLLECT THE DATA 7HEN THE DATA ENTRY IS COMPLETE THE APPLICATION PROGRAM INSERTS THE NEW ROW OF DATA USING PROGRAMMATIC 31, 2EGARDLESS OF WHETHER INTERACTIVE OR PROGRAMMATIC 31, IS USED HOWEVER THE ).3%24 STATEMENT IS THE SAME 4HE TABLE NAME SPECIFIED IN THE ).3%24 STATEMENT IS NORMALLY AN UNQUALIFIED TABLE NAME SPECIFYING A TABLE THAT YOU OWN 4O INSERT DATA INTO A TABLE OWNED BY ANOTHER USER YOU CAN SPECIFY A QUALIFIED TABLE NAME /F COURSE YOU MUST ALSO HAVE PERMISSION TO INSERT DATA INTO THE TABLE OR THE ).3%24 STATEMENT WILL FAIL 4HE 31, SECURITY SCHEME AND PERMISSIONS ARE DESCRIBED IN #HAPTER 4HE PURPOSE OF THE COLUMN LIST IN THE ).3%24 STATEMENT IS TO MATCH THE DATA VALUES IN THE 6!,5%3 CLAUSE WITH THE COLUMNS THAT ARE TO RECEIVE THEM 4HE LIST OF VALUES AND THE LIST OF COLUMNS MUST BOTH CONTAIN THE SAME NUMBER OF ITEMS AND THE DATA TYPE OF EACH VALUE MUST BE COMPATIBLE WITH THE DATA TYPE OF THE CORRESPONDING COLUMN OR AN ERROR WILL OCCUR 4HE !.3))3/ STANDARD MANDATES UNQUALIFIED COLUMN NAMES IN THE COLUMN LIST BUT MANY IMPLEMENTATIONS ALLOW QUALIFIED NAMES /F COURSE THERE CAN BE NO AMBIGUITY IN THE COLUMN NAMES ANYWAY BECAUSE THEY MUST ALL REFERENCE COLUMNS OF THE TARGET TABLE
#HAPTERçç
$ATABASEç5PDATESç
)NSERTINGõ.5,,õ6ALUES 7HEN 31, INSERTS A NEW ROW OF DATA INTO A TABLE IT AUTOMATICALLY ASSIGNS A .5,, VALUE TO ANY COLUMN WHOSE NAME IS MISSING FROM THE COLUMN LIST IN THE ).3%24 STATEMENT )N THIS ).3%24 STATEMENT WHICH ADDED -R *ACOBSEN TO THE 3!,%32%03 TABLE THE 15/4! AND -!.!'%2 COLUMNS WERE OMITTED ).3%24 ).4/ 3!,%32%03 .!-% !'% %-0,?.5- 3!,%3 4)4,% ()2%?$!4% 2%0?/&&)#% 6!,5%3 g(ENRY *ACOBSENg g3ALES -GRg g g
!S A RESULT THE NEWLY ADDED ROW HAS A .5,, VALUE IN THE 15/4! AND -!.!'%2 COLUMNS AS SHOWN IN &IGURE 9OU CAN MAKE THE ASSIGNMENT OF A .5,, VALUE MORE EXPLICIT BY INCLUDING THESE COLUMNS IN THE COLUMN LIST AND SPECIFYING THE KEYWORD .5,, IN THE VALUES LIST 4HIS ).3%24 STATEMENT HAS EXACTLY THE SAME EFFECT AS THE PREVIOUS ONE
)NSERTINGõ!LLõ#OLUMNS !S A CONVENIENCE 31, ALLOWS YOU TO OMIT THE COLUMN LIST FROM THE ).3%24 STATEMENT 7HEN THE COLUMN LIST IS OMITTED 31, AUTOMATICALLY GENERATES A COLUMN LIST CONSISTING OF ALL COLUMNS OF THE TABLE IN LEFT TO RIGHT SEQUENCE 4HIS IS THE SAME COLUMN SEQUENCE GENERATED BY 31, WHEN YOU USE A 3%,%#4 QUERY 5SING THIS SHORTCUT THE PREVIOUS ).3%24 STATEMENT COULD BE REWRITTEN EQUIVALENTLY AS ).3%24 ).4/ 3!,%32%03 6!,5%3 g(ENRY *ACOBSENg g3ALES -GRg g g .5,, .5,,
7HEN YOU OMIT THE COLUMN LIST THE .5,, KEYWORD MUST BE USED IN THE VALUES LIST TO EXPLICITLY ASSIGN .5,, VALUES TO COLUMNS AS SHOWN IN THE EXAMPLE )N ADDITION THE SEQUENCE OF DATA VALUES MUST CORRESPOND EXACTLY TO THE SEQUENCE OF COLUMNS IN THE TABLE /MITTING THE COLUMN LIST IS CONVENIENT IN INTERACTIVE 31, BECAUSE IT REDUCES THE LENGTH OF THE ).3%24 STATEMENT YOU MUST TYPE &OR PROGRAMMATIC 31, THE COLUMN LIST SHOULD ALWAYS BE SPECIFIED BECAUSE IT MAKES THE PROGRAM EASIER TO READ AND UNDERSTAND )N ADDITION TABLE STRUCTURES OFTEN CHANGE OVER TIME TO INCLUDE NEW COLUMNS OR TO DROP COLUMNS THAT ARE NO LONGER USED ! PROGRAM THAT CONTAINS AN ).3%24 STATEMENT WITHOUT AN EXPLICIT COLUMN LIST MAY WORK CORRECTLY FOR MONTHS OR YEARS AND THEN SUDDENLY BEGIN PRODUCING ERRORS WHEN THE NUMBER OF COLUMNS OR DATA TYPES OF COLUMNS IS CHANGED BY A DATABASE ADMINISTRATOR
4HEõ-ULTIROWõ).3%24õ3TATEMENT 4HE SECOND FORM OF THE ).3%24 STATEMENT SHOWN IN &IGURE ADDS MULTIPLE ROWS OF DATA TO ITS TARGET TABLE )N THIS FORM OF THE ).3%24 STATEMENT THE DATA VALUES FOR THE NEW ROWS ARE NOT EXPLICITLY SPECIFIED WITHIN THE STATEMENT TEXT )NSTEAD THE SOURCE OF NEW ROWS IS A DATABASE QUERY SPECIFIED IN THE STATEMENT
0!24ç)))
).3%24 ).4/ 3!,%32%03 .!-% !'% %-0,?.5- 3!,%3 15/4! 4)4,% -!.!'%2 ()2%?$!4% 2%0?/&&)#% 6!,5%3 g(ENRY *ACOBSENg .5,, g3ALES -GRg .5,, g g
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!DDING ROWS WHOSE VALUES COME FROM WITHIN THE DATABASE ITSELF MAY SEEM STRANGE AT FIRST BUT ITS VERY USEFUL IN SOME SPECIAL SITUATIONS &OR EXAMPLE SUPPOSE YOU WANT TO COPY THE ORDER NUMBER DATE AND AMOUNT OF ALL ORDERS PLACED BEFORE *ANUARY FROM THE /2$%23 TABLE INTO ANOTHER TABLE CALLED /,$/2$%23 4HE MULTIROW ).3%24 STATEMENT PROVIDES A CONCISE EFFICIENT WAY TO COPY THE DATA #OPY OLD ORDERS INTO THE /,$/2$%23 TABLE ).3%24 ).4/ /,$/2$%23 /2$%2?.5- /2$%2?$!4% !-/5.4 3%,%#4 /2$%2?.5- /2$%2?$!4% !-/5.4 &2/- /2$%23 7(%2% /2$%2?$!4% g g ROWS INSERTED
4HIS ).3%24 STATEMENT LOOKS COMPLICATED BUT ITS REALLY VERY SIMPLE 4HE STATEMENT IDENTIFIES THE TABLE TO RECEIVE THE NEW ROWS /,$/2$%23 AND THE COLUMNS TO RECEIVE THE DATA JUST LIKE THE SINGLE ROW ).3%24 STATEMENT 4HE REMAINDER OF THE STATEMENT IS A QUERY THAT RETRIEVES DATA FROM THE /2$%23 TABLE &IGURE GRAPHICALLY ILLUSTRATES THE OPERATION OF THIS ).3%24 STATEMENT #ONCEPTUALLY 31, FIRST PERFORMS THE QUERY AGAINST THE /2$%23 TABLE AND THEN INSERTS THE QUERY RESULTS ROW BY ROW INTO THE /,$/2$%23 TABLE (ERES ANOTHER SITUATION WHERE YOU COULD USE THE MULTIROW ).3%24 STATEMENT 3UPPOSE YOU WANT TO ANALYZE CUSTOMER BUYING PATTERNS BY LOOKING AT WHICH CUSTOMERS AND SALESPEOPLE ARE RESPONSIBLE FOR BIG ORDERSTHOSE OVER 4HE QUERIES THAT YOU WILL BE RUNNING WILL COMBINE DATA FROM THE #534/-%23 3!,%32%03 AND /2$%23 TABLES 4HESE THREE TABLE QUERIES WILL EXECUTE FAIRLY QUICKLY ON THE SMALL SAMPLE DATABASE BUT IN A REAL CORPORATE DATABASE WITH MANY MILLIONS OF ROWS THEY WOULD TAKE A LONG TIME 2ATHER THAN RUNNING MANY LONG THREE TABLE QUERIES YOU COULD CREATE A NEW TABLE NAMED ")'/2$%23 TO CONTAIN THE REQUIRED DATA DEFINED AS FOLLOWS
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$ATABASEç5PDATESç
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/NCE YOU HAVE CREATED THE ")'/2$%23 TABLE THIS MULTIROW ).3%24 STATEMENT CAN BE USED TO POPULATE IT ,OAD DATA INTO THE ")'/2$%23 TABLE FOR ANALYSIS ).3%24 ).4/ ")'/2$%23 !-/5.4 #/-0!.9 .!-% 0%2& 02/$5#4 -&2 149 3%,%#4 !-/5.4 #/-0!.9 .!-% 3!,%3 15/4! 02/$5#4 -&2 149 &2/- /2$%23 #534/-%23 3!,%32%03 7(%2% #534 #534?.5- !.$ 2%0 %-0,?.5- !.$ !-/5.4 ROWS INSERTED
)N A LARGE DATABASE THIS ).3%24 STATEMENT MAY TAKE A WHILE TO EXECUTE BECAUSE IT INVOLVES A THREE TABLE QUERY 7HEN THE STATEMENT IS COMPLETE THE DATA IN THE ")'/2$%23 TABLE WILL DUPLICATE INFORMATION IN OTHER TABLES )N ADDITION THE ")'/2$%23 TABLE WONT BE AUTOMATICALLY KEPT UP TO DATE WHEN NEW ORDERS ARE ADDED TO THE DATABASE SO ITS DATA MAY QUICKLY BECOME OUTDATED %ACH OF THESE FACTORS SEEMS LIKE A DISADVANTAGE (OWEVER THE SUBSEQUENT DATA ANALYSIS QUERIES AGAINST THE ")'/2$%23 TABLE CAN BE EXPRESSED VERY SIMPLYTHEY BECOME SINGLE TABLE QUERIES &URTHERMORE EACH OF THOSE QUERIES WILL RUN MUCH FASTER THAN IF IT WERE A THREE TABLE JOIN #ONSEQUENTLY THIS IS PROBABLY A GOOD STRATEGY FOR PERFORMING THE ANALYSIS ESPECIALLY IF THE THREE ORIGINAL TABLES ARE LARGE )N THIS SITUATION ITS LIKELY THAT THE ")'/2$%23 TABLE WILL BE USED AS A TEMPORARY TABLE FOR DOING THE ANALYSIS )T WILL BE CREATED AND POPULATED WITH DATA REPRESENTING A SNAPSHOT OF THE ORDER STATUS IN TIME THE ANALYSIS PROGRAMS WILL BE RUN AND THEN THE TABLE WILL BE EMPTIED OR DROPPED
0!24ç)))
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4HE 31, STANDARD SPECIFIES SEVERAL LOGICAL RESTRICTIONS ON THE QUERY THAT APPEARS WITHIN THE MULTIROW ).3%24 STATEMENT s 4HE QUERY CANNOT CONTAIN AN /2$%2 "9 CLAUSE )TS USELESS TO SORT THE QUERY RESULTS ANYWAY BECAUSE THEYRE BEING INSERTED INTO A TABLE THAT IS LIKE ALL TABLES UNORDERED s 4HE QUERY RESULTS MUST CONTAIN THE SAME NUMBER OF COLUMNS AS THE COLUMN LIST IN THE ).3%24 STATEMENT OR AS THE ENTIRE TARGET TABLE IF THE COLUMN LIST IS OMITTED AND THE DATA TYPES MUST BE COMPATIBLE COLUMN BY COLUMN
"ULKõ,OADõ5TILITIES $ATA TO BE INSERTED INTO A DATABASE IS OFTEN DOWNLOADED FROM ANOTHER COMPUTER SYSTEM OR COLLECTED FROM OTHER SITES AND STORED IN A SEQUENTIAL FILE 4O LOAD THE DATA INTO A TABLE YOU COULD WRITE A PROGRAM WITH A LOOP THAT READS EACH RECORD OF THE FILE AND USES THE SINGLE ROW ).3%24 STATEMENT TO ADD THE ROW TO THE TABLE (OWEVER THE OVERHEAD OF HAVING THE $"-3 REPEATEDLY EXECUTE SINGLE ROW ).3%24 STATEMENTS MAY BE QUITE HIGH )F INSERTING A SINGLE ROW TAKES HALF A SECOND UNDER A TYPICAL SYSTEM LOAD ITS PROBABLY ACCEPTABLE PERFORMANCE FOR AN INTERACTIVE PROGRAM "UT THAT PERFORMANCE QUICKLY BECOMES UNACCEPTABLE WHEN APPLIED TO THE TASK OF BULK LOADING ROWS OF DATA )N THIS CASE LOADING THE DATA WOULD REQUIRE OVER SIX HOURS &OR THIS REASON MOST COMMERCIAL $"-3 PRODUCTS INCLUDE A BULK LOAD FEATURE THAT LOADS DATA FROM A FILE INTO A TABLE AT HIGH SPEED 4HE !.3))3/ 31, STANDARD DOES NOT ADDRESS THIS FUNCTION AND IT IS USUALLY PROVIDED AS A STAND ALONE UTILITY PROGRAM RATHER THAN AS PART OF THE 31, LANGUAGE %ACH VENDORS UTILITY PROVIDES A SLIGHTLY DIFFERENT SET OF FEATURES FUNCTIONS AND COMMANDS 7HEN 31, IS USED FROM WITHIN AN APPLICATION PROGRAM ANOTHER TECHNIQUE IS FREQUENTLY PROVIDED FOR MORE EFFICIENTLY INSERTING A LARGE AMOUNT OF DATA INTO A DATABASE 4HE STANDARD PROGRAMMATIC ).3%24 STATEMENT INSERTS A SINGLE ROW OF DATA JUST LIKE THE INTERACTIVE SINGLE ROW ).3%24 STATEMENTS IN THE PRECEDING EXAMPLES "UT MANY COMMERCIAL $"-3 PRODUCTS ALLOW DATA FROM TWO OR MORE ROWS OFTEN UP TO HUNDREDS OF ROWS TO BE SUPPLIED AS PART OF A SINGLE BULK ).3%24 STATEMENT !LL OF THE SUPPLIED DATA MUST BE FOR NEW ROWS OF THE SINGLE TABLE THAT IS THE TARGET OF THE ).3%24 STATEMENT AND NAMED IN THE ).4/ CLAUSE %XECUTING A BULK ).3%24 STATEMENT FOR ROWS OF DATA HAS EXACTLY THE SAME EFFECT AS EXECUTING INDIVIDUAL SINGLE ROW ).3%24 STATEMENTS (OWEVER IT IS USUALLY MUCH MORE EFFICIENT BECAUSE IT INVOLVES ONLY ONE CALL TO THE $"-3 7HEN THOUSANDS OF ROWS ARE LOADED THE PERFORMANCE GAIN CAN BE AN ORDER OF MAGNITUDE OR MORE
$ELETINGõ$ATAõFROMõTHEõ$ATABASE ! ROW OF DATA IS TYPICALLY DELETED FROM A DATABASE WHEN THE ENTITY REPRESENTED BY THE ROW DISAPPEARS FROM THE OUTSIDE WORLD &OR EXAMPLE IN THE SAMPLE DATABASE s 7HEN A CUSTOMER CANCELS AN ORDER THE CORRESPONDING ROW OF THE /2$%23 TABLE MUST BE DELETED s 7HEN A SALESPERSON LEAVES THE COMPANY THE CORRESPONDING ROW OF THE 3!,%32%03 TABLE MUST BE DELETED s 7HEN A SALES OFFICE IS CLOSED THE CORRESPONDING ROW OF THE /&&)#%3 TABLE MUST BE DELETED )F THE SALESPEOPLE IN THE OFFICE ARE TERMINATED THEIR ROWS SHOULD BE DELETED FROM THE 3!,%32%03 TABLE AS WELL )F THEY ARE REASSIGNED THEIR 2%0?/&&)#% COLUMN VALUES MUST BE UPDATED
#HAPTERçç
$ATABASEç5PDATESç
1, Ê£äxÊ $%,%4%ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
)N EACH CASE THE ROW IS DELETED TO MAINTAIN THE DATABASE AS AN ACCURATE MODEL OF THE REAL WORLD 4HE SMALLEST UNIT OF DATA THAT CAN BE DELETED FROM A RELATIONAL DATABASE IS A SINGLE ROW
4HEõ$%,%4%õ3TATEMENT 4HE $%,%4% STATEMENT SHOWN IN &IGURE REMOVES SELECTED ROWS OF DATA FROM A SINGLE TABLE 4HE &2/- CLAUSE SPECIFIES THE TARGET TABLE CONTAINING THE ROWS 4HE 7(%2% CLAUSE SPECIFIES WHICH ROWS OF THE TABLE ARE TO BE DELETED 3UPPOSE (ENRY *ACOBSEN THE NEW SALESPERSON HIRED EARLIER IN THIS CHAPTER HAS JUST DECIDED TO LEAVE THE COMPANY 4HE $%,%4% STATEMENT THAT REMOVES HIS ROW FROM THE 3!,%32%03 TABLE IS SHOWN NEXT 2EMOVE (ENRY *ACOBSEN FROM THE DATABASE
4HE 7(%2% CLAUSE IN THIS EXAMPLE IDENTIFIES A SINGLE ROW OF THE 3!,%32%03 TABLE WHICH 31, REMOVES FROM THE TABLE 4HE 7(%2% CLAUSE SHOULD HAVE A FAMILIAR APPEARANCEITS EXACTLY THE SAME 7(%2% CLAUSE THAT YOU WOULD SPECIFY IN A 3%,%#4 STATEMENT TO RETRIEVE THE SAME ROW FROM THE TABLE 4HE SEARCH CONDITIONS THAT CAN BE SPECIFIED IN THE 7(%2% CLAUSE OF THE $%,%4% STATEMENT ARE THE SAME ONES AVAILABLE IN THE 7(%2% CLAUSE OF THE 3%,%#4 STATEMENT AS DESCRIBED IN #HAPTERS THROUGH 2ECALL THAT SEARCH CONDITIONS IN THE 7(%2% CLAUSE OF A 3%,%#4 STATEMENT CAN SPECIFY A SINGLE ROW OR AN ENTIRE SET OF ROWS DEPENDING ON THE SPECIFIC SEARCH CONDITION 4HE SAME IS TRUE OF THE 7(%2% CLAUSE IN A $%,%4% STATEMENT 3UPPOSE FOR EXAMPLE THAT -R *ACOBSENS CUSTOMER )NTER#ORP CUSTOMER NUMBER HAS CALLED TO CANCEL ALL ITS ORDERS (ERE IS THE $%,%4% STATEMENT THAT REMOVES THE ORDERS FROM THE /2$%23 TABLE 2EMOVE ALL ORDERS FOR )NTER#ORP CUSTOMER NUMBER $%,%4% &2/- /2$%23 7(%2% #534 ROWS DELETED
)N THIS CASE THE 7(%2% CLAUSE SELECTS TWO ROWS OF THE /2$%23 TABLE AND 31, REMOVES BOTH OF THEM FROM THE TABLE #ONCEPTUALLY 31, APPLIES THE 7(%2% CLAUSE TO EACH ROW OF THE /2$%23 TABLE DELETING THOSE WHERE THE SEARCH CONDITION YIELDS A 425% RESULT AND RETAINING THOSE WHERE THE SEARCH CONDITION YIELDS A &!,3% OR .5,, RESULT "ECAUSE THIS TYPE OF $%,%4% STATEMENT SEARCHES THROUGH A TABLE FOR THE ROWS TO BE DELETED IT IS SOMETIMES CALLED A SEARCHED $%,%4% STATEMENT 4HIS TERM IS USED TO CONTRAST IT WITH
0!24ç)))
$%,%4% &2/- 3!,%32%03 7(%2% .!-% g(ENRY *ACOBSENg ROW DELETED
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0ARTç)))ç
5PDATINGç$ATA
ANOTHER FORM OF THE $%,%4% STATEMENT CALLED THE POSITIONED $%,%4% STATEMENT WHICH ALWAYS DELETES A SINGLE ROW 4HE POSITIONED $%,%4% STATEMENT APPLIES ONLY TO PROGRAMMATIC 31, AND IS DESCRIBED IN #HAPTER (ERE ARE SOME ADDITIONAL EXAMPLES OF SEARCHED $%,%4% STATEMENTS $ELETE ALL ORDERS PLACED BEFORE .OVEMBER $%,%4% &2/- /2$%23 7(%2% /2$%2?$!4% g g ROWS DELETED
$ELETE ALL ROWS FOR CUSTOMERS SERVED BY "ILL !DAMS -ARY *ONES OR $AN 2OBERTS EMPLOYEE NUMBERS AND $%,%4% &2/- #534/-%23 7(%2% #534?2%0 ). ROWS DELETED
$ELETE ALL SALESPEOPLE HIRED BEFORE *ULY WHO HAVE NOT YET BEEN ASSIGNED A QUOTA $%,%4% &2/- 3!,%32%03 7(%2% ()2%?$!4% g g !.$ 15/4! )3 .5,, ROWS DELETED
$ELETINGõ!LLõ2OWS 4HE 7(%2% CLAUSE IN A $%,%4% STATEMENT IS OPTIONAL BUT IT IS ALMOST ALWAYS PRESENT )F THE 7(%2% CLAUSE IS OMITTED FROM A $%,%4% STATEMENT ALL ROWS OF THE TARGET TABLE ARE DELETED AS IN THIS EXAMPLE $ELETE ALL ORDERS $%,%4% &2/- /2$%23 ROWS DELETED
!LTHOUGH THIS $%,%4% STATEMENT PRODUCES AN EMPTY TABLE IT DOES NOT ERASE THE /2$%23 TABLE FROM THE DATABASE 4HE DEFINITION OF THE /2$%23 TABLE AND ITS COLUMNS IS STILL STORED IN THE DATABASE 4HE TABLE STILL EXISTS AND NEW ROWS CAN STILL BE INSERTED INTO THE /2$%23 TABLE WITH THE ).3%24 STATEMENT 4O ERASE THE DEFINITION OF THE TABLE FROM THE DATABASE THE $2/0 4!",% STATEMENT DESCRIBED IN #HAPTER MUST BE USED "ECAUSE OF THE POTENTIAL DAMAGE FROM SUCH A $%,%4% STATEMENT BE CAREFUL TO ALWAYS SPECIFY A SEARCH CONDITION AND BE SURE THAT IT ACTUALLY SELECTS THE ROWS YOU WANT 7HEN USING INTERACTIVE 31, ITS A GOOD IDEA FIRST TO USE THE 7(%2% CLAUSE IN A 3%,%#4 STATEMENT TO DISPLAY THE SELECTED ROWS -AKE SURE THEY ARE THE ONES YOU WANT TO DELETE AND ONLY THEN USE THE 7(%2% CLAUSE IN A $%,%4% STATEMENT
#HAPTERçç
$ATABASEç5PDATESç
$%,%4%õWITHõ3UBQUERY
$%,%4% STATEMENTS WITH SIMPLE SEARCH CONDITIONS SUCH AS THOSE IN THE PREVIOUS EXAMPLES SELECT ROWS FOR DELETION BASED SOLELY ON THE CONTENTS OF THE ROWS THEMSELVES 3OMETIMES THE SELECTION OF ROWS MUST BE MADE BASED ON DATA FROM OTHER TABLES &OR EXAMPLE SUPPOSE YOU WANT TO DELETE ALL ORDERS TAKEN BY 3UE 3MITH 7ITHOUT KNOWING HER EMPLOYEE NUMBER YOU CANT FIND THE ORDERS BY CONSULTING THE /2$%23 TABLE ALONE 4O FIND THE ORDERS YOU COULD USE A TWO TABLE QUERY &IND THE ORDERS TAKEN BY 3UE 3MITH 3%,%#4 /2$%2?.5- !-/5.4 &2/- /2$%23 3!,%32%03 7(%2% 2%0 %-0,?.5- !.$ .!-% g3UE 3MITHg /2$%2?.5- !-/5.4
$%,%4% &2/- /2$%23 3!,%32%03 7(%2% 2%0 %-0,?.5- !.$ .!-% g3UE 3MITHg %RROR -ORE THAN ONE TABLE SPECIFIED IN &2/- CLAUSE
4HE WAY TO HANDLE THE REQUEST IS WITH ONE OF THE SUBQUERY SEARCH CONDITIONS (ERE IS A VALID FORM OF THE $%,%4% STATEMENT THAT HANDLES THE REQUEST $ELETE THE ORDERS TAKEN BY 3UE 3MITH $%,%4% &2/- /2$%23 7(%2% 2%0 3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% .!-% g3UE 3MITHg ROWS DELETED
4HE SUBQUERY FINDS THE EMPLOYEE NUMBER FOR 3UE 3MITH AND THE 7(%2% CLAUSE THEN SELECTS THE ORDERS WITH A MATCHING VALUE !S THIS EXAMPLE SHOWS SUBQUERIES CAN PLAY AN IMPORTANT ROLE IN THE $%,%4% STATEMENT BECAUSE THEY LET YOU DELETE ROWS BASED ON INFORMATION IN OTHER TABLES (ERE ARE TWO MORE EXAMPLES OF $%,%4% STATEMENTS THAT USE SUBQUERY SEARCH CONDITIONS $ELETE CUSTOMERS SERVED BY SALESPEOPLE WHOSE SALES ARE LESS THAN PERCENT OF QUOTA $%,%4% &2/- #534/-%23 7(%2% #534?2%0 ). 3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% 3!,%3 15/4! ROWS DELETED
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"UT YOU CANT USE A JOIN IN A $%,%4% STATEMENT 4HE PARALLEL $%,%4% STATEMENT IS ILLEGAL
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5PDATINGç$ATA
$ELETE ANY SALESPERSON WHOSE CURRENT ORDERS TOTAL LESS THAN PERCENT OF THEIR QUOTA $%,%4% &2/- 3!,%32%03 7(%2% 15/4! 3%,%#4 35-!-/5.4 &2/- /2$%23 7(%2% 2%0 %-0,?.5- ROW DELETED
3UBQUERIES IN THE 7(%2% CLAUSE CAN BE NESTED JUST AS THEY CAN BE IN THE 7(%2% CLAUSE OF THE 3%,%#4 STATEMENT 4HEY CAN ALSO CONTAIN OUTER REFERENCES TO THE TARGET TABLE OF THE $%,%4% STATEMENT )N THIS RESPECT THE &2/- CLAUSE OF THE $%,%4% STATEMENT FUNCTIONS LIKE THE &2/- CLAUSE OF THE 3%,%#4 STATEMENT (ERE IS AN EXAMPLE OF A DELETION REQUEST THAT REQUIRES A SUBQUERY WITH AN OUTER REFERENCE $ELETE CUSTOMERS WHO HAVE NOT ORDERED SINCE .OVEMBER $%,%4% &2/- #534/-%23 7(%2% ./4 %8)343 3%,%#4 &2/- /2$%23 7(%2% #534 #534?.5- !.$ /2$%2?$!4% g g ROWS DELETED
#ONCEPTUALLY THIS $%,%4% STATEMENT OPERATES BY GOING THROUGH THE #534/-%23 TABLE ROW BY ROW AND CHECKING THE SEARCH CONDITION &OR EACH CUSTOMER THE SUBQUERY SELECTS ANY ORDERS PLACED BY THAT CUSTOMER BEFORE THE CUTOFF DATE 4HE REFERENCE TO THE #534?.5- COLUMN IN THE SUBQUERY IS AN OUTER REFERENCE TO THE CUSTOMER NUMBER IN THE ROW OF THE #534/-%23 TABLE CURRENTLY BEING CHECKED BY THE $%,%4% STATEMENT 4HE SUBQUERY IN THIS EXAMPLE IS A CORRELATED SUBQUERY AS DESCRIBED IN #HAPTER /UTER REFERENCES WILL OFTEN BE FOUND IN SUBQUERIES OF A $%,%4% STATEMENT BECAUSE THEY IMPLEMENT THE JOIN BETWEEN THE TABLES IN THE SUBQUERY AND THE TARGET TABLE OF THE $%,%4% STATEMENT 4HE 31, STANDARD SPECIFIES THAT THE $%,%4% STATEMENT SHOULD TREAT SUCH A SUBQUERY AS APPLYING TO THE ENTIRE TARGET TABLE BEFORE ANY ROWS HAVE BEEN DELETED 4HIS PLACES MORE OVERHEAD ON THE $"-3 WHICH MUST HANDLE THE SUBQUERY PROCESSING AND ROW DELETION MORE CAREFULLY BUT THE BEHAVIOR OF THE STATEMENT IS WELL DEFINED BY THE STANDARD
-ODIFYINGõ$ATAõINõTHEõ$ATABASE 4YPICALLY THE VALUES OF DATA ITEMS STORED IN A DATABASE ARE MODIFIED WHEN CORRESPONDING CHANGES OCCUR IN THE OUTSIDE WORLD &OR EXAMPLE IN THE SAMPLE DATABASE s 7HEN A CUSTOMER CALLS TO CHANGE THE QUANTITY ON AN ORDER THE 149 COLUMN IN THE APPROPRIATE ROW OF THE /2$%23 TABLE MUST BE MODIFIED s 7HEN A MANAGER MOVES FROM ONE OFFICE TO ANOTHER THE -'2 COLUMN IN THE /&&)#%3 TABLE AND THE 2%0?/&&)#% COLUMN IN THE 3!,%32%03 TABLE MUST BE CHANGED TO REFLECT THE NEW ASSIGNMENT s 7HEN SALES QUOTAS ARE RAISED BY PERCENT IN THE .EW 9ORK SALES OFFICE THE 15/4! COLUMN OF THE APPROPRIATE ROWS IN THE 3!,%32%03 TABLE MUST BE MODIFIED
#HAPTERçç
$ATABASEç5PDATESç
)N EACH CASE DATA VALUES IN THE DATABASE ARE UPDATED TO MAINTAIN THE DATABASE AS AN ACCURATE MODEL OF THE REAL WORLD 4HE SMALLEST UNIT OF DATA THAT CAN BE MODIFIED IN A DATABASE IS A SINGLE COLUMN OF A SINGLE ROW
4HEõ50$!4%õ3TATEMENT 4HE 50$!4% STATEMENT SHOWN IN &IGURE MODIFIES THE VALUES OF ONE OR MORE COLUMNS IN SELECTED ROWS OF A SINGLE TABLE 4HE TARGET TABLE TO BE UPDATED IS NAMED IN THE STATEMENT AND YOU MUST HAVE THE REQUIRED PERMISSION TO UPDATE THE TABLE AS WELL AS EACH OF THE INDIVIDUAL COLUMNS THAT WILL BE MODIFIED 4HE 7(%2% CLAUSE SELECTS THE ROWS OF THE TABLE TO BE MODIFIED 4HE 3%4 CLAUSE SPECIFIES WHICH COLUMNS ARE TO BE UPDATED AND CALCULATES THE NEW VALUES FOR THEM (ERE IS A SIMPLE 50$!4% STATEMENT THAT CHANGES THE CREDIT LIMIT AND SALESPERSON FOR A CUSTOMER 2AISE THE CREDIT LIMIT FOR !CME -ANUFACTURING TO AND REASSIGN THE COMPANY TO -ARY *ONES EMPLOYEE NUMBER
)N THIS EXAMPLE THE 7(%2% CLAUSE IDENTIFIES A SINGLE ROW OF THE #534/-%23 TABLE AND THE 3%4 CLAUSE ASSIGNS NEW VALUES TO TWO OF THE COLUMNS IN THAT ROW 4HE 7(%2% CLAUSE IS EXACTLY THE SAME ONE YOU WOULD USE IN A $%,%4% OR 3%,%#4 STATEMENT TO IDENTIFY THE ROW )N FACT THE SEARCH CONDITIONS THAT CAN APPEAR IN THE 7(%2% CLAUSE OF AN 50$!4% STATEMENT ARE EXACTLY THE SAME AS THOSE AVAILABLE IN THE 3%,%#4 AND $%,%4% STATEMENTS ,IKE THE $%,%4% STATEMENT THE 50$!4% STATEMENT CAN UPDATE SEVERAL ROWS AT ONCE WITH THE PROPER SEARCH CONDITION AS IN THIS EXAMPLE 4RANSFER ALL SALESPEOPLE FROM THE #HICAGO OFlCE NUMBER TO THE .EW 9ORK OFlCE NUMBER AND LOWER THEIR QUOTAS BY PERCENT 50$!4% 3!,%32%03 3%4 2%0?/&&)#% 15/4! 15/4! 7(%2% 2%0?/&&)#% ROWS UPDATED
1, Ê£äÈÊ 50$!4%ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
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50$!4% #534/-%23 3%4 #2%$)4?,)-)4 #534?2%0 7(%2% #/-0!.9 g!CME -FGg ROW UPDATED
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5PDATINGç$ATA
)N THIS CASE THE 7(%2% CLAUSE SELECTS SEVERAL ROWS OF THE 3!,%32%03 TABLE AND THE VALUE OF THE 2%0?/&&)#% AND 15/4! COLUMNS ARE MODIFIED IN ALL OF THEM #ONCEPTUALLY 31, PROCESSES THE 50$!4% STATEMENT BY GOING THROUGH THE 3!,%32%03 TABLE ROW BY ROW UPDATING THOSE ROWS FOR WHICH THE SEARCH CONDITION YIELDS A 425% RESULT AND SKIPPING OVER THOSE FOR WHICH THE SEARCH CONDITION YIELDS A &!,3% OR .5,, RESULT "ECAUSE IT SEARCHES THE TABLE THIS FORM OF THE 50$!4% STATEMENT IS SOMETIMES CALLED A SEARCHED 50$!4% STATEMENT 4HIS TERM DISTINGUISHES IT FROM A DIFFERENT FORM OF THE 50$!4% STATEMENT CALLED A POSITIONED 50$!4% STATEMENT WHICH ALWAYS UPDATES A SINGLE ROW 4HE POSITIONED 50$!4% STATEMENT APPLIES ONLY TO PROGRAMMATIC 31, AND IS DESCRIBED IN #HAPTER (ERE ARE SOME ADDITIONAL EXAMPLES OF SEARCHED 50$!4% STATEMENTS 2EASSIGN ALL CUSTOMERS SERVED BY EMPLOYEE NUMBERS OR TO EMPLOYEE NUMBER 50$!4% #534/-%23 3%4 #534?2%0 7(%2% #534?2%0 ). ROWS UPDATED
!SSIGN A QUOTA OF TO ANY SALESPERSON WHO CURRENTLY HAS NO QUOTA 50$!4% 3!,%32%03 3%4 15/4! 7(%2% 15/4! )3 .5,, ROW UPDATED
4HE 3%4 CLAUSE IN THE 50$!4% STATEMENT IS A LIST OF ASSIGNMENTS SEPARATED BY COMMAS %ACH ASSIGNMENT IDENTIFIES A TARGET COLUMN TO BE UPDATED AND SPECIFIES HOW TO CALCULATE THE NEW VALUE FOR THE TARGET COLUMN %ACH TARGET COLUMN SHOULD APPEAR ONLY ONCE IN THE LIST THERE SHOULD NOT BE TWO ASSIGNMENTS FOR THE SAME TARGET COLUMN 4HE !.3))3/ SPECIFICATION MANDATES UNQUALIFIED NAMES FOR THE TARGET COLUMNS BUT SOME 31, IMPLEMENTATIONS ALLOW QUALIFIED COLUMN NAMES 4HERE CAN BE NO AMBIGUITY IN THE COLUMN NAMES ANYWAY BECAUSE THEY MUST REFER TO COLUMNS OF THE TARGET TABLE 4HE EXPRESSION IN EACH ASSIGNMENT CAN BE ANY VALID 31, EXPRESSION THAT YIELDS A VALUE OF THE APPROPRIATE DATA TYPE FOR THE TARGET COLUMN 4HE EXPRESSION MUST BE COMPUTABLE BASED ON THE VALUES OF THE ROW CURRENTLY BEING UPDATED IN THE TARGET TABLE )N MOST $"-3 IMPLEMENTATIONS THE EXPRESSION MAY NOT INCLUDE ANY COLUMN FUNCTIONS OR SUBQUERIES )F AN EXPRESSION IN THE ASSIGNMENT LIST REFERENCES ONE OF THE COLUMNS OF THE TARGET TABLE THE VALUE USED TO CALCULATE THE EXPRESSION IS THE VALUE OF THAT COLUMN IN THE CURRENT ROW BEFORE ANY UPDATES ARE APPLIED 4HE SAME IS TRUE OF COLUMN REFERENCES THAT OCCUR IN THE 7(%2% CLAUSE &OR EXAMPLE CONSIDER THIS SOMEWHAT CONTRIVED 50$!4% STATEMENT 50$!4% 3!,%32%03 3%4 15/4! 3!,%3 15/4! 7(%2% 15/4!
"EFORE THE UPDATE "ILL !DAMS HAD A 15/4! VALUE OF AND A 3!,%3 VALUE OF !FTER THE UPDATE HIS ROW HAS A 3!,%3 VALUE OF NOT 4HE ORDER OF THE ASSIGNMENTS IN THE 3%4 CLAUSE IS THUS IMMATERIAL THE ASSIGNMENTS CAN BE SPECIFIED IN ANY ORDER
#HAPTERçç
$ATABASEç5PDATESç
5PDATINGõ!LLõ2OWS 4HE 7(%2% CLAUSE IN THE 50$!4% STATEMENT IS OPTIONAL )F THE 7(%2% CLAUSE IS OMITTED THEN ALL ROWS OF THE TARGET TABLE ARE UPDATED AS IN THIS EXAMPLE 2AISE ALL QUOTAS BY PERCENT 50$!4% 3!,%32%03 3%4 15/4! 15/4! ROWS UPDATED
5NLIKE THE $%,%4% STATEMENT IN WHICH THE 7(%2% CLAUSE IS ALMOST NEVER OMITTED THE 50$!4% STATEMENT WITHOUT A 7(%2% CLAUSE PERFORMS A USEFUL FUNCTION )T BASICALLY PERFORMS A BULK UPDATE OF THE ENTIRE TABLE AS DEMONSTRATED IN THE PRECEDING EXAMPLE
50$!4%õWITHõ3UBQUERY
!S WITH THE $%,%4% STATEMENT SUBQUERIES CAN PLAY AN IMPORTANT ROLE IN THE 50$!4% STATEMENT BECAUSE THEY LET YOU SELECT ROWS TO UPDATE BASED ON INFORMATION CONTAINED IN OTHER TABLES (ERE ARE SEVERAL EXAMPLES OF 50$!4% STATEMENTS THAT USE SUBQUERIES
50$!4% #534/-%23 3%4 #2%$)4?,)-)4 #2%$)4?,)-)4 7(%2% #534?.5- ). 3%,%#4 $)34).#4 #534 &2/- /2$%23 7(%2% !-/5.4 ROWS UPDATED
2EASSIGN ALL CUSTOMERS SERVED BY SALESPEOPLE WHOSE SALES ARE LESS THAN PERCENT OF THEIR QUOTA 50$!4% #534/-%23 3%4 #534?2%0 7(%2% #534?2%0 ). 3%,%#4 %-0,?.5- &2/- 3!,%32%03 7(%2% 3!,%3 15/4! ROWS UPDATED
(AVE ALL SALESPEOPLE WHO SERVE OVER THREE CUSTOMERS REPORT DIRECTLY TO 3AM #LARK EMPLOYEE NUMBER 50$!4% 3!,%32%03 3%4 -!.!'%2 7(%2% 3%,%#4 #/5.4 &2/- #534/-%23 7(%2% #534?2%0 %-0,?.5- ROW UPDATED
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2AISE BY THE CREDIT LIMIT OF ANY CUSTOMER WHO HAS PLACED AN ORDER FOR MORE THAN
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0ARTç)))ç
5PDATINGç$ATA
!S IN THE $%,%4% STATEMENT SUBQUERIES IN THE 7(%2% CLAUSE OF THE 50$!4% STATEMENT CAN BE NESTED TO ANY LEVEL AND CAN CONTAIN OUTER REFERENCES TO THE TARGET TABLE OF THE 50$!4% STATEMENT 4HE COLUMN %-0,?.5- IN THE SUBQUERY OF THE PRECEDING EXAMPLE IS SUCH AN OUTER REFERENCE IT REFERS TO THE %-0,?.5- COLUMN IN THE ROW OF THE 3!,%32%03 TABLE CURRENTLY BEING CHECKED BY THE 50$!4% STATEMENT 4HE SUBQUERY IN THIS EXAMPLE IS A CORRELATED SUBQUERY AS DESCRIBED IN #HAPTER /UTER REFERENCES WILL OFTEN BE FOUND IN SUBQUERIES OF AN 50$!4% STATEMENT BECAUSE THEY IMPLEMENT THE JOIN BETWEEN THE TABLES IN THE SUBQUERY AND THE TARGET TABLE OF THE 50$!4% STATEMENT 4HE 31, STANDARD SPECIFIES THAT A REFERENCE TO THE TARGET TABLE IN A SUBQUERY IS EVALUATED AS IF NONE OF THE TARGET TABLE HAD BEEN UPDATED
3UMMARY 4HIS CHAPTER DESCRIBED THE 31, STATEMENTS THAT ARE USED TO MODIFY THE CONTENTS OF A DATABASE s 4HE SINGLE ROW ).3%24 STATEMENT ADDS ONE ROW OF DATA TO A TABLE 4HE VALUES FOR THE NEW ROW ARE SPECIFIED IN THE STATEMENT AS CONSTANTS s 4HE MULTIROW ).3%24 STATEMENT ADDS ZERO OR MORE ROWS TO A TABLE 4HE VALUES FOR THE NEW ROWS COME FROM A QUERY SPECIFIED AS PART OF THE ).3%24 STATEMENT s 4HE $%,%4% STATEMENT DELETES ZERO OR MORE ROWS OF DATA FROM A TABLE 4HE ROWS TO BE DELETED ARE SPECIFIED BY A SEARCH CONDITION s 4HE 50$!4% STATEMENT MODIFIES THE VALUES OF ONE OR MORE COLUMNS IN ZERO OR MORE ROWS OF A TABLE 4HE ROWS TO BE UPDATED ARE SPECIFIED BY A SEARCH CONDITION 4HE COLUMNS TO BE UPDATED AND THE EXPRESSIONS THAT CALCULATE THEIR NEW VALUES ARE SPECIFIED IN THE 50$!4% STATEMENT 5NLIKE THE 3%,%#4 STATEMENT WHICH CAN OPERATE ON MULTIPLE TABLES THE ).3%24 $%,%4% AND 50$!4% STATEMENTS WORK ON ONLY A SINGLE TABLE AT A TIME 4HE SEARCH CONDITION USED IN THE $%,%4% AND 50$!4% STATEMENTS HAS THE SAME FORM AS THE SEARCH CONDITION FOR THE 3%,%#4 STATEMENT
#(!04%2
$ATAç)NTEGRITY
4
HE TERM DATA INTEGRITY REFERS TO THE CORRECTNESS AND COMPLETENESS OF THE DATA IN A DATABASE 7HEN THE CONTENTS OF A DATABASE ARE MODIFIED WITH THE ).3%24 $%,%4% OR 50$!4% STATEMENTS THE INTEGRITY OF THE STORED DATA CAN BE LOST IN MANY DIFFERENT WAYS &OR EXAMPLE s )NVALID DATA MAY BE ADDED TO THE DATABASE SUCH AS AN ORDER THAT SPECIFIES A NONEXISTENT PRODUCT s %XISTING DATA MAY BE MODIFIED TO AN INCORRECT VALUE SUCH AS REASSIGNING A SALESPERSON TO A NONEXISTENT OFFICE s #HANGES TO THE DATABASE MAY BE LOST DUE TO A SYSTEM ERROR OR POWER FAILURE s #HANGES MAY BE PARTIALLY APPLIED SUCH AS ADDING AN ORDER FOR A PRODUCT WITHOUT ADJUSTING THE QUANTITY AVAILABLE FOR SALE /NE OF THE IMPORTANT ROLES OF A RELATIONAL $"-3 IS TO PRESERVE THE INTEGRITY OF ITS STORED DATA TO THE GREATEST EXTENT POSSIBLE 4HIS CHAPTER DESCRIBES THE 31, LANGUAGE FEATURES THAT ASSIST THE $"-3 IN THIS TASK
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5PDATINGç$ATA
7HATõ)Sõ$ATAõ)NTEGRITY 4O PRESERVE THE CONSISTENCY AND CORRECTNESS OF ITS STORED DATA A RELATIONAL $"-3 TYPICALLY IMPOSES ONE OR MORE DATA INTEGRITY CONSTRAINTS 4HESE CONSTRAINTS RESTRICT THE DATA VALUES THAT CAN BE INSERTED INTO THE DATABASE OR THAT RESULT FROM A DATABASE UPDATE 3EVERAL DIFFERENT TYPES OF DATA INTEGRITY CONSTRAINTS ARE COMMONLY FOUND IN RELATIONAL DATABASES INCLUDING s 2EQUIRED DATA 3OME COLUMNS IN A DATABASE MUST CONTAIN A VALID DATA VALUE IN EVERY ROW THEY ARE NOT ALLOWED TO CONTAIN MISSING OR .5,, VALUES )N THE SAMPLE DATABASE EVERY ORDER MUST HAVE AN ASSOCIATED CUSTOMER WHO PLACED THE ORDER 4HEREFORE THE #534 COLUMN IN THE /2$%23 TABLE IS A REQUIRED COLUMN 4HE $"-3 CAN BE ASKED TO PREVENT .5,, VALUES IN THIS COLUMN s 6ALIDITY CHECKING %VERY COLUMN IN A DATABASE HAS A DOMAIN A SET OF DATA VALUES THAT ARE LEGAL FOR THAT COLUMN 4HE SAMPLE DATABASE USES ORDER NUMBERS THAT BEGIN AT SO THE DOMAIN OF THE /2$%2?.5- COLUMN IS POSITIVE INTEGERS GREATER THAN 3IMILARLY EMPLOYEE NUMBERS IN THE %-0,?.5- COLUMN MUST FALL WITHIN THE NUMERIC RANGE OF TO 4HE $"-3 CAN BE ASKED TO PREVENT OTHER DATA VALUES IN THESE COLUMNS s %NTITY INTEGRITY 4HE PRIMARY KEY OF A TABLE MUST CONTAIN A UNIQUE VALUE IN EACH ROW WHICH IS DIFFERENT FROM THE VALUES IN ALL OTHER ROWS &OR EXAMPLE EACH ROW OF THE 02/$5#43 TABLE HAS A UNIQUE SET OF VALUES IN ITS -&2?)$ AND 02/$5#4?)$ COLUMNS WHICH UNIQUELY IDENTIFIES THE PRODUCT REPRESENTED BY THAT ROW $UPLICATE VALUES ARE ILLEGAL BECAUSE THEY WOULDNT ALLOW THE DATABASE TO DISTINGUISH ONE PRODUCT FROM ANOTHER 4HE $"-3 CAN BE ASKED TO ENFORCE THIS UNIQUE VALUE CONSTRAINT s 2EFERENTIAL INTEGRITY ! FOREIGN KEY IN A RELATIONAL DATABASE LINKS EACH ROW IN THE CHILD TABLE CONTAINING THE FOREIGN KEY TO THE ROW OF THE PARENT TABLE CONTAINING THE MATCHING PRIMARY KEY VALUE )N THE SAMPLE DATABASE THE VALUE IN THE 2%0?/&&)#% COLUMN OF EACH 3!,%32%03 ROW LINKS THE SALESPERSON REPRESENTED BY THAT ROW TO THE OFFICE WHERE HE OR SHE WORKS 4HE 2%0?/&&)#% COLUMN MUST CONTAIN A VALID VALUE FROM THE /&&)#% COLUMN OF THE /&&)#%3 TABLE OR THE SALESPERSON WILL BE ASSIGNED TO AN INVALID OFFICE 4HE $"-3 CAN BE ASKED TO ENFORCE THIS FOREIGN KEY PRIMARY KEY CONSTRAINT s /THER DATA RELATIONSHIPS 4HE REAL WORLD SITUATION MODELED BY A DATABASE WILL OFTEN HAVE ADDITIONAL CONSTRAINTS THAT GOVERN THE LEGAL DATA VALUES THAT MAY APPEAR IN THE DATABASE &OR EXAMPLE IN THE SAMPLE DATABASE THE SALES VICE PRESIDENT MAY WANT TO ENSURE THAT THE QUOTA TARGET FOR EACH OFFICE DOES NOT EXCEED THE TOTAL OF THE QUOTA TARGETS FOR THE SALESPEOPLE IN THAT OFFICE 4HE $"-3 CAN BE ASKED TO CHECK MODIFICATIONS TO THE OFFICE AND SALESPERSON QUOTA TARGETS TO MAKE SURE THAT THEIR VALUES ARE CONSTRAINED IN THIS WAY s "USINESS RULES 5PDATES TO A DATABASE MAY BE CONSTRAINED BY BUSINESS RULES GOVERNING THE REAL WORLD TRANSACTIONS THAT ARE REPRESENTED BY THE UPDATES &OR EXAMPLE THE COMPANY USING THE SAMPLE DATABASE MAY HAVE A BUSINESS RULE THAT FORBIDS ACCEPTING AN ORDER FOR WHICH THERE IS AN INADEQUATE PRODUCT INVENTORY 4HE $"-3 CAN BE ASKED TO CHECK EACH NEW ROW ADDED TO THE /2$%23 TABLE TO MAKE SURE THAT THE VALUE IN ITS 149 COLUMN DOES NOT VIOLATE THIS BUSINESS RULE
#HAPTERçç
$ATAç)NTEGRITYç
s #ONSISTENCY -ANY REAL WORLD TRANSACTIONS CAUSE MULTIPLE UPDATES TO A DATABASE &OR EXAMPLE ACCEPTING A CUSTOMER ORDER MAY INVOLVE ADDING A ROW TO THE /2$%23 TABLE INCREASING THE 3!,%3 COLUMN IN THE 3!,%32%03 TABLE FOR THE PERSON WHO TOOK THE ORDER AND INCREASING THE 3!,%3 COLUMN IN THE /&&)#%3 TABLE FOR THE OFFICE WHERE THAT SALESPERSON IS ASSIGNED 4HE ).3%24 AND BOTH 50$!4%S MUST ALL TAKE PLACE IN ORDER FOR THE DATABASE TO REMAIN IN A CONSISTENT CORRECT STATE 4HE $"-3 CAN BE ASKED TO ENFORCE THIS TYPE OF CONSISTENCY RULE OR TO SUPPORT APPLICATIONS THAT IMPLEMENT SUCH RULES 4HE !.3))3/ 31, STANDARD SPECIFIES SOME OF THE SIMPLER DATA INTEGRITY CONSTRAINTS &OR EXAMPLE THE REQUIRED DATA CONSTRAINT IS SUPPORTED BY THE !.3))3/ STANDARD AND IMPLEMENTED IN A UNIFORM WAY ACROSS ALMOST ALL COMMERCIAL 31, PRODUCTS -ORE COMPLEX CONSTRAINTS SUCH AS BUSINESS RULES CONSTRAINTS ARE NOT SPECIFIED BY THE !.3))3/ STANDARD AND THERE IS A WIDE VARIATION IN THE TECHNIQUES AND 31, SYNTAX USED TO SUPPORT THEM 4HE 31, FEATURES THAT SUPPORT THE FIRST FIVE INTEGRITY CONSTRAINTS ARE DESCRIBED IN THIS CHAPTER 4HE 31, TRANSACTION MECHANISM WHICH SUPPORTS THE CONSISTENCY CONSTRAINT IS DESCRIBED IN #HAPTER
4HE SIMPLEST DATA INTEGRITY CONSTRAINT REQUIRES THAT A COLUMN CONTAIN A NON .5,, VALUE 4HE !.3))3/ STANDARD AND MOST COMMERCIAL 31, PRODUCTS SUPPORT THIS CONSTRAINT BY ALLOWING YOU TO DECLARE THAT A COLUMN IS ./4 .5,, WHEN THE TABLE CONTAINING THE COLUMN IS FIRST CREATED 4HE ./4 .5,, CONSTRAINT IS SPECIFIED AS PART OF THE #2%!4% 4!",% STATEMENT DESCRIBED IN #HAPTER 7HEN A COLUMN IS DECLARED ./4 .5,, THE $"-3 ENFORCES THE CONSTRAINT BY ENSURING THE FOLLOWING s %VERY ).3%24 STATEMENT THAT ADDS ONE OR MORE NEW ROWS TO THE TABLE MUST SPECIFY A NON .5,, DATA VALUE FOR THE COLUMN !N ATTEMPT TO INSERT A ROW CONTAINING A .5,, VALUE EITHER EXPLICITLY OR IMPLICITLY RESULTS IN AN ERROR s %VERY 50$!4% STATEMENT THAT UPDATES THE COLUMN MUST ASSIGN IT A NON .5,, DATA VALUE !GAIN AN ATTEMPT TO UPDATE THE COLUMN TO A .5,, VALUE RESULTS IN AN ERROR /NE DISADVANTAGE OF THE ./4 .5,, CONSTRAINT IS THAT SOME 31, IMPLEMENTATIONS REQUIRE THAT IT BE SPECIFIED ONLY WHEN A TABLE IS FIRST CREATED 4YPICALLY YOU CAN GO BACK TO A PREVIOUSLY CREATED TABLE AND CHANGE A COLUMN TO ALLOW OR DISALLOW .5,, VALUES FOR A COLUMN (OWEVER THERE IS A POTENTIAL LOGICAL PROBLEM WITH ADDING THE ./4 .5,, CONSTRAINT TO AN EXISTING TABLE COLUMN )F ONE OR MORE ROWS OF THAT TABLE ALREADY CONTAIN .5,, VALUES THEN WHAT SHOULD THE $"-3 DO WITH THOSE ROWS 4HEY REPRESENT VALID REAL WORLD OBJECTS BUT THEY NOW VIOLATE THE NEW REQUIRED DATA CONSTRAINT 7HEN THE $"-3 DOES NOT SUPPORT ADDING A ./4 .5,, CONSTRAINT TO AN EXISTING TABLE THE RESTRICTION IS OFTEN AT LEAST PARTIALLY THE RESULT OF THE WAY THE $"-3 IMPLEMENTS .5,, VALUES INTERNALLY 3OME $"-3S RESERVE AN EXTRA BYTE IN EVERY STORED ROW OF DATA FOR EACH COLUMN THAT PERMITS .5,, VALUES 4HE EXTRA BYTE SERVES AS A NULL INDICATOR FOR THE COLUMN AND IS SET TO SOME SPECIFIED VALUE TO INDICATE A .5,, VALUE 7HEN A COLUMN IS DEFINED AS ./4 .5,, THE INDICATOR BYTE IS NOT PRESENT SAVING DISK STORAGE SPACE $YNAMICALLY ADDING AND REMOVING ./4 .5,, CONSTRAINTS WOULD THUS REQUIRE ON THE FLY RECONFIGURATION OF THE STORED ROWS ON THE DISK WHICH MAY NOT BE PRACTICAL IN A LARGE TABLE
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2EQUIREDõ$ATA
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5PDATINGç$ATA
3IMPLEõ6ALIDITYõ#HECKING 4HE MOST RUDIMENTARY SUPPORT FOR RESTRICTING THE LEGAL VALUES THAT CAN APPEAR IN A COLUMN COMES FROM THE DATA TYPES SPECIFIED IN THE 31, STANDARD 7HEN A TABLE IS CREATED EACH COLUMN IN THE TABLE IS ASSIGNED A DATA TYPE AND THE $"-3 ENSURES THAT ONLY DATA OF THE SPECIFIED TYPE IS INTRODUCED INTO THE COLUMN &OR EXAMPLE THE %-0,?.5- COLUMN IN THE 3!,%32%03 TABLE IS DEFINED AS AN ).4%'%2 AND THE $"-3 WILL PRODUCE AN ERROR IF AN ).3%24 OR 50$!4% STATEMENT TRIES TO STORE A CHARACTER STRING OR A DECIMAL NUMBER IN THE COLUMN (OWEVER THE FIRST VERSION OF THE 31, STANDARD 31, AND MANY EARLY COMMERCIAL 31, PRODUCTS DID NOT PROVIDE A WAY TO RESTRICT A COLUMN TO CERTAIN SPECIFIC DATA VALUES 4HE $"-3 WOULD HAPPILY INSERT A 3!,%32%03 ROW WITH AN EMPLOYEE NUMBER OF EVEN THOUGH EMPLOYEE NUMBERS IN THE SAMPLE DATABASE HAVE THREE DIGITS BY CONVENTION ! HIRE DATE OF $ECEMBER WOULD ALSO BE ACCEPTED EVEN THOUGH THE COMPANY IS CLOSED ON #HRISTMAS 0RIOR TO THE INTRODUCTION OF CHECK CONSTRAINTS AND DOMAINS IN THE 31, STANDARD COVERED IN SUBSEQUENT TOPICS SOME COMMERCIAL 31, IMPLEMENTATIONS PROVIDE EXTENDED FEATURES TO CHECK FOR LEGAL DATA VALUES &OR COMPATIBILITY MANY OF THESE EXTENDED FEATURES ARE STILL SUPPORTED BY THEIR VENDORS )N $" FOR EXAMPLE EACH TABLE IN THE DATABASE CAN BE ASSIGNED A CORRESPONDING VALIDATION PROCEDURE A USER WRITTEN PROGRAM TO CHECK FOR VALID DATA VALUES $" INVOKES THE VALIDATION PROCEDURE EACH TIME A 31, STATEMENT TRIES TO CHANGE OR INSERT A ROW OF THE TABLE AND GIVES THE VALIDATION PROCEDURE THE PROPOSED COLUMN VALUES FOR THE ROW 4HE VALIDATION PROCEDURE CHECKS THE DATA AND INDICATES BY ITS RETURN VALUE WHETHER THE DATA IS ACCEPTABLE 4HE VALIDATION PROCEDURE IS A CONVENTIONAL PROGRAM WRITTEN IN 3 ASSEMBLER OR 0,) FOR EXAMPLE SO IT CAN PERFORM WHATEVER DATA VALUE CHECKS ARE REQUIRED INCLUDING RANGE CHECKS AND INTERNAL CONSISTENCY CHECKS WITHIN THE ROW (OWEVER THE VALIDATION PROCEDURE CANNOT ACCESS THE DATABASE SO IT CANNOT BE USED TO CHECK FOR UNIQUE VALUES OR FOREIGN KEYPRIMARY KEY RELATIONSHIPS 31, 3ERVER ALSO PROVIDES A DATA VALIDATION CAPABILITY BY ALLOWING YOU TO CREATE A RULE THAT DETERMINES WHAT DATA VALUES CAN LEGALLY BE ENTERED INTO A PARTICULAR COLUMN 31, 3ERVER CHECKS THE RULE EACH TIME AN ).3%24 OR 50$!4% STATEMENT IS ATTEMPTED FOR THE TABLE THAT CONTAINS THE COLUMN 5NLIKE $"S VALIDATION PROCEDURES 31, 3ERVER RULES ARE WRITTEN IN THE 4RANSACT 31, DIALECT THAT IS USED BY 31, 3ERVER &OR EXAMPLE HERE IS A 4RANSACT 31, STATEMENT THAT ESTABLISHES A RULE FOR THE 15/4! COLUMN IN THE 3!,%32%03 TABLE #2%!4% 25,% 15/4!?,)-)4 !3 6!,5% "%47%%. !.$
4HIS RULE PREVENTS YOU FROM INSERTING OR UPDATING A QUOTA TO A NEGATIVE VALUE OR TO A VALUE GREATER THAN !S SHOWN IN THE EXAMPLE 31, 3ERVER ALLOWS YOU TO ASSIGN THE RULE A NAME 15/4!?,)-)4 IN THIS EXAMPLE ,IKE $" VALIDATION PROCEDURES HOWEVER 31, 3ERVER RULES MAY NOT REFERENCE COLUMNS OR OTHER DATABASE OBJECTS "EGINNING WITH 31, THE 31, STANDARD PROVIDES EXTENDED SUPPORT FOR VALIDITY CHECKING THROUGH TWO DIFFERENT FEATURESCOLUMN CHECK CONSTRAINTS AND DOMAINS "OTH GIVE THE DATABASE CREATOR A WAY TO TELL THE $"-3 HOW TO DETERMINE WHETHER A DATA VALUE IS VALID 4HE CHECK CONSTRAINT FEATURE SPECIFIES THE DATA VALIDITY TEST FOR A SINGLE COLUMN
#HAPTERçç
$ATAç)NTEGRITYç
4HE DOMAIN FEATURE LETS YOU SPECIFY THE VALIDITY TEST ONCE AND THEN REUSE IT IN THE DEFINITION OF MANY DIFFERENT COLUMNS WHOSE LEGAL DATA VALUES ARE THE SAME
#OLUMNõ#HECKõ#ONSTRAINTS ! CHECK CONSTRAINT IS A SEARCH CONDITION LIKE THE SEARCH CONDITION IN A 7(%2% CLAUSE THAT PRODUCES A TRUEFALSE VALUE 7HEN A CHECK CONSTRAINT IS SPECIFIED FOR A COLUMN THE $"-3 AUTOMATICALLY CHECKS THE VALUE OF THAT COLUMN EACH TIME A NEW ROW IS INSERTED OR A ROW IS UPDATED TO ENSURE THAT THE SEARCH CONDITION IS TRUE )F NOT THE ).3%24 OR 50$!4% STATEMENT FAILS ! COLUMN CHECK CONSTRAINT IS SPECIFIED AS PART OF THE COLUMN DEFINITION WITHIN THE #2%!4% 4!",% STATEMENT DESCRIBED IN #HAPTER #HECK CONSTRAINTS MAY ALSO BE ADDED TO EXISTING TABLES AS PART OF AN !,4%2 4!",% STATEMENT ALSO DESCRIBED IN #HAPTER #ONSIDER THIS EXCERPT FROM A #2%!4% 4!",% STATEMENT MODIFIED FROM THE DEFINITION OF THE DEMO DATABASE TO INCLUDE THREE CHECK CONSTRAINTS
4HE FIRST CONSTRAINT ON THE %-0,?.5- COLUMN REQUIRES THAT VALID EMPLOYEE NUMBERS BE THREE DIGIT NUMBERS BETWEEN AND 4HE SECOND CONSTRAINT ON THE !'% COLUMN SIMILARLY PREVENTS HIRING OF MINORS 4HE THIRD CONSTRAINT ON THE 15/4! COLUMN PREVENTS A SALESPERSON FROM HAVING A QUOTA TARGET LESS THAN !LL THREE OF THESE COLUMN CHECK CONSTRAINTS ARE VERY SIMPLE EXAMPLES OF THE CAPABILITY SPECIFIED BY THE 31, STANDARD )N GENERAL THE PARENTHESES FOLLOWING THE KEYWORD #(%#+ CAN CONTAIN ANY VALID SEARCH CONDITION THAT MAKES SENSE IN THE CONTEXT OF A COLUMN DEFINITION 7ITH THIS FLEXIBILITY A CHECK CONSTRAINT CAN COMPARE VALUES FROM TWO DIFFERENT COLUMNS OF THE TABLE OR EVEN COMPARE A PROPOSED DATA VALUE AGAINST OTHER VALUES FROM THE DATABASE 4HESE CAPABILITIES ARE MORE FULLY DESCRIBED IN THE h!DVANCED #ONSTRAINT #APABILITIESv SECTION LATER IN THIS CHAPTER
$OMAINS ! DOMAIN GENERALIZES THE CHECK CONSTRAINT CONCEPT AND ALLOWS YOU TO EASILY APPLY THE SAME CHECK CONSTRAINT TO MANY DIFFERENT COLUMNS WITHIN A DATABASE ! DOMAIN IS A COLLECTION OF LEGAL DATA VALUES !LTHOUGH DOMAINS HAVE BEEN SPECIFIED IN THE 31, STANDARD SINCE 31, THERE IS SPARSE SUPPORT FOR THEM IN CURRENT 31, IMPLEMENTATIONS !S OF THIS WRITING $" /RACLE 31, 3ERVER AND -Y31, ALL LACK SUPPORT FOR DOMAINS ALTHOUGH SOME PROPRIETARY EXTENSIONS COME CLOSE SUCH AS /RACLES #2%!4% 490% STATEMENT
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#2%!4% 4!",% 3!,%32%03 %-0,?.5- ).4%'%2 ./4 .5,, #(%#+ %-0,?.5- "%47%%. !.$ !'% ).4%'%2 #(%#+ !'% 15/4! $%#)-!, #(%#+ 15/4!
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5PDATINGç$ATA
9OU SPECIFY A DOMAIN AND ASSIGN IT A DOMAIN NAME BY USING THE #2%!4% $/-!). STATEMENT DESCRIBED IN #HAPTER !S WITH THE CHECK CONSTRAINT DEFINITION A SEARCH CONDITION IS USED TO DEFINE THE RANGE OF LEGAL DATA VALUES &OR EXAMPLE HERE IS A #2%!4% $/-!). STATEMENT TO CREATE THE DOMAIN 6!,)$?%-0,/9%%?)$ WHICH INCLUDES ALL LEGAL EMPLOYEE NUMBERS #2%!4% $/-!). 6!,)$?%-0,/9%%?)$ ).4%'%2 #(%#+ 6!,5% "%47%%. !.$
!FTER THE 6!,)$?%-0,/9%%?)$ DOMAIN HAS BEEN DEFINED IT MAY BE USED INSTEAD OF A DATA TYPE TO DEFINE COLUMNS IN DATABASE TABLES 5SING THIS CAPABILITY THE EXAMPLE #2%!4% 4!",% STATEMENT FOR THE 3!,%32%03 TABLE WOULD APPEAR AS #2%!4% 4!",% 3!,%32%03 %-0,?.5- 6!,)$?%-0,/9%%?)$ !'% ).4%'%2 #(%#+ !'% 15/4! $%#)-!, #(%#+ 15/4!
4HE ADVANTAGE OF USING THE DOMAIN IS THAT IF OTHER COLUMNS IN OTHER TABLES ALSO CONTAIN EMPLOYEE NUMBERS THE DOMAIN NAME CAN BE USED REPEATEDLY SIMPLIFYING THE TABLE DEFINITIONS 4HE /&&)#%3 TABLE CONTAINS SUCH A COLUMN #2%!4% 4!",% /&&)#%3 /&&)#% ).4%'%2 ./4 .5,, #)49 6!2#(!2 ./4 .5,, 2%')/. 6!2#(!2 ./4 .5,, -'2 6!,)$?%-0,/9%%?)$ 4!2'%4 $%#)-!, 3!,%3 $%#)-!, ./4 .5,,
!NOTHER ADVANTAGE OF DOMAINS IS THAT THE DEFINITION OF VALID DATA SUCH AS VALID EMPLOYEE NUMBERS IN THIS EXAMPLE IS STORED IN ONE CENTRAL PLACE WITHIN THE DATABASE )F THE DEFINITION CHANGES LATER FOR EXAMPLE IF THE COMPANY GROWS AND EMPLOYEE NUMBERS IN THE RANGE n MUST BE ALLOWED IT IS MUCH EASIER TO CHANGE ONE DOMAIN DEFINITION THAN TO CHANGE MANY COLUMN CONSTRAINTS SCATTERED THROUGHOUT THE DATABASE ! LARGE ENTERPRISE DATABASE MAY HAVE HUNDREDS OF DEFINED DOMAINS AND THE BENEFITS OF 31, DOMAINS FOR CHANGE MANAGEMENT CAN BE VERY SUBSTANTIAL
#HAPTERçç
$ATAç)NTEGRITYç
%NTITYõ)NTEGRITY ! TABLES PRIMARY KEY MUST HAVE A UNIQUE VALUE FOR EACH ROW OF THE TABLE OR THE DATABASE WILL LOSE ITS INTEGRITY AS A MODEL OF THE OUTSIDE WORLD &OR EXAMPLE IF TWO ROWS OF THE 3!,%32%03 TABLE BOTH HAD VALUE IN THEIR %-0,?.5- COLUMN IT WOULD BE IMPOSSIBLE TO TELL WHICH ROW REALLY REPRESENTED THE REAL WORLD ENTITY ASSOCIATED WITH THAT KEY VALUE"ILL !DAMS WHO IS EMPLOYEE NUMBER &OR THIS REASON THE REQUIREMENT THAT PRIMARY KEYS HAVE UNIQUE VALUES IS CALLED THE ENTITY INTEGRITY CONSTRAINT 4HE FIRST COMMERCIAL 31, DATABASES DID NOT SUPPORT PRIMARY KEYS BUT SUPPORT IS NOW COMMON )T WAS ADDED TO $" IN AND WAS ADDED TO THE ORIGINAL !.3))3/ 31, STANDARD IN AN INTERMEDIATE UPDATE BEFORE THE FULL 31, STANDARD APPEARED 9OU SPECIFY THE PRIMARY KEY AS PART OF THE #2%!4% 4!",% OR !,4%2 4!",% STATEMENT DESCRIBED IN #HAPTER 4HE SAMPLE DATABASE DEFINITION IN !PPENDIX ! INCLUDES PRIMARY KEY DEFINITIONS FOR ALL OF ITS TABLES FOLLOWING THE !.3))3/ STANDARD SYNTAX 7HEN A PRIMARY KEY IS SPECIFIED FOR A TABLE THE $"-3 AUTOMATICALLY CHECKS THE UNIQUENESS OF THE PRIMARY KEY VALUE FOR EVERY ).3%24 AND 50$!4% STATEMENT PERFORMED ON THE TABLE !N ATTEMPT TO INSERT A ROW WITH A DUPLICATE PRIMARY KEY VALUE OR TO UPDATE A ROW SO THAT ITS PRIMARY KEY WOULD BE A DUPLICATE WILL FAIL WITH AN ERROR MESSAGE
)T IS SOMETIMES APPROPRIATE TO REQUIRE A COLUMN THAT IS NOT THE PRIMARY KEY OF A TABLE TO CONTAIN A UNIQUE VALUE IN EVERY ROW &OR EXAMPLE SUPPOSE YOU WANTED TO RESTRICT THE DATA IN THE 3!,%32%03 TABLE SO THAT NO TWO SALESPEOPLE COULD HAVE EXACTLY THE SAME NAME IN THE TABLE 9OU COULD ACHIEVE THIS GOAL BY IMPOSING A UNIQUENESS CONSTRAINT ON THE .!-% COLUMN 4HE $"-3 ENFORCES A UNIQUENESS CONSTRAINT IN THE SAME WAY THAT IT ENFORCES THE PRIMARY KEY CONSTRAINT !NY ATTEMPT TO INSERT OR UPDATE A ROW IN THE TABLE THAT VIOLATES THE UNIQUENESS CONSTRAINT WILL FAIL 7HILE BOTH UNIQUENESS AND PRIMARY KEY CONSTRAINTS PREVENT DUPLICATE VALUES FROM APPEARING IN A SET OF COLUMNS IN A TABLE THERE ARE TWO FUNDAMENTAL DIFFERENCES s ! TABLE MAY HAVE ONLY ONE PRIMARY KEY CONSTRAINT DEFINED ON IT WHILE A TABLE CAN HAVE ANY NUMBER OF UNIQUE CONSTRAINTS DEFINED s #OLUMNS NAMED IN A PRIMARY KEY CONSTRAINT MUST BE DEFINED AS ./4 .5,, WHILE COLUMNS INCLUDED IN A UNIQUE CONSTRAINT MAY BE DEFINED AS EITHER .5,, OR ./4 .5,, 4HE !.3))3/ 31, STANDARD USES THE #2%!4% 4!",% AND !,4%2 4!",% STATEMENTS TO SPECIFY UNIQUENESS CONSTRAINTS FOR COLUMNS OR COMBINATIONS OF COLUMNS (OWEVER UNIQUENESS CONSTRAINTS WERE IMPLEMENTED IN $" LONG BEFORE THE PUBLICATION OF THE !.3) )3/ STANDARD AND $" MADE THEM A PART OF ITS #2%!4% ).$%8 STATEMENT 4HIS STATEMENT IS ONE OF THE 31, DATABASE ADMINISTRATION STATEMENTS THAT DEALS WITH PHYSICAL STORAGE OF THE DATABASE ON THE DISK .ORMALLY THE 31, USER DOESNT HAVE TO WORRY ABOUT THESE STATEMENTS AT ALL THEY ARE USED ONLY BY THE DATABASE ADMINISTRATOR -ANY COMMERCIAL 31, PRODUCTS FOLLOWED THE ORIGINAL $" PRACTICE RATHER THAN THE !.3))3/ STANDARD FOR UNIQUENESS CONSTRAINTS AND REQUIRED THE USE OF A #2%!4% ).$%8 STATEMENT 3UBSEQUENT VERSIONS OF $" ADDED A UNIQUENESS CONSTRAINT TO THE #2%!4% 4!",% AND !,4%2 4!",% STATEMENTS -OST OF THE OTHER COMMERCIAL VENDORS HAVE FOLLOWED THE SAME PATH AND NOW SUPPORT THE !.3))3/ SYNTAX FOR THE UNIQUENESS CONSTRAINT
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5NIQUENESSõANDõ.5,,õ6ALUES .5,, VALUES WOULD POSE A PROBLEM IF THEY WERE TO OCCUR IN THE PRIMARY KEY OF A TABLE OR IN A COLUMN THAT IS SPECIFIED IN A UNIQUENESS CONSTRAINT 3UPPOSE YOU TRIED TO INSERT A ROW WITH A PRIMARY KEY THAT WAS .5,, OR PARTIALLY .5,, IF THE PRIMARY KEY IS COMPOSED OF MORE THAN ONE COLUMN "ECAUSE OF THE .5,, VALUE THE $"-3 CANNOT CONCLUSIVELY DECIDE WHETHER THE PRIMARY KEY DUPLICATES ONE THAT IS ALREADY IN THE TABLE 4HE ANSWER MUST BE hMAYBE v DEPENDING ON THE hREALv VALUE OF THE MISSING .5,, DATA &OR THIS REASON THE 31, STANDARD REQUIRES THAT EVERY COLUMN THAT IS PART OF A PRIMARY KEY MUST BE DECLARED ./4 .5,, 4HE 31, STANDARD DOES NOT IMPOSE THE SAME RESTRICTION FOR COLUMNS NAMED IN A UNIQUENESS CONSTRAINT ALTHOUGH SOME 31, IMPLEMENTATIONS SUCH AS $" FORBID THEM (OWEVER THERE IS CONSIDERABLE VARIATION IN HOW VARIOUS 31, IMPLEMENTATIONS ENFORCE UNIQUE CONSTRAINTS INVOLVING COLUMNS CONTAINING .5,, VALUES PARTICULARLY WHEN A UNIQUE CONSTRAINT INVOLVES MULTIPLE COLUMNS THAT ALLOW .5,, VALUES 4O ILLUSTRATE THESE DIFFERENCES CONSIDER THE FOLLOWING TABLE THAT MIGHT BE USED TO ASSIGN STUDENTS TO ADVISORS #2%!4% 4!",% !$6)3/2?!33)'.-%.43 345$%.4?.!-% 6!2#(!2 !$6)3/2?.!-% 6!2#(!2 5.)15% 345$%.4?.!-% !$6)3/2?.!-%
4HE FOLLOWING TABLE ILLUSTRATES THE RESULTS OF RUNNING A SERIES OF ).3%24 STATEMENTS FOR THE !$6)3/2?!33)'.-%.43 TABLE 4HE FIRST COLUMN SHOWS THE VALUE FOR THE 345$%.4? .!-% COLUMN THE SECOND COLUMN SHOWS THE VALUE FOR THE !$6)3/2?.!-% COLUMN AND THE REMAINING THREE COLUMNS SHOW THE RESULTS FOR CURRENT VERSIONS OF /RACLE 31, 3ERVER AND -Y31, RESPECTIVELY $" WAS NOT INCLUDED BECAUSE IT DOES NOT ALLOW UNIQUE CONSTRAINTS ON COLUMNS THAT ALLOW .5,, VALUES 2EMARKABLY NO TWO $"-3S YIELD THE SAME RESULTS FOR ALL ROWS 2OW .UMBER
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$ATAç)NTEGRITYç
2EFERENTIALõ)NTEGRITY #HAPTER DISCUSSED PRIMARY KEYS FOREIGN KEYS AND THE PARENTCHILD RELATIONSHIPS THAT THEY CREATE BETWEEN TABLES &IGURE SHOWS THE 3!,%32%03 AND /&&)#%3 TABLES AND ILLUSTRATES ONCE AGAIN HOW FOREIGN KEYS AND PRIMARY KEYS WORK 4HE /&&)#% COLUMN IS THE PRIMARY KEY FOR THE /&&)#%3 TABLE AND IT UNIQUELY IDENTIFIES EACH ROW 4HE 2%0?/&&)#% COLUMN IN THE 3!,%32%03 TABLE IS A FOREIGN KEY FOR THE /&&)#%3 TABLE )T IDENTIFIES THE OFFICE WHERE EACH SALESPERSON IS ASSIGNED 4HE 2%0?/&&)#% AND /&&)#% COLUMNS CREATE A PARENTCHILD RELATIONSHIP BETWEEN THE /&&)#%3 AND 3!,%32%03 ROWS %ACH /&&)#%3 PARENT ROW HAS ZERO OR MORE 3!,%32%03 CHILD ROWS WITH MATCHING OFFICE NUMBERS 3IMILARLY EACH 3!,%32%03 CHILD ROW HAS EXACTLY ONE /&&)#%3 PARENT ROW WITH A MATCHING OFFICE NUMBER 3UPPOSE YOU TRIED TO INSERT A NEW ROW INTO THE 3!,%32%03 TABLE THAT CONTAINED AN INVALID OFFICE NUMBER AS IN THIS EXAMPLE ).3%24 ).4/ 3!,%32%03 %-0,?.5- .!-% 2%0?/&&)#% !'% ()2%?$!4% 3!,%3 6!,5%3 g'EORGE 3MITHg g g
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/N THE SURFACE THERES NOTHING WRONG WITH THIS ).3%24 STATEMENT )N FACT SOME 31, IMPLEMENTATIONS WILL SUCCESSFULLY ADD THE ROW 4HE DATABASE WILL SHOW THAT 'EORGE 3MITH WORKS IN OFFICE NUMBER EVEN THOUGH NO OFFICE NUMBER IS LISTED IN THE /&&)#%3 TABLE 4HE NEWLY INSERTED ROW CLEARLY BREAKS THE PARENTCHILD RELATIONSHIP BETWEEN THE /&&)#%3 AND 3!,%32%03 TABLES )N FACT THE OFFICE NUMBER IN THE ).3%24 STATEMENT IS PROBABLY AN ERRORTHE USER MAY HAVE INTENDED OFFICE NUMBER OR
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)T SEEMS CLEAR THAT EVERY LEGAL VALUE IN THE 2%0?/&&)#% COLUMN SHOULD BE FORCED TO MATCH SOME VALUE THAT APPEARS IN THE /&&)#% COLUMN 4HIS RULE IS KNOWN AS A REFERENTIAL INTEGRITY CONSTRAINT )T ENSURES THE INTEGRITY OF THE PARENTCHILD RELATIONSHIPS CREATED BY FOREIGN KEYS AND PRIMARY KEYS 2EFERENTIAL INTEGRITY HAS BEEN A KEY PART OF THE RELATIONAL MODEL SINCE IT WAS FIRST PROPOSED BY % & #ODD (OWEVER REFERENTIAL INTEGRITY CONSTRAINTS WERE NOT INCLUDED IN )"-S PROTOTYPE 3YSTEM2$"-3 NOR IN EARLY RELEASES OF $" OR 31,$3 )"- ADDED REFERENTIAL INTEGRITY SUPPORT TO $" IN AND REFERENTIAL INTEGRITY WAS ADDED TO THE 31, STANDARD AFTER THE RELEASE OF THE INITIAL 31, VERSION -OST $"-3 VENDORS TODAY SUPPORT REFERENTIAL INTEGRITY CONSTRAINTS
2EFERENTIALõ)NTEGRITYõ0ROBLEMS &OUR TYPES OF DATABASE UPDATES CAN CORRUPT THE REFERENTIAL INTEGRITY OF THE PARENTCHILD RELATIONSHIPS IN A DATABASE 5SING THE /&&)#%3 AND 3!,%32%03 TABLES IN &IGURE AS ILLUSTRATIONS THE FOUR UPDATE SITUATIONS ARE THE FOLLOWING s )NSERTING A NEW CHILD ROW 7HEN AN ).3%24 STATEMENT ADDS A NEW ROW TO THE CHILD 3!,%32%03 TABLE ITS FOREIGN KEY 2%0?/&&)#% VALUE MUST MATCH ONE OF THE PRIMARY KEY /&&)#% VALUES IN THE PARENT TABLE /&&)#%3 )F THE FOREIGN KEY VALUE DOES NOT MATCH ANY PRIMARY KEY INSERTING THE ROW WILL CORRUPT THE DATABASE BECAUSE THERE WILL BE A CHILD WITHOUT A PARENT AN ORPHAN .OTE THAT INSERTING A ROW IN THE PARENT TABLE NEVER POSES A PROBLEM IT SIMPLY BECOMES A PARENT WITHOUT ANY CHILDREN s 5PDATING THE FOREIGN KEY IN A CHILD ROW 4HIS IS A DIFFERENT FORM OF THE PREVIOUS PROBLEM )F THE FOREIGN KEY 2%0?/&&)#% IS MODIFIED BY AN 50$!4% STATEMENT THE NEW VALUE MUST MATCH A PRIMARY KEY /&&)#% VALUE IN THE PARENT /&&)#%3 TABLE /THERWISE THE UPDATED ROW WILL BE AN ORPHAN s $ELETING A PARENT ROW )F A ROW OF THE PARENT TABLE /&&)#%3 THAT HAS ONE OR MORE CHILDREN IN THE 3!,%32%03 TABLE IS DELETED THE CHILD ROWS WILL BECOME ORPHANS 4HE FOREIGN KEY 2%0?/&&)#% VALUES IN THESE ROWS WILL NO LONGER MATCH ANY PRIMARY KEY /&&)#% VALUE IN THE PARENT TABLE .OTE THAT DELETING A ROW FROM THE CHILD TABLE NEVER POSES A PROBLEM THE PARENT OF THIS ROW SIMPLY HAS ONE LESS CHILD AFTER THE DELETION s 5PDATING THE PRIMARY KEY IN A PARENT ROW 4HIS IS A DIFFERENT FORM OF THE PREVIOUS PROBLEM )F THE PRIMARY KEY /&&)#% OF A ROW IN THE PARENT TABLE /&&)#%3 IS MODIFIED ALL OF THE CURRENT CHILDREN OF THAT ROW BECOME ORPHANS BECAUSE THEIR FOREIGN KEYS NO LONGER MATCH A PRIMARY KEY VALUE 4HE REFERENTIAL INTEGRITY FEATURES OF THE !.3))3/ 31, STANDARD HANDLE EACH OF THESE FOUR SITUATIONS 4HE FIRST PROBLEM ).3%24 INTO THE CHILD TABLE IS HANDLED BY CHECKING THE VALUES OF THE FOREIGN KEY COLUMNS BEFORE THE ).3%24 STATEMENT IS PERMITTED )F THEY DONT MATCH A PRIMARY KEY VALUE THE ).3%24 STATEMENT IS REJECTED WITH AN ERROR MESSAGE )N &IGURE THIS MEANS THAT BEFORE A NEW SALESPERSON CAN BE ADDED TO THE 3!,%32%03 TABLE THE OFFICE TO WHICH THE SALESPERSON IS ASSIGNED MUST ALREADY BE IN THE /&&)#%3 TABLE !S YOU CAN SEE THIS RESTRICTION MAKES SENSE IN THE SAMPLE DATABASE
#HAPTERçç
$ATAç)NTEGRITYç
4HE SECOND PROBLEM 50$!4% OF THE CHILD TABLE IS SIMILARLY HANDLED BY CHECKING THE UPDATED FOREIGN KEY VALUE )F THERE IS NO MATCHING PRIMARY KEY VALUE THE 50$!4% STATEMENT IS REJECTED WITH AN ERROR MESSAGE )N &IGURE THIS MEANS THAT BEFORE A SALESPERSON CAN BE REASSIGNED TO A DIFFERENT OFFICE THAT OFFICE MUST ALREADY BE IN THE /&&)#%3 TABLE !GAIN THIS RESTRICTION MAKES SENSE IN THE SAMPLE DATABASE 4HE THIRD PROBLEM $%,%4% OF A PARENT ROW IS MORE COMPLEX &OR EXAMPLE SUPPOSE YOU CLOSED THE ,OS !NGELES OFFICE AND WANTED TO DELETE THE CORRESPONDING ROW FROM THE /&&)#%3 TABLE IN &IGURE 7HAT SHOULD HAPPEN TO THE TWO CHILD ROWS IN THE 3!,%32%03 TABLE THAT REPRESENT THE SALESPEOPLE ASSIGNED TO THE ,OS !NGELES OFFICE $EPENDING ON THE SITUATION YOU MIGHT WANT TO s 0REVENT THE OFFICE FROM BEING DELETED UNTIL THE SALESPEOPLE ARE REASSIGNED s !UTOMATICALLY DELETE THE TWO SALESPEOPLE FROM THE 3!,%32%03 TABLE AS WELL s 3ET THE 2%0?/&&)#% COLUMN FOR THE TWO SALESPEOPLE TO .5,, INDICATING THAT THEIR OFFICE ASSIGNMENT IS UNKNOWN
4HE FOURTH PROBLEM 50$!4% OF THE PRIMARY KEY IN THE PARENT TABLE HAS SIMILAR COMPLEXITY &OR EXAMPLE SUPPOSE FOR SOME REASON YOU WANTED TO CHANGE THE NUMBER OF THE ,OS !NGELES OFFICE FROM TO !S WITH THE PREVIOUS EXAMPLE THE QUESTION IS WHAT SHOULD HAPPEN TO THE TWO CHILD ROWS IN THE 3!,%32%03 TABLE THAT REPRESENT SALESPEOPLE FROM THE ,OS !NGELES OFFICE !GAIN THERE ARE FOUR LOGICAL POSSIBILITIES s 0REVENT THE OFFICE NUMBER FROM BEING CHANGED UNTIL THE SALESPEOPLE ARE REASSIGNED )N THIS CASE YOU SHOULD FIRST ADD A NEW ROW TO THE /&&)#%3 TABLE WITH THE NEW OFFICE NUMBER FOR ,OS !NGELES THEN UPDATE THE 3!,%32%03 TABLE AND FINALLY DELETE THE OLD /&&)#%3 ROW FOR ,OS !NGELES s !UTOMATICALLY UPDATE THE OFFICE NUMBER FOR THE TWO SALESPEOPLE IN THE 3!,%32%03 TABLE SO THAT THEIR ROWS ARE STILL LINKED TO THE ,OS !NGELES ROW IN THE /&&)#%3 TABLE VIA ITS NEW OFFICE NUMBER s 3ET THE 2%0?/&&)#% COLUMN FOR THE TWO SALESPEOPLE TO .5,, INDICATING THAT THEIR OFFICE ASSIGNMENT IS UNKNOWN s 3ET THE 2%0?/&&)#% COLUMN FOR THE TWO SALESPEOPLE TO SOME DEFAULT VALUE SUCH AS THE OFFICE NUMBER FOR THE HEADQUARTERS OFFICE IN .EW 9ORK INDICATING THAT THE SALESPEOPLE ARE AUTOMATICALLY REASSIGNED TO THAT OFFICE !LTHOUGH SOME OF THESE ALTERNATIVES MAY SEEM MORE LOGICAL THAN OTHERS IN THIS PARTICULAR EXAMPLE ITS RELATIVELY EASY TO COME UP WITH EXAMPLES WHERE ANY ONE OF THE FOUR POSSIBILITIES IS THE RIGHT THING TO DO IF YOU WANT THE DATABASE TO ACCURATELY MODEL THE REAL WORLD SITUATION 4HE ORIGINAL 31, STANDARD PROVIDED ONLY THE FIRST POSSIBILITY FOR THE PRECEDING EXAMPLESIT PROHIBITED THE MODIFICATION OF A PRIMARY KEY VALUE THAT WAS IN USE AND PROHIBITED THE DELETION OF A ROW CONTAINING SUCH A PRIMARY KEY $" HOWEVER PERMITTED OTHER OPTIONS THROUGH ITS CONCEPT OF DELETE RULES 3TARTING WITH 31, THE 31, STANDARD EXPANDED THESE DELETE RULES INTO DELETE AND UPDATE RULES THAT COVER BOTH DELETING OF PARENT ROWS AND UPDATING OF PRIMARY KEYS
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s 3ET THE 2%0?/&&)#% COLUMN FOR THE TWO SALESPEOPLE TO SOME DEFAULT VALUE SUCH AS THE OFFICE NUMBER FOR THE HEADQUARTERS OFFICE IN .EW 9ORK INDICATING THAT THE SALESPEOPLE ARE AUTOMATICALLY REASSIGNED TO THAT OFFICE
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$ELETEõANDõ5PDATEõ2ULES
&OR EACH PARENTCHILD RELATIONSHIP CREATED BY A FOREIGN KEY IN A DATABASE THE 31, STANDARD ALLOWS YOU TO SPECIFY AN ASSOCIATED DELETE RULE AND AN ASSOCIATED UPDATE RULE 4HE DELETE RULE TELLS THE $"-3 WHAT TO DO WHEN A USER TRIES TO DELETE A ROW OF THE PARENT TABLE 4HESE FOUR DELETE RULES CAN BE SPECIFIED s 2%342)#4 DELETE RULE 4HE 2%342)#4 DELETE RULE PREVENTS YOU FROM DELETING A ROW FROM THE PARENT TABLE IF THE ROW HAS ANY CHILDREN ! $%,%4% STATEMENT THAT ATTEMPTS TO DELETE SUCH A PARENT ROW IS REJECTED WITH AN ERROR MESSAGE $ELETIONS FROM THE PARENT TABLE ARE THUS RESTRICTED TO ROWS WITHOUT ANY CHILDREN !PPLIED TO &IGURE THIS RULE CAN BE SUMMARIZED AS h9OU CANT DELETE AN OFFICE IF ANY SALESPEOPLE ARE ASSIGNED TO ITv s #!3#!$% DELETE RULE 4HE #!3#!$% DELETE RULE TELLS THE $"-3 THAT WHEN A PARENT ROW IS DELETED ALL OF ITS CHILD ROWS SHOULD ALSO AUTOMATICALLY BE DELETED FROM THE CHILD TABLE &OR &IGURE THIS RULE CAN BE SUMMARIZED AS h$ELETING AN OFFICE AUTOMATICALLY DELETES ALL THE SALESPEOPLE ASSIGNED TO THAT OFFICEv s 3%4 .5,, DELETE RULE 4HE 3%4 .5,, DELETE RULE TELLS THE $"-3 THAT WHEN A PARENT ROW IS DELETED THE FOREIGN KEY VALUES IN ALL OF ITS CHILD ROWS SHOULD AUTOMATICALLY BE SET TO .5,, $ELETIONS FROM THE PARENT TABLE THUS CAUSE A hSET TO .5,,v UPDATE ON SELECTED COLUMNS OF THE CHILD TABLE &OR THE TABLES IN &IGURE THIS RULE CAN BE SUMMARIZED AS h)F AN OFFICE IS DELETED INDICATE THAT THE CURRENT OFFICE ASSIGNMENT OF ITS SALESPEOPLE IS UNKNOWNv s 3%4 $%&!5,4 DELETE RULE 4HE 3%4 $%&!5,4 DELETE RULE TELLS THE $"-3 THAT WHEN A PARENT ROW IS DELETED THE FOREIGN KEY VALUES IN ALL OF ITS CHILD ROWS SHOULD AUTOMATICALLY BE SET TO THE DEFAULT VALUE FOR THAT PARTICULAR COLUMN $ELETIONS FROM THE PARENT TABLE THUS CAUSE A hSET TO $%&!5,4v UPDATE ON SELECTED COLUMNS OF THE CHILD TABLE &OR THE TABLES IN &IGURE THIS RULE CAN BE SUMMARIZED AS h)F AN OFFICE IS DELETED INDICATE THAT THE CURRENT OFFICE ASSIGNMENT OF ITS SALESPEOPLE IS THE DEFAULT OFFICE SPECIFIED IN THE DEFINITION OF THE 3!,%32%03 TABLEv 4HE 31, STANDARD ACTUALLY CALLS THE PREVIOUSLY DESCRIBED 2%342)#4 RULE ./ !#4)/. 4HE 31, STANDARD NAMING IS SOMEWHAT CONFUSING )T MEANS h)F YOU TRY TO DELETE A PARENT ROW THAT STILL HAS CHILDREN THE $"-3 WILL TAKE NO ACTION ON THE ROWv 4HE $"-3 WILL HOWEVER GENERATE AN ERROR CODE )NTUITIVELY THE NAME THAT $" AND OTHERS USE FOR THE RULE RESTRICT SEEMS A BETTER DESCRIPTION OF THE SITUATIONTHE $"-3 WILL RESTRICT THE $%,%4% OPERATION FROM TAKING PLACE AND GENERATE AN ERROR CODE 2ECENT RELEASES OF $" SUPPORT BOTH A 2%342)#4 AND A ./ !#4)/. DELETE RULE 4HE DIFFERENCE BETWEEN THEM IS THE TIMING OF THE ENFORCEMENT OF THE RULE 4HE 2%342)#4 RULE IS ENFORCED BEFORE ANY OTHER CONSTRAINTS THE ./ !#4)/. RULE IS ENFORCED AFTER OTHER REFERENTIAL CONSTRAINTS 5NDER ALMOST ALL CIRCUMSTANCES THE TWO RULES OPERATE IDENTICALLY !S YOU CAN IMAGINE SUPPORT FOR THE DELETE RULES VARIES AMONG 31, IMPLEMENTATIONS 4ABLE SHOWS WHICH RULES ARE SUPPORTED IN CURRENT VERSIONS OF POPULAR $"-3 PRODUCTS
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$ATAç)NTEGRITYç
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&ROM THE /2$%23 TABLE IN THE SAMPLE DATABASE HERE ARE THREE FOREIGN KEY CONSTRAINT DEFINITIONS THAT USE VARIOUS DELETE RULES
*UST AS THE DELETE RULE TELLS THE $"-3 WHAT TO DO WHEN A USER TRIES TO DELETE A ROW OF THE PARENT TABLE THE UPDATE RULE TELLS THE $"-3 WHAT TO DO WHEN A USER TRIES TO UPDATE THE VALUE OF ONE OF THE PRIMARY KEY COLUMNS IN THE PARENT TABLE !GAIN THERE ARE FOUR POSSIBILITIES PARALLELING THOSE AVAILABLE FOR DELETE RULES s 2%342)#4 UPDATE RULE 4HE 2%342)#4 UPDATE RULE PREVENTS YOU FROM UPDATING THE PRIMARY KEY OF A ROW IN THE PARENT TABLE IF THAT ROW HAS ANY CHILDREN !N 50$!4% STATEMENT THAT ATTEMPTS TO MODIFY THE PRIMARY KEY OF SUCH A PARENT ROW IS REJECTED WITH AN ERROR MESSAGE #HANGES TO PRIMARY KEYS IN THE PARENT TABLE ARE THUS RESTRICTED TO ROWS WITHOUT ANY CHILDREN !PPLIED TO &IGURE THIS RULE CAN BE SUMMARIZED AS h9OU CANT CHANGE AN OFFICE NUMBER IF SALESPEOPLE ARE ASSIGNED TO THE OFFICEv s #!3#!$% UPDATE RULE 4HE #!3#!$% UPDATE RULE TELLS THE $"-3 THAT WHEN A PRIMARY KEY VALUE IS CHANGED IN A PARENT ROW THE CORRESPONDING FOREIGN KEY VALUE IN ALL OF ITS CHILD ROWS SHOULD ALSO AUTOMATICALLY BE CHANGED IN THE CHILD TABLE TO MATCH THE NEW PRIMARY KEY &OR &IGURE THIS RULE CAN BE SUMMARIZED AS h#HANGING AN OFFICE NUMBER AUTOMATICALLY CHANGES THE OFFICE NUMBER FOR ALL THE SALESPEOPLE ASSIGNED TO THAT OFFICEv
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s 3%4 .5,, UPDATE RULE 4HE 3%4 .5,, UPDATE RULE TELLS THE $"-3 THAT WHEN A PRIMARY KEY VALUE IN A PARENT ROW IS UPDATED THE FOREIGN KEY VALUES IN ALL OF ITS CHILD ROWS SHOULD AUTOMATICALLY BE SET TO .5,, 0RIMARY KEY CHANGES IN THE PARENT TABLE THUS CAUSE A hSET TO .5,,v UPDATE ON SELECTED COLUMNS OF THE CHILD TABLE &OR THE TABLES IN &IGURE THIS RULE CAN BE SUMMARIZED AS h)F AN OFFICE NUMBER IS CHANGED INDICATE THAT THE CURRENT OFFICE ASSIGNMENT OF ITS SALESPEOPLE IS UNKNOWNv s 3%4 $%&!5,4 UPDATE RULE 4HE 3%4 $%&!5,4 UPDATE RULE TELLS THE $"-3 THAT WHEN A PRIMARY KEY VALUE IN A PARENT ROW IS UPDATED THE FOREIGN KEY VALUES IN ALL OF ITS CHILD ROWS SHOULD AUTOMATICALLY BE SET TO THE DEFAULT VALUE FOR THAT PARTICULAR COLUMN 0RIMARY KEY CHANGES IN THE PARENT TABLE THUS CAUSE A hSET TO $%&!5,4v UPDATE ON SELECTED COLUMNS OF THE CHILD TABLE &OR THE TABLES IN &IGURE THIS RULE CAN BE SUMMARIZED AS h)F AN OFFICE NUMBER IS CHANGED AUTOMATICALLY CHANGE THE OFFICE ASSIGNMENT OF ITS SALESPEOPLE TO THE DEFAULT OFFICE SPECIFIED IN THE DEFINITION OF THE 3!,%32%03 TABLEv 4HE 2%342)#4 UPDATE RULE IS A NAMING CONVENTION USED BY $" AND A FEW OTHER IMPLEMENTATIONS THE 31, STANDARD AGAIN CALLS THIS UPDATE RULE ./ !#4)/. !S WITH THE UPDATE RULES SUPPORT FOR THE DELETE RULES VARIES AMONG 31, IMPLEMENTATIONS 4ABLE SHOWS WHICH RULES ARE SUPPORTED IN CURRENT VERSIONS OF POPULAR $"-3 PRODUCTS 9OU CAN SPECIFY TWO DIFFERENT RULES AS THE DELETE RULE AND THE UPDATE RULE FOR A PARENT CHILD RELATIONSHIP ALTHOUGH IN MOST CASES THE TWO RULES WILL BE THE SAME )F YOU DO NOT SPECIFY A RULE THE 2%342)#4 RULE IS THE DEFAULT BECAUSE IT HAS THE LEAST POTENTIAL FOR ACCIDENTAL DESTRUCTION OR MODIFICATION OF DATA %ACH OF THE RULES IS APPROPRIATE IN DIFFERENT SITUATIONS )F FOR EXAMPLE WE WANTED TO SET THE DELETE RULE TO 3%4 .5,, AND THE UPDATE RULE TO #!3#!$% FOR THE (!3-'2 CONSTRAINT BETWEEN THE 3!,%32%03 AND /&&)#%3 TABLE WE COULD USE THIS !,4%2 4!",% STATEMENT TO CREATE THE CONSTRAINT INSTEAD OF THE ONE SHOWN IN !PPENDIX ! !,4%2 4!",% /&&)#%3 !$$ #/.342!).4 (!3-'2 &/2%)'. +%9 -'2 2%&%2%.#%3 3!,%32%03%-0,?.5- /. 50$!4% #!3#!$% /. $%,%4% 3%4 .5,,
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5SUALLY THE REAL WORLD BEHAVIOR MODELED BY THE DATABASE WILL INDICATE WHICH RULE IS APPROPRIATE )N THE SAMPLE DATABASE THE /2$%23 TABLE CONTAINS THREE FOREIGN KEYPRIMARY KEY RELATIONSHIPS AS SHOWN IN &IGURE 4HESE THREE RELATIONSHIPS LINK EACH ORDER TO s 4HE PRODUCT THAT WAS ORDERED s 4HE CUSTOMER WHO PLACED THE ORDER s 4HE SALESPERSON WHO TOOK THE ORDER &OR EACH OF THESE RELATIONSHIPS DIFFERENT RULES SEEM APPROPRIATE s 4HE RELATIONSHIP BETWEEN AN ORDER AND THE PRODUCT THAT IS ORDERED SHOULD PROBABLY USE THE 2%342)#4 RULE FOR DELETE AND UPDATE )T SHOULDNT BE POSSIBLE TO DELETE PRODUCT INFORMATION FROM THE DATABASE IF THERE ARE STILL CURRENT ORDERS FOR THAT PRODUCT OR TO CHANGE THE PRODUCT NUMBER
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s 4HE RELATIONSHIP BETWEEN AN ORDER AND THE CUSTOMER WHO PLACED IT SHOULD PROBABLY USE THE #!3#!$% RULE FOR DELETE AND UPDATE 9OU PROBABLY WILL DELETE A CUSTOMER ROW FROM THE DATABASE ONLY IF THE CUSTOMER IS INACTIVE OR ENDS THE CUSTOMERS RELATIONSHIP WITH THE COMPANY )N THIS CASE WHEN YOU DELETE THE CUSTOMER ANY CURRENT ORDERS FOR THAT CUSTOMER SHOULD ALSO BE DELETED 3IMILARLY CHANGES IN A CUSTOMER NUMBER SHOULD AUTOMATICALLY PROPAGATE TO ORDERS FOR THAT CUSTOMER
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s 4HE RELATIONSHIP BETWEEN AN ORDER AND THE SALESPERSON WHO TOOK IT SHOULD PROBABLY USE THE 3%4 .5,, RULE )F THE SALESPERSON LEAVES THE COMPANY ANY ORDERS TAKEN BY THAT SALESPERSON BECOME THE RESPONSIBILITY OF AN UNKNOWN SALESPERSON UNTIL THEY ARE REASSIGNED !LTERNATIVELY THE 3%4 $%&!5,4 RULE COULD BE USED TO AUTOMATICALLY ASSIGN THESE ORDERS TO THE SALES VICE PRESIDENT 4HIS RELATIONSHIP SHOULD PROBABLY USE THE #!3#!$% UPDATE RULE SO THAT EMPLOYEE NUMBER CHANGES AUTOMATICALLY PROPAGATE TO THE /2$%23 TABLE
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4HE 2%342)#4 RULE FOR DELETES AND UPDATES IS A SINGLE LEVEL RULEIT AFFECTS ONLY THE PARENT TABLE IN A RELATIONSHIP 4HE #!3#!$% RULE ON THE OTHER HAND CAN BE A MULTILEVEL RULE AS SHOWN IN &IGURE !SSUME FOR THIS DISCUSSION THAT THE /&&)#%33!,%32%03 AND 3!,%32%03/2$%23 RELATIONSHIPS SHOWN IN THE FIGURE BOTH HAVE #!3#!$% RULES 7HAT HAPPENS WHEN YOU DELETE ,OS !NGELES FROM THE /&&)#%3 TABLE 4HE #!3#!$% RULE FOR THE /&&)#%33!,%32%03 RELATIONSHIP TELLS THE $"-3 TO AUTOMATICALLY DELETE ALL OF THE 3!,%32%03 ROWS THAT REFER TO THE ,OS !NGELES OFFICE OFFICE NUMBER AS WELL "UT DELETING THE 3!,%32%03 ROW FOR 3UE 3MITH BRINGS INTO PLAY THE #!3#!$% RULE FOR THE 3!,%32%03/2$%23 RELATIONSHIP 4HIS RULE TELLS THE $"-3 TO AUTOMATICALLY DELETE ALL OF THE /2$%23 ROWS THAT REFER TO 3UE EMPLOYEE NUMBER $ELETING AN OFFICE THUS CAUSES CASCADED DELETION OF SALESPEOPLE WHICH CAUSES CASCADED DELETION OF ORDERS !S THE EXAMPLE SHOWS #!3#!$% DELETE RULES MUST BE SPECIFIED WITH CARE BECAUSE THEY CAN CAUSE WIDESPREAD AUTOMATIC DELETION OF DATA IF THEYRE USED INCORRECTLY #ASCADED UPDATE RULES CAN CAUSE SIMILAR MULTILEVEL UPDATES IF THE FOREIGN KEY IN THE CHILD TABLE IS ALSO ITS PRIMARY KEY )N PRACTICE THIS IS NOT VERY COMMON SO CASCADED UPDATES TYPICALLY HAVE LESS FAR REACHING EFFECTS THAN CASCADED DELETES 4HE 3%4 .5,, AND 3%4 $%&!5,4 UPDATE AND DELETE RULES ARE BOTH TWO LEVEL RULES THEIR IMPACT STOPS WITH THE CHILD TABLE &IGURE SHOWS THE /&&)#%3 3!,%32%03 AND /2$%23 TABLES AGAIN WITH A 3%4 .5,, DELETE RULE FOR THE /&&)#%33!,%32%03 RELATIONSHIP 4HIS TIME WHEN THE ,OS !NGELES OFFICE IS DELETED THE 3%4 .5,, DELETE RULE TELLS THE $"-3 TO SET THE 2%0?/&&)#% COLUMN TO .5,, IN THE 3!,%32%03 ROWS THAT REFER TO OFFICE NUMBER 4HE ROWS REMAIN IN THE 3!,%32%03 TABLE HOWEVER AND THE IMPACT OF THE DELETE OPERATION EXTENDS ONLY TO THE CHILD TABLE
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)N THE SAMPLE DATABASE THE 3!,%32%03 TABLE CONTAINS THE 2%0?/&&)#% COLUMN A FOREIGN KEY FOR THE /&&)#%3 TABLE 4HE /&&)#%3 TABLE CONTAINS THE -'2 COLUMN A FOREIGN KEY FOR THE 3!,%32%03 TABLE !S SHOWN IN &IGURE THESE TWO RELATIONSHIPS FORM A REFERENTIAL CYCLE !NY GIVEN ROW OF THE 3!,%32%03 TABLE REFERS TO A ROW OF THE /&&)#%3 TABLE WHICH REFERS TO A ROW OF THE 3!,%32%03 TABLE AND SO ON 4HIS CYCLE INCLUDES ONLY TWO TABLES BUT ITS ALSO POSSIBLE TO CONSTRUCT CYCLES OF THREE OR MORE TABLES 2EGARDLESS OF THE NUMBER OF TABLES THAT THEY INVOLVE REFERENTIAL CYCLES POSE SPECIAL PROBLEMS FOR REFERENTIAL INTEGRITY CONSTRAINTS &OR EXAMPLE SUPPOSE THAT .5,, VALUES WERE NOT ALLOWED IN THE PRIMARY OR FOREIGN KEYS OF THE TWO TABLES IN &IGURE 4HIS IS NOT IN FACT THE WAY THE SAMPLE DATABASE IS ACTUALLY DEFINED FOR REASONS THAT WILL BECOME OBVIOUS IN A MOMENT #ONSIDER THIS DATABASE CHANGE REQUEST AND THE ).3%24 STATEMENTS THAT ATTEMPT TO IMPLEMENT IT
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5NFORTUNATELY THE FIRST ).3%24 STATEMENT FOR "EN !DAMS WILL FAIL 7HY "ECAUSE THE NEW ROW REFERS TO OFFICE NUMBER WHICH IS NOT YET IN THE DATABASE /F COURSE REVERSING THE ORDER OF THE ).3%24 STATEMENTS DOESNT HELP ).3%24 ).4/ /&&)#%3 /&&)#% #)49 2%')/. -'2 4!2'%4 3!,%3 6!,5%3 g$ETROITg g%ASTERNg ).3%24 ).4/ 3!,%32%03 %-0,?.5- .!-% 2%0?/&&)#% ()2%?$!4% 3!,%3 6!,5%3 g"EN !DAMSg g g
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4HE FIRST ).3%24 STATEMENT FOR $ETROIT THIS TIME WILL STILL FAIL BECAUSE THE NEW ROW REFERS TO EMPLOYEE NUMBER AS THE OFFICE MANAGER AND "EN !DAMS IS NOT YET IN THE DATABASE 4O PREVENT THIS INSERTION DEADLOCK AT LEAST ONE OF THE FOREIGN KEYS IN A REFERENTIAL CYCLE MUST PERMIT .5,, VALUES )N THE ACTUAL DEFINITION OF THE SAMPLE DATABASE THE -'2 COLUMN DOES NOT PERMIT .5,,S BUT THE 2%0?/&&)#% DOES 4HE TWO ROW INSERTION CAN THEN BE ACCOMPLISHED WITH TWO ).3%24S AND AN 50$!4% AS SHOWN HERE ).3%24 ).4/ 3!,%32%03 %-0,?.5- .!-% 2%0?/&&)#% ()2%?$!4% 3!,%3 6!,5%3 g"EN !DAMSg .5,, g g ).3%24 ).4/ /&&)#%3 /&&)#% #)49 2%')/. -'2 4!2'%4 3!,%3 6!,5%3 g$ETROITg g%ASTERNg 50$!4% 3!,%32%03 3%4 2%0?/&&)#% 7(%2% %-0,?.5-
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!S THE EXAMPLE SHOWS SOMETIMES IT WOULD BE CONVENIENT IF THE REFERENTIAL INTEGRITY CONSTRAINT WERE NOT CHECKED UNTIL AFTER A SERIES OF INTERRELATED UPDATES ARE PERFORMED 3OME DEFERRED CHECKING CAPABILITIES ARE SPECIFIED BY THE 31, STANDARD STARTING WITH 31, AS DESCRIBED LATER IN THE h$EFERRED #ONSTRAINT #HECKINGv SECTION 2EFERENTIAL CYCLES ALSO RESTRICT THE DELETE AND UPDATE RULES THAT CAN BE SPECIFIED FOR THE RELATIONSHIPS THAT FORM THE CYCLE #ONSIDER THE THREE TABLES IN THE REFERENTIAL CYCLE SHOWN IN &IGURE 4HE 0%43 TABLE SHOWS THREE PETS AND THE BOYS THEY LIKE THE ')2,3 TABLE SHOWS THREE GIRLS AND THE PETS THEY LIKE AND THE "/93 TABLE SHOWS FOUR BOYS AND THE GIRLS THEY LIKE FORMING A REFERENTIAL CYCLE !LL THREE OF THE RELATIONSHIPS IN THE CYCLE SPECIFY THE 2%342)#4 DELETE RULE .OTE THAT 'EORGES ROW IS THE ONLY ROW YOU CAN DELETE FROM THE THREE TABLES %VERY OTHER ROW IS THE PARENT IN SOME RELATIONSHIP AND IS THEREFORE PROTECTED FROM DELETION BY THE 2%342)#4 RULE "ECAUSE OF THIS ANOMALY YOU SHOULD NOT SPECIFY THE 2%342)#4 RULE FOR ALL OF THE RELATIONSHIPS IN A REFERENTIAL CYCLE 4HE #!3#!$% RULE PRESENTS A SIMILAR PROBLEM AS SHOWN IN &IGURE 4HIS FIGURE CONTAINS EXACTLY THE SAME DATA AS IN &IGURE BUT ALL THREE DELETE RULES HAVE BEEN CHANGED TO #!3#!$% 3UPPOSE YOU TRY TO DELETE "OB FROM THE "/93 TABLE 4HE DELETE RULES FORCE THE $"-3 TO DELETE 2OVER WHO LIKES "OB FROM THE 0%43 TABLE WHICH FORCES YOU TO DELETE "ETTY
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WHO LIKES 2OVER FROM THE ')2,3 TABLE WHICH FORCES YOU TO DELETE 3AM WHO LIKES "ETTY AND SO ON UNTIL ALL OF THE ROWS IN ALL THREE TABLES HAVE BEEN DELETED &OR THESE SMALL TABLES THIS MIGHT BE PRACTICAL BUT FOR A PRODUCTION DATABASE WITH THOUSANDS OF ROWS IT WOULD QUICKLY BECOME IMPOSSIBLE TO KEEP TRACK OF THE CASCADED DELETIONS AND TO RETAIN THE INTEGRITY OF THE DATABASE &OR THIS REASON $" ENFORCES A RULE THAT PREVENTS REFERENTIAL CYCLES OF TWO OR MORE TABLES WHERE ALL OF THE DELETE RULES ARE #!3#!$% !T LEAST ONE RELATIONSHIP IN THE CYCLE MUST HAVE A 2%342)#4 OR 3%4 .5,, DELETE RULE TO BREAK THE CYCLE OF CASCADED DELETIONS
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5NLIKE PRIMARY KEYS FOREIGN KEYS IN A RELATIONAL DATABASE ARE ALLOWED TO CONTAIN .5,, VALUES )N THE SAMPLE DATABASE THE FOREIGN KEY 2%0?/&&)#% IN THE 3!,%32%03 TABLE PERMITS .5,, VALUES )N FACT THIS COLUMN DOES CONTAIN A .5,, VALUE IN 4OM 3NYDERS ROW BECAUSE 4OM HAS NOT YET BEEN ASSIGNED TO AN OFFICE "UT THE .5,, VALUE POSES AN INTERESTING QUESTION ABOUT THE REFERENTIAL INTEGRITY CONSTRAINT CREATED BY THE PRIMARY KEYFOREIGN KEY RELATIONSHIP $OES THE .5,, VALUE MATCH ONE OF THE PRIMARY KEY VALUES OR DOESNT IT 4HE ANSWER IS hMAYBEvIT DEPENDS ON THE REAL VALUE OF THE MISSING OR UNKNOWN DATA
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4HE !.3))3/ 31, STANDARD AUTOMATICALLY ASSUMES THAT A FOREIGN KEY THAT CONTAINS A .5,, VALUE SATISFIES THE REFERENTIAL INTEGRITY CONSTRAINT )N OTHER WORDS IT GIVES THE ROW THE BENEFIT OF THE DOUBT AND ALLOWS IT TO BE PART OF THE CHILD TABLE EVEN THOUGH ITS FOREIGN KEY VALUE DOESNT MATCH ANY ROW IN THE PARENT TABLE )NTERESTINGLY THE REFERENTIAL INTEGRITY CONSTRAINT IS ASSUMED TO BE SATISFIED IF ANY PART OF THE FOREIGN KEY HAS A .5,, VALUE 4HIS CAN PRODUCE UNEXPECTED AND UNINTUITIVE BEHAVIOR FOR COMPOUND FOREIGN KEYS SUCH AS THE ONE THAT LINKS THE /2$%23 TABLE TO THE 02/$5#43 TABLE 3UPPOSE FOR A MOMENT THAT THE /2$%23 TABLE IN THE SAMPLE DATABASE PERMITTED .5,, VALUES FOR THE 02/$5#4 COLUMN AND THAT THE 02/$5#43/2$%23 RELATIONSHIP HAD A 3%4 .5,, DELETE RULE 4HIS IS NOT THE ACTUAL STRUCTURE OF THE SAMPLE DATABASE FOR THE REASONS ILLUSTRATED BY THIS EXAMPLE !N ORDER FOR A PRODUCT WITH A MANUFACTURER )$ -&2 OF !"# AND A .5,, PRODUCT )$ 02/$5#4 CAN BE SUCCESSFULLY INSERTED INTO THE /2$%23 TABLE BECAUSE OF THE .5,, VALUE IN THE 02/$5#4 COLUMN &OLLOWING THE !.3))3/ STANDARD THE $"-3 ASSUMES THAT THE ROW MEETS THE REFERENTIAL INTEGRITY CONSTRAINT FOR /2$%23 AND 02/$5#43 EVEN THOUGH NO PRODUCT IN THE 02/$5#43 TABLE HAS A MANUFACTURER )$ OF !"# 4HE 3%4 .5,, DELETE RULE CAN PRODUCE A SIMILAR EFFECT $ELETING A ROW FROM THE 02/$5#43 TABLE WILL CAUSE THE FOREIGN KEY VALUE IN ALL OF ITS CHILD ROWS IN THE /2$%23 TABLE TO BE SET TO .5,, !CTUALLY ONLY THOSE COLUMNS OF THE FOREIGN KEY THAT ACCEPT .5,, VALUES ARE SET TO .5,, )F THERE WERE A SINGLE ROW IN THE 02/$5#43 TABLE FOR MANUFACTURER $%& DELETING THAT ROW WOULD CAUSE ITS CHILD ROWS IN THE /2$%23 TABLE TO HAVE THEIR 02/$5#4 COLUMN SET TO .5,, BUT THEIR -&2 COLUMN WOULD CONTINUE TO HAVE THE VALUE $%& !S A RESULT THE ROWS WOULD HAVE AN -&2 VALUE THAT DID NOT MATCH ANY ROW IN THE 02/$5#43 TABLE 4O AVOID CREATING THIS SITUATION YOU SHOULD BE VERY CAREFUL WITH .5,, VALUES IN COMPOUND FOREIGN KEYS !N APPLICATION THAT ENTERS OR UPDATES DATA IN THE TABLE THAT CONTAINS THE FOREIGN KEY SHOULD USUALLY ENFORCE AN hALL .5,,S OR NO .5,,Sv RULE ON THE COLUMNS OF THE FOREIGN KEY &OREIGN KEYS THAT ARE PARTIALLY .5,, AND PARTIALLY NON .5,, CAN EASILY CREATE PROBLEMS 4HE 31, STANDARD ADDRESSES THIS PROBLEM BY GIVING THE DATABASE ADMINISTRATOR MORE CONTROL OVER THE HANDLING OF .5,, VALUES IN FOREIGN KEYS FOR INTEGRITY CONSTRAINTS 4HE INTEGRITY CONSTRAINT IN THE #2%!4% 4!",% STATEMENT PROVIDES TWO OPTIONS BUT SUPPORT FOR THEM IS SPARSE AMONG CURRENT 31, IMPLEMENTATIONS s -!4#( &5,, OPTION 4HE -!4#( &5,, OPTION REQUIRES THAT FOREIGN KEYS IN A CHILD TABLE FULLY MATCH A PRIMARY KEY IN THE PARENT TABLE 7ITH THIS OPTION NO PART OF THE FOREIGN KEY CAN CONTAIN A .5,, VALUE SO THE ISSUE OF .5,, VALUE HANDLING IN DELETE AND UPDATE RULES DOES NOT ARISE s -!4#( 0!24)!, OPTION 4HE -!4#( 0!24)!, OPTION ALLOWS .5,, VALUES IN PARTS OF A FOREIGN KEY SO LONG AS THE NON .5,, VALUES MATCH THE CORRESPONDING PARTS OF SOME PRIMARY KEY IN THE PARENT TABLE 7ITH THIS OPTION .5,, VALUE HANDLING IN DELETE AND UPDATE RULES PROCEEDS AS PREVIOUSLY DESCRIBED
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$ATAç)NTEGRITYç
!DVANCEDõ#ONSTRAINTõ#APABILITIES 0RIMARY KEY AND FOREIGN KEY CONSTRAINTS UNIQUENESS CONSTRAINTS AND RESTRICTIONS ON MISSING .5,, VALUES ALL PROVIDE DATA INTEGRITY CHECKING FOR VERY SPECIFIC STRUCTURES AND SITUATIONS WITHIN A DATABASE 3TARTING WITH 31, THE 31, STANDARD GOES BEYOND THESE CAPABILITIES TO INCLUDE A MUCH MORE GENERAL CAPABILITY FOR SPECIFYING AND ENFORCING DATA INTEGRITY CONSTRAINTS 4HE COMPLETE SCHEME INCLUDES FOUR TYPES OF CONSTRAINTS s #OLUMN CONSTRAINTS 3PECIFIED AS PART OF A COLUMN DEFINITION WHEN A TABLE IS CREATED OR ADDED LATER WHEN A TABLE IS ALTERED #ONCEPTUALLY THEY RESTRICT THE LEGAL VALUES THAT MAY APPEAR IN THE COLUMN #OLUMN CONSTRAINTS APPEAR IN THE INDIVIDUAL COLUMN DEFINITIONS WITHIN THE #2%!4% 4!",% AND !,4%2 4!",% STATEMENTS
s 4ABLE CONSTRAINTS 3PECIFIED AS PART OF THE TABLE DEFINITION WHEN A TABLE IS CREATED #ONCEPTUALLY THEY RESTRICT THE LEGAL VALUES THAT MAY APPEAR IN ROWS OF THE TABLE 4ABLE CONSTRAINTS ARE SPECIFIED IN THE #2%!4% 4!",% STATEMENT THAT DEFINES A TABLE 5SUALLY THEY APPEAR AS A GROUP AFTER THE COLUMN DEFINITIONS BUT THE 31, STANDARD ALLOWS THEM TO BE INTERSPERSED WITH THE COLUMN DEFINITIONS s !SSERTIONS 4HE MOST GENERAL TYPE OF 31, CONSTRAINT ,IKE DOMAINS THEY ARE SPECIFIED OUTSIDE OF THE TABLE AND COLUMN STRUCTURE OF THE DATABASE #ONCEPTUALLY AN ASSERTION SPECIFIES A RELATIONSHIP AMONG DATA VALUES THAT CROSSES MULTIPLE TABLES WITHIN THE DATABASE 5NFORTUNATELY ALSO LIKE DOMAINS VERY FEW CURRENT 31, IMPLEMENTATIONS SUPPORT ASSERTIONS %ACH OF THE FOUR DIFFERENT TYPES OF CONSTRAINTS HAS ITS OWN CONCEPTUAL PURPOSE AND EACH APPEARS IN A DIFFERENT PART OF 31, STATEMENT SYNTAX (OWEVER THE DISTINCTIONS BETWEEN THEM ARE SOMEWHAT ARBITRARY !NY COLUMN CONSTRAINT THAT APPEARS FOR AN INDIVIDUAL COLUMN DEFINITION CAN JUST AS EASILY BE SPECIFIED AS A TABLE CONSTRAINT 3IMILARLY ANY TABLE CONSTRAINT CAN BE SPECIFIED AS AN ASSERTION )N PRACTICE ITS PROBABLY BEST TO SPECIFY EACH DATABASE CONSTRAINT WHERE IT SEEMS TO MOST NATURALLY FIT GIVEN THE REAL WORLD SITUATION THAT THE DATABASE IS TRYING TO MODEL #ONSTRAINTS THAT APPLY GLOBALLY TO THE ENTIRE SITUATION BUSINESS PROCESSES INTERRELATIONSHIPS AMONG CUSTOMERS AND PRODUCTS AND SO ON SHOULD APPEAR AS ASSERTIONS #ONSTRAINTS THAT APPLY TO A SPECIFIC TYPE OF ENTITY A CUSTOMER OR AN ORDER SHOULD APPEAR AS TABLE CONSTRAINTS OR COLUMN CONSTRAINTS WITHIN THE APPROPRIATE TABLE THAT DESCRIBES THAT TYPE OF ENTITY 7HEN THE SAME CONSTRAINT APPLIES TO MANY DIFFERENT COLUMNS IN THE DATABASE THAT ALL REFER TO THE SAME TYPE OF ENTITY THEN A DOMAIN IS APPROPRIATE
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s $OMAINS ! SPECIALIZED FORM OF COLUMN CONSTRAINTS 4HEY PROVIDE A LIMITED CAPABILITY TO DEFINE NEW DATA TYPES WITHIN A DATABASE )N EFFECT A DOMAIN IS ONE OF THE PREDEFINED DATABASE DATA TYPES PLUS SOME ADDITIONAL CONSTRAINTS WHICH ARE SPECIFIED AS PART OF THE DOMAIN DEFINITION /NCE A DOMAIN IS DEFINED AND NAMED THE DOMAIN NAME CAN BE USED IN PLACE OF A DATA TYPE TO DEFINE NEW COLUMNS 4HE COLUMNS INHERIT THE CONSTRAINTS OF THE DOMAIN $OMAINS ARE DEFINED OUTSIDE OF THE TABLE AND COLUMN DEFINITIONS OF THE DATABASE BY USING THE #2%!4% $/-!). STATEMENT !S ALREADY MENTIONED VERY FEW 31, IMPLEMENTATIONS PROVIDE SUPPORT FOR THIS STATEMENT
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!SSERTIONS %XAMPLES OF THE FIRST THREE TYPES OF CONSTRAINTS HAVE PREVIOUSLY APPEARED IN EARLIER SECTIONS OF THIS CHAPTER !N ASSERTION IS SPECIFIED USING THE 31, #2%!4% !33%24)/. STATEMENT (ERE IS AN ASSERTION THAT MIGHT BE USEFUL IN THE DEMO DATABASE %NSURE THAT AN OFlCES TARGET DOES NOT EXCEED THE SUM OF THE QUOTAS FOR ITS SALESPEOPLE #2%!4% !33%24)/. TARGET?VALID #(%#+ /&&)#%34!2'%4 35-3!,%32%0315/4! !.$ 3!,%32%032%0?/&&)#% /&&)#%3/&&)#%
"ECAUSE IT IS AN OBJECT IN THE DATABASE LIKE A TABLE OR A COLUMN THE ASSERTION MUST BE GIVEN A NAME IN THIS CASE ITS TARGET?VALID 4HE NAME IS USED IN ERROR MESSAGES PRODUCED BY THE $"-3 WHEN THE ASSERTION IS VIOLATED 4HE ASSERTION CAUSING AN ERROR MAY BE OBVIOUS IN A SMALL DEMO DATABASE BUT IN A LARGE DATABASE THAT MIGHT CONTAIN DOZENS OR HUNDREDS OF ASSERTIONS ITS CRITICAL TO KNOW WHICH OF THE ASSERTIONS WAS VIOLATED (ERE IS ANOTHER EXAMPLE OF AN ASSERTION THAT MIGHT BE USEFUL IN THE SAMPLE DATABASE %NSURE THAT THE TOTAL OF THE ORDERS FOR ANY CUSTOMER DOES NOT EXCEED THEIR CREDIT LIMIT #2%!4% !33%24)/. CREDIT?ORDERS #(%#+ #534/-%23#2%$)4?,)-)4 3%,%#4 35-/2$%23!-/5.4 &2/- /2$%23 7(%2% /2$%23#534 #534/-%23#534?.5-
!S THESE EXAMPLES SHOW A 31, ASSERTION IS DEFINED BY A SEARCH CONDITION WHICH IS ENCLOSED IN PARENTHESES AND FOLLOWS THE KEYWORD #(%#+ %VERY TIME AN ATTEMPT IS MADE TO MODIFY THE CONTENTS OF THE DATABASE THROUGH AN ).3%24 OR 50$!4% OR $%,%4% STATEMENT THE SEARCH CONDITION IS CHECKED AGAINST THE PROPOSED MODIFIED DATABASE CONTENTS )F THE SEARCH CONDITION REMAINS 425% THE MODIFICATION IS ALLOWED )F THE SEARCH CONDITION WOULD BECOME UNTRUE THE $"-3 DOES NOT CARRY OUT THE PROPOSED MODIFICATION AND AN ERROR CODE IS RETURNED INDICATING AN ASSERTION VIOLATION )N THEORY ASSERTIONS COULD CAUSE A LARGE AMOUNT OF DATABASE PROCESSING OVERHEAD AS THEY ARE CHECKED FOR EACH STATEMENT THAT MIGHT MODIFY THE DATABASE )N PRACTICE THE $"-3 WILL ANALYZE THE ASSERTION AND DETERMINE WHICH TABLES AND COLUMNS IT INVOLVES /NLY CHANGES THAT INVOLVE THOSE PARTICULAR TABLES OR COLUMNS WILL ACTUALLY TRIGGER THE SEARCH CONDITION .ONETHELESS ASSERTIONS SHOULD BE DEFINED WITH GREAT CARE TO ENSURE THAT THEY IMPOSE A REASONABLE AMOUNT OF OVERHEAD FOR THE BENEFIT THEY PROVIDE
31,õ#ONSTRAINTõ4YPES 4HE TYPES OF CONSTRAINTS THAT CAN BE SPECIFIED IN THE 31, STANDARD STARTING WITH 31, AND THE ROLE PLAYED BY EACH CAN BE SUMMARIZED AS FOLLOWS s ./4 .5,, CONSTRAINT 4HE ./4 .5,, CONSTRAINT CAN APPEAR ONLY AS A COLUMN CONSTRAINT )T PREVENTS THE COLUMN FROM BEING ASSIGNED A .5,, VALUE s 02)-!29 +%9 CONSTRAINT ! 02)-!29 +%9 CONSTRAINT CAN APPEAR AS A COLUMN CONSTRAINT OR A TABLE CONSTRAINT )F THE PRIMARY KEY CONSISTS OF A SINGLE COLUMN THE COLUMN CONSTRAINT MAY BE MORE CONVENIENT )F IT CONSISTS OF MULTIPLE COLUMNS IT SHOULD BE SPECIFIED AS A TABLE CONSTRAINT
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$ATAç)NTEGRITYç
s 5.)15% CONSTRAINT ! 5.)15% CONSTRAINT CAN APPEAR AS A COLUMN CONSTRAINT OR A TABLE CONSTRAINT )F THE UNIQUE VALUES RESTRICTION IS BEING ENFORCED ONLY FOR A SINGLE COLUMN THE COLUMN CONSTRAINT IS THE EASIEST WAY TO SPECIFY IT )F THE UNIQUE VALUES RESTRICTION APPLIES TO A SET OF TWO OR MORE COLUMNS THAT IS THE COMBINATION OF VALUES FOR THOSE COLUMNS MUST BE UNIQUE FOR ALL ROWS IN THE TABLE THEN THE TABLE CONSTRAINT FORM SHOULD BE USED s 2EFERENTIAL &/2%)'. +%9 CONSTRAINT ! REFERENTIAL &/2%)'. +%9 CONSTRAINT CAN APPEAR AS A COLUMN CONSTRAINT OR A TABLE CONSTRAINT )F THE FOREIGN KEY CONSISTS OF A SINGLE COLUMN THE COLUMN CONSTRAINT MAY BE MORE CONVENIENT )F IT CONSISTS OF MULTIPLE COLUMNS IT SHOULD BE SPECIFIED AS A TABLE CONSTRAINT )F A TABLE HAS MANY FOREIGN KEY RELATIONSHIPS TO OTHER TABLES IT MAY BE MOST CONVENIENT TO GATHER ALL OF ITS FOREIGN KEY CONSTRAINTS TOGETHER AT ONE PLACE IN THE TABLE DEFINITION RATHER THAN HAVING THEM SCATTERED THROUGHOUT THE COLUMN DEFINITIONS
%ACH INDIVIDUAL CONSTRAINT WITHIN A DATABASE NO MATTER WHAT ITS TYPE MAY BE ASSIGNED A CONSTRAINT NAME TO UNIQUELY IDENTIFY IT FROM THE OTHER CONSTRAINTS )TS PROBABLY UNNECESSARY TO ASSIGN CONSTRAINT NAMES IN A SIMPLE DATABASE WHERE EACH CONSTRAINT IS CLEARLY ASSOCIATED WITH A SINGLE TABLE COLUMN OR DOMAIN AND WHERE THERE IS LITTLE POTENTIAL FOR CONFUSION )N A MORE COMPLEX DATABASE INVOLVING MULTIPLE CONSTRAINTS ON A SINGLE TABLE OR COLUMN IT CAN BE VERY USEFUL TO BE ABLE TO IDENTIFY THE INDIVIDUAL CONSTRAINTS BY NAME ESPECIALLY WHEN ERRORS START TO OCCUR !LSO DEFAULT NAMES ASSIGNED BY THE $"-3 ARE OFTEN CONFUSING AND MEANINGLESS SO ITS ALWAYS BETTER TO ASSIGN YOUR OWN CONSTRAINT NAMES .OTE THAT THE CHECK CONSTRAINT IN AN ASSERTION MUST HAVE A CONSTRAINT NAME THIS NAME EFFECTIVELY BECOMES THE NAME OF THE ASSERTION CONTAINING THE CONSTRAINT
$EFERREDõ#ONSTRAINTõ#HECKING )N THEIR SIMPLEST FORM THE VARIOUS CONSTRAINTS THAT ARE SPECIFIED WITHIN A DATABASE ARE CHECKED EVERY TIME AN ATTEMPT IS MADE TO CHANGE THE DATABASE CONTENTSTHAT IS DURING THE EXECUTION OF EVERY ATTEMPTED ).3%24 50$!4% OR $%,%4% STATEMENT &OR DATABASE SYSTEMS CLAIMING ONLY )NTERMEDIATE LEVEL OR %NTRY LEVEL CONFORMANCE TO THE 31, STANDARD THIS IS THE ONLY MODE OF OPERATION ALLOWED FOR DATABASE CONSTRAINTS 4HE &ULL LEVEL 31, STANDARD SPECIFIES AN ADDITIONAL CAPABILITY FOR DEFERRED CONSTRAINT CHECKING 7HEN CONSTRAINT CHECKING IS DEFERRED THE CONSTRAINTS ARE NOT CHECKED FOR EACH INDIVIDUAL 31, STATEMENT )NSTEAD CONSTRAINT CHECKING IS HELD IN ABEYANCE UNTIL THE END OF A 31, TRANSACTION 4RANSACTION PROCESSING AND THE ASSOCIATED 31, STATEMENTS ARE DESCRIBED IN DETAIL IN #HAPTER 7HEN THE COMPLETION OF THE TRANSACTION IS SIGNALED BY THE 31, #/--)4 STATEMENT THE $"-3 CHECKS THE DEFERRED CONSTRAINTS )F ALL OF THE CONSTRAINTS ARE SATISFIED THEN THE #/--)4 STATEMENT CAN PROCEED AND THE TRANSACTION CAN COMPLETE NORMALLY !T THIS POINT ANY CHANGES MADE TO THE DATABASE DURING THE TRANSACTION BECOME PERMANENT )F HOWEVER ONE OR MORE OF THE CONSTRAINTS WOULD BE VIOLATED BY THE PROPOSED TRANSACTION THEN THE #/--)4 STATEMENT FAILS AND THE TRANSACTION IS ROLLED BACKTHAT IS ALL OF THE PROPOSED CHANGES TO THE DATABASE ARE REVERSED AND THE DATABASE GOES BACK TO ITS STATE BEFORE THE TRANSACTION BEGAN
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s #HECK CONSTRAINT ! CHECK CONSTRAINT CAN APPEAR AS A COLUMN CONSTRAINT OR A TABLE CONSTRAINT )T IS ALSO THE ONLY KIND OF CONSTRAINT THAT FORMS PART OF THE DEFINITION OF A DOMAIN OR AN ASSERTION 4HE CHECK CONSTRAINT IS SPECIFIED AS A SEARCH CONDITION LIKE THE SEARCH CONDITION THAT APPEARS IN THE 7(%2% CLAUSE OF A DATABASE QUERY 4HE CONSTRAINT IS SATISFIED IF THE SEARCH CONDITION HAS A 425% VALUE
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5PDATINGç$ATA
$EFERRED CONSTRAINT CHECKING CAN BE VERY IMPORTANT WHEN SEVERAL UPDATES TO A DATABASE MUST ALL BE MADE AT ONCE TO KEEP THE DATABASE IN A CONSISTENT STATE &OR EXAMPLE SUPPOSE THE DEMO DATABASE CONTAINED THIS ASSERTION %NSURE THAT AN OFlCES TARGET IS EXACTLY EQUAL TO THE SUM OF THE QUOTAS FOR ITS SALESPEOPLE #2%!4% !33%24)/. QUOTA?TOTALS #(%#+ /&&)#%34!2'%4 35-3!,%32%0315/4! !.$ 3!,%32%032%0?/&&)#% /&&)#%3/&&)#%
7ITHOUT THE DEFERRED CONSTRAINT CHECKING THIS CONSTRAINT WOULD EFFECTIVELY PREVENT YOU FROM EVER ADDING A SALESPERSON TO THE DATABASE 7HY "ECAUSE TO KEEP THE OFFICE TARGET AND THE SALESPERSONS QUOTAS IN THE RIGHT RELATIONSHIP YOU MUST BOTH ADD A NEW SALESPERSON ROW WITH THE APPROPRIATE QUOTA USING AN ).3%24 STATEMENT AND INCREASE THE TARGET FOR THE APPROPRIATE OFFICE BY THE SAME AMOUNT USING AN 50$!4% STATEMENT )F YOU TRY TO PERFORM THE ).3%24 STATEMENT ON THE 3!,%32%03 TABLE FIRST THE /&&)#%3 TABLE WILL NOT YET HAVE BEEN UPDATED THE ASSERTION WILL NOT BE 425% AND THE STATEMENT WILL FAIL 3IMILARLY IF YOU TRY TO PERFORM THE 50$!4% STATEMENT ON THE /&&)#%3 TABLE FIRST THE 3!,%32%03 TABLE WILL NOT YET HAVE BEEN UPDATED THE ASSERTION WILL NOT BE 425% AND THE STATEMENT WILL FAIL 4HE ONLY SOLUTION TO THIS DILEMMA IS TO DEFER CONSTRAINT CHECKING UNTIL BOTH STATEMENTS HAVE COMPLETED AND THEN CHECK TO MAKE SURE THAT BOTH OPERATIONS TAKEN TOGETHER HAVE LEFT THE DATABASE IN A VALID STATE 4HE 31, DEFERRED CONSTRAINT MECHANISM PROVIDES FOR THIS CAPABILITY AND MUCH MORE %ACH INDIVIDUAL CONSTRAINT OF ALL TYPES WITHIN THE DATABASE CAN BE IDENTIFIED AS EITHER $%&%22!",% OR ./4 $%&%22!",% WHEN IT IS FIRST CREATED OR DEFINED s $%&%22!",% CONSTRAINT ! $%&%22!",% CONSTRAINT IS ONE WHOSE CHECKING CAN BE DEFERRED TO THE END OF A TRANSACTION 4HE ASSERTION IN THE PREVIOUS EXAMPLE IS ONE THAT SHOULD BE DEFERRABLE 7HEN UPDATING QUOTAS OR ADDING NEW SALESPEOPLE TO THE DATABASE YOU CERTAINLY WANT TO BE ABLE TO DEFER CONSTRAINT CHECKING AS THE EXAMPLE SHOWED s ./4 $%&%22!",% CONSTRAINT ! ./4 $%&%22!",% CONSTRAINT IS ONE WHOSE CHECKING CANNOT BE DEFERRED ! PRIMARY KEY CONSTRAINT A UNIQUENESS CONSTRAINT AND MANY COLUMN CHECK CONSTRAINTS WOULD USUALLY FALL INTO THIS CATEGORY 4HESE DATA INTEGRITY CHECKS TYPICALLY DONT DEPEND ON OTHER DATABASE INTERACTIONS 4HEY CAN AND SHOULD BE CHECKED AFTER EVERY 31, STATEMENT THAT TRIES TO MODIFY THE DATABASE "ECAUSE IT PROVIDES THE MOST STRINGENT INTEGRITY CHECKING ./4 $%&%22!",% IS THE DEFAULT 9OU MUST EXPLICITLY DECLARE A CONSTRAINT TO BE $%&%22!",% IF YOU WANT TO DEFER ITS OPERATION .OTE ALSO THAT THESE CONSTRAINT ATTRIBUTES DEFINE ONLY THE DEFERABILITY OF A CONSTRAINTTHAT IS WHETHER ITS OPERATION CAN BE DEFERRED 4HE CONSTRAINT DEFINITION MAY ALSO SPECIFY THE INITIAL STATE OF THE CONSTRAINT s ).)4)!,,9 )--%$)!4% CONSTRAINT !N ).)4)!,,9 )--%$)!4% CONSTRAINT IS ONE THAT STARTS OUT AS AN IMMEDIATE CONSTRAINT THAT IS IT WILL BE CHECKED IMMEDIATELY FOR EACH 31, STATEMENT s ).)4)!,,9 $%&%22%$ CONSTRAINT !N ).)4)!,,9 $%&%22%$ CONSTRAINT IS ONE THAT STARTS OUT AS A DEFERRED CONSTRAINT THAT IS ITS CHECKING WILL BE DEFERRED UNTIL THE END OF A TRANSACTION /F COURSE THIS OPTION CANNOT BE SPECIFIED IF THE CONSTRAINT IS DEFINED AS ./4 $%&%22!",%
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$ATAç)NTEGRITYç
4HE CONSTRAINT IS PUT INTO THE SPECIFIED INITIAL STATE WHEN IT IS FIRST CREATED )T IS ALSO RESET INTO THIS INITIAL STATE AT THE BEGINNING OF EACH TRANSACTION "ECAUSE IT PROVIDES THE MOST STRINGENT INTEGRITY CHECKING ).)4)!,,9 )--%$)!4% IS THE DEFAULT 9OU MUST EXPLICITLY DECLARE A CONSTRAINT TO BE ).)4)!,,9 $%&%22%$ IF YOU WANT IT TO AUTOMATICALLY START OUT EACH TRANSACTION IN A DEFERRED STATE 4HE 31, STANDARD ADDS ONE MORE MECHANISM TO CONTROL THE IMMEDIATE OR DEFERRED PROCESSING OF CONSTRAINTS 9OU CAN DYNAMICALLY CHANGE THE PROCESSING OF A CONSTRAINT DURING DATABASE OPERATION USING THE 3%4 #/.342!).43 STATEMENT &OR EXAMPLE SUPPOSE THE SAMPLE DATABASE CONTAINS THIS ASSERTION #2%!4% !33%24)/. QUOTA?TOTALS #(%#+ /&&)#%34!2'%4 35-3!,%32%0315/4! !.$ 3!,%32%032%0?/&&)#% /&&)#%3/&&)#% $%&%22!",% ).)4)!,,9 )--%$)!4%
4HE INITIALLY IMMEDIATE CHECKING CAUSES THE CONSTRAINT TO BE PROCESSED STATEMENT BY STATEMENT FOR ALL NORMAL DATABASE PROCESSING &OR THE SPECIAL TRANSACTION THAT ADDS A NEW SALESPERSON TO THE DATABASE HOWEVER YOU WILL NEED TO TEMPORARILY DEFER CONSTRAINT PROCESSING 4HIS SEQUENCE OF STATEMENTS ACCOMPLISHES THE GOAL
!FTER THE #/--)4 STATEMENT ENDS THE TRANSACTION THE QUOTA?TOTALS CONSTRAINT IS RESET BACK INTO )--%$)!4% MODE BECAUSE OF THE ).)4)!,,9 )--%$)!4% SPECIFICATION )F THERE WERE MORE WORK TO BE DONE AFTER THE 50$!4% STATEMENT BEFORE THE END OF THE TRANSACTION YOU COULD MANUALLY SET THE CONSTRAINT BACK INTO )--%$)!4% MODE USING THIS STATEMENT 3%4 #/.342!).43 QUOTA?TOTALS )--%$)!4%
9OU CAN SET THE SAME MODE FOR SEVERAL DIFFERENT CONSTRAINTS BY INCLUDING THE CONSTRAINT NAMES IN A COMMA SEPARATED LIST 3%4 #/.342!).43 QUOTA?TOTALS REP?TOTALS )--%$)!4%
&INALLY YOU CAN SET THE PROCESSING MODE FOR ALL CONSTRAINTS WITH A SINGLE STATEMENT 3%4 #/.342!).43 !,, $%&%22%$
4HE 31, CAPABILITIES FOR DEFERRED CONSTRAINT CHECKING FORM A VERY COMPREHENSIVE FACILITY FOR MANAGING THE INTEGRITY OF A DATABASE !S WITH MANY CAPABILITIES IN THE 31, STANDARD INDIVIDUAL PIECES OF THE 31, CAPABILITY WERE TAKEN FROM EXISTING 31, IMPLEMENTATIONS
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3%4 #/.342!).43 QUOTA?TOTALS $%&%22%$ ).3%24 ).4/ 3!,%32%03 %-0,?.5- .!-% 2%0?/&&)#% ()2%?$!4% 15/4! 3!,%3 6!,5%3 NUM NAME OFFICE?NUM DATE AMOUNT 50$!4% /&&)#%3 3%4 4!2'%4 4!2'%4 AMOUNT 7(%2% /&&)#% OFFICE?NUM #/--)4
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5PDATINGç$ATA
AND INDIVIDUAL PIECES HAVE FOUND THEIR WAY INTO OTHER IMPLEMENTATIONS SINCE THE PUBLICATION OF THE STANDARD )"-S $" FOR EXAMPLE INCLUDES DEFERRED CONSTRAINT CHECKING CAPABILITY AND SUPPORTS 31, STYLE DEFERABILITY OPTIONS )TS 3%4 #/.342!).43 STATEMENT HOWEVER DIFFERS FROM THE 31, STANDARD )T OPERATES ON INDIVIDUAL TABLES IN THE DATABASE TURNING ON AND OFF THE DEFERRAL OF CONSTRAINT CHECKING ASSOCIATED WITH THE TABLE CONTENTS
"USINESSõ2ULES -ANY OF THE DATA INTEGRITY ISSUES IN THE REAL WORLD HAVE TO DO WITH THE RULES AND PROCEDURES OF AN ORGANIZATION &OR EXAMPLE THE COMPANY THAT IS MODELED BY THE SAMPLE DATABASE MIGHT HAVE RULES LIKE THESE s .O CUSTOMER IS ALLOWED TO PLACE ORDERS THAT WOULD EXCEED THE CUSTOMERS CREDIT LIMIT s 4HE SALES VICE PRESIDENT MUST BE NOTIFIED WHENEVER ANY CUSTOMER IS ASSIGNED A CREDIT LIMIT HIGHER THAN s /RDERS MAY REMAIN ON THE BOOKS FOR ONLY SIX MONTHS ORDERS OLDER THAN SIX MONTHS MUST BE CANCELED AND REENTERED ASSUMING THE CUSTOMER STILL WANTS THEM )N ADDITION THERE ARE OFTEN ACCOUNTING RULES THAT MUST BE FOLLOWED TO MAINTAIN THE INTEGRITY OF TOTALS COUNTS AND OTHER AMOUNTS STORED IN A DATABASE &OR THE SAMPLE DATABASE THESE RULES PROBABLY MAKE SENSE s 7HENEVER A NEW ORDER IS TAKEN THE 3!,%3 COLUMN FOR THE SALESPERSON WHO TOOK THE ORDER AND FOR THE OFFICE WHERE THAT SALESPERSON WORKS SHOULD BE INCREASED BY THE ORDER AMOUNT $ELETING AN ORDER OR CHANGING THE ORDER AMOUNT SHOULD ALSO CAUSE THE 3!,%3 COLUMNS TO BE ADJUSTED s 7HENEVER A NEW ORDER IS TAKEN THE 149?/.?(!.$ COLUMN FOR THE PRODUCT BEING ORDERED SHOULD BE DECREASED BY THE QUANTITY OF PRODUCTS ORDERED $ELETING AN ORDER CHANGING THE QUANTITY OR CHANGING THE PRODUCT ORDERED SHOULD ALSO CAUSE CORRESPONDING ADJUSTMENTS TO THE 149?/.?(!.$ COLUMN 4HESE RULES FALL OUTSIDE THE REALM OF 31, AS DEFINED BY THE 31, STANDARD AND AS IMPLEMENTED BY MANY 31, BASED $"-3 PRODUCTS TODAY 4HE $"-3 TAKES RESPONSIBILITY FOR STORING AND ORGANIZING DATA AND ENSURING ITS BASIC INTEGRITY BUT ENFORCING THE BUSINESS RULES IS THE RESPONSIBILITY OF THE APPLICATION PROGRAMS THAT ACCESS THE DATABASE 0LACING THE BURDEN OF ENFORCING BUSINESS RULES ON THE APPLICATION PROGRAMS THAT ACCESS THE DATABASE HAS SEVERAL DISADVANTAGES s $UPLICATION OF EFFORT )F SIX DIFFERENT PROGRAMS DEAL WITH VARIOUS UPDATES TO THE /2$%23 TABLE EACH MUST INCLUDE CODE THAT ENFORCES THE RULES RELATING TO /2$%23 UPDATES s ,ACK OF CONSISTENCY )F SEVERAL PROGRAMS WRITTEN BY DIFFERENT PROGRAMMERS HANDLE UPDATES TO A TABLE THEY WILL PROBABLY ENFORCE THE RULES SOMEWHAT DIFFERENTLY
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$ATAç)NTEGRITYç
s -AINTENANCE PROBLEMS )F THE BUSINESS RULES CHANGE THE PROGRAMMERS MUST IDENTIFY EVERY PROGRAM THAT ENFORCES THE RULES THEN LOCATE THE CODE AND MODIFY IT CORRECTLY s #OMPLEXITY 4HERE ARE OFTEN MANY RULES TO REMEMBER %VEN IN THE SMALL SAMPLE DATABASE A PROGRAM THAT HANDLES ORDER CHANGES MUST WORRY ABOUT ENFORCING CREDIT LIMITS ADJUSTING SALES TOTALS FOR SALESPEOPLE AND OFFICES AND ADJUSTING THE QUANTITIES ON HAND ! PROGRAM THAT HANDLES SIMPLE UPDATES CAN BECOME COMPLEX VERY QUICKLY
7HATõ)SõAõ4RIGGER 4HE CONCEPT OF A TRIGGER IS RELATIVELY STRAIGHTFORWARD &OR ANY EVENT THAT CAUSES A CHANGE IN THE CONTENTS OF A TABLE A USER CAN SPECIFY AN ASSOCIATED ACTION THAT THE $"-3 SHOULD CARRY OUT 4HE THREE EVENTS THAT CAN TRIGGER AN ACTION ARE ATTEMPTS TO ).3%24 $%,%4% OR 50$!4% ROWS OF THE TABLE 4HE ACTION TRIGGERED BY AN EVENT IS SPECIFIED BY A SEQUENCE OF 31, STATEMENTS 4O UNDERSTAND HOW A TRIGGER WORKS LETS EXAMINE A CONCRETE EXAMPLE 7HEN A NEW ORDER IS ADDED TO THE /2$%23 TABLE THESE TWO CHANGES TO THE DATABASE SHOULD ALSO TAKE PLACE s 4HE 3!,%3 COLUMN FOR THE SALESPERSON WHO TOOK THE ORDER SHOULD BE INCREASED BY THE AMOUNT OF THE ORDER s 4HE 149?/.?(!.$ AMOUNT FOR THE PRODUCT BEING ORDERED SHOULD BE DECREASED BY THE QUANTITY ORDERED 4HIS 4RANSACT 31, STATEMENT DEFINES A 31, 3ERVER TRIGGER NAMED .%7/2$%2 THAT CAUSES THESE DATABASE UPDATES TO HAPPEN AUTOMATICALLY #2%!4% 42)''%2 .%7/2$%2 /. /2$%23 &/2 ).3%24 !3 50$!4% 3!,%32%03 3%4 3!,%3 3!,%3 ).3%24%$!-/5.4 &2/- 3!,%32%03 ).3%24%$ 7(%2% 3!,%32%03%-0,?.5- ).3%24%$2%0 50$!4% 02/$5#43 3%4 149?/.?(!.$ 149?/.?(!.$ ).3%24%$149 &2/- 02/$5#43 ).3%24%$ 7(%2% 02/$5#43-&2?)$ ).3%24%$-&2 !.$ 02/$5#4302/$5#4?)$ ).3%24%$02/$5#4
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4HE REQUIREMENT THAT APPLICATION PROGRAMS ENFORCE BUSINESS RULES IS NOT UNIQUE TO 31, !PPLICATION PROGRAMS HAVE HAD THAT RESPONSIBILITY SINCE THE EARLIEST DAYS OF #/"/, PROGRAMS AND FILE SYSTEMS (OWEVER THERE HAS BEEN A STEADY TREND OVER THE YEARS TO PUT MORE hUNDERSTANDINGv OF THE DATA AND MORE RESPONSIBILITY FOR ITS INTEGRITY INTO THE DATABASE ITSELF )N THE 3YBASE $"-3 INTRODUCED THE CONCEPT OF A TRIGGER AS A STEP TOWARD INCLUDING BUSINESS RULES IN A RELATIONAL DATABASE 4HE CONCEPT PROVED TO BE VERY POPULAR SO SUPPORT FOR TRIGGERS BEGAN TO APPEAR IN MANY 31, $"-3 PRODUCTS IN THE EARLY S INCLUDING THOSE OF THE MAINSTREAM ENTERPRISE $"-3 VENDORS 4RIGGERS AND THE ENFORCEMENT OF BUSINESS RULES THAT THEY PROVIDE HAVE BEEN ESPECIALLY USEFUL IN ENTERPRISE DATABASE ENVIRONMENTS 7HEN HUNDREDS OF APPLICATION PROGRAMS ARE BEING DEVELOPED OR MODIFIED EVERY YEAR BY DOZENS OF APPLICATION PROGRAMMERS THE ABILITY TO CENTRALIZE THE DEFINITION AND ADMINISTRATION OF BUSINESS RULES CAN BE VERY USEFUL
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5PDATINGç$ATA
4HE FIRST PART OF THE TRIGGER DEFINITION TELLS 31, 3ERVER THAT THE TRIGGER IS TO BE INVOKED WHENEVER AN ).3%24 STATEMENT IS ATTEMPTED ON THE /2$%23 TABLE 4HE REMAINDER OF THE DEFINITION AFTER THE KEYWORD !3 DEFINES THE ACTION OF THE TRIGGER )N THIS CASE THE ACTION IS A SEQUENCE OF TWO 50$!4% STATEMENTS ONE FOR THE 3!,%32%03 TABLE AND ONE FOR THE 02/$5#43 TABLE 4HE ROW BEING INSERTED IS REFERRED TO USING THE PSEUDOnTABLE NAME INSERTED WITHIN THE 50$!4% STATEMENTS !S THE EXAMPLE SHOWS 31, 3ERVER EXTENDS THE 31, LANGUAGE SUBSTANTIALLY TO SUPPORT TRIGGERS /THER EXTENSIONS NOT SHOWN HERE INCLUDE )&4(%.%,3% TESTS LOOPING PROCEDURE CALLS AND EVEN 02).4 STATEMENTS THAT DISPLAY USER MESSAGES 4RIGGERS WERE ADDED TO THE 31, VERSION OF THE !.3))3/ 31, STANDARD WELL AFTER THE TIME WHEN THE MOST POPULAR $"-3 BRANDS ADDED SUPPORT FOR THEM !S WITH OTHER 31, FEATURES WHOSE POPULARITY HAS PRECEDED STANDARDIZATION THIS HAS LED TO A CONSIDERABLE DIVERGENCE IN TRIGGER SUPPORT ACROSS VARIOUS $"-3 BRANDS 3OME OF THE DIFFERENCES BETWEEN BRANDS ARE MERELY DIFFERENCES IN SYNTAX /THERS REFLECT REAL DIFFERENCES IN THE UNDERLYING CAPABILITY $"S TRIGGER SUPPORT PROVIDES AN INSTRUCTIVE EXAMPLE OF THE DIFFERENCES (ERE IS THE SAME TRIGGER DEFINITION SHOWN PREVIOUSLY FOR 31, 3ERVER THIS TIME USING THE $" SYNTAX #2%!4% 42)''%2 .%7/2$%2 !&4%2 ).3%24 /. /2$%23 2%&%2%.#).' .%7 !3 .%7?/2$ &/2 %!#( 2/7 -/$% $"31, "%'). !4/-)# 50$!4% 3!,%32%03 3%4 3!,%3 3!,%3 .%7?/2$!-/5.4 7(%2% 3!,%32%03%-0,?.5- .%7?/2$2%0 50$!4% 02/$5#43 3%4 149?/.?(!.$ 149?/.?(!.$ n .%7?/2$149 7(%2% 02/$5#43-&2?)$ .%7?/2$-&2 !.$ 02/$5#4302/$5#4?)$ .%7?/2$02/$5#4 %.$
4HE BEGINNING OF THE TRIGGER DEFINITION INCLUDES THE SAME ELEMENTS AS THE 31, 3ERVER DEFINITION BUT REARRANGES THEM )T EXPLICITLY TELLS $" THAT THE TRIGGER IS TO BE INVOKED AFTER A NEW ORDER IS INSERTED INTO THE DATABASE $" ALSO ALLOWS YOU TO SPECIFY THAT THE TRIGGER IS TO BE CARRIED OUT BEFORE A TRIGGERING ACTION IS APPLIED TO THE DATABASE CONTENTS 4HIS DOESNT MAKE SENSE IN THIS EXAMPLE BECAUSE THE TRIGGERING EVENT IS AN ).3%24 OPERATION BUT IT DOES MAKE SENSE FOR 50$!4% OR $%,%4% OPERATIONS 4HE $" 2%&%2%.#).' CLAUSE SPECIFIES A TABLE ALIAS .%7?/2$ THAT WILL BE USED TO REFER TO THE ROW BEING INSERTED THROUGHOUT THE REMAINDER OF THE TRIGGER DEFINITION 4HE ALIAS CREATED BY THE 2%&%2%.#).' CLAUSE .%7?/2$ SERVES THE SAME PURPOSE AS THE ).3%24%$ KEYWORD IN THE 31, 3ERVER TRIGGER 4HE STATEMENT REFERENCES THE NEW VALUES IN THE INSERTED ROW BECAUSE THIS IS AN ).3%24 OPERATION TRIGGER &OR A $%,%4% OPERATION TRIGGER THE OLD VALUES WOULD BE REFERENCED &OR AN 50$!4% OPERATION TRIGGER $" GIVES YOU THE ABILITY TO REFER TO BOTH THE OLD PRE 50$!4% VALUES AND NEW POST 50$!4% VALUES "%'). !4/-)# AND %.$ SERVE AS BRACKETS AROUND THE SEQUENCE OF 31, STATEMENTS THAT DEFINE THE TRIGGERED ACTION 4HE TWO SEARCHED 50$!4% STATEMENTS IN THE BODY OF THE TRIGGER DEFINITION ARE STRAIGHTFORWARD MODIFICATIONS OF THEIR 31, 3ERVER COUNTERPARTS 4HEY FOLLOW THE STANDARD 31, SYNTAX FOR SEARCHED 50$!4% STATEMENTS USING THE TABLE ALIAS SPECIFIED BY THE 2%&%2%.#).' CLAUSE TO IDENTIFY THE PARTICULAR ROW OF THE 3!,%32%03 TABLE AND THE 02/$5#43 TABLE TO BE UPDATED 4HE ROW BEING INSERTED IS REFERRED TO USING THE PSEUDOnTABLE NAME INSERTED WITHIN THE 50$!4% STATEMENTS
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$ATAç)NTEGRITYç
4RIGGERSõANDõ2EFERENTIALõ)NTEGRITY 4RIGGERS PROVIDE AN ALTERNATIVE WAY TO IMPLEMENT THE REFERENTIAL INTEGRITY CONSTRAINTS PROVIDED BY FOREIGN KEYS AND PRIMARY KEYS )N FACT ADVOCATES OF THE TRIGGER FEATURE POINT OUT THAT THE TRIGGER MECHANISM IS MORE FLEXIBLE THAN THE STRICT REFERENTIAL INTEGRITY PROVIDED BY THE !.3))3/ STANDARD (OWEVER OPPONENTS OF THE TRIGGER FEATURE POINT OUT THAT TRIGGER BEHAVIOR VARIES GREATLY FROM ONE $"-3 TO ANOTHER PARTICULARLY IN THE WAY TRANSACTIONS ARE ROLLED BACK HOW FAILED TRIGGERS ARE CLEANED UP AND HOW LOCKING WORKS DURING THE DURATION OF TRIGGER EXECUTION &OR EXAMPLE HERE IS A 31, 3ERVER TRIGGER THAT ENFORCES REFERENTIAL INTEGRITY FOR THE /&&)#%33!,%32%03 RELATIONSHIP AND DISPLAYS A MESSAGE WHEN AN ATTEMPTED UPDATE FAILS
4RIGGERS CAN ALSO BE USED TO PROVIDE EXTENDED FORMS OF REFERENTIAL INTEGRITY &OR EXAMPLE $" INITIALLY PROVIDED CASCADED DELETES THROUGH ITS #!3#!$% DELETE RULE BUT DID NOT SUPPORT CASCADED UPDATES IF A PRIMARY KEY VALUE IS CHANGED 4HIS LIMITATION NEED NOT APPLY TO TRIGGERS HOWEVER 4HE FOLLOWING 31, 3ERVER TRIGGER CASCADES ANY UPDATE OF THE /&&)#% COLUMN IN THE /&&)#%3 TABLE DOWN INTO THE 2%0?/&&)#% COLUMN OF THE 3!,%32%03 TABLE #2%!4% 42)''%2 #(!.'%?2%0?/&&)#% /. /&&)#%3 &/2 50$!4% !3 )& 50$!4% /&&)#% "%'). 50$!4% 3!,%32%03 3%4 3!,%32%032%0?/&&)#% ).3%24%$/&&)#% &2/- 3!,%32%03 ).3%24%$ $%,%4%$ 7(%2% 3!,%32%032%0?/&&)#% $%,%4%$/&&)#% %.$
!S IN THE PREVIOUS 31, 3ERVER EXAMPLE THE REFERENCES $%,%4%$/&&)#% AND ).3%24%$/&&)#% IN THE TRIGGER REFER RESPECTIVELY TO THE VALUES OF THE /&&)#% COLUMN BEFORE AND AFTER THE 50$!4% STATEMENT 4HE TRIGGER DEFINITION MUST BE ABLE TO DIFFERENTIATE BETWEEN THESE BEFORE AND AFTER VALUES TO PERFORM THE APPROPRIATE SEARCH AND UPDATE ACTIONS SPECIFIED BY THE TRIGGER
4RIGGERõ!DVANTAGESõANDõ$ISADVANTAGES /VER THE LAST SEVERAL YEARS THE TRIGGER MECHANISMS IN MANY COMMERCIAL $"-3 PRODUCTS HAVE EXPANDED SIGNIFICANTLY )N MANY COMMERCIAL IMPLEMENTATIONS THE DISTINCTIONS BETWEEN TRIGGERS AND STORED PROCEDURES DESCRIBED IN #HAPTER HAVE BLURRED SO THE
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ACTION TRIGGERED BY A SINGLE DATABASE CHANGE MAY BE DEFINED BY HUNDREDS OF LINES OF STORED PROCEDURE PROGRAMMING 4HE ROLE OF TRIGGERS HAS THUS EVOLVED BEYOND THE ENFORCEMENT OF DATA INTEGRITY INTO A PROGRAMMING CAPABILITY WITHIN THE DATABASE ! COMPLETE DISCUSSION OF TRIGGERS IS BEYOND THE SCOPE OF THIS BOOK BUT EVEN THESE SIMPLE EXAMPLES SHOW THE POWER OF THE TRIGGER MECHANISM 4HE MAJOR ADVANTAGE OF TRIGGERS IS THAT BUSINESS RULES CAN BE STORED IN THE DATABASE AND ENFORCED CONSISTENTLY WITH EACH UPDATE TO THE DATABASE 4HIS CAN DRAMATICALLY REDUCE THE COMPLEXITY OF APPLICATION PROGRAMS THAT ACCESS THE DATABASE 4RIGGERS ALSO HAVE SOME DISADVANTAGES INCLUDING THESE s $ATABASE COMPLEXITY 7HEN THE RULES ARE MOVED INTO THE DATABASE SETTING UP THE DATABASE BECOMES A MORE COMPLEX TASK 5SERS WHO COULD REASONABLY BE EXPECTED TO CREATE SMALL AD HOC APPLICATIONS WITH 31, WILL FIND THAT THE PROGRAMMING LOGIC OF TRIGGERS MAKES THE TASK MUCH MORE DIFFICULT s (IDDEN RULES 7ITH THE RULES HIDDEN AWAY INSIDE THE DATABASE PROGRAMS THAT APPEAR TO PERFORM STRAIGHTFORWARD DATABASE UPDATES MAY IN FACT GENERATE AN ENORMOUS AMOUNT OF DATABASE ACTIVITY 4HE PROGRAMMER NO LONGER HAS TOTAL CONTROL OVER WHAT HAPPENS TO THE DATABASE )NSTEAD A PROGRAM INITIATED DATABASE ACTION MAY CAUSE OTHER HIDDEN ACTIONS s (IDDEN PERFORMANCE IMPLICATIONS 7ITH TRIGGERS STORED INSIDE THE DATABASE THE CONSEQUENCES OF EXECUTING A 31, STATEMENT ARE NO LONGER COMPLETELY VISIBLE TO THE PROGRAMMER )N PARTICULAR AN APPARENTLY SIMPLE 31, STATEMENT COULD IN CONCEPT TRIGGER A PROCESS THAT INVOLVES A SEQUENTIAL SCAN OF A VERY LARGE DATABASE TABLE WHICH COULD TAKE A LONG TIME TO COMPLETE 4HESE PERFORMANCE IMPLICATIONS OF ANY GIVEN 31, STATEMENT ARE INVISIBLE TO THE PROGRAMMER
4RIGGERSõANDõTHEõ31,õ3TANDARD 4RIGGERS WERE ONE OF THE MOST WIDELY PRAISED AND PUBLICIZED FEATURES OF 3YBASE 31, 3ERVER WHEN IT WAS FIRST INTRODUCED AND THEY HAVE SINCE FOUND THEIR WAY INTO MANY COMMERCIAL 31, PRODUCTS !LTHOUGH THE 31, STANDARD PROVIDED AN OPPORTUNITY TO STANDARDIZE THE $"-3 IMPLEMENTATION OF TRIGGERS THE STANDARDS COMMITTEE INCLUDED CHECK CONSTRAINTS INSTEAD LEAVING TRIGGERS FOR A SUBSEQUENT VERSION 31, ALSO KNOWN AS 31, !S THE TRIGGER AND CHECK CONSTRAINT EXAMPLES IN THE PRECEDING SECTIONS SHOW CHECK CONSTRAINTS CAN BE EFFECTIVELY USED TO LIMIT THE DATA THAT CAN BE ADDED TO A TABLE OR MODIFIED IN A TABLE (OWEVER UNLIKE TRIGGERS THEY LACK THE ABILITY TO CAUSE AN INDEPENDENT ACTION IN THE DATABASE SUCH AS ADDING A ROW OR CHANGING A DATA ITEM IN ANOTHER TABLE 3OME EXPERTS HAVE ARGUED THAT TRIGGERS ARE A POLLUTION OF THE DATA MANAGEMENT FUNCTION OF A DATABASE AND THAT THE FUNCTIONS PERFORMED BY TRIGGERS BELONG IN FOURTH GENERATION LANGUAGES ',S AND OTHER DATABASE TOOLS RATHER THAN IN THE $"-3 ITSELF 7HILE THE DEBATE CONTINUES $"-3 PRODUCTS HAVE EXPERIMENTED WITH NEW TRIGGER CAPABILITIES THAT EXTEND BEYOND THE DATABASE ITSELF 4HESE EXTENDED TRIGGER CAPABILITIES ALLOW MODIFICATIONS TO DATA IN A DATABASE TO AUTOMATICALLY CAUSE ACTIONS SUCH AS SENDING MAIL ALERTING A USER OR LAUNCHING ANOTHER PROGRAM TO PERFORM A TASK 4HIS MAKES TRIGGERS EVEN MORE USEFUL AND WILL ADD TO THE DEBATE OVER HOW EXTENSIVELY THEY SHOULD BE USED (OWEVER THERE IS NO DOUBT THAT TRIGGERS HAVE BECOME A MORE AND MORE IMPORTANT PART OF 31, IN ENTERPRISE APPLICATIONS OVER THE LAST SEVERAL YEARS
#HAPTERçç
$ATAç)NTEGRITYç
3UMMARY 4HE 31, LANGUAGE PROVIDES A NUMBER OF FEATURES THAT HELP TO PROTECT THE INTEGRITY OF DATA STORED IN A RELATIONAL DATABASE s 2EQUIRED COLUMNS CAN BE SPECIFIED WHEN A TABLE IS CREATED AND THE $"-3 WILL PREVENT .5,, VALUES IN THESE COLUMNS s $ATA VALIDATION IS LIMITED TO DATA TYPE CHECKING IN STANDARD 31, BUT MANY $"-3 PRODUCTS OFFER OTHER DATA VALIDATION FEATURES s %NTITY INTEGRITY CONSTRAINTS ENSURE THAT THE PRIMARY KEY UNIQUELY IDENTIFIES EACH ENTITY REPRESENTED IN THE DATABASE s 2EFERENTIAL INTEGRITY CONSTRAINTS ENSURE THAT RELATIONSHIPS AMONG ENTITIES IN THE DATABASE ARE PRESERVED DURING DATABASE CHANGES INSERTS UPDATES AND DELETES s 4HE 31, STANDARD AND NEWER IMPLEMENTATIONS PROVIDE EXTENSIVE REFERENTIAL INTEGRITY SUPPORT INCLUDING DELETE AND UPDATE RULES THAT TELL THE $"-3 HOW TO HANDLE THE DELETION AND MODIFICATION OF ROWS THAT ARE REFERENCED BY OTHER ROWS
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s "USINESS RULES CAN BE ENFORCED BY THE $"-3 THROUGH THE TRIGGER MECHANISM POPULARIZED BY 3YBASE AND 31, 3ERVER AND LATER INCLUDED IN THE 31, STANDARD 4RIGGERS ALLOW THE $"-3 TO TAKE COMPLEX ACTIONS IN RESPONSE TO EVENTS SUCH AS ATTEMPTED ).3%24 $%,%4% OR 50$!4% STATEMENTS #HECK CONSTRAINTS PROVIDE A MORE LIMITED WAY TO INCLUDE BUSINESS RULES IN THE DEFINITION OF A DATABASE AND HAVE THE $"-3 ENFORCE THEM
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#(!04%2
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ATABASE UPDATES ARE USUALLY TRIGGERED BY REAL WORLD EVENTS SUCH AS THE RECEIPT OF A NEW ORDER FROM A CUSTOMER )N FACT RECEIVING A NEW ORDER WOULD GENERATE NOT JUST ONE BUT THIS SERIES OF FOUR UPDATES TO THE SAMPLE DATABASE
s !DD THE NEW ORDER TO THE /2$%23 TABLE s 5PDATE THE SALES TOTAL FOR THE SALESPERSON WHO TOOK THE ORDER s 5PDATE THE SALES TOTAL FOR THE SALESPERSONS OFFICE s 5PDATE THE QUANTITY ON HAND TOTAL FOR THE ORDERED PRODUCT 4O LEAVE THE DATABASE IN A SELF CONSISTENT STATE ALL FOUR UPDATES MUST OCCUR AS A UNIT )F A SYSTEM FAILURE OR ANOTHER ERROR CREATES A SITUATION WHERE SOME OF THE UPDATES ARE PROCESSED AND OTHERS ARE NOT THE INTEGRITY OF THE DATABASE WILL BE COMPROMISED 3IMILARLY IF ANOTHER USER CALCULATES TOTALS OR RATIOS PARTWAY THROUGH THE SEQUENCE OF UPDATES THE CALCULATIONS WILL BE INCORRECT 4HE SEQUENCE OF UPDATES MUST THUS BE AN ALL OR NOTHING PROPOSITION IN THE DATABASE 31, PROVIDES PRECISELY THIS CAPABILITY THROUGH ITS TRANSACTION PROCESSING FEATURES WHICH ARE DESCRIBED IN THIS CHAPTER
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7HATõ)SõAõ4RANSACTION ! TRANSACTION IS A SEQUENCE OF ONE OR MORE 31, STATEMENTS THAT TOGETHER FORM A LOGICAL UNIT OF WORK 4HE 31, STATEMENTS THAT FORM THE TRANSACTION ARE TYPICALLY CLOSELY RELATED AND PERFORM INTERDEPENDENT ACTIONS %ACH STATEMENT IN THE TRANSACTION PERFORMS SOME PART OF A TASK BUT ALL OF THEM ARE REQUIRED TO COMPLETE THE TASK 'ROUPING THE STATEMENTS AS A SINGLE TRANSACTION TELLS THE $"-3 THAT THE ENTIRE STATEMENT SEQUENCE SHOULD BE EXECUTED IN A MANNER THAT PASSES WHAT IS KNOWN AS THE !#)$ TEST !#)$ IS AN ACRONYM COMMONLY USED WHEN REFERRING TO FOUR CHARACTERISTICS OF A TRANSACTION s !TOMIC ! TRANSACTION HAS AN ALL OR NOTHING NATURE %ITHER ALL OPERATIONS IN A TRANSACTION ARE PERFORMED OR NONE OF THEM ARE PERFORMED )F SOME STATEMENTS ARE EXECUTED AND THE TRANSACTION FAILS THE RESULTS OF THE STATEMENTS THAT EXECUTED MUST BE ROLLED BACK /NLY WHEN ALL STATEMENTS ARE EXECUTED PROPERLY CAN A TRANSACTION BE CONSIDERED COMPLETE AND THE RESULTS OF THE TRANSACTION APPLIED TO THE DATABASE s #ONSISTENT ! TRANSACTION MUST TRANSFORM THE DATABASE FROM ONE CONSISTENT STATE TO ANOTHER 4HE DATABASE MUST BE CONSISTENT AT THE END OF EACH TRANSACTION MEANING THAT ALL RULES THAT DEFINE AND CONSTRAIN THE DATA MUST BE ADHERED TO BEFORE THE TRANSACTION CAN END !LSO NO USER SHOULD SEE INCONSISTENT DATA BECAUSE OF CHANGES MADE BY TRANSACTIONS THAT HAVE NOT YET COMPLETED s )SOLATED %ACH TRANSACTION MUST EXECUTE ON ITS OWN WITHOUT INTERFERENCE FROM OTHER TRANSACTIONS 4O BE ISOLATED NO TRANSACTION CAN ACT UPON CHANGES MADE BY OTHER TRANSACTIONS UNTIL THOSE TRANSACTIONS ARE COMPLETE s $URABLE /NCE A TRANSACTION IS COMPLETE ALL CHANGES MADE BY IT SHOULD BE PRESERVED 4HE DATA SHOULD BE IN A CONSISTENT STATE EVEN IF A HARDWARE OR APPLICATION ERROR OCCURS AFTER COMPLETION OF THE TRANSACTION )N OBJECT ORIENTED PROGRAMMING THE TERM PERSISTENCE IS USED FOR THIS PROPERTY (ERE ARE SOME EXAMPLES OF TYPICAL TRANSACTIONS FOR THE SAMPLE DATABASE ALONG WITH THE 31, STATEMENT SEQUENCE THAT COMPRISES EACH TRANSACTION s !DD AN ORDER 4O ACCEPT A CUSTOMERS ORDER THE ORDER ENTRY PROGRAM SHOULD A QUERY THE 02/$5#43 TABLE TO ENSURE THAT THE PRODUCT IS IN STOCK B INSERT THE ORDER INTO THE /2$%23 TABLE C UPDATE THE 02/$5#43 TABLE SUBTRACTING THE QUANTITY ORDERED FROM THE QUANTITY ON HAND OF THE PRODUCT D UPDATE THE 3!,%32%03 TABLE ADDING THE ORDER AMOUNT TO THE TOTAL SALES OF THE SALESPERSON WHO TOOK THE ORDER AND E UPDATE THE /&&)#%3 TABLE ADDING THE ORDER AMOUNT TO THE TOTAL SALES OF THE OFFICE WHERE THE SALESPERSON WORKS s #ANCEL AN ORDER 4O CANCEL A CUSTOMERS ORDER THE PROGRAM SHOULD A DELETE THE ORDER FROM THE /2$%23 TABLE B UPDATE THE 02/$5#43 TABLE ADJUSTING THE QUANTITY ON HAND TOTAL FOR THE PRODUCT C UPDATE THE 3!,%32%03 TABLE SUBTRACTING THE ORDER AMOUNT FROM THE SALESPERSONS TOTAL SALES AND D UPDATE THE /&&)#%3 TABLE SUBTRACTING THE ORDER AMOUNT FROM THE OFFICES TOTAL SALES
#HAPTERçç
4R A N S A C T I O N ç 0 R O C E S S I N G ç
s 2EASSIGN A CUSTOMER 7HEN A CUSTOMER IS REASSIGNED FROM ONE SALESPERSON TO ANOTHER THE PROGRAM SHOULD A UPDATE THE #534/-%23 TABLE TO REFLECT THE CHANGE B UPDATE THE /2$%23 TABLE TO SHOW THE NEW SALESPERSON FOR ALL ORDERS PLACED BY THE CUSTOMER C UPDATE THE 3!,%32%03 TABLE REDUCING THE QUOTA FOR THE SALESPERSON LOSING THE CUSTOMER AND D UPDATE THE 3!,%32%03 TABLE RAISING THE QUOTA FOR THE SALESPERSON GAINING THE CUSTOMER )N EACH OF THESE CASES A SEQUENCE OF FOUR OR FIVE ACTIONS WHERE EACH ACTION CONSISTS OF A SEPARATE 31, STATEMENT IS REQUIRED TO HANDLE THE SINGLE LOGICAL TRANSACTION 4HE TRANSACTION CONCEPT IS CRITICAL FOR PROGRAMS THAT UPDATE A DATABASE BECAUSE IT ENSURES THE INTEGRITY OF THE DATABASE ! 31, BASED $"-3 MAKES THIS COMMITMENT ABOUT THE STATEMENTS IN A TRANSACTION 4HE STATEMENTS IN A TRANSACTION WILL BE EXECUTED AS AN ATOMIC UNIT OF WORK IN THE DATABASE %ITHER THE RESULTS OF ALL OF THE STATEMENTS WILL BE APPLIED TO THE DATABASE OR NONE OF THE STATEMENTS WILL HAVE RESULTS POSTED TO THE DATABASE
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4HE $"-3 IS RESPONSIBLE FOR KEEPING THIS COMMITMENT EVEN IF THE APPLICATION PROGRAM ABORTS OR A HARDWARE FAILURE OCCURS IN THE MIDDLE OF THE TRANSACTION AS SHOWN IN &IGURE )N EACH CASE THE $"-3 MUST MAKE SURE THAT WHEN FAILURE RECOVERY IS COMPLETE THE DATABASE NEVER REFLECTS A PARTIAL TRANSACTION
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4HEõ!.3))3/õ31,õ4RANSACTIONõ-ODEL 4HE !.3))3/ 31, STANDARD DEFINES A 31, TRANSACTION MODEL AND SEVEN STATEMENTS THAT SUPPORT TRANSACTION PROCESSING s 34!24 42!.3!#4)/. 3ETS THE PROPERTIES OF A NEW TRANSACTION AND STARTS THAT TRANSACTION s 3%4 42!.3!#4)/. 3ETS THE PROPERTIES OF THE NEXT TRANSACTION TO BE EXECUTED )T HAS NO EFFECT HOWEVER ON ANY CURRENTLY EXECUTING TRANSACTION s 3%4 #/.342!).43 3ETS THE CONSTRAINT MODE WITHIN A CURRENT TRANSACTION 4HE CONSTRAINT MODE CONTROLS WHETHER A CONSTRAINT IS APPLIED IMMEDIATELY TO DATA AS IT IS MODIFIED OR WHETHER ENFORCEMENT OF THE CONSTRAINT IS TO BE DEFERRED UNTIL LATER IN THE TRANSACTION 3%4 #/.342!).43 IS PRESENTED IN #HAPTER s 3!6%0/).4 #REATES A SAVEPOINT WITHIN A TRANSACTION ! SAVEPOINT IS A PLACE WITHIN A TRANSACTIONS SEQUENCE OF EVENTS THAT CAN ACT AS AN INTERMEDIATE RECOVERY POINT ! CURRENT TRANSACTION CAN BE ROLLED BACK TO THE SAVEPOINT INSTEAD OF TO THE BEGINNING OF THE TRANSACTION s 2%,%!3% 3!6%0/).4 2ELEASES A SAVEPOINT FREEING UP ANY RESOURCES IT MAY BE HOLDING s #/--)4 4ERMINATES A SUCCESSFUL TRANSACTION AND COMMITS ALL CHANGES TO THE DATABASE s 2/,,"!#+ 7HEN USED WITHOUT A SAVEPOINT TERMINATES AN UNSUCCESSFUL TRANSACTION AND ROLLS BACK ANY CHANGES TO THE BEGINNING OF A TRANSACTION ESSENTIALLY RESTORING THE DATABASE TO ITS CONSISTENT STATE BEFORE THE TRANSACTION AS IF THE TRANSACTION HAD NEVER EXECUTED 7HEN USED WITH A SAVEPOINT ROLLS BACK THE TRANSACTION TO THE NAMED SAVEPOINT BUT ALLOWS IT TO CONTINUE 4HE FIRST VERSION OF THE 31, STANDARD 31, DEFINED AN IMPLICIT TRANSACTION MODE BASED ON THE TRANSACTION SUPPORT IN THE EARLY RELEASES OF $" )N IMPLICIT MODE ONLY THE #/--)4 AND 2/,,"!#+ STATEMENTS ARE SUPPORTED ! 31, TRANSACTION AUTOMATICALLY BEGINS WITH THE FIRST 31, STATEMENT EXECUTED BY A USER OR A PROGRAM AND ENDS WHEN A #/--)4 OR 2/,,"!#+ IS EXECUTED 4HE END OF ONE TRANSACTION IMPLICITLY STARTS A NEW ONE )N PROGRAMMATIC 31, SUCCESSFUL TERMINATION OF A PROGRAM IS HANDLED AS IF A #/--)4 WAS ISSUED AND ABNORMAL TERMINATION OF A PROGRAM IS HANDLED AS IF A 2/,,"!#+ WAS ISSUED -ANY COMMERCIAL PRODUCTS NOTABLY $" AND /RACLE STILL DEFAULT TO IMPLICIT TRANSACTION MODE WHEN YOU FIRST CONNECT TO THE DATABASE 4HE 31, AND 31, VERSIONS OF THE !.3))3/ 31, STANDARD INTRODUCED THE OTHER STATEMENTS SHOWN IN THE PRECEDING LIST -OST MODERN COMMERCIAL PRODUCTS SUPPORT THEM HOWEVER THERE ARE EXCEPTIONS &OR EXAMPLE 3YBASE !3% AND 31, 3%26%2 SUPPORT A "%'). 42!.3!#4)/. STATEMENT INSTEAD OF 34!24 42!.3!#4)/. AND A 3!6% 42!.3!#4)/. STATEMENT INSTEAD OF 3!6%0/).4
4HEõ34!24õ42!.3!#4)/.õANDõ3%4õ42!.3!#4)/.õ3TATEMENTS 4HE SYNTAX DIAGRAMS FOR THE 34!24 42!.3!#4)/. AND 3%4 42!.3!#4)/. STATEMENTS ARE SHOWN IN &IGURE 4HE FUNDAMENTAL DIFFERENCE BETWEEN THE TWO IS THAT 34!24 42!.3!#4)/. STARTS A NEW TRANSACTION WITH AN OPTION TO SET CERTAIN PROPERTIES OF THE
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4R A N S A C T I O N ç 0 R O C E S S I N G ç
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TRANSACTION WHILE THE 3%4 42!.3!#4)/. STATEMENT SETS PROPERTIES THAT WILL BE USED BY THE NEXT TRANSACTIONIT CANNOT BE USED WITHIN AN EXISTING TRANSACTION AND THEREFORE CAN HAVE NO EFFECT ON ANY EXISTING TRANSACTION /NE OTHER DIFFERENCE IS THAT THE 3%4 42!.3!#4)/. STATEMENT HAS A ,/#!, OPTION WHICH CAN BE USED TO SET OPTIONS FOR LOCAL SERVER EXECUTION OF A TRANSACTION THAT SPANS MULTIPLE SERVERS 4HE THREE PROPERTIES THAT MAY BE SET BY THESE STATEMENTS IN ANY ORDER DESIRED ARE s )SOLATION LEVEL $EFINES HOW ISOLATED A TRANSACTION WILL BE FROM THE ACTIONS OF OTHER TRANSACTIONS 4HE SPECIFIC OPTIONS 2%!$ 5.#/--)44%$ 2%!$ #/--)44%$ 2%0%!4!",% 2%!$ AND 3%2)!,):!",% ARE PRESENTED IN DETAIL IN THE h)SOLATION ,EVELSv TOPIC LATER IN THIS CHAPTER )F NO ISOLATION LEVEL IS SPECIFIED THE DEFAULT IS 3%2)!,):!",% s !CCESS LEVEL $EFINES WHETHER THE TRANSACTION CAN CONTAIN STATEMENTS THAT MODIFY THE DATABASE 2%!$ 72)4% OR NOT 2%!$ /.,9 4HE DEFAULT DEPENDS ON THE ISOLATION LEVEL SELECTED BUT IF NO ISOLATION LEVEL IS SPECIFIED THE DEFAULT IS 2%!$ 72)4% s $IAGNOSTICS SIZE $EFINES THE SIZE OF THE DIAGNOSTICS AREA USED FOR CONDITIONS THAT CAN BE RAISED BY 31, STATEMENTS AS THEY EXECUTE ! CONDITION IS A WARNING EXCEPTION OR OTHER TYPE OF MESSAGE GENERATED BY 31, STATEMENT EXECUTION &OR EXAMPLE IF DIAGNOSTICS SIZE IS SET TO THEN UP TO CONDITIONS CAN BE STORED FOR AN EXECUTED STATEMENT .OTE THAT AS OF THIS WRITING THE DIAGNOSTICS SIZE OPTION IS NOT SUPPORTED BY 31, 3ERVER 3YBASE !3% /RACLE -Y31, $" OR MOST OTHER CURRENT 31, IMPLEMENTATIONS
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(ERE IS AN EXAMPLE OF A 34!24 42!.3!#4)/. STATEMENT THAT SETS AN ISOLATION LEVEL OF 2%!$ 5.#/--)44%$ AN ACCESS LEVEL OF 2%!$ /.,9 AND A DIAGNOSTICS SIZE OF 34!24 42!.3!#4)/. )3/,!4)/. ,%6%, 2%!$ 5.#/--)44%$ 2%!$ /.,9 $)!'./34)#3 3):%
4HEõ3!6%0/).4õANDõ2%,%!3%õ3!6%0/).4õ3TATEMENTS !S STATED EARLIER THE 3!6%0/).4 STATEMENT ESTABLISHES A POINT WITHIN A TRANSACTION TO WHICH THE TRANSACTION CAN BE ROLLED BACK USING A SUBSEQUENT 2/,,"!#+ STATEMENT 4HE SYNTAX IS QUITE SIMPLE WITH THE ONLY PARAMETER BEING A UNIQUE NAME FOR THE SAVEPOINT WITHIN THE TRANSACTION 3!6%0/).4 SAVEPOINT NAME
4HE OBVIOUS ADVANTAGE OF USING A SAVEPOINT IS THE ABILITY TO ROLL BACK PART OF A TRANSACTION WHEN A MINOR AND POTENTIALLY RECOVERABLE ERROR CONDITION IS ENCOUNTERED 4HE RIGHTMOST TRANSACTION IN &IGURE SHOWS SUCH AN EXAMPLE )N MOST IMPLEMENTATIONS TRANSACTIONS CAN HAVE AS MANY SAVEPOINTS AS NECESSARY PROVIDED EACH IS GIVEN A UNIQUE NAME WITHIN THE TRANSACTION &OR EXAMPLE AN ORDER ENTRY APPLICATION MIGHT CREATE A SAVEPOINT AFTER EACH LINE ITEM IS ENTERED ON THE ORDER 3HOULD THE ADDITION OF A NEW LINE ITEM EXCEED THE CREDIT LIMIT OF THE CUSTOMER THE APPLICATION CAN ROLL BACK TO THE SAVEPOINT JUST BEFORE THE CURRENT LINE ITEM 4HE ROLLBACK WOULD REVERSE THE LINE ITEM THAT CAUSED THE PROBLEM ALLOWING THE APPLICATION TO PRESENT AN ERROR MESSAGE TO THE PERSON ENTERING THE ORDER AND THEN TO PROCEED FROM THAT POINT PERHAPS WITH A LESS EXPENSIVE ITEM THAT WOULD NOT EXCEED THE LIMIT 4HE DISADVANTAGE OF SAVEPOINTS IS THAT THEY POTENTIALLY REQUIRE A LOT OF RESOURCES STORAGE ANDOR MEMORY 7HILE TERMINATION OF THE TRANSACTION RELEASES ALL THE SAVEPOINTS AUTOMATICALLY SOMETIMES IT IS WISE TO EXPLICITLY RELEASE SAVEPOINTS THAT ARE NO LONGER NECESSARY 4HIS CAN BE DONE WITH THE 2%,%!3% 3!6%0/).4 STATEMENT WHICH HAS SYNTAX THAT IS EQUALLY SIMPLE 2%,%!3% 3!6%0/).4 SAVEPOINT NAME
4HEõ#/--)4õANDõ2/,,"!#+õ3TATEMENTS 31, SUPPORTS TWO 31, TRANSACTION PROCESSING STATEMENTS FOR EXPLICITLY ENDING TRANSACTIONS SHOWN IN &IGURE /PTIONS INCLUDE THE FOLLOWING s 7/2+ 4HIS KEYWORD HAS NO EFFECT BUT IS INCLUDED IN THE STANDARD FOR COMPATIBILITY WITH SOME 31, IMPLEMENTATIONS THAT REQUIRE IT s !.$ ;./= #(!). 3PECIFIES WHETHER A NEW TRANSACTION IS TO BE AUTOMATICALLY STARTED WITH THE SAME PROPERTIES AS THE ONE THAT JUST ENDED !S OF THIS WRITING THIS OPTION IS NOT SUPPORTED BY /RACLE 31, 3ERVER $" 5$" OR -Y31, s 4/ 3!6%0/).4 &OR THE 2/,,"!#+ STATEMENT ONLY THIS OPTION SPECIFIES ROLLBACK TO A SAVEPOINT THAT WAS PREVIOUSLY CREATED WITHIN THE TRANSACTION INSTEAD OF TO THE BEGINNING OF THE TRANSACTION
#HAPTERçç
4R A N S A C T I O N ç 0 R O C E S S I N G ç
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4HE #/--)4 AND 2/,,"!#+ STATEMENTS ARE EXECUTABLE 31, STATEMENTS JUST LIKE 3%,%#4 ).3%24 50$!4% AND $%,%4% (ERE IS AN EXAMPLE OF A SUCCESSFUL UPDATE TRANSACTION THAT CHANGES THE QUANTITY AND AMOUNT OF AN ORDER AND ADJUSTS THE TOTALS FOR THE PRODUCT SALESPERSON AND OFFICE ASSOCIATED WITH THE ORDER ! CHANGE LIKE THIS WOULD TYPICALLY BE HANDLED BY A FORMS BASED CHANGE ORDER PROGRAM WHICH WOULD USE PROGRAMMATIC 31, TO EXECUTE THE STATEMENTS SHOWN HERE
50$!4% /2$%23 3%4 149 !-/5.4 7(%2% /2$%2?.5- 50$!4% 3!,%32%03 3%4 3!,%3 3!,%3 7(%2% %-0,?.5- 50$!4% /&&)#%3 3%4 3!,%3 3!,%3 7(%2% /&&)#% 50$!4% 02/$5#43 3%4 149?/.?(!.$ 149?/.?(!.$ 7(%2% -&2?)$ g13!g !.$ 02/$5#4?)$ g8+g
CONlRM THE CHANGE ONE LAST TIME WITH THE CUSTOMER #/--)4 7/2+
(ERE IS THE SAME TRANSACTION BUT THIS TIME ASSUME THAT THE USER MAKES AN ERROR ENTERING THE PRODUCT NUMBER 4O CORRECT THE ERROR THE TRANSACTION IS ROLLED BACK SO THAT IT CAN BE REENTERED CORRECTLY #HANGE THE QUANTITY ON ORDER NUMBER FROM TO WHICH RAISES ITS AMOUNT FROM TO 4HE ORDER IS FOR 1!3 8+ REDUCERS AND WAS PLACED WITH ,ARRY &ITCH EMPLOYEE NUMBER WHO WORKS IN ,OS !NGELES OFlCE NUMBER
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50$!4% /2$%23 3%4 149 !-/5.4 7(%2% /2$%2?.5- 50$!4% 3!,%32%03 3%4 3!,%3 3!,%3 7(%2% %-0,?.5- 50$!4% /&&)#%3 3%4 3!,%3 3!,%3 7(%2% /&&)#% 50$!4% 02/$5#43 3%4 149?/.?(!.$ 149?/.?(!.$ 7(%2% -&2?)$ g1!3g !.$ 02/$5#4?)$ g8+g
OOPS THE MANUFACTURER IS h13! v NOT h1!3v 2/,,"!#+ 7/2+
&IGURE SHOWS TYPICAL TRANSACTIONS THAT ILLUSTRATE COMMON CONDITIONS
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#HAPTERçç
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2ECALL THAT THE !.3))3/ 31, STANDARD IS PRIMARILY FOCUSED ON A PROGRAMMATIC 31, LANGUAGE FOR USE IN APPLICATION PROGRAMS 4RANSACTIONS PLAY AN IMPORTANT ROLE IN PROGRAMMATIC 31, BECAUSE EVEN A SIMPLE APPLICATION PROGRAM OFTEN NEEDS TO CARRY OUT A SEQUENCE OF TWO OR THREE 31, STATEMENTS TO ACCOMPLISH ITS TASK "ECAUSE USERS CAN CHANGE THEIR MINDS AND OTHER CONDITIONS CAN OCCUR SUCH AS BEING OUT OF STOCK ON A PRODUCT THAT A CUSTOMER WANTS TO ORDER AN APPLICATION PROGRAM MUST BE ABLE TO PROCEED PARTWAY THROUGH A TRANSACTION AND THEN CHOOSE TO ABORT OR CONTINUE 4HE #/--)4 AND 2/,,"!#+ STATEMENTS PROVIDE PRECISELY THIS CAPABILITY 4HE #/--)4 AND 2/,,"!#+ STATEMENTS CAN ALSO BE USED IN INTERACTIVE 31, BUT IN PRACTICE THEY ARE RARELY SEEN IN THIS CONTEXT )NTERACTIVE 31, IS GENERALLY USED FOR DATABASE QUERIES UPDATES ARE LESS COMMON AND MULTISTATEMENT UPDATES ARE ALMOST NEVER PERFORMED BY TYPING THE STATEMENTS INTO AN INTERACTIVE 31, FACILITY !S A RESULT TRANSACTIONS ARE TYPICALLY A MINOR CONCERN IN INTERACTIVE 31, )N FACT MANY INTERACTIVE 31, PRODUCTS DEFAULT TO AN AUTOCOMMIT MODE WHERE A #/--)4 STATEMENT IS AUTOMATICALLY EXECUTED AFTER EACH 31, STATEMENT TYPED BY THE USER 4HIS EFFECTIVELY MAKES EACH INTERACTIVE 31, STATEMENT ITS OWN TRANSACTION
4HE ALL OR NOTHING COMMITMENT THAT A $"-3 MAKES FOR THE STATEMENTS IN A TRANSACTION SEEMS ALMOST LIKE MAGIC TO A NEW 31, USER (OW CAN THE $"-3 POSSIBLY BACK OUT THE CHANGES MADE TO A DATABASE ESPECIALLY IF A SYSTEM FAILURE OCCURS DURING THE MIDDLE OF A TRANSACTION 4HE ACTUAL TECHNIQUES USED BY BRANDS OF $"-3 VARY BUT ALMOST ALL OF THEM ARE BASED ON A TRANSACTION LOG AS SHOWN IN &IGURE !LTHOUGH THE TERM LOG IS COMMONLY USED SOME $"-3 PRODUCTS USE MORE ELABORATE MECHANISMS TO STORE DATABASE CHANGE INFORMATION NEEDED FOR RECOVERY /RACLE FOR EXAMPLE STORES DATABASE CHANGES IN SPECIAL DATABASE SEGMENTS (ERE IS HOW THE TRANSACTION LOG WORKS IN SIMPLIFIED CONCEPTUAL FORM 7HEN A USER EXECUTES A 31, STATEMENT THAT MODIFIES THE DATABASE THE $"-3 AUTOMATICALLY WRITES A RECORD IN THE TRANSACTION LOG SHOWING TWO COPIES OF EACH ROW AFFECTED BY THE STATEMENT /NE COPY SHOWS THE ROW BEFORE THE CHANGE AND THE OTHER COPY SHOWS THE ROW AFTER THE CHANGE /NLY AFTER THE LOG IS WRITTEN DOES THE $"-3 ACTUALLY MODIFY THE ROW ON THE DISK )F THE USER SUBSEQUENTLY EXECUTES A #/--)4 STATEMENT THE END OF TRANSACTION IS NOTED IN THE TRANSACTION LOG )F THE USER EXECUTES A 2/,,"!#+ STATEMENT THE $"-3 EXAMINES THE LOG TO FIND THE hBEFOREv IMAGES OF THE ROWS THAT HAVE BEEN MODIFIED SINCE THE TRANSACTION BEGAN 5SING THESE IMAGES THE $"-3 RESTORES THE ROWS TO THEIR EARLIER STATE EFFECTIVELY BACKING OUT ALL DATABASE CHANGES MADE DURING THE TRANSACTION )N OLDER DATABASE SYSTEMS WHEN A SYSTEM FAILURE OCCURRED THE SYSTEM OPERATOR TYPICALLY RECOVERED THE DATABASE BY RUNNING A SPECIAL RECOVERY UTILITY SUPPLIED WITH THE $"-3 )N NEWER DATABASE SYSTEMS THE RECOVERY OPERATION NORMALLY RUNS AUTOMATICALLY AT THE FIRST AVAILABLE OPPORTUNITY 4HE RECOVERY UTILITY EXAMINES THE END OF THE TRANSACTION LOG LOOKING FOR TRANSACTIONS THAT WERE NOT COMMITTED BEFORE THE FAILURE 4HE UTILITY ROLLS BACK EACH OF THESE INCOMPLETE TRANSACTIONS SO THAT ONLY COMMITTED TRANSACTIONS ARE REFLECTED IN THE DATABASE TRANSACTIONS IN PROCESS AT THE TIME OF THE FAILURE HAVE BEEN ROLLED BACK 4HE USE OF A TRANSACTION LOG OBVIOUSLY IMPOSES AN OVERHEAD ON UPDATES TO THE DATABASE )N PRACTICE THE MAINSTREAM COMMERCIAL $"-3 PRODUCTS MINIMIZE THIS OVERHEAD BY USING
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MUCH MORE SOPHISTICATED LOGGING TECHNIQUES THAN THE SIMPLE SCHEME DESCRIBED HERE )N ADDITION THE TRANSACTION LOG IS USUALLY STORED ON A DISK STORAGE SYSTEM DIFFERENT FROM THE ONE THAT STORES THE DATABASE TO MINIMIZE DISK ACCESS CONTENTION 3OME $"-3 BRANDS ALLOW YOU TO DISABLE TRANSACTION LOGGING FOR SPECIFIC DATABASE OBJECTS OR FOR PARTICULAR DATABASE OPERATIONS SUCH AS BULK LOADING A TABLE TO INCREASE THE PERFORMANCE OF THE $"-3 3PECIALIZED DATABASES SUCH AS IN MEMORY DATABASES OR CACHED DATABASE COPIES MAY ALSO USE THIS LOG FREE ARCHITECTURE 4HIS MAY ALSO BE AN ACCEPTABLE ALTERNATIVE IN SPECIALIZED PRODUCTION DATABASES FOR EXAMPLE WHERE THE DATABASE CONTENTS ARE REPLICATED ON A DUPLICATE COMPUTER SYSTEM )N MOST COMMON PRODUCTION DATABASES HOWEVER A LOGGING SCHEME AND ITS OVERHEAD ARE AN INTEGRAL PART OF THE DATABASE OPERATION
4RANSACTIONSõANDõ-ULTIUSERõ0ROCESSING 7HEN TWO OR MORE USERS CONCURRENTLY ACCESS A DATABASE TRANSACTION PROCESSING TAKES ON A NEW DIMENSION .OW THE $"-3 MUST NOT ONLY RECOVER PROPERLY FROM SYSTEM FAILURES OR ERRORS BUT IT MUST ALSO ENSURE THAT THE USERS ACTIONS DO NOT INTERFERE WITH ONE ANOTHER )DEALLY EACH USER SHOULD BE ABLE TO ACCESS THE DATABASE AS IF HE OR SHE HAD EXCLUSIVE ACCESS TO IT WITHOUT WORRYING ABOUT THE ACTIONS OF OTHER USERS 4HE 31, TRANSACTION MODEL ALLOWS A 31, BASED $"-3 TO INSULATE USERS FROM ONE ANOTHER IN THIS WAY
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4R A N S A C T I O N ç 0 R O C E S S I N G ç
4HE BEST WAY TO UNDERSTAND HOW 31, HANDLES CONCURRENT TRANSACTIONS IS TO LOOK AT THE PROBLEMS THAT RESULT IF TRANSACTIONS ARE NOT HANDLED PROPERLY !LTHOUGH THEY CAN SHOW UP IN MANY DIFFERENT WAYS FOUR FUNDAMENTAL PROBLEMS CAN OCCUR 4HE NEXT FOUR SECTIONS GIVE A SIMPLE EXAMPLE OF EACH PROBLEM
4HEõ,OSTõ5PDATEõ0ROBLEM &IGURE SHOWS A SIMPLE APPLICATION WHERE TWO USERS ACCEPT TELEPHONE ORDERS FROM CUSTOMERS 4HE ORDER ENTRY PROGRAM CHECKS THE 02/$5#43 TABLE FOR ADEQUATE INVENTORY BEFORE ACCEPTING THE CUSTOMERS ORDER )N THE FIGURE *OE STARTS ENTERING AN ORDER FOR !#) WIDGETS FROM HIS CUSTOMER !T NEARLY THE SAME TIME -ARY STARTS ENTERING HER CUSTOMERS ORDER FOR !#) WIDGETS %ACH ORDER ENTRY PROGRAM DOES A QUERY ON THE 02/$5#43 TABLE AND EACH FINDS THAT WIDGETS ARE IN STOCKMORE THAN ENOUGH TO COVER THE CUSTOMERS REQUEST *OE ASKS HIS CUSTOMER TO CONFIRM THE ORDER AND HIS COPY OF THE ORDER ENTRY PROGRAM UPDATES THE 02/$5#43 TABLE TO SHOW n WIDGETS
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REMAINING FOR SALE AND INSERTS A NEW ORDER FOR WIDGETS INTO THE /2$%23 TABLE ! FEW SECONDS LATER -ARY ASKS HER CUSTOMER TO CONFIRM THE ORDER (ER COPY OF THE ORDER ENTRY PROGRAM UPDATES THE 02/$5#43 TABLE TO SHOW n WIDGETS REMAINING IN STOCK AND INSERTS A NEW ORDER FOR WIDGETS INTO THE /2$%23 TABLE 4HE HANDLING OF THE TWO ORDERS HAS OBVIOUSLY LEFT THE DATABASE IN AN INCONSISTENT STATE 4HE FIRST OF THE TWO UPDATES TO THE 02/$5#43 TABLE HAS BEEN LOST "OTH CUSTOMERS ORDERS HAVE BEEN ACCEPTED BUT NOT ENOUGH WIDGETS ARE IN INVENTORY TO SATISFY BOTH ORDERS &URTHER THE DATABASE SHOWS THAT THERE ARE STILL WIDGETS REMAINING FOR SALE 4HIS EXAMPLE ILLUSTRATES THE LOST UPDATE PROBLEM THAT CAN OCCUR WHENEVER TWO PROGRAMS READ THE SAME DATA FROM THE DATABASE USE THE DATA AS THE BASIS FOR A CALCULATION AND THEN TRY TO UPDATE THE DATA
4HEõ5NCOMMITTEDõ$ATAõ0ROBLEM &IGURE SHOWS THE SAME ORDER PROCESSING APPLICATION AS &IGURE *OE AGAIN BEGINS TAKING AN ORDER FOR !#) WIDGETS FROM HIS CUSTOMER 4HIS TIME *OES COPY OF THE
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4HEõ)NCONSISTENTõ$ATAõ0ROBLEM &IGURE SHOWS THE ORDER PROCESSING APPLICATION ONCE MORE !GAIN *OE BEGINS TAKING AN ORDER FOR !#) WIDGETS FROM HIS CUSTOMER ! SHORT TIME LATER -ARY ALSO BEGINS TALKING TO HER CUSTOMER ABOUT THE SAME WIDGETS AND HER PROGRAM DOES A SINGLE ROW QUERY TO FIND OUT HOW MANY ARE AVAILABLE 4HIS TIME -ARYS CUSTOMER INQUIRES ABOUT THE !#) WIDGETS AS AN ALTERNATIVE AND -ARYS PROGRAM DOES A SINGLE ROW QUERY ON THAT ROW -EANWHILE *OES CUSTOMER DECIDES TO ORDER THE WIDGETS SO HIS PROGRAM UPDATES THAT ROW OF THE DATABASE AND DOES A #/--)4 TO FINALIZE THE ORDER IN THE DATABASE !FTER CONSIDERING THE !#) WIDGETS AS AN ALTERNATIVE -ARYS CUSTOMER DECIDES TO ORDER THE !#) WIDGETS THAT -ARY ORIGINALLY PROPOSED (ER PROGRAM DOES A NEW SINGLE ROW QUERY TO GET THE INFORMATION FOR THE !#) WIDGETS AGAIN "UT INSTEAD OF SHOWING THE WIDGETS THAT WERE IN STOCK JUST A MOMENT AGO THE NEW QUERY SHOWS ONLY IN STOCK )N THIS EXAMPLE UNLIKE THE PRECEDING TWO THE STATUS OF THE DATABASE HAS REMAINED AN ACCURATE MODEL OF THE REAL WORLD SITUATION 4HERE ARE ONLY !#) WIDGETS LEFT BECAUSE *OES CUSTOMER HAS PURCHASED OF THEM 4HERE IS NO PROBLEM WITH -ARY HAVING SEEN UNCOMMITTED DATA FROM *OES PROGRAMTHE ORDER WAS COMPLETE AND COMMITTED TO THE DATABASE (OWEVER FROM THE POINT OF VIEW OF -ARYS PROGRAM THE DATABASE DID NOT REMAIN CONSISTENT DURING HER TRANSACTION !T THE BEGINNING OF THE TRANSACTION A ROW CONTAINED CERTAIN DATA AND LATER IN THE SAME TRANSACTION IT CONTAINED DIFFERENT DATA SO EXTERNAL EVENTS HAVE INTERFERED WITH HER CONSISTENT VIEW OF THE DATABASE 4HIS INCONSISTENCY CAN CAUSE PROBLEMS EVEN IF -ARYS PROGRAM NEVER TRIES TO UPDATE THE DATABASE BASED ON THE RESULTS OF THE FIRST QUERY
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ORDER PROCESSING PROGRAM QUERIES THE 02/$5#43 TABLE FINDS WIDGETS AVAILABLE AND UPDATES THE 02/$5#43 TABLE TO SHOW WIDGETS REMAINING AFTER THE CUSTOMERS ORDER 4HEN *OE BEGINS TO DISCUSS WITH THE CUSTOMER THE RELATIVE MERITS OF THE !#) AND !#) WIDGETS )N THE MEANTIME -ARYS CUSTOMER TRIES TO ORDER !#) WIDGETS -ARYS COPY OF THE ORDER PROCESSING PROGRAM QUERIES THE 02/$5#43 TABLE FINDS ONLY WIDGETS AVAILABLE AND REFUSES THE ORDER )T ALSO GENERATES A NOTICE TELLING THE PURCHASING MANAGER TO BUY MORE !#) WIDGETS WHICH ARE IN GREAT DEMAND .OW *OES CUSTOMER DECIDES NOT TO ORDER THE SIZE WIDGETS AFTER ALL AND *OES ORDER ENTRY PROGRAM DOES A 2/,,"!#+ TO ABORT ITS TRANSACTION "ECAUSE -ARYS ORDER PROCESSING PROGRAM WAS ALLOWED TO SEE THE UNCOMMITTED UPDATE OF *OES PROGRAM THE ORDER FROM -ARYS CUSTOMER WAS REFUSED AND THE PURCHASING MANAGER WILL ORDER MORE WIDGETS EVEN THOUGH OF THEM ARE STILL IN STOCK 4HE SITUATION WOULD HAVE BEEN EVEN WORSE IF -ARYS CUSTOMER HAD DECIDED TO SETTLE FOR THE AVAILABLE WIDGETS )N THIS CASE -ARYS PROGRAM WOULD HAVE UPDATED THE 02/$5#43 TABLE TO SHOW ZERO UNITS AVAILABLE "UT WHEN THE 2/,,"!#+ OF *OES TRANSACTION OCCURRED THE $"-3 WOULD HAVE SET THE AVAILABLE INVENTORY BACK TO WIDGETS EVEN THOUGH OF THEM ARE COMMITTED TO -ARYS CUSTOMER 4HE PROBLEM IN THIS EXAMPLE IS THAT -ARYS PROGRAM HAS BEEN ALLOWED TO SEE THE UNCOMMITTED UPDATES FROM *OES PROGRAM AND HAS ACTED ON THEM PRODUCING THE ERRONEOUS RESULTS 4HE 31, STANDARD REFERS TO THIS AS PROBLEM 0 ALSO KNOWN AS THE DIRTY READ PROBLEM )N THE PARLANCE OF THE STANDARD THE DATA THAT -ARYS PROGRAM HAS SEEN IS DIRTY BECAUSE IT HAS NOT BEEN COMMITTED BY *OES PROGRAM
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&OR EXAMPLE IF THE PROGRAM IS ACCUMULATING TOTALS OR CALCULATING STATISTICS IT CANNOT BE SURE THAT THE STATISTICS REFLECT A STABLE CONSISTENT VIEW OF THE DATA 4HE PROBLEM IN THIS CASE IS THAT -ARYS PROGRAM HAS BEEN ALLOWED TO SEE COMMITTED UPDATES FROM *OES PROGRAM THAT AFFECT ROWS THAT -ARYS PROGRAM HAS ALREADY EXAMINED 4HE 31, STANDARD REFERS TO THIS PROBLEM AS 0 ALSO KNOWN AS THE NONREPEATABLE READ PROBLEM 4HE NAME COMES FROM THE FACT THAT -ARYS PROGRAM CANT REPEAT THE SAME READ ACCESS TO THE DATABASE AND OBTAIN THE SAME RESULTS
4HEõ0HANTOMõ)NSERTõ0ROBLEM &IGURE SHOWS AN ORDER PROCESSING APPLICATION ONCE MORE 4HIS TIME THE SALES MANAGER RUNS A REPORT PROGRAM THAT SCANS THE /2$%23 TABLE PRINTING A LIST OF THE ORDERS FROM CUSTOMERS OF "ILL !DAMS AND COMPUTING THEIR TOTAL )N THE MEANTIME A CUSTOMER CALLS "ILL TO PLACE AN ADDITIONAL ORDER FOR 4HE ORDER IS INSERTED INTO THE DATABASE AND THE TRANSACTION IS COMMITTED ! SHORT TIME LATER THE SALES MANAGERS PROGRAM STILL OPERATING WITHIN ITS INITIAL TRANSACTION AGAIN SCANS THE /2$%23 TABLE RUNNING THE VERY SAME QUERY 4HIS TIME THERE IS AN ADDITIONAL ORDER AND THE TOTAL IS HIGHER THAN FOR THE FIRST QUERY
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!S IN THE PREVIOUS EXAMPLE THE PROBLEM HERE IS INCONSISTENT DATA 4HE DATABASE REMAINS AN ACCURATE MODEL OF THE REAL WORLD SITUATION AND ITS INTEGRITY IS INTACT BUT THE SAME QUERY EXECUTED TWICE DURING THE SAME TRANSACTION YIELDED TWO DIFFERENT RESULTS )N THE PREVIOUS EXAMPLE THE QUERY WAS A SINGLE ROW QUERY AND THE INCONSISTENCY IN THE DATA WAS CAUSED BY A COMMITTED 50$!4% STATEMENT ! COMMITTED $%,%4% STATEMENT COULD CAUSE THE SAME KIND OF PROBLEM )N THE EXAMPLE OF &IGURE THE PROBLEM IS CAUSED BY A COMMITTED ).3%24 STATEMENT 4HE ADDITIONAL ROW DID NOT PARTICIPATE IN THE FIRST QUERY BUT IT SHOWS UP AS A PHANTOM ROW OUT OF NOWHERE IN THE SECOND QUERY !S WITH THE INCONSISTENT DATA PROBLEM THE CONSEQUENCES OF THE PHANTOM INSERT PROBLEM CAN BE INCONSISTENT AND INCORRECT CALCULATIONS 4HE 31, STANDARD REFERS TO THIS AS 0 AND ALSO USES THE NAME PHANTOM TO DESCRIBE IT
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#ONCURRENTõ4RANSACTIONS !S THE THREE MULTIUSER UPDATE EXAMPLES SHOW WHEN USERS SHARE ACCESS TO A DATABASE AND ONE OR MORE USERS IS UPDATING DATA THERE IS A POTENTIAL FOR DATABASE CORRUPTION 31, USES ITS TRANSACTION MECHANISM TO ELIMINATE THIS SOURCE OF DATABASE CORRUPTION )N ADDITION TO THE ALL OR NOTHING COMMITMENT FOR THE STATEMENTS IN A TRANSACTION A 31, BASED $"-3 MAKES THIS COMMITMENT ABOUT TRANSACTIONS $URING A TRANSACTION THE USER WILL SEE A COMPLETELY CONSISTENT VIEW OF THE DATABASE 4HE USER WILL NEVER SEE THE UNCOMMITTED CHANGES OF OTHER USERS AND EVEN COMMITTED CHANGES MADE BY OTHERS WILL NOT AFFECT DATA SEEN BY THE USER IN MID TRANSACTION 4RANSACTIONS ARE THUS THE KEY TO BOTH RECOVERY AND CONCURRENCY CONTROL IN A 31, DATABASE 4HE PRECEDING COMMITMENT CAN BE RESTATED EXPLICITLY IN TERMS OF CONCURRENT TRANSACTION EXECUTION )F TWO TRANSACTIONS ! AND " ARE EXECUTING CONCURRENTLY THE $"-3 ENSURES THAT THE RESULTS WILL BE THE SAME AS THEY WOULD BE IF EITHER A 4RANSACTION ! WERE EXECUTED lRST FOLLOWED BY 4RANSACTION " OR B 4RANSACTION " WERE EXECUTED lRST FOLLOWED BY 4RANSACTION ! 4HIS CONCEPT IS KNOWN AS THE SERIALIZABILITY OF TRANSACTIONS %FFECTIVELY IT MEANS THAT EACH DATABASE USER CAN ACCESS THE DATABASE AS IF NO OTHER USERS WERE CONCURRENTLY ACCESSING THE DATABASE )N PRACTICE DOZENS OR HUNDREDS OF TRANSACTIONS MAY BE CONCURRENTLY EXECUTING WITHIN A LARGE PRODUCTION DATABASE 4HE SERIALIZABILITY CONCEPT CAN BE DIRECTLY EXTENDED TO COVER THIS SITUATION 3ERIALIZABILITY GUARANTEES THAT IF SOME NUMBER . CONCURRENT TRANSACTIONS ARE EXECUTING THE $"-3 MUST ENSURE THAT ITS RESULTS ARE THE SAME AS IF THEY HAD BEEN EXECUTED IN SOME SEQUENCE ONE AT A TIME 4HE CONCEPT DOES NOT SPECIFY WHICH SEQUENCE OF TRANSACTIONS MUST BE USED ONLY THAT THE RESULTS MUST MATCH THE RESULTS OF SOME SEQUENCE 4HE FACT THAT A $"-3 INSULATES YOU FROM THE ACTIONS OF OTHER CONCURRENT USERS DOESNT MEAN HOWEVER THAT YOU CAN FORGET ALL ABOUT THE OTHER USERS )N FACT THE SITUATION IS QUITE THE OPPOSITE "ECAUSE OTHER USERS WANT TO CONCURRENTLY UPDATE THE DATABASE YOU SHOULD KEEP YOUR TRANSACTIONS AS SHORT AND SIMPLE AS POSSIBLE TO MAXIMIZE THE AMOUNT OF PARALLEL PROCESSING THAT CAN OCCUR 3UPPOSE FOR EXAMPLE THAT YOU RUN A PROGRAM THAT PERFORMS A SEQUENCE OF THREE LARGE QUERIES 3INCE THE PROGRAM DOESNT UPDATE THE DATABASE IT MIGHT SEEM THAT IT DOESNT NEED TO WORRY ABOUT TRANSACTIONS )T CERTAINLY SEEMS UNNECESSARY TO USE #/--)4 STATEMENTS "UT IN FACT IF THE CURRENT SESSION IS IN IMPLICIT TRANSACTION MODE THE PROGRAM SHOULD USE A #/--)4 STATEMENT AFTER EACH QUERY 7HY 2ECALL THAT 31, IN IMPLICIT TRANSACTION MODE AUTOMATICALLY BEGINS A TRANSACTION WITH THE FIRST 31, STATEMENT IN A PROGRAM 7ITHOUT A #/--)4 STATEMENT THE TRANSACTION CONTINUES UNTIL THE PROGRAM ENDS &URTHER 31, GUARANTEES THAT THE DATA RETRIEVED DURING A TRANSACTION WILL BE SELF CONSISTENT UNAFFECTED BY OTHER USERS TRANSACTIONS 4HIS MEANS THAT ONCE YOUR PROGRAM RETRIEVES A ROW FROM THE DATABASE NO OTHER USER CAN MODIFY THE ROW UNTIL YOUR TRANSACTION ENDS BECAUSE YOU MIGHT TRY TO RETRIEVE THE ROW AGAIN LATER IN YOUR TRANSACTION AND THE $"-3 MUST GUARANTEE THAT YOU WILL SEE THE SAME DATA 4HUS AS YOUR PROGRAM PERFORMS ITS THREE QUERIES IT WILL PREVENT OTHER USERS FROM UPDATING LARGER AND LARGER PORTIONS OF THE DATABASE 4HE MORAL OF THIS EXAMPLE IS SIMPLE YOU MUST ALWAYS WORRY ABOUT TRANSACTIONS WHEN WRITING PROGRAMS FOR A PRODUCTION 31, DATABASE 4RANSACTIONS SHOULD ALWAYS BE AS SHORT AS POSSIBLE h#/--)4 EARLY AND #/--)4 OFTENv IS GOOD ADVICE WHEN YOU ARE USING
#HAPTERçç
4R A N S A C T I O N ç 0 R O C E S S I N G ç
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-OST MAJOR $"-3 PRODUCTS USE SOPHISTICATED LOCKING TECHNIQUES TO HANDLE CONCURRENT 31, TRANSACTIONS FOR MANY SIMULTANEOUS USERS (OWEVER THE BASIC CONCEPTS BEHIND LOCKING AND TRANSACTIONS ARE VERY SIMPLE &IGURE SHOWS A SIMPLE LOCKING SCHEME AND HOW IT HANDLES CONTENTION BETWEEN TWO CONCURRENT TRANSACTIONS !S 4RANSACTION ! IN THE FIGURE ACCESSES THE DATABASE THE $"-3 AUTOMATICALLY LOCKS EACH PIECE OF THE DATABASE THAT THE TRANSACTION RETRIEVES OR MODIFIES 4RANSACTION " PROCEEDS IN PARALLEL AND THE $"-3 ALSO LOCKS THE PIECES OF THE DATABASE THAT IT ACCESSES )F 4RANSACTION " TRIES TO ACCESS PART OF THE DATABASE THAT HAS BEEN LOCKED BY 4RANSACTION ! THE $"-3 BLOCKS 4RANSACTION " CAUSING IT TO WAIT FOR THE DATA TO BE UNLOCKED 4HE $"-3 RELEASES THE LOCKS HELD BY 4RANSACTION ! ONLY WHEN IT ENDS IN A #/--)4 OR 2/,,"!#+ OPERATION 4HE $"-3 THEN UNBLOCKS 4RANSACTION " ALLOWING IT TO PROCEED 4RANSACTION " CAN NOW LOCK THAT PIECE OF THE DATABASE ON ITS OWN BEHALF PROTECTING IT FROM THE EFFECTS OF OTHER TRANSACTIONS !S THE FIGURE SHOWS THE LOCKING TECHNIQUE TEMPORARILY GIVES A TRANSACTION EXCLUSIVE ACCESS TO A PIECE OF A DATABASE PREVENTING OTHER TRANSACTIONS FROM MODIFYING THE LOCKED DATA ,OCKING THUS SOLVES ALL OF THE CONCURRENT TRANSACTION PROBLEMS )T PREVENTS LOST UPDATES UNCOMMITTED DATA AND INCONSISTENT DATA FROM CORRUPTING THE DATABASE (OWEVER LOCKING INTRODUCES A NEW PROBLEMIT MAY CAUSE A TRANSACTION TO WAIT FOR A VERY LONG TIME WHILE THE PIECES OF THE DATABASE THAT IT WANTS TO ACCESS ARE LOCKED BY OTHER TRANSACTIONS
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PROGRAMMATIC 31, !LSO KEEP IN MIND THAT THERE IS GREAT VARIETY IN THE WAY $"-3 PRODUCTS HANDLE TRANSACTIONS SO ALWAYS CONSULT YOUR PRODUCT DOCUMENTATION )N PRACTICE IMPLEMENTING A STRICT MULTIUSER TRANSACTION MODEL CAN IMPOSE A SUBSTANTIAL OVERHEAD ON THE OPERATION OF A DATABASE WITH DOZENS HUNDREDS OR THOUSANDS OF CONCURRENT USERS )N ADDITION THE SPECIFICS OF THE APPLICATION MAY NOT REQUIRE THE ABSOLUTE ISOLATION AMONG THE USER PROGRAMS THAT THE 31, TRANSACTION MODEL IMPLIES &OR EXAMPLE MAYBE THE APPLICATION DESIGNER KNOWS THAT AN ORDER INQUIRY PROGRAM HAS BEEN DESIGNED SO THAT IT WILL NEVER ATTEMPT TO READ AND THEN REREAD A ROW OF THE DATABASE DURING A SINGLE TRANSACTION )N THIS CASE THE INCONSISTENT DATA PROBLEM CANT OCCUR BECAUSE OF THE PROGRAM STRUCTURE !LTERNATIVELY MAYBE THE APPLICATION DESIGNER KNOWS THAT ALL OF A PROGRAMS ACCESS TO PARTICULAR TABLES OF A DATABASE IS READ ONLY )F THE PROGRAMMER CAN CONVEY INFORMATION LIKE THIS TO THE $"-3 SOME OF THE OVERHEAD OF 31, TRANSACTIONS CAN BE ELIMINATED 4HE ORIGINAL 31, STANDARD DID NOT ADDRESS THIS DATABASE PERFORMANCE ISSUE AND MOST OF THE MAJOR $"-3 BRANDS IMPLEMENTED PROPRIETARY SCHEMES FOR ENHANCING THE PERFORMANCE OF 31, TRANSACTIONS 4HE 31, STANDARD SPECIFIED A NEW 3%4 42!.3!#4)/. STATEMENT AND THE 31, STANDARD INTRODUCED A NEW 34!24 42!.3!#4)/. STATEMENT BOTH SHOWN IN &IGURE WHOSE FUNCTION IS TO SPECIFY THE LEVEL OF 31, TRANSACTION MODEL SUPPORT THAT AN APPLICATION NEEDS 9OU DONT NEED THE 3%4 42!.3!#4)/. OR 34!24 42!.3!#4)/. STATEMENTS FOR CASUAL USE OF 31, OR FOR RELATIVELY SIMPLE OR LOW VOLUME 31, TRANSACTION PROCESSING 4O FULLY UNDERSTAND ITS OPERATION ITS USEFUL TO UNDERSTAND THE LOCKING AND OTHER TECHNIQUES USED BY COMMERCIAL $"-3 PRODUCTS TO IMPLEMENT MULTIUSER 31, TRANSACTIONS 4HE REMAINDER OF THIS CHAPTER DISCUSSES LOCKING THE PERFORMANCE OPTIMIZING CAPABILITIES OF 31, AND THE VARIOUS $"-3 BRANDS THAT DEPEND ON IT
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TRANSACTIONS SUCH AS THOSE THAT MODIFY THE STRUCTURE OF THE DATABASE OR FOR COMPLEX QUERIES THAT MUST SEQUENTIALLY SCAN MANY LARGE TABLES )N THESE CASES IT MAY BE MORE EFFICIENT TO RAPIDLY DO A SINGLE LOCKING OPERATION QUICKLY EXECUTE THE DATABASE OPERATION AND THEN QUICKLY UNLOCK THE DATABASE THAN TO INDIVIDUALLY LOCK DOZENS OF TABLES !N ENHANCED FORM OF LOCKING IS TABLE LEVEL LOCKING )N THIS SCHEME THE $"-3 LOCKS ONLY THE TABLES ACCESSED BY A TRANSACTION /THER TRANSACTIONS CAN CONCURRENTLY ACCESS OTHER TABLES 4HIS TECHNIQUE PERMITS MORE PARALLEL PROCESSING BUT CAN STILL LEAD TO UNACCEPTABLY SLOW PERFORMANCE IN APPLICATIONS SUCH AS ORDER ENTRY WHERE MANY USERS MUST SHARE ACCESS TO THE SAME TABLE OR TABLES -ANY OLDER $"-3 PRODUCTS IMPLEMENT LOCKING AT THE PAGE LEVEL )N THIS SCHEME THE $"-3 LOCKS INDIVIDUAL BLOCKS OF DATA PAGES FROM THE DISK AS THEY ARE ACCESSED BY A TRANSACTION /THER TRANSACTIONS ARE PREVENTED FROM ACCESSING THE LOCKED PAGES BUT MAY ACCESS AND LOCK FOR THEMSELVES OTHER PAGES OF DATA 0AGE SIZES OF +" +" AND +" ARE COMMONLY USED 3INCE A LARGE TABLE WILL BE SPREAD OUT OVER HUNDREDS OR THOUSANDS OF PAGES TWO TRANSACTIONS TRYING TO ACCESS TWO DIFFERENT ROWS OF A TABLE WILL USUALLY BE ACCESSING TWO DIFFERENT PAGES ALLOWING THE TWO TRANSACTIONS TO PROCEED IN PARALLEL (OWEVER TABLES WITH SHORT ROWS INCREASE THE ODDS THAT INDIVIDUAL ROWS NEEDED BY DIFFERENT TRANSACTIONS WILL HAPPEN TO BE IN THE SAME PAGE /VER THE LAST DECADE MOST OF THE MAJOR COMMERCIAL $"-3 SYSTEMS HAVE MOVED BEYOND PAGE LEVEL LOCKING TO ROW LEVEL LOCKS 2OW LEVEL LOCKING ALLOWS TWO CONCURRENT TRANSACTIONS THAT ACCESS TWO DIFFERENT ROWS OF A TABLE TO PROCEED IN PARALLEL EVEN IF THE TWO ROWS FALL IN THE SAME DISK BLOCK 7HILE THIS MAY SEEM A REMOTE POSSIBILITY IT CAN BE A REAL PROBLEM WITH SMALL TABLES CONTAINING SMALL RECORDS SUCH AS THE /&&)#%3 TABLE IN THE SAMPLE DATABASE 2OW LEVEL LOCKING PROVIDES A HIGH DEGREE OF PARALLEL TRANSACTION EXECUTION 5NFORTUNATELY KEEPING TRACK OF LOCKS ON VARIABLE LENGTH PIECES OF THE DATABASE IN OTHER WORDS ROWS RATHER THAN FIXED SIZE PAGES IS A MUCH MORE COMPLEX TASK SO INCREASED PARALLELISM COMES AT THE COST OF MORE SOPHISTICATED LOCKING LOGIC AND INCREASED OVERHEAD )N FACT FOR CERTAIN TRANSACTIONS OR APPLICATIONS THE OVERHEAD OF ROW LEVEL LOCKING MIGHT BE GREATER THAN THE PERFORMANCE GAINS OF PERMITTING MORE PARALLEL OPERATION WITHIN THE DATABASE 3OME $"-3 PRODUCTS ADDRESS THIS SITUATION BY AUTOMATICALLY PROMOTING MANY INDIVIDUAL ROW LEVEL LOCKS INTO A PAGE LEVEL OR TABLE LEVEL LOCK WHEN THE NUMBER OF ROW LEVEL LOCKS FOR A GIVEN TRANSACTION RISES ABOVE A CERTAIN LIMIT )TS NOT ALWAYS THE CASE THAT A MORE GRANULAR SMALLER LEVEL OF LOCK IMPLEMENTATION IS BETTER THE BEST SCHEME HEAVILY DEPENDS ON THE SPECIFIC TRANSACTIONS AND THE 31, OPERATIONS THAT THEY CONTAIN )TS THEORETICALLY POSSIBLE TO MOVE BEYOND ROW LEVEL LOCKING TO LOCKING AT THE INDIVIDUAL DATA ITEM LEVEL )N THEORY THIS WOULD PROVIDE EVEN MORE PARALLELISM THAN ROW LEVEL LOCKS BECAUSE IT WOULD ALLOW CONCURRENT ACCESS TO THE SAME ROW BY TWO DIFFERENT TRANSACTIONS PROVIDED THEY WERE ACCESSING DIFFERENT SETS OF COLUMNS 4HE OVERHEAD IN MANAGING ITEM LEVEL LOCKING HOWEVER HAS THUS FAR OUTWEIGHED ITS POTENTIAL ADVANTAGES .O COMMERCIAL 31, $"-3 USES ITEM LEVEL LOCKING )N FACT LOCKING IS AN AREA OF CONSIDERABLE RESEARCH IN DATABASE TECHNOLOGY AND THE LOCKING SCHEMES USED IN COMMERCIAL $"-3 PRODUCTS ARE MUCH MORE SOPHISTICATED THAN THE FUNDAMENTAL SCHEME DESCRIBED HERE 4HE MOST STRAIGHTFORWARD OF THESE ADVANCED LOCKING SCHEMES USING SHARED AND EXCLUSIVE LOCKS IS DESCRIBED IN THE NEXT SECTION
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3HAREDõANDõ%XCLUSIVEõ,OCKS 4O INCREASE CONCURRENT ACCESS TO A DATABASE MOST COMMERCIAL $"-3 PRODUCTS USE A LOCKING SCHEME WITH MORE THAN ONE TYPE OF LOCK ! SCHEME USING SHARED AND EXCLUSIVE LOCKS IS QUITE COMMON s 3HARED LOCK 5SED BY THE $"-3 WHEN A TRANSACTION WANTS TO READ DATA FROM THE DATABASE !NOTHER CONCURRENT TRANSACTION CAN ALSO ACQUIRE A SHARED LOCK ON THE SAME DATA ALLOWING THE OTHER TRANSACTION TO ALSO READ THE DATA s %XCLUSIVE LOCK 5SED BY THE $"-3 WHEN A TRANSACTION WANTS TO UPDATE DATA IN THE DATABASE 7HEN A TRANSACTION HAS AN EXCLUSIVE LOCK ON SOME DATA OTHER TRANSACTIONS CANNOT ACQUIRE ANY TYPE OF LOCK SHARED OR EXCLUSIVE ON THE DATA &IGURE SHOWS THE RULES FOR THIS LOCKING SCHEME AND THE PERMITTED COMBINATIONS OF LOCKS THAT CAN BE HELD BY TWO CONCURRENT TRANSACTIONS .OTE THAT A TRANSACTION CAN ACQUIRE AN EXCLUSIVE LOCK ONLY IF NO OTHER TRANSACTION CURRENTLY HAS A SHARED OR AN EXCLUSIVE LOCK ON THE DATA )F A TRANSACTION TRIES TO ACQUIRE A LOCK NOT PERMITTED BY THE RULES IN &IGURE IT IS BLOCKED UNTIL OTHER TRANSACTIONS UNLOCK THE DATA THAT IT REQUIRES &IGURE SHOWS THE SAME TRANSACTIONS SHOWN IN &IGURE THIS TIME USING SHARED AND EXCLUSIVE LOCKS )F YOU COMPARE THE TWO FIGURES YOU CAN SEE HOW THE NEW LOCKING SCHEME IMPROVES CONCURRENT ACCESS TO THE DATABASE -ATURE AND COMPLEX $"-3 PRODUCTS SUCH AS $" HAVE MORE THAN TWO TYPES OF LOCKS AND USE DIFFERENT LOCKING TECHNIQUES AT DIFFERENT LEVELS OF THE DATABASE $ESPITE THE INCREASED COMPLEXITY THE GOAL OF THE LOCKING SCHEME REMAINS THE SAME TO PREVENT UNWANTED INTERFERENCE BETWEEN TRANSACTIONS WHILE PROVIDING THE GREATEST POSSIBLE CONCURRENT ACCESS TO THE DATABASE ALL WITH MINIMAL LOCKING OVERHEAD
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5NFORTUNATELY THE USE OF ANY LOCKING SCHEME TO SUPPORT CONCURRENT 31, TRANSACTIONS LEADS TO A PROBLEM CALLED A DEADLOCK &IGURE ILLUSTRATES A DEADLOCK SITUATION 0ROGRAM ! UPDATES THE /2$%23 TABLE THEREBY LOCKING PART OF IT -EANWHILE 0ROGRAM " UPDATES THE 02/$5#43 TABLE LOCKING PART OF IT .OW 0ROGRAM ! TRIES TO UPDATE THE 02/$5#43 TABLE AND 0ROGRAM " TRIES TO UPDATE THE /2$%23 TABLE IN EACH CASE TRYING TO UPDATE A PART OF THE TABLE THAT HAS BEEN PREVIOUSLY LOCKED BY THE OTHER PROGRAM THE SAME ROW OR THE SAME PAGE DEPENDING ON THE TYPE OF LOCKING IMPLEMENTED 7ITHOUT $"-3 OR OUTSIDE INTERVENTION
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EACH PROGRAM WILL WAIT FOREVER FOR THE OTHER PROGRAM TO COMMIT OR ROLL BACK ITS TRANSACTION UNLOCKING THE DATA 4HE SITUATION IN THE FIGURE IS A SIMPLE DEADLOCK BETWEEN TWO PROGRAMS BUT MORE COMPLEX SITUATIONS CAN OCCUR WHERE THREE FOUR OR MORE PROGRAMS ARE IN A CYCLE OF LOCKS EACH WAITING FOR DATA THAT IS LOCKED BY ONE OF THE OTHER PROGRAMS 4O DEAL WITH DEADLOCKS A $"-3 TYPICALLY INCLUDES LOGIC THAT PERIODICALLY FOR EXAMPLE ONCE EVERY FIVE SECONDS CHECKS THE LOCKS HELD BY VARIOUS TRANSACTIONS 7HEN IT DETECTS A DEADLOCK THE $"-3 CHOOSES ONE OF THE TRANSACTIONS AS THE DEADLOCK LOSER AND ROLLS BACK THE TRANSACTION 4HIS FREES THE LOCKS HELD BY THE LOSING TRANSACTION ALLOWING THE DEADLOCK WINNER TO PROCEED 4HE LOSING PROGRAM RECEIVES AN ERROR CODE INFORMING IT THAT IT HAS LOST A DEADLOCK AND THAT ITS CURRENT TRANSACTION HAS BEEN ROLLED BACK
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4HIS SCHEME FOR BREAKING DEADLOCKS MEANS THAT ANY 31, STATEMENT CAN POTENTIALLY RETURN A DEADLOCK LOSER ERROR CODE EVEN IF NOTHING IS WRONG WITH THE STATEMENT PER SE 4HUS EVEN THOUGH #/--)4 AND 2/,,"!#+ ARE THE 31, TRANSACTION PROCESSING STATEMENTS ITS POSSIBLE FOR OTHER 31, STATEMENTSAN ).3%24 STATEMENT FOR EXAMPLE OR EVEN A 3%,%#4 STATEMENTTO BE A DEADLOCK LOSER 4HE TRANSACTION ATTEMPTING THE STATEMENT IS ROLLED BACK THROUGH NO FAULT OF ITS OWN BUT BECAUSE OF OTHER CONCURRENT ACTIVITY IN THE DATABASE 4HIS MAY SEEM UNFAIR BUT IN PRACTICE ITS MUCH BETTER THAN THE OTHER TWO ALTERNATIVESETERNAL DEADLOCK OR DATABASE CORRUPTION )F A DEADLOCK LOSER ERROR OCCURS IN INTERACTIVE 31, THE USER
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CAN SIMPLY RETYPE THE 31, STATEMENTS )N PROGRAMMATIC 31, THE APPLICATION PROGRAM MUST BE PREPARED TO HANDLE THE DEADLOCK LOSER ERROR CODE 4YPICALLY THE PROGRAM WILL RESPOND BY EITHER ALERTING THE USER OR AUTOMATICALLY RETRYING THE TRANSACTION 4HE PROBABILITY OF DEADLOCKS CAN BE DRAMATICALLY REDUCED BY CAREFULLY PLANNING DATABASE UPDATES !LL PROGRAMS THAT UPDATE MULTIPLE TABLES DURING A TRANSACTION SHOULD WHENEVER POSSIBLE UPDATE THE TABLES IN THE SAME SEQUENCE 4HIS ALLOWS THE LOCKS TO FLOW SMOOTHLY ACROSS THE TABLES MINIMIZING THE POSSIBILITY OF DEADLOCKS )N ADDITION SOME OF THE ADVANCED LOCKING FEATURES DESCRIBED IN LATER SECTIONS OF THIS CHAPTER CAN BE USED TO FURTHER REDUCE THE NUMBER OF DEADLOCKS THAT OCCUR
!DVANCEDõ,OCKINGõ4ECHNIQUES
-ANY COMMERCIAL DATABASE PRODUCTS OFFER ADVANCED LOCKING FACILITIES THAT GO WELL BEYOND THOSE PROVIDED BY STANDARD 31, TRANSACTIONS 4HESE INCLUDE s %XPLICIT LOCKING ! PROGRAM CAN EXPLICITLY LOCK AN ENTIRE TABLE OR SOME OTHER PART OF THE DATABASE IF IT WILL BE REPEATEDLY ACCESSED BY THE PROGRAM
s ,OCKING PARAMETERS 4HE DATABASE ADMINISTRATOR CAN MANUALLY ADJUST THE SIZE OF THE LOCKABLE PIECE OF THE DATABASE AND OTHER LOCKING PARAMETERS TO TUNE LOCKING PERFORMANCE 4HESE FACILITIES TEND TO BE NONSTANDARD AND PRODUCT SPECIFIC (OWEVER SEVERAL OF THEM PARTICULARLY THOSE INITIALLY INTRODUCED IN MAINFRAME VERSIONS OF $" YEARS AGO HAVE BEEN IMPLEMENTED IN SEVERAL COMMERCIAL 31, PRODUCTS AND HAVE ACHIEVED THE STATUS OF COMMON IF NOT STANDARD FEATURES )N FACT THE ISOLATION LEVEL CAPABILITIES INTRODUCED IN $" HAVE FOUND THEIR WAY INTO THE 31, STANDARD
%XPLICITõ,OCKING
)F A TRANSACTION REPEATEDLY ACCESSES A TABLE THE OVERHEAD OF ACQUIRING SMALL LOCKS ON MANY PARTS OF THE TABLE CAN BE VERY SUBSTANTIAL ! BULK UPDATE PROGRAM THAT WALKS THROUGH EVERY ROW OF A TABLE FOR EXAMPLE WILL LOCK THE ENTIRE TABLE PIECE BY PIECE AS IT PROCEEDS &OR THIS TYPE OF TRANSACTION THE PROGRAM SHOULD EXPLICITLY LOCK THE ENTIRE TABLE PROCESS THE UPDATES AND THEN UNLOCK THE TABLE ,OCKING THE ENTIRE TABLE HAS THREE ADVANTAGES s )T ELIMINATES THE OVERHEAD OF ROW BY ROW OR PAGE BY PAGE LOCKING s )T ELIMINATES THE POSSIBILITY THAT ANOTHER TRANSACTION WILL LOCK PART OF THE TABLE FORCING THE BULK UPDATE TRANSACTION TO WAIT s )T ELIMINATES THE POSSIBILITY THAT ANOTHER TRANSACTION WILL LOCK PART OF THE TABLE AND DEADLOCK THE BULK UPDATE TRANSACTION FORCING IT TO BE RESTARTED /F COURSE LOCKING THE TABLE HAS THE DISADVANTAGE THAT ALL OTHER TRANSACTIONS ATTEMPTING TO ACCESS THE TABLE MUST WAIT WHILE THE UPDATE IS IN PROCESS (OWEVER BECAUSE THE BULK UPDATE TRANSACTION CAN PROCEED MUCH MORE QUICKLY THE OVERALL THROUGHPUT OF THE $"-3 CAN BE INCREASED BY EXPLICITLY LOCKING THE TABLE
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s )SOLATION LEVELS 9OU CAN TELL THE $"-3 THAT A SPECIFIC PROGRAM WILL NOT RE RETRIEVE DATA DURING A TRANSACTION ALLOWING THE $"-3 TO RELEASE LOCKS BEFORE THE TRANSACTION ENDS
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)N THE )"- DATABASES THE ,/#+ 4!",% STATEMENT SHOWN IN &IGURE IS USED TO EXPLICITLY LOCK AN ENTIRE TABLE )T OFFERS TWO LOCKING MODES s %8#,53)6% MODE ACQUIRES AN EXCLUSIVE LOCK ON THE ENTIRE TABLE .O OTHER TRANSACTION CAN ACCESS ANY PART OF THE TABLE FOR ANY PURPOSE WHILE THE LOCK IS HELD 4HIS IS THE MODE YOU WOULD REQUEST FOR A BULK UPDATE TRANSACTION s 3(!2% MODE ACQUIRES A SHARED LOCK ON THE ENTIRE TABLE /THER TRANSACTIONS CAN READ PARTS OF THE TABLE THAT IS THEY CAN ALSO ACQUIRE SHARED LOCKS BUT THEY CANNOT UPDATE ANY PART OF IT /F COURSE IF THE TRANSACTION ISSUING THE ,/#+ 4!",% STATEMENT NOW UPDATES PART OF THE TABLE IT WILL STILL INCUR THE OVERHEAD OF ACQUIRING EXCLUSIVE LOCKS ON THE PARTS OF THE TABLE THAT IT UPDATES 4HIS IS THE MODE YOU WOULD REQUEST IF YOU WANTED A SNAPSHOT OF A TABLE ACCURATE AT A PARTICULAR POINT IN TIME /RACLE ALSO SUPPORTS A $" STYLE ,/#+ 4!",% STATEMENT AND -Y31, SUPPORTS SIMILAR CAPABILITY WITH ,/#+ 4!",%3 AND 5.,/#+ 4!",%3 STATEMENTS 3EVERAL OTHER DATABASE MANAGEMENT SYSTEMS SUCH AS 31, 3ERVER DO NOT SUPPORT EXPLICIT LOCKING AT ALL CHOOSING INSTEAD TO OPTIMIZE THEIR IMPLICIT LOCKING TECHNIQUES
)SOLATIONõ,EVELS
5NDER THE STRICT DEFINITION OF A 31, TRANSACTION NO ACTION BY A CONCURRENTLY EXECUTING TRANSACTION IS ALLOWED TO IMPACT THE DATA VISIBLE DURING THE COURSE OF YOUR TRANSACTION )F YOUR PROGRAM PERFORMS A DATABASE QUERY DURING A TRANSACTION PROCEEDS WITH OTHER WORK AND LATER PERFORMS THE SAME DATABASE QUERY A SECOND TIME THE 31, TRANSACTION MECHANISM GUARANTEES THAT THE DATA RETURNED BY THE TWO QUERIES WILL BE IDENTICAL UNLESS YOUR TRANSACTION ACTED TO CHANGE THE DATA 4HIS ABILITY TO RELIABLY RE RETRIEVE A ROW DURING A TRANSACTION IS THE HIGHEST LEVEL OF ISOLATION THAT YOUR PROGRAM CAN HAVE FROM OTHER PROGRAMS AND USERS 4HE LEVEL OF ISOLATION IS CALLED THE ISOLATION LEVEL OF YOUR TRANSACTION 4HIS ABSOLUTE ISOLATION OF YOUR TRANSACTION FROM ALL OTHER CONCURRENTLY EXECUTING TRANSACTIONS IS VERY COSTLY IN TERMS OF DATABASE LOCKING AND LOSS OF DATABASE CONCURRENCY !S YOUR PROGRAM READS EACH ROW OF QUERY RESULTS THE $"-3 MUST LOCK THE ROW WITH A SHARED LOCK TO PREVENT CONCURRENT TRANSACTIONS FROM MODIFYING THE ROW 4HESE LOCKS MUST BE HELD UNTIL THE END OF YOUR TRANSACTION JUST IN CASE YOUR PROGRAM PERFORMS THE QUERY AGAIN )N MANY CASES THE $"-3 CAN SIGNIFICANTLY REDUCE ITS LOCKING OVERHEAD IF IT KNOWS IN ADVANCE HOW A PROGRAM WILL ACCESS A DATABASE DURING A TRANSACTION 4O GAIN THIS EFFICIENCY THE MAJOR )"- MAINFRAME DATABASES ADDED SUPPORT FOR THE CONCEPT OF A USER SPECIFIED ISOLATION LEVEL THAT GIVES THE USER CONTROL OVER THE TRADE OFF BETWEEN ISOLATION AND PROCESSING EFFICIENCY 4HE 31, SPECIFICATION FORMALIZED THE )"- ISOLATION LEVEL CONCEPT AND EXPANDED IT TO INCLUDE FOUR ISOLATION LEVELS SHOWN IN &IGURE 4HE ISOLATION LEVELS ARE LINKED DIRECTLY TO THE FUNDAMENTAL MULTIUSER UPDATE PROBLEMS DISCUSSED EARLIER IN THIS CHAPTER !S THE LEVEL OF ISOLATION DECREASES MOVING DOWN THE ROWS OF THE TABLE THE $"-3 INSULATES THE USER FROM FEWER OF THE MULTIUSER UPDATE PROBLEMS
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4HE 3%2)!,):!",% ISOLATION LEVEL IS THE HIGHEST LEVEL PROVIDED !T THIS LEVEL THE $"-3 GUARANTEES THAT THE EFFECTS OF CONCURRENTLY EXECUTING TRANSACTIONS ARE EXACTLY THE SAME AS IF THEY EXECUTED IN SEQUENCE 4HIS IS THE DEFAULT ISOLATION LEVEL SPECIFIED IN THE !.3))3/ 31, STANDARD BECAUSE IT IS THE WAY 31, DATABASES ARE SUPPOSED TO WORK )F YOUR PROGRAM NEEDS TO PERFORM THE SAME MULTIROW QUERY TWICE DURING A TRANSACTION AND BE GUARANTEED THAT THE RESULTS WILL BE IDENTICAL REGARDLESS OF OTHER ACTIVITY IN THE DATABASE THEN IT SHOULD USE THE 3%2)!,):!",% ISOLATION LEVEL 4HE 2%0%!4!",% 2%!$ ISOLATION LEVEL IS THE SECOND HIGHEST LEVEL !T THIS LEVEL YOUR TRANSACTION IS NOT ALLOWED TO SEE EITHER COMMITTED OR UNCOMMITTED UPDATES FROM OTHER TRANSACTIONS SO THE LOST UPDATE UNCOMMITTED DATA AND MODIFIED DATA PROBLEMS CANNOT OCCUR (OWEVER A ROW INSERTED INTO THE DATABASE BY ANOTHER CONCURRENT TRANSACTION MAY BECOME VISIBLE DURING YOUR TRANSACTION !S A RESULT A MULTIROW QUERY RUN EARLY IN YOUR TRANSACTION MAY YIELD DIFFERENT RESULTS THAN THE SAME QUERY RUN LATER IN THE SAME TRANSACTION THE PHANTOM INSERT PROBLEM )F YOUR PROGRAM DOES NOT DEPEND ON THE CAPABILITY TO REPEAT A MULTIROW QUERY DURING A SINGLE TRANSACTION YOU CAN SAFELY USE THE 2%0%!4!",% 2%!$ ISOLATION LEVEL TO IMPROVE $"-3 PERFORMANCE WITHOUT SACRIFICING DATA INTEGRITY 4HIS IS ONE OF THE ISOLATION LEVELS SUPPORTED IN THE )"- MAINFRAME DATABASE PRODUCTS 4HE 2%!$ #/--)44%$ ISOLATION LEVEL IS THE THIRD HIGHEST LEVEL )N THIS MODE YOUR TRANSACTION IS NOT ALLOWED TO SEE UNCOMMITTED UPDATES FROM OTHER TRANSACTIONS SO THE LOST UPDATE AND THE UNCOMMITTED DATA PROBLEMS CANNOT OCCUR (OWEVER UPDATES THAT ARE COMMITTED BY OTHER CONCURRENTLY EXECUTING TRANSACTIONS MAY BECOME VISIBLE DURING THE COURSE OF YOUR TRANSACTION 9OUR PROGRAM COULD FOR EXAMPLE PERFORM A SINGLE ROW 3%,%#4 STATEMENT TWICE DURING THE COURSE OF A TRANSACTION AND FIND THAT THE DATA IN THE ROW HAD BEEN MODIFIED BY ANOTHER USER )F YOUR PROGRAM DOES NOT DEPEND ON THE CAPABILITY TO REREAD A SINGLE ROW OF DATA DURING A TRANSACTION AND IT IS NOT ACCUMULATING TOTALS OR DOING OTHER CALCULATIONS THAT RELY ON A SELF CONSISTENT SET OF DATA IT CAN SAFELY USE THE 2%!$ #/--)44%$ ISOLATION LEVEL .OTE THAT IF YOUR PROGRAM ATTEMPTS TO UPDATE A ROW THAT HAS ALREADY BEEN UPDATED BY ANOTHER USER YOUR TRANSACTION WILL AUTOMATICALLY BE ROLLED BACK TO PREVENT THE LOST UPDATE PROBLEM FROM OCCURRING
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4HE 2%!$ 5.#/--)44%$ ISOLATION LEVEL IS THE LOWEST LEVEL SPECIFIED IN THE 31, STANDARD )N THIS MODE YOUR TRANSACTION MAY BE IMPACTED BY COMMITTED OR UNCOMMITTED UPDATES FROM OTHER TRANSACTIONS SO THE UNCOMMITTED DATA MODIFIED DATA AND PHANTOM INSERT PROBLEMS CAN OCCUR 4HE $"-3 STILL PREVENTS THE LOST UPDATE PROBLEM 'ENERALLY THE 2%!$ 5.#/--)44%$ LEVEL IS APPROPRIATE ONLY FOR CERTAIN AD HOC QUERY APPLICATIONS WHERE THE USER CAN TOLERATE THE FACT THAT THE QUERY RESULTS MAY CONTAIN DIRTY DATA 3OME $"-3 BRANDS CALL THIS ISOLATION MODE A DIRTY READ CAPABILITY BECAUSE OF THIS POSSIBILITY )F IT IS IMPORTANT THAT QUERY RESULTS CONTAIN ONLY INFORMATION THAT HAS IN FACT BEEN COMMITTED TO THE DATABASE YOUR PROGRAM SHOULD NOT USE THIS MODE 2ECALL THAT THE 31, STANDARD SPECIFIES 3%4 42!.3!#4)/. AND 34!24 42!.3!#4)/. STATEMENTS SHOWN IN &IGURE WHICH CAN BE USED TO SET THE ISOLATION LEVEL OF TRANSACTIONS 4HESE STATEMENTS ALSO ALLOW YOU TO SPECIFY WHETHER THE TRANSACTION IS 2%!$ /.,9 THAT IS IT WILL ONLY QUERY THE DATABASE OR 2%!$ 72)4% IT MAY QUERY OR UPDATE THE DATABASE 4HE $"-3 CAN USE THIS INFORMATION ALONG WITH THE ISOLATION LEVEL TO OPTIMIZE ITS DATABASE PROCESSING 4HE DEFAULT ISOLATION LEVEL IS 3%2)!,):!",% )F THE 2%!$ 5.#/--)44%$ ISOLATION LEVEL IS SPECIFIED THEN 2%!$ /.,9 IS ASSUMED AND YOU MAY NOT SPECIFY A 2%!$ 72)4% TRANSACTION /THERWISE A 2%!$ 72)4% TRANSACTION IS THE DEFAULT 4HESE DEFAULTS PROVIDE FOR THE MAXIMUM SAFETY OF TRANSACTIONS AT THE EXPENSE OF DATABASE PERFORMANCE BUT THEY PREVENT INEXPERIENCED 31, PROGRAMMERS FROM INADVERTENTLY SUFFERING ONE OF THE MULTIUSER TRANSACTION PROCESSING PROBLEMS .OTE THAT THE 3%4 42!.3!#4)/. AND 34!24 42!.3!#4)/. STATEMENTS SPECIFIED IN THE 31, STANDARD ARE EXECUTABLE 31, STATEMENTS )TS POSSIBLE IN FACT SOMETIMES VERY DESIRABLE TO HAVE ONE TRANSACTION OF A PROGRAM EXECUTE IN ONE MODE AND HAVE THE NEXT TRANSACTION EXECUTE IN A DIFFERENT MODE (OWEVER YOU CANT SWITCH ISOLATION LEVELS OR READWRITE MODES IN THE MIDDLE OF A TRANSACTION 4HE STANDARD EFFECTIVELY REQUIRES THAT THE 3%4 42!.3!#4)/. STATEMENT BE THE FIRST STATEMENT OF A TRANSACTION 4HIS MEANS IT MUST BE EXECUTED AS THE FIRST STATEMENT AFTER A #/--)4 OR 2/,,"!#+ OR AS THE FIRST STATEMENT OF A PROGRAM BEFORE ANY OTHER STATEMENT AFFECTING THE CONTENT OR STRUCTURE OF A DATABASE !S NOTED EARLIER IN THE h!DVANCED ,OCKING 4ECHNIQUESv SECTION MANY OF THE COMMERCIAL $"-3 PRODUCTS IMPLEMENTED THEIR OWN LOCKING AND PERFORMANCE ENHANCEMENT SCHEMES LONG BEFORE THESE FEATURES WERE ADDED TO THE 31, STANDARD AND THESE LOCKING STRATEGIES AFFECT THE HEART OF THE INTERNAL DATABASE ARCHITECTURE AND LOGIC )TS NOT SURPRISING THAT THE ADOPTION OF THE 31, STANDARD IN THIS AREA HAS BEEN RELATIVELY SLOW COMPARED WITH SOME OTHER AREAS WHERE IMPLEMENTATION WAS MUCH EASIER &OR EXAMPLE THE )"- MAINFRAME DATABASES $" AND 31,$3 HISTORICALLY OFFERED A CHOICE OF TWO ISOLATION LEVELS2%0%!4!",% 2%!$ OR 2%!$ #/--)44%$ CALLED #523/2 34!"),)49 MODE IN )"- TERMINOLOGY )N THE )"- IMPLEMENTATIONS THE CHOICE IS MADE DURING THE PROGRAM DEVELOPMENT PROCESS IN THE ").$ STEP DESCRIBED IN #HAPTER !LTHOUGH THE MODES ARE NOT STRICTLY PART OF THE 31, LANGUAGE THE CHOICE OF MODE STRONGLY IMPACTS HOW THE APPLICATION PERFORMS AND HOW IT CAN USE RETRIEVED DATA 4HE )NGRES $"-3 OFFERS A CAPABILITY SIMILAR TO THE ISOLATION MODES OF THE )"- DATABASES BUT PROVIDES IT IN A DIFFERENT FORM 5SING THE 3%4 ,/#+-/$% STATEMENT AN APPLICATION PROGRAM CAN TELL )NGRES WHICH TYPE OF LOCKING TO USE WHEN HANDLING A DATABASE QUERY 4HE OPTIONS ARE THE FOLLOWING s .O LOCKING 3IMILAR TO THE )"- #523/2 34!"),)49 MODE JUST DESCRIBED s 3HARED LOCKING 3IMILAR TO THE )"- 2%0%!4!",% 2%!$ MODE JUST DESCRIBED s %XCLUSIVE LOCKING 0ROVIDES EXCLUSIVE ACCESS TO THE TABLE DURING THE QUERY AND OFFERS A CAPABILITY LIKE THE )"- ,/#+ 4!",% STATEMENT
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4R A N S A C T I O N ç 0 R O C E S S I N G ç
4HE )NGRES DEFAULT IS SHARED LOCKING WHICH PARALLELS THE REPEATABLE READ DEFAULT IN THE )"- SCHEME .OTE HOWEVER THAT THE )NGRES LOCKING MODES ARE SET BY AN EXECUTABLE 31, STATEMENT 5NLIKE THE )"- MODES WHICH MUST BE CHOSEN AT COMPILE TIME THE )NGRES MODES CAN BE CHOSEN WHEN THE PROGRAM EXECUTES AND CAN EVEN BE CHANGED FROM ONE QUERY TO THE NEXT
,OCKINGõ0ARAMETERS
! MATURE $"-3 SUCH AS $" 31,$3 /RACLE 3YBASE !3% OR 31, 3ERVER EMPLOYS MUCH MORE COMPLEX LOCKING TECHNIQUES THAN THOSE DESCRIBED HERE 4HE DATABASE ADMINISTRATOR CAN IMPROVE THE PERFORMANCE OF THESE SYSTEMS BY MANUALLY SETTING THE LOCKING PARAMETERS /N THE OTHER HAND THE VENDORS OF CURRENT MAJOR $"-3 PRODUCTS TYPICALLY DISCOURAGE ATTEMPTS TO CONTROL LOCKING MANUALLY BECAUSE THINGS HAVE BECOME SO COMPLEX THAT SEEMINGLY SIMPLE CHANGES CAN MAKE THINGS WORSE INSTEAD OF BETTER /LDER SYSTEMS HOWEVER MIGHT BENEFIT FROM SOME TUNING 4YPICAL PARAMETERS THAT CAN BE TUNED INCLUDE THESE s ,OCK SIZE 3OME $"-3 PRODUCTS OFFER A CHOICE OF TABLE LEVEL PAGE LEVEL ROW LEVEL AND OTHER LOCK SIZES $EPENDING ON THE SPECIFIC APPLICATION A DIFFERENT SIZE LOCK MAY BE APPROPRIATE
s ,OCK ESCALATION ! $"-3 WILL OFTEN AUTOMATICALLY ESCALATE LOCKS REPLACING MANY SMALL LOCKS WITH A SINGLE LARGER LOCK FOR EXAMPLE REPLACING MANY PAGE LEVEL LOCKS WITH A TABLE LEVEL LOCK 4HE DATABASE ADMINISTRATOR MAY HAVE SOME CONTROL OVER THIS ESCALATION PROCESS s ,OCK TIMEOUT %VEN WHEN A TRANSACTION IS NOT DEADLOCKED WITH ANOTHER TRANSACTION IT MAY WAIT A VERY LONG TIME FOR THE OTHER TRANSACTION TO RELEASE ITS LOCKS 3OME $"-3 BRANDS IMPLEMENT A TIMEOUT FEATURE WHERE A 31, STATEMENT FAILS WITH A 31, ERROR CODE IF IT CANNOT OBTAIN THE LOCKS IT NEEDS WITHIN A CERTAIN PERIOD 4HE TIMEOUT PERIOD CAN USUALLY BE SET BY THE DATABASE ADMINISTRATOR
6ERSIONING
4HE LOCKING TECHNIQUES DESCRIBED IN THE PRECEDING SECTIONS ARE THE MOST WIDELY USED TECHNIQUES FOR SUPPORTING CONCURRENT MULTIUSER TRANSACTION PROCESSING IN RELATIONAL $"-3 PRODUCTS ,OCKING IS SOMETIMES CALLED A PESSIMISTIC APPROACH TO CONCURRENCY BECAUSE BY LOCKING PARTS OF THE DATABASE THE $"-3 IS IMPLICITLY ASSUMING THAT CONCURRENT TRANSACTIONS WILL PROBABLY INTERFERE WITH ONE ANOTHER )N RECENT YEARS A DIFFERENT APPROACH TO CONCURRENCY CALLED VERSIONING HAS BEEN IMPLEMENTED IN SOME $"-3 PRODUCTS AND HAS BEEN INCREASING IN POPULARITY 6ERSIONING IS SOMETIMES CALLED AN OPTIMISTIC APPROACH TO CONCURRENCY BECAUSE IN THIS APPROACH THE $"-3 IMPLICITLY ASSUMES THAT CONCURRENT TRANSACTIONS WILL NOT INTERFERE WITH ONE ANOTHER 7ITH A LOCKING PESSIMISTIC ARCHITECTURE THE $"-3 INTERNALLY MAINTAINS ONE AND ONLY ONE COPY OF THE DATA FOR EACH ROW IN THE DATABASE !S MULTIPLE USERS ACCESS THE DATABASE THE LOCKING SCHEME ARBITRATES THE ACCESS TO THIS ROW OF DATA AMONG THE USERS MORE PRECISELY AMONG THEIR CONCURRENT TRANSACTIONS )N CONTRAST WITH A VERSIONING OPTIMISTIC ARCHITECTURE
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s .UMBER OF LOCKS ! $"-3 TYPICALLY ALLOWS EACH TRANSACTION TO HAVE SOME FINITE NUMBER OF LOCKS 4HE DATABASE ADMINISTRATOR CAN OFTEN SET THIS LIMIT RAISING IT TO PERMIT MORE COMPLEX TRANSACTIONS OR LOWERING IT TO ENCOURAGE EARLIER LOCK ESCALATION
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THE $"-3 WILL CREATE TWO OR MORE COPIES OF THE DATA FOR A ROW IN THE DATABASE WHEN A USER ATTEMPTS TO UPDATE THE ROW /NE COPY OF THE ROW WILL CONTAIN THE OLD DATA FOR THE ROW BEFORE THE UPDATE THE OTHER COPY OF THE ROW WILL CONTAIN THE NEW DATA FOR THE ROW AFTER THE UPDATE 4HE $"-3 INTERNALLY KEEPS TRACK OF WHICH TRANSACTIONS SHOULD SEE WHICH VERSION OF THE ROW DEPENDING ON THEIR ISOLATION LEVELS
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&IGURE SHOWS A SIMPLE VERSIONING ARCHITECTURE IN ACTION 4RANSACTION ! STARTS THE ACTION READING A ROW OF THE 02/$5#43 TABLE AND FINDING UNITS OF !#) SIZE WIDGETS AVAILABLE 4RANSACTION " COMES ALONG NEXT AND UPDATES THE SAME ROW REDUCING THE QUANTITY
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AVAILABLE TO UNITS )N RESPONSE THE $"-3 INTERNALLY CREATES A NEW COPY OF THE ROW &ROM THIS POINT ON IF 4RANSACTION " REREADS THE CONTENTS OF THE ROW THE CONTENTS WILL COME FROM THIS NEW COPY SINCE IT REFLECTS 4RANSACTION "S UPDATED QUANTITY ON HAND UNITS .EXT 4RANSACTION # COMES ALONG AND TRIES TO READ THE SAME ROW "ECAUSE 4RANSACTION "S UPDATE HAS NOT YET BEEN COMMITTED THE $"-3 GIVES 4RANSACTION # THE DATA FROM THE OLD COPY OF THE ROW SHOWING UNITS AVAILABLE 4HE SAME THING HAPPENS A FEW SECONDS LATER FOR 4RANSACTION $ IT WILL ALSO SEE UNITS AVAILABLE .OW 4RANSACTION " PERFORMS A #/--)4 OPERATION MAKING ITS UPDATE OF THE ROW PERMANENT ! SHORT TIME LATER 4RANSACTION % ATTEMPTS TO READ THE ROW 7ITH 4RANSACTION "S UPDATE NOW COMMITTED THE $"-3 WILL GIVE 4RANSACTION % THE DATA FROM THE NEW COPY SHOWING UNITS &INALLY 4RANSACTIONS # $ AND % END THEIR DATABASE ACTIVITY WITH A #/--)4 OPERATION 4HE ACTIVITY SHOWN IN &IGURE MEETS THE SERIALIZABILITY REQUIREMENT FOR PROPER $"-3 OPERATION 4HE SEQUENTIAL TRANSACTION SERIES ! # $ " % WOULD PRODUCE THE SAME RESULTS SHOWN IN THE FIGURE )N FACT THE SERIES ! $ # " % WOULD ALSO PRODUCE THESE RESULTS &URTHERMORE THE VERSIONING IMPLEMENTATION DELIVERS THE CORRECT OPERATION WITHOUT CAUSING ANY OF THE TRANSACTIONS TO WAIT 4HIS IS NOT TRUE OF THE TYPICAL LOCKING IMPLEMENTATION AS SHOWN IN &IGURE )N &IGURE 4RANSACTION ! AGAIN STARTS THE ACTION FINDING UNITS OF !#) WIDGETS AVAILABLE )NTERNALLY THE $"-3 PLACES A SHARED LOCK ON THE ROW 4RANSACTION " NEXT TRIES TO UPDATE THE ROW REDUCING QUANTITY ON HAND TO UNITS )F 4RANSACTION ! IS OPERATING AT A STRICT ISOLATION LEVEL SUCH AS 2%0%!4!",% 2%!$ 4RANSACTION " WILL BE HELD AT THIS POINT BECAUSE IT CANNOT ACQUIRE THE REQUIRED EXCLUSIVE LOCK )F 4RANSACTION ! IS OPERATING AT A LESS STRICT ISOLATION LEVEL THE $"-3 CAN ALLOW 4RANSACTION " TO PROCEED GIVING IT AN EXCLUSIVE LOCK ON THE ROW AND ACTUALLY UPDATING THE DATA 4HE INTERNAL ROW IN THE DATABASE RECALL THAT THERE IS ONLY A SINGLE COPY OF THE ROW IN THIS LOCKING ARCHITECTURE NOW SHOWS UNITS AVAILABLE 7HEN 4RANSACTION # COMES ALONG IT MUST WAIT FOR 4RANSACTION " TO RELEASE ITS LOCK UNLESS 4RANSACTION # IS OPERATING AT A VERY LOW 2%!$ 5.#/--)44%$ ISOLATION LEVEL 4HE SAME IS TRUE OF 4RANSACTION $ /NLY AFTER 4RANSACTION " HAS COMMITTED ITS CHANGES CAN 4RANSACTIONS # AND $ PROCEED #OMPARING THE OPERATIONS IN &IGURES AND TWO DIFFERENCES ARE WORTH NOTING &IRST AND MORE FUNDAMENTALLY THE VERSIONING APPROACH IN &IGURE ALLOWS MORE CONCURRENT TRANSACTIONS TO PROCEED IN PARALLEL 4HE LOCKING APPROACH IN &IGURE WILL UNDER MOST CIRCUMSTANCES CAUSE TWO OR MORE TRANSACTIONS TO WAIT FOR OTHERS TO COMPLETE AND FREE THEIR LOCKS 4HE SECOND AND MORE SUBTLE DIFFERENCE IS THAT THE EFFECTIVE ORDER OF SERIAL TRANSACTION EXECUTION IS DIFFERENT BETWEEN THE TWO FIGURES !S NOTED IN &IGURE THE TRANSACTION SEQUENCE ! # $ " % PRODUCES THE RESULTS )N &IGURE THE SEQUENCE ! " # $ % PRODUCES THE RESULTS .OTE THAT NEITHER SEQUENCE IS CONSIDERED CORRECT OR INCORRECT THE SERIALIZABILITY PRINCIPLE STATES ONLY THAT THE RESULTS PRODUCED BY THE $"-3 MUST MATCH SOME SEQUENCE OF SERIAL TRANSACTIONS 4HE EXAMPLE IN &IGURE INCLUDES ONLY ONE UPDATING TRANSACTION SO ONLY TWO COPIES OF THE UPDATED ROW ARE REQUIRED BEFORE AND AFTER THE UPDATE 4HE VERSIONING ARCHITECTURE IS EASILY EXTENDED TO SUPPORT MORE CONCURRENT UPDATES &OR EACH ATTEMPT TO UPDATE THE ROW THE $"-3 CAN CREATE ANOTHER NEW ROW REFLECTING THE UPDATE 7ITH THIS MULTIVERSIONED APPROACH THE TASK OF KEEPING TRACK OF WHICH TRANSACTION SHOULD SEE WHICH VERSION OF THE ROW OBVIOUSLY BECOMES MORE COMPLEX )N PRACTICE THE DECISION ABOUT WHICH VERSION OF THE ROW SHOULD BE VISIBLE TO EACH CONCURRENT TRANSACTION DEPENDS NOT ONLY ON THE SEQUENCE OF DATABASE OPERATIONS BUT ALSO ON THE ISOLATION LEVELS REQUESTED BY EACH OF THE TRANSACTIONS
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6ERSIONING DOES NOT COMPLETELY ELIMINATE THE POSSIBILITY OF DEADLOCKS WITHIN THE DATABASE 4HE TWO TRANSACTIONS IN &IGURE WITH THEIR INTERLEAVED ATTEMPTS TO UPDATE TWO DIFFERENT TABLES EACH IN A DIFFERENT ORDER WILL STILL PRODUCE PROBLEMS EVEN FOR A VERSIONING SCHEME (OWEVER FOR WORKLOADS WITH A MIX OF DATABASE 2%!$ OPERATIONS AND DATABASE 50$!4% OPERATIONS VERSIONING CAN SIGNIFICANTLY REDUCE THE LOCKING AND LOCK TIMEOUTS OR DEADLOCKS ASSOCIATED WITH SHARED LOCKS
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3UMMARY 4HIS CHAPTER DESCRIBED THE TRANSACTION MECHANISM PROVIDED BY THE 31, LANGUAGE s ! TRANSACTION IS A LOGICAL UNIT OF WORK IN A 31, BASED DATABASE )T CONSISTS OF A SEQUENCE OF 31, STATEMENTS THAT ARE EFFECTIVELY EXECUTED AS A SINGLE UNIT BY THE $"-3 s 4HE 3%4 42!.3!#4)/. AND 34!24 TRANSACTION STATEMENTS CAN BE USED TO SET THE ISOLATION LEVEL AND ACCESS LEVEL OF TRANSACTIONS s 4HE 3!6%0/).4 STATEMENT CREATES AN INTERMEDIATE RECOVERY POINT WITHIN A TRANSACTION s 4HE 2%,%!3% 3!6%0/).4 STATEMENT REMOVES A SAVEPOINT AND RELEASES ANY RESOURCES IT IS HOLDING s 4HE #/--)4 STATEMENT SIGNALS SUCCESSFUL COMPLETION OF A TRANSACTION MAKING ALL OF ITS DATABASE MODIFICATIONS PERMANENT s 4HE 2/,,"!#+ STATEMENT ASKS THE $"-3 TO ABORT A TRANSACTION BACKING OUT ALL OF ITS DATABASE MODIFICATIONS
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4HE ADVANTAGE OF A VERSIONING ARCHITECTURE IS THAT UNDER THE RIGHT CIRCUMSTANCES IT CAN SIGNIFICANTLY INCREASE THE NUMBER OF CONCURRENT TRANSACTIONS THAT CAN EXECUTE IN PARALLEL #ONCURRENT EXECUTION IS BECOMING MORE AND MORE IMPORTANT IN LARGE $"-3 INSTALLATIONS ESPECIALLY THOSE THAT SUPPORT WEB SITES THAT MAY HAVE THOUSANDS OR TENS OF THOUSANDS OF CONCURRENT USERS 6ERSIONING IS ALSO BECOMING MORE USEFUL AS THE NUMBER OF PROCESSORS ON TYPICAL $"-3 SERVER COMPUTER SYSTEMS INCREASES 3ERVERS CONTAINING OR MORE PROCESSORS ARE BECOMING INCREASINGLY COMMON AND LARGE $"-3 SERVERS MAY SUPPORT OR MORE PROCESSORS IN A SYMMETRIC MULTIPROCESSING 3-0 CONFIGURATION 4HESE SERVERS CAN ACTUALLY EXECUTE MANY DATABASE ACCESS APPLICATIONS IN PARALLEL BY SPREADING THE WORKLOAD OUT OVER MANY PROCESSORS 4HE DISADVANTAGE OF A VERSIONING ARCHITECTURE IS THE INTERNAL $"-3 OVERHEAD THAT IT CREATES /NE OBVIOUS OVERHEAD IS THE ADDED MEMORY AND DISK REQUIREMENT OF STORING TWO OR MORE COPIES OF ROWS THAT ARE BEING UPDATED )N PRACTICE A MORE SERIOUS OVERHEAD IS THE MEMORY MANAGEMENT REQUIRED TO ALLOCATE MEMORY FOR EACH TEMPORARY COPY OF A ROW AS IT IS NEEDED POTENTIALLY THOUSANDS OF TIMES PER SECOND AND THEN RELEASING THE MEMORY TO BE REUSED WHEN THE OLDER COPIES OF THE ROW ARE NO LONGER NEEDED !N ADDITIONAL OVERHEAD IS KEEPING TRACK OF WHICH TRANSACTIONS SHOULD SEE WHICH COPIES OF WHICH ROWS )MPLICITLY A VERSIONING ARCHITECTURE IS BASED ON THE UNDERLYING ASSUMPTION THAT MOST CONCURRENT TRANSACTIONS WILL TEND NOT TO INTERFERE WITH ONE ANOTHER )F THIS ASSUMPTION PROVES ACCURATE IE IF CONCURRENTLY EXECUTING TRANSACTIONS MOSTLY ACCESS AND UPDATE DIFFERENT ROWS OR IF THE TRANSACTION WORKLOAD IS DOMINATED BY 2%!$ OPERATIONS RATHER THAN 50$!4%S THEN THE ADDED OVERHEAD OF THE VERSIONING SCHEME WILL BE MORE THAN OFFSET BY A SIGNIFICANT BOOST IN THE AMOUNT OF PARALLEL WORK THAT CAN BE PERFORMED )F THE ASSUMPTION PROVES INACCURATE IE IF CONCURRENTLY EXECUTING TRANSACTIONS TEND TO ACCESS AND UPDATE THE SAME ROWS THEN THE OVERHEAD OF THE VERSIONING TECHNIQUE WILL TEND TO BECOME VERY HIGH SWAMPING THE CONCURRENCY GAINS
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s 4RANSACTIONS ARE THE KEY TO RECOVERING A DATABASE AFTER A SYSTEM FAILURE ONLY TRANSACTIONS THAT WERE COMMITTED AT THE TIME OF FAILURE REMAIN IN THE RECOVERED DATABASE s 4RANSACTIONS ARE THE KEY TO CONCURRENT ACCESS IN A MULTIUSER DATABASE ! USER OR PROGRAM IS GUARANTEED THAT ITS TRANSACTION WILL NOT BE INTERFERED WITH BY OTHER CONCURRENT TRANSACTIONS s /CCASIONALLY A CONFLICT WITH ANOTHER CONCURRENTLY EXECUTING TRANSACTION MAY CAUSE THE $"-3 TO ROLL BACK A TRANSACTION THROUGH NO FAULT OF ITS OWN !N APPLICATION PROGRAM THAT USES 31, MUST BE PREPARED TO DEAL WITH THIS SITUATION IF IT OCCURS s 4HE SUBTLETIES OF TRANSACTION MANAGEMENT AND THEIR IMPACT ON $"-3 PERFORMANCE ARE ONE OF THE MORE COMPLEX AREAS OF USING AND OPERATING A LARGE PRODUCTION DATABASE 4HIS IS ALSO AN AREA WHERE MAJOR $"-3 BRANDS DIVERGE IN THEIR CAPABILITIES AND TUNING OPTIONS s -ANY $"-3 BRANDS USE LOCKING TECHNIQUES TO HANDLE CONCURRENT TRANSACTIONS &OR THESE PRODUCTS ADJUSTMENTS TO THE LOCKING PARAMETERS AND EXPLICIT LOCKING STATEMENTS ALLOW YOU TO TUNE TRANSACTION PROCESSING PERFORMANCE s !N ALTERNATIVE VERSIONING TECHNIQUE FOR HANDLING CONCURRENT TRANSACTIONS IS SUPPORTED BY SOME CURRENT PRODUCTS &OR $"-3 PRODUCTS THAT USE VERSIONING ADJUSTMENTS TO THE DEPTH OF THE VERSIONING SCHEME AND TO THE TRANSACTION MIX ITSELF ARE THE KEYS TO PERFORMANCE TUNING
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N IMPORTANT ROLE OF 31, IS TO DEFINE THE STRUCTURE AND ORGANIZATION OF A DATABASE #HAPTERS n DESCRIBE THE 31, FEATURES THAT SUPPORT THIS ROLE #HAPTER DESCRIBES HOW TO CREATE A DATABASE AND ITS TABLES #HAPTER DESCRIBES VIEWS AN IMPORTANT 31, FEATURE THAT LETS USERS SEE ALTERNATE ORGANIZATIONS OF DATABASE DATA 4HE 31, SECURITY FEATURES THAT PROTECT STORED DATA ARE DESCRIBED IN #HAPTER &INALLY #HAPTER DISCUSSES THE SYSTEM CATALOG A COLLECTION OF SYSTEM TABLES THAT DESCRIBE THE STRUCTURE OF A DATABASE
#(!04%2ç #REATING A $ATABASE #(!04%2ç 6IEWS #(!04%2ç 31, 3ECURITY #(!04%2ç 4HE 3YSTEM #ATALOG
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ANY 31, USERS DONT HAVE TO WORRY ABOUT CREATING A DATABASE THEY USE INTERACTIVE OR PROGRAMMATIC 31, TO ACCESS A DATABASE OF CORPORATE INFORMATION OR TO ACCESS SOME OTHER DATABASE THAT HAS BEEN CREATED BY SOMEONE ELSE )N A TYPICAL CORPORATE DATABASE FOR EXAMPLE THE DATABASE ADMINISTRATOR MAY GIVE YOU PERMISSION TO RETRIEVE AND PERHAPS TO UPDATE THE STORED DATA (OWEVER THE ADMINISTRATOR WILL NOT ALLOW YOU TO CREATE NEW DATABASES OR TO MODIFY THE STRUCTURE OF THE EXISTING TABLES !S YOU GROW MORE COMFORTABLE WITH 31, YOU WILL PROBABLY WANT TO START CREATING YOUR OWN PRIVATE TABLES TO STORE PERSONAL DATA SUCH AS ENGINEERING TEST RESULTS OR SALES FORECASTS )F YOU ARE USING A MULTIUSER DATABASE YOU MAY WANT TO CREATE TABLES OR EVEN ENTIRE DATABASES THAT WILL BE SHARED WITH OTHER USERS )F YOU ARE USING A PERSONAL COMPUTER DATABASE YOU WILL CERTAINLY WANT TO CREATE YOUR OWN TABLES AND DATABASES TO SUPPORT YOUR PERSONAL APPLICATIONS 4HIS CHAPTER DESCRIBES THE 31, LANGUAGE FEATURES THAT LET YOU CREATE DATABASES AND TABLES AND DEFINE THEIR STRUCTURE
4HEõ$ATAõ$EFINITIONõ,ANGUAGE 4HE 3%,%#4 ).3%24 $%,%4% 50$!4% #/--)4 AND 2/,,"!#+ STATEMENTS DESCRIBED IN 0ARTS )) AND ))) OF THIS BOOK ARE ALL CONCERNED WITH MANIPULATING THE DATA IN A DATABASE 4HESE STATEMENTS COLLECTIVELY ARE CALLED THE 31, $ATA -ANIPULATION ,ANGUAGE OR $-, 4HE $-, STATEMENTS CAN MODIFY THE DATA STORED IN A DATABASE BUT THEY CANNOT CHANGE ITS STRUCTURE .ONE OF THESE STATEMENTS CREATES OR DELETES TABLES OR COLUMNS FOR EXAMPLE
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#HANGES TO THE STRUCTURE OF A DATABASE ARE HANDLED BY A DIFFERENT SET OF 31, STATEMENTS USUALLY CALLED THE 31, $ATA $EFINITION ,ANGUAGE OR $$, 5SING $$, STATEMENTS YOU CAN s $EFINE AND CREATE A NEW TABLE s 2EMOVE A TABLE THATS NO LONGER NEEDED s #HANGE THE DEFINITION OF AN EXISTING TABLE s $EFINE A VIRTUAL TABLE OR VIEW OF DATA s %STABLISH SECURITY CONTROLS FOR A DATABASE s "UILD AN INDEX TO MAKE TABLE ACCESS FASTER s #ONTROL THE PHYSICAL STORAGE OF DATA BY THE $"-3 &OR THE MOST PART THE $$, STATEMENTS INSULATE YOU FROM THE LOW LEVEL DETAILS OF HOW DATA IS PHYSICALLY STORED IN THE DATABASE 4HEY MANIPULATE ABSTRACT DATABASE OBJECTS SUCH AS TABLES AND COLUMNS (OWEVER THE $$, CANNOT AVOID PHYSICAL STORAGE ISSUES ENTIRELY AND BY NECESSITY THE $$, STATEMENTS AND CLAUSES THAT CONTROL PHYSICAL STORAGE VARY FROM ONE $"-3 TO ANOTHER 4HE CORE OF THE $ATA $EFINITION ,ANGUAGE IS BASED ON THREE 31, VERBS s #2%!4% $EFINES AND CREATES A DATABASE OBJECT s $2/0 2EMOVES AN EXISTING DATABASE OBJECT s !,4%2 #HANGES THE DEFINITION OF A DATABASE OBJECT )N ALL MAJOR 31, BASED $"-3 PRODUCTS THESE THREE $$, VERBS CAN BE USED WHILE THE $"-3 IS RUNNING 4HE DATABASE STRUCTURE IS THUS DYNAMIC 4HE $"-3 CAN BE CREATING DROPPING OR CHANGING THE DEFINITION OF THE TABLES IN THE DATABASE FOR EXAMPLE WHILE IT IS SIMULTANEOUSLY PROVIDING ACCESS TO THE DATABASE FOR ITS USERS 4HIS IS A MAJOR ADVANTAGE OF 31, AND RELATIONAL DATABASES OVER EARLIER SYSTEMS WHERE THE $"-3 HAD TO BE STOPPED BEFORE YOU COULD CHANGE THE STRUCTURE OF THE DATABASE )T MEANS THAT A RELATIONAL DATABASE CAN GROW AND CHANGE EASILY OVER TIME 0RODUCTION USE OF A DATABASE CAN CONTINUE WHILE NEW TABLES AND APPLICATIONS ARE ADDED !LTHOUGH THE $$, AND $-, ARE TWO DISTINCT PARTS OF 31, IN MOST 31, BASED $"-3 PRODUCTS THE SPLIT IS ONLY A CONCEPTUAL ONE 5SUALLY THE $$, AND $-, STATEMENTS ARE SUBMITTED TO THE $"-3 IN EXACTLY THE SAME WAY AND THEY CAN BE FREELY INTERMIXED IN BOTH INTERACTIVE 31, SESSIONS AND PROGRAMMATIC 31, APPLICATIONS )F YOU NEED A TABLE TO STORE TEMPORARY RESULTS YOU CAN CREATE THE TABLE POPULATE IT MANIPULATE THE DATA AND THEN DELETE THE TABLE !GAIN THIS IS A MAJOR ADVANTAGE OVER EARLIER DATA MODELS IN WHICH THE STRUCTURE OF THE DATABASE WAS FIXED WHEN THE DATABASE WAS CREATED !LTHOUGH VIRTUALLY ALL COMMERCIAL 31, PRODUCTS SUPPORT THE $$, AS AN INTEGRAL PART OF THE 31, LANGUAGE THE ORIGINAL 31, STANDARD 31, DID NOT REQUIRE IT )N FACT THE 31, STANDARD IMPLIES A STRONG SEPARATION BETWEEN THE $-, AND THE $$, ALLOWING VENDORS TO ACHIEVE COMPLIANCE WITH THE $-, PART OF THE STANDARD THROUGH A 31, LAYER ON TOP OF A NON 31, UNDERLYING DATABASE 3UBSEQUENT VERSIONS OF THE 31, STANDARD STILL DIFFERENTIATE BETWEEN DIFFERENT TYPES OF 31, STATEMENTS 4HE STANDARD CALLS THE $$, STATEMENTS h31, SCHEMA STATEMENTS v AND THE $-, STATEMENTS h31, DATA STATEMENTSv AND h31, TRANSACTION STATEMENTSv (OWEVER THE STANDARD WAS BROUGHT INTO ALIGNMENT WITH THE ACTUAL
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IMPLEMENTATION OF POPULAR 31, PRODUCTS BY REQUIRING THAT $$, STATEMENTS BE EXECUTED INTERACTIVELY AND BY A PROGRAM 4HE 31, STANDARD SPECIFIES ONLY THE PARTS OF THE $$, THAT ARE RELATIVELY INDEPENDENT OF PHYSICAL STORAGE STRUCTURES OPERATING SYSTEM DEPENDENCIES AND OTHER $"-3 BRAND SPECIFIC CAPABILITIES )N PRACTICE ALL $"-3 BRANDS INCLUDE SIGNIFICANT EXTENSIONS TO THE STANDARD $$, TO DEAL WITH THESE ISSUES AND OTHER ENHANCED DATABASE CAPABILITIES 4HE DIFFERENCES BETWEEN THE !.3))3/ STANDARD AND THE $$, AS IMPLEMENTED IN POPULAR 31, PRODUCTS ARE DESCRIBED FOR EACH 31, STATEMENT THROUGH THE REMAINDER OF THIS CHAPTER
#REATINGõAõ$ATABASE )N A LARGE MAINFRAME OR ENTERPRISE LEVEL NETWORK $"-3 INSTALLATION THE CORPORATE DATABASE ADMINISTRATOR IS SOLELY RESPONSIBLE FOR CREATING NEW DATABASES /N SMALLER WORKGROUP $"-3 INSTALLATIONS INDIVIDUAL USERS MAY BE ALLOWED TO CREATE THEIR OWN PERSONAL DATABASES BUT ITS MUCH MORE COMMON FOR DATABASES TO BE CREATED CENTRALLY AND THEN ACCESSED BY INDIVIDUAL USERS )F YOU ARE USING A PERSONAL COMPUTER $"-3 YOU ARE PROBABLY BOTH THE DATABASE ADMINISTRATOR AND THE USER AND YOU WILL HAVE TO CREATE THE DATABASES THAT YOU USE PERSONALLY 4HE 31, STANDARD SPECIFIED THE 31, LANGUAGE USED TO DESCRIBE A DATABASE STRUCTURE BUT IT DID NOT SPECIFY HOW TO CREATE DATABASES BECAUSE EACH $"-3 BRAND HAD TAKEN A SLIGHTLY DIFFERENT APPROACH 4HOSE DIFFERENCES PERSIST IN PRESENT DAY MAINSTREAM $"-3 PRODUCTS 4HE TECHNIQUES USED BY THESE 31, PRODUCTS ILLUSTRATE THE DIFFERENCES s )"-S $" HAS A SIMPLE DEFAULT DATABASE STRUCTURE ! $" DATABASE IS ASSOCIATED WITH A RUNNING COPY OF THE $" SERVER SOFTWARE AND USERS ACCESS THE DATABASE BY CONNECTING TO THE $" SERVER ! $" hDATABASEv IS THUS EFFECTIVELY DEFINED BY AN INSTALLATION OF THE $" SOFTWARE ON A PARTICULAR COMPUTER SYSTEM
s -ICROSOFT 31, 3ERVER AND 3YBASE INCLUDE A #2%!4% $!4!"!3% STATEMENT AS PART OF THEIR $ATA $EFINITION ,ANGUAGE ! COMPANION $2/0 $!4!"!3% STATEMENT DESTROYS PREVIOUSLY CREATED DATABASES 4HESE STATEMENTS CAN BE USED WITH INTERACTIVE OR PROGRAMMATIC 31, 4HE NAMES OF THESE DATABASES ARE TRACKED IN A SPECIAL MASTER DATABASE THAT IS ASSOCIATED WITH A SINGLE INSTALLATION OF 31, 3ERVER 7HILE THE ARCHITECTURE IS DIFFERENT FROM $" AND /RACLE A 3YBASE OR 31, 3ERVER DATABASE IS SIMILAR IN CONCEPT TO AN /RACLE OR $" SCHEMA $ATABASE NAMES MUST BE UNIQUE WITHIN THIS 31, 3ERVER INSTALLATION /PTIONS TO THE #2%!4% $!4!"!3% STATEMENT SPECIFY THE PHYSICAL )/ DEVICE ON WHICH THE DATABASE IS TO BE LOCATED
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s /RACLE BY DEFAULT CAN CREATE A DATABASE AS PART OF THE /RACLE SOFTWARE INSTALLATION PROCESS LIKE $" DOES (OWEVER RARELY DOES AN /RACLE ADMINISTRATOR ALLOW THE INSTALLER TO CREATE THE DATABASE OPTING INSTEAD TO USE /RACLES #2%!4% $!4!"!3% COMMAND OR A '5) TOOL SUPPLIED BY /RACLE TO CREATE THE DATABASE WITH PARAMETER SETTINGS CUSTOMIZED FOR THE EXPECTED USE OF THE DATABASE &OR THE MOST PART EACH COPY OF THE /RACLE $"-3 SOFTWARE MANAGES A SINGLE DATABASE WHICH IS NAMED IN AN /RACLE CONFIGURATION FILE USER TABLES ARE PLACED WITHIN SCHEMAS IN THAT DATABASE .OTE THAT MULTIPLE /RACLE DATABASES CAN BE MANAGED ON A GIVEN SERVER OR MAINFRAME BUT IN THOSE ARRANGEMENTS EACH HAS ITS OWN COPY OF THE $"-3 SOFTWARE RUNNING ON THAT COMPUTER SYSTEM
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s )NFORMIX 5NIVERSAL 3ERVER NOW AN )"- PRODUCT SUPPORTS #2%!4% $!4!"!3% AND $2/0 $!4!"!3% 31, STATEMENTS AS WELL !N OPTION IN THE #2%!4% $!4!"!3% STATEMENT ALLOWS THE DATABASE TO BE CREATED IN A SPECIFIC DBSPACE WHICH IS A NAMED AREA OF DISK STORAGE CONTROLLED BY THE )NFORMIX SOFTWARE !NOTHER OPTION CONTROLS THE TYPE OF DATABASE LOGGING TO BE PERFORMED FOR THE NEW DATABASE WITH TRADE OFFS BETWEEN PERFORMANCE AND DATA INTEGRITY DURING SYSTEM FAILURES s -Y31, ALSO SUPPORTS #2%!4% $!4!"!3% AND $2/0 $!4!"!3% 31, STATEMENTS /PTIONS IN THE #2%!4% $!4!"!3% CONTROL STORAGE PARAMETERS AND THE CHOICE OF DATABASE ENGINES USED TO MANAGE THE DATABASE %ACH DATABASE IS PLACED IN ITS OWN DIRECTORY UNDER THE ROOT DIRECTORY FOR THE -Y31, INSTALLATION 4HE 31, STANDARD SPECIFICALLY AVOIDS A SPECIFICATION OF THE TERM DATABASE BECAUSE IT IS OVERLOADED WITH CONTRADICTORY MEANINGS FROM $"-3 PRODUCTS 4HE STANDARD USES THE TERM CATALOG TO DESCRIBE A NAMED COLLECTION OF TABLES THAT IS CALLED A DATABASE BY MOST POPULAR $"-3 BRANDS !DDITIONAL INFORMATION ABOUT THE DATABASE STRUCTURE SPECIFIED BY THE 31, STANDARD IS PROVIDED LATER IN THE SECTION h$ATABASE 3TRUCTURE AND THE !.3))3/ 3TANDARDv 4HE STANDARD DOES NOT SPECIFY HOW A CATALOG IS CREATED OR DESTROYED AND SPECIFICALLY SAYS THAT CREATION OR DESTRUCTION IS IMPLEMENTATION DEPENDENT )T ALSO INDICATES HOW MANY CATALOGS THERE ARE AND WHETHER INDIVIDUAL 31, STATEMENTS THAT CAN ACCESS DATA FROM DIFFERENT CATALOGS ARE IMPLEMENTATION DEFINED )N PRACTICE AS SHOWN BY THE PRECEDING EXAMPLES MANY OF THE MAJOR $"-3 VENDORS HAVE MOVED TOWARD THE USE OF A #2%!4% $!4!"!3%$2/0 $!4!"!3% STATEMENT PAIR
4ABLEõ$EFINITIONS 4HE MOST IMPORTANT STRUCTURE IN A RELATIONAL DATABASE IS THE TABLE )N A MULTIUSER PRODUCTION DATABASE THE MAJOR TABLES ARE TYPICALLY CREATED ONCE BY THE DATABASE ADMINISTRATOR AND THEN USED DAY AFTER DAY !S YOU USE THE DATABASE YOU WILL OFTEN FIND IT CONVENIENT TO DEFINE YOUR OWN TABLES TO STORE PERSONAL DATA OR DATA EXTRACTED FROM OTHER TABLES 4HESE TABLES MAY BE TEMPORARY LASTING FOR ONLY A SINGLE INTERACTIVE 31, SESSION OR MORE PERMANENT LASTING WEEKS OR MONTHS )N A PERSONAL COMPUTER DATABASE THE TABLE STRUCTURE IS EVEN MORE FLUID "ECAUSE YOU ARE BOTH THE USER AND THE DATABASE ADMINISTRATOR YOU CAN CREATE AND DESTROY TABLES TO SUIT YOUR OWN NEEDS WITHOUT WORRYING ABOUT OTHER USERS
#REATINGõAõ4ABLEõ#2%!4%õ4!",% 4HE #2%!4% 4!",% STATEMENT SHOWN IN &IGURE DEFINES A NEW TABLE IN THE DATABASE AND PREPARES IT TO ACCEPT DATA 4HE VARIOUS CLAUSES OF THE STATEMENT SPECIFY THE ELEMENTS OF THE TABLE DEFINITION 4HE SYNTAX DIAGRAM FOR THE STATEMENT APPEARS COMPLEX BECAUSE THERE ARE SO MANY PARTS OF THE DEFINITION TO BE SPECIFIED AND SO MANY OPTIONS FOR EACH ELEMENT )N ADDITION SOME OF THE OPTIONS ARE AVAILABLE IN SOME $"-3 BRANDS OR IN THE 31, STANDARD BUT NOT IN OTHER BRANDS )N PRACTICE CREATING A NEW TABLE IS RELATIVELY STRAIGHTFORWARD 7HEN YOU EXECUTE A #2%!4% 4!",% STATEMENT YOU BECOME THE OWNER OF THE NEWLY CREATED TABLE WHICH IS GIVEN THE NAME SPECIFIED IN THE STATEMENT !LTERNATIVELY IF YOU HAVE THE PRIVILEGE TO DO SO YOU MAY CREATE TABLES FOR OTHER USERS BY QUALIFYING THE TABLE NAME WITH THE IDENTIFIER OF A DIFFERENT OWNER 4HE TABLE NAME MUST BE A LEGAL 31, NAME AND IT MUST NOT CONFLICT WITH THE NAME OF ONE OF YOUR EXISTING TABLES 4HE NEWLY CREATED TABLE IS EMPTY BUT THE $"-3 PREPARES IT TO ACCEPT DATA ADDED WITH THE ).3%24 STATEMENT
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#OLUMNõ$EFINITIONS 4HE COLUMNS OF THE NEWLY CREATED TABLE ARE DEFINED IN THE BODY OF THE #2%!4% 4!",% STATEMENT 4HE COLUMN DEFINITIONS APPEAR IN A COMMA SEPARATED LIST ENCLOSED IN PARENTHESES 4HE ORDER OF THE COLUMN DEFINITIONS DETERMINES THE LEFT TO RIGHT ORDER OF THE COLUMNS IN THE TABLE )N THE #2%!4% 4!",% STATEMENTS SUPPORTED BY THE MAJOR $"-3 BRANDS EACH COLUMN DEFINITION SPECIFIES THE FOLLOWING s #OLUMN NAME 5SED TO REFER TO THE COLUMN IN 31, STATEMENTS %VERY COLUMN IN THE TABLE MUST HAVE A UNIQUE NAME BUT THE NAMES MAY DUPLICATE THOSE OF COLUMNS IN OTHER TABLES s $ATA TYPE OR DOMAIN )DENTIFIES THE KIND OF DATA THAT THE COLUMN STORES $ATA TYPES WERE DISCUSSED IN #HAPTER $OMAINS DESCRIBED IN #HAPTER ARE SPECIFIED IN THE 31, STANDARD BUT VERY FEW $"-3 PRODUCTS SUPPORT THEM 3OME DATA TYPES SUCH AS 6!2#(!2 AND $%#)-!, REQUIRE ADDITIONAL INFORMATION FOR EXAMPLE THE LENGTH OR NUMBER OF DECIMAL PLACES IN THE DATA 4HIS ADDITIONAL INFORMATION IS ENCLOSED IN PARENTHESES FOLLOWING THE KEYWORD THAT SPECIFIES THE DATA TYPE s 2EQUIRED DATA $ETERMINES WHETHER THE COLUMN CONTAINS REQUIRED DATA AND PREVENTS .5,, VALUES FROM APPEARING IN THE COLUMN OTHERWISE .5,, VALUES ARE ALLOWED s $EFAULT VALUE 5SES AN OPTIONAL DEFAULT VALUE FOR THE COLUMN WHEN AN ).3%24 STATEMENT FOR THE TABLE DOES NOT SPECIFY A VALUE FOR THE COLUMN 4HE 31, STANDARD ALLOWS SEVERAL ADDITIONAL PARTS OF A COLUMN DEFINITION WHICH CAN BE USED TO REQUIRE THAT THE COLUMN CONTAINS UNIQUE VALUES TO SPECIFY THAT THE COLUMN IS A PRIMARY KEY OR A FOREIGN KEY OR TO RESTRICT THE DATA VALUES THAT THE COLUMN MAY CONTAIN 4HESE ARE SINGLE COLUMN VERSIONS OF CAPABILITIES PROVIDED BY OTHER CLAUSES IN THE #2%!4% 4!",% STATEMENT AND ARE DESCRIBED AS PART OF THAT STATEMENT IN THE FOLLOWING SECTIONS (ERE ARE SOME SIMPLE #2%!4% 4!",% STATEMENTS FOR THE TABLES IN THE SAMPLE DATABASE $ElNE THE /&&)#%3 TABLE AND ITS COLUMNS #2%!4% 4!",% /&&)#%3 /&&)#% ).4%'%2 ./4 .5,, #)49 6!2#(!2 ./4 .5,, 2%')/. 6!2#(!2 ./4 .5,, -'2 ).4%'%2 4!2'%4 $%#)-!, 3!,%3 $%#)-!, ./4 .5,,
$ElNE THE /2$%23 TABLE AND ITS COLUMNS #2%!4% 4!",% /2$%23 /2$%2?.5- ).4%'%2 ./4 .5,, /2$%2?$!4% $!4% ./4 .5,, #534 ).4%'%2 ./4 .5,, 2%0 ).4%'%2 -&2 #(!2 ./4 .5,, 02/$5#4 #(!2 ./4 .5,, 149 ).4%'%2 ./4 .5,, !-/5.4 $%#)-!, ./4 .5,,
#HAPTERçç
#REATINGçAç$ATABASEç
4HE #2%!4% 4!",% STATEMENT FOR A GIVEN TABLE CAN VARY SLIGHTLY FROM ONE $"-3 BRAND TO ANOTHER BECAUSE EACH $"-3 SUPPORTS ITS OWN SET OF DATA TYPES AND USES ITS OWN KEYWORDS TO IDENTIFY THEM IN THE COLUMN DEFINITIONS )N ADDITION THE 31, STANDARD ALLOWS YOU TO SPECIFY A DOMAIN INSTEAD OF A DATA TYPE WITHIN A COLUMN DEFINITION $OMAINS ARE DESCRIBED IN #HAPTER ! DOMAIN IS A SPECIFIC COLLECTION OF VALID DATA VALUES WHICH IS DEFINED WITHIN THE DATABASE AND ASSIGNED A NAME 4HE DOMAIN DEFINITION IS BASED ON ONE OF THE $"-3 SUPPORTED DATA TYPES BUT PERFORMS ADDITIONAL DATA VALUE CHECKING THAT RESTRICTS THE LEGAL VALUES &OR EXAMPLE IF THIS DOMAIN DEFINITION APPEARED IN A 31, COMPLIANT DATABASE #2%!4% $/-!). 6!,)$?/&&)#%?)$ ).4%'%2 #(%#+ 6!,5% "%47%%. !.$
THEN THE /&&)#%3 TABLE DEFINITION COULD BE MODIFIED TO $ElNE THE /&&)#%3 TABLE AND ITS COLUMNS #2%!4% 4!",% /&&)#%3 /&&)#% 6!,)$?/&&)#%?)$ ./4 .5,, #)49 6!2#(!2 ./4 .5,, 2%')/. 6!2#(!2 ./4 .5,, -'2 ).4%'%2 4!2'%4 $%#)-!, 3!,%3 $%#)-!, ./4 .5,,
-ISSINGõANDõ$EFAULTõ6ALUES 4HE DEFINITION OF EACH COLUMN WITHIN A TABLE TELLS THE $"-3 WHETHER THE DATA FOR THE COLUMN IS ALLOWED TO BE MISSINGTHAT IS WHETHER THE COLUMN IS ALLOWED TO HAVE A .5,, VALUE )N MOST OF THE MAJOR $"-3 BRANDS AND IN THE 31, STANDARD THE DEFAULT IS TO ALLOW MISSING DATA FOR A COLUMN )F THE COLUMN MUST CONTAIN A LEGAL DATA VALUE FOR EVERY ROW OF A TABLE THEN ITS DEFINITION MUST INCLUDE THE ./4 .5,, CLAUSE 4HE 3YBASE !3% AND -ICROSOFT 31, 3ERVER $"-3 PRODUCTS USE THE OPPOSITE CONVENTION ASSUMING THAT .5,, VALUES ARE NOT ALLOWED UNLESS THE COLUMN IS EXPLICITLY DECLARED .5,, OR UNLESS THE DEFAULT NULLABILITY MODE DEFINED FOR THE DATABASE IS SET TO ALLOW .5,,S BY DEFAULT 4HE 31, STANDARD AND MANY OF THE MAJOR 31, $"-3 PRODUCTS SUPPORT DEFAULT VALUES FOR COLUMNS )F A COLUMN HAS A DEFAULT VALUE IT IS SPECIFIED WITHIN THE COLUMN DEFINITION &OR EXAMPLE HERE IS A #2%!4% 4!",% STATEMENT FOR THE /&&)#%3 TABLE THAT SPECIFIES DEFAULT VALUES
0!24ç)6
AND THE $"-3 WOULD AUTOMATICALLY CHECK ANY NEWLY INSERTED ROWS TO ENSURE THAT THEIR OFFICE NUMBERS FALL IN THE DESIGNATED RANGE $OMAINS ARE PARTICULARLY EFFECTIVE WHEN THE SAME LEGAL DATA VALUE RESTRICTIONS APPLY TO MANY DIFFERENT COLUMNS WITHIN THE DATABASE )N THE SAMPLE DATABASE OFFICE NUMBERS APPEAR IN THE /&&)#%3 AND THE 3!,%32%03 TABLE AND THE 6!,)$?/&&)#%?)$ DOMAIN WOULD BE USED TO DEFINE THE COLUMNS IN BOTH OF THESE TABLES ! REAL WORLD DATABASE MAY HAVE DOZENS OR HUNDREDS OF SUCH COLUMNS WHOSE DATA IS DRAWN FROM THE SAME DOMAIN
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0ARTç)6ç
$ATABASEç3TRUCTURE
$ElNE THE /&&)#%3 TABLE WITH DEFAULT VALUES !.3))3/ SYNTAX #2%!4% 4!",% /&&)#%3 /&&)#% ).4%'%2 ./4 .5,, #)49 6!2#(!2 ./4 .5,, 2%')/. 6!2#(!2 ./4 .5,, $%&!5,4 g%ASTERNg -'2 ).4%'%2 $%&!5,4 4!2'%4 $%#)-!, $%&!5,4 .5,, 3!,%3 $%#)-!, ./4 .5,, $%&!5,4
7ITH THIS TABLE DEFINITION ONLY THE OFFICE NUMBER AND THE CITY NEED TO BE SPECIFIED WHEN YOU INSERT A NEW OFFICE 4HE REGION DEFAULTS TO %ASTERN THE OFFICE MANAGER TO 3AM #LARK EMPLOYEE NUMBER THE SALES TO ZERO AND THE TARGET TO .5,, .OTE THAT THE TARGET WOULD DEFAULT TO .5,, EVEN WITHOUT THE $%&!5,4 .5,, SPECIFICATION
0RIMARYõANDõ&OREIGNõ+EYõ$EFINITIONS )N ADDITION TO DEFINING THE COLUMNS OF A TABLE THE #2%!4% 4!",% STATEMENT CAN IDENTIFY A PRIMARY KEY FOR THE TABLE AND FOR RELATIONSHIPS TO OTHER TABLES IN THE DATABASE 4HE 02)-!29 +%9 AND &/2%)'. +%9 CLAUSES HANDLE THESE FUNCTIONS 4HESE CLAUSES HAVE BEEN SUPPORTED BY THE )"- 31, DATABASES FOR SOME TIME AND HAVE BEEN ADDED TO THE !.3))3/ SPECIFICATION -OST MAJOR 31, PRODUCTS SUPPORT THEM 4HE 02)-!29 +%9 CLAUSE SPECIFIES THE COLUMN OR COLUMNS THAT FORM THE PRIMARY KEY FOR THE TABLE 2ECALL FROM #HAPTER THAT THIS COLUMN OR COLUMN COMBINATION SERVES AS A UNIQUE IDENTIFIER FOR EACH ROW OF THE TABLE 4HE $"-3 AUTOMATICALLY REQUIRES THAT THE PRIMARY KEY VALUE BE UNIQUE IN EVERY ROW OF THE TABLE )N ADDITION THE COLUMN DEFINITION FOR EVERY COLUMN IN THE PRIMARY KEY MUST SPECIFY THAT THE COLUMN IS ./4 .5,, 4HE &/2%)'. +%9 CLAUSE SPECIFIES A FOREIGN KEY IN THE TABLE AND THE RELATIONSHIP THAT IT CREATES TO ANOTHER PARENT TABLE IN THE DATABASE 4HE CLAUSE SPECIFIES s 4HE COLUMN OR COLUMNS THAT FORM THE FOREIGN KEY ALL OF WHICH ARE COLUMNS OF THE TABLE BEING CREATED s 4HE TABLE THAT IS REFERENCED BY THE FOREIGN KEY 4HIS IS THE PARENT TABLE IN THE RELATIONSHIP THE TABLE BEING DEFINED IS THE CHILD s !N OPTIONAL LIST OF THE COLUMN NAMES IN THE PARENT TABLE THAT ARE TO BE MATCHED WITH THE FOREIGN KEY COLUMNS IN THE TABLE BEING DEFINED )F THE COLUMN NAMES ARE OMITTED THEN COLUMN NAMES IDENTICAL TO THE FOREIGN KEY COLUMNS MUST EXIST IN THE PARENT TABLE s !N OPTIONAL NAME FOR THE RELATIONSHIP 4HE NAME IS NOT USED IN ANY 31, DATA MANIPULATION STATEMENTS BUT IT MAY APPEAR IN ERROR MESSAGES AND IS REQUIRED IF YOU WANT TO BE ABLE TO DROP THE FOREIGN KEY LATER s (OW THE $"-3 SHOULD TREAT A .5,, VALUE IN ONE OR MORE COLUMNS OF THE FOREIGN KEY WHEN MATCHING IT AGAINST ROWS OF THE PARENT TABLE s !N OPTIONAL DELETE RULE FOR THE RELATIONSHIP #!3#!$% 3%4 .5,, 3%4 $%&!5,4 OR ./ !#4)/. AS DESCRIBED IN #HAPTER WHICH DETERMINES THE ACTION TO TAKE WHEN A PARENT ROW IS DELETED s !N OPTIONAL UPDATE RULE FOR THE RELATIONSHIP AS DESCRIBED IN #HAPTER WHICH DETERMINES THE ACTION TO TAKE WHEN PART OF THE PRIMARY KEY IN A PARENT ROW IS UPDATED s !N OPTIONAL CHECK CONSTRAINT WHICH RESTRICTS THE DATA IN THE TABLE SO THAT ITS ROWS MEET A SPECIFIED SEARCH CONDITION
#HAPTERçç
#REATINGçAç$ATABASEç
(ERE IS AN EXPANDED #2%!4% 4!",% STATEMENT FOR THE /2$%23 TABLE WHICH INCLUDES A DEFINITION OF ITS PRIMARY KEY AND THE THREE FOREIGN KEYS THAT IT CONTAINS $ElNE THE /2$%23 TABLE WITH ITS PRIMARY AND FOREIGN KEYS #2%!4% 4!",% /2$%23 /2$%2?.5- ).4%'%2 ./4 .5,, /2$%2?$!4% $!4% ./4 .5,, #534 ).4%'%2 ./4 .5,, 2%0 ).4%'%2 -&2 #(!2 ./4 .5,, 02/$5#4 #(!2 ./4 .5,, 149 ).4%'%2 ./4 .5,, !-/5.4 $%#)-!, ./4 .5,, 02)-!29 +%9 /2$%2?.5- #/.342!).4 0,!#%$"9 &/2%)'. +%9 #534 2%&%2%.#%3 #534/-%23 /. $%,%4% #!3#!$% #/.342!).4 4!+%."9 &/2%)'. +%9 2%0 2%&%2%.#%3 3!,%32%03 /. $%,%4% 3%4 .5,, #/.342!).4 )3&/2 &/2%)'. +%9 -&2 02/$5#4 2%&%2%.#%3 02/$5#43 /. $%,%4% 2%342)#4
0!24ç)6
&IGURE SHOWS THE THREE RELATIONSHIPS CREATED BY THIS STATEMENT AND THE NAMES IT ASSIGNS TO THEM )N GENERAL ITS A GOOD IDEA TO ASSIGN A RELATIONSHIP NAME BECAUSE IT HELPS TO CLARIFY THE RELATIONSHIP CREATED BY THE FOREIGN KEY &OR EXAMPLE EACH ORDER WAS PLACED BY THE CUSTOMER WHOSE NUMBER APPEARS IN THE #534 COLUMN OF THE /2$%23 TABLE 4HE RELATIONSHIP CREATED BY THIS COLUMN HAS BEEN GIVEN THE NAME 0,!#%$"9 7HEN THE $"-3 PROCESSES THE #2%!4% 4!",% STATEMENT IT CHECKS EACH FOREIGN KEY DEFINITION AGAINST THE DEFINITION OF THE TABLE THAT IT REFERENCES 4HE $"-3 MAKES SURE THAT THE FOREIGN KEY AND THE PRIMARY KEY OF THE REFERENCED TABLE AGREE IN THE NUMBER OF COLUMNS THEY CONTAIN AND IN THEIR DATA TYPES 4HE REFERENCED TABLE MUST ALREADY BE DEFINED IN THE DATABASE FOR THIS CHECKING TO SUCCEED .OTE THAT THE &/2%)'. +%9 CLAUSE ALSO SPECIFIES THE DELETE AND UPDATE RULES THAT ARE TO BE ENFORCED FOR THE PARENTCHILD TABLE RELATIONSHIP THAT IT CREATES $ELETE AND UPDATE RULES AND THE ACTIONS THAT CAN TRIGGER THEM ARE DESCRIBED IN #HAPTER 4HE $"-3 ENFORCES THE DEFAULT RULES ./ !#4)/. IF NO RULE IS EXPLICITLY SPECIFIED )F YOU WANT TO CREATE TWO OR MORE TABLES FROM A REFERENTIAL CYCLE LIKE THE /&&)#%3 AND 3!,%32%03 TABLES IN THE SAMPLE DATABASE YOU CANNOT INCLUDE THE FOREIGN KEY DEFINITION IN THE FIRST #2%!4% 4!",% STATEMENT BECAUSE THE REFERENCED TABLE DOES NOT YET EXIST 4HE $"-3 WILL REJECT THE ATTEMPTED #2%!4% 4!",% STATEMENT WITH AN ERROR SAYING THAT THE TABLE DEFINITION REFERS TO AN UNDEFINED TABLE )NSTEAD YOU MUST CREATE THE FIRST TABLE WITHOUT ITS FOREIGN KEY DEFINITION AND ADD THE FOREIGN KEY LATER BY USING THE !,4%2 4!",% STATEMENT 4HE 31, STANDARD AND SEVERAL OF THE MAJOR $"-3 PRODUCTS OFFER A DIFFERENT SOLUTION TO THIS PROBLEM WITH THE #2%!4% 3#(%-! STATEMENT WHICH CREATES AN ENTIRE SET OF TABLES AT ONCE 4HIS STATEMENT AND THE OTHER DATABASE OBJECTS INCLUDED WITHIN A 31, SCHEMA ARE DESCRIBED LATER IN THE h3CHEMASv SECTION
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0ARTç)6ç
$ATABASEç3TRUCTURE
1, Ê£ÎÓÊ ,i>ÌÃ
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iÊ#2%!4% 4!",%ÊÃÌ>ÌiiÌ
5NIQUENESSõ#ONSTRAINTS 4HE 31, STANDARD SPECIFIES THAT UNIQUENESS CONSTRAINTS ARE ALSO DEFINED IN THE #2%!4% 4!",% STATEMENT USING THE 5.)15% CLAUSE SHOWN IN &IGURE (ERE IS A #2%!4% 4!",% STATEMENT FOR THE /&&)#%3 TABLE MODIFIED TO REQUIRE UNIQUE #)49 VALUES $ElNE THE /&&)#%3 TABLE WITH A UNIQUENESS CONSTRAINT #2%!4% 4!",% /&&)#%3 /&&)#% ).4%'%2 ./4 .5,, #)49 6!2#(!2 ./4 .5,, 2%')/. 6!2#(!2 ./4 .5,, -'2 ).4%'%2 4!2'%4 $%#)-!, 3!,%3 $%#)-!, ./4 .5,, 02)-!29 +%9 /&&)#% #/.342!).4 (!3-'2 &/2%)'. +%9 -'2 2%&%2%.#%3 3!,%32%03 /. $%,%4% 3%4 .5,, 5.)15% #)49
#HAPTERçç
#REATINGçAç$ATABASEç
)F A PRIMARY KEY FOREIGN KEY UNIQUENESS CONSTRAINT OR CHECK CONSTRAINT INVOLVES A SINGLE COLUMN THE !.3))3/ STANDARD PERMITS A SHORTHAND FORM OF THE DEFINITION 4HE PRIMARY KEY FOREIGN KEY UNIQUENESS CONSTRAINT OR CHECK CONSTRAINT IS SIMPLY ADDED TO THE END OF THE COLUMN DEFINITION AS SHOWN IN THIS EXAMPLE $ElNE THE /&&)#%3 TABLE WITH A UNIQUENESS CONSTRAINT !.3))3/ SYNTAX #2%!4% 4!",% /&&)#%3 /&&)#% ).4%'%2 ./4 .5,, 02)-!29 +%9 #)49 6!2#(!2 ./4 .5,, 5.)15% 2%')/. 6!2#(!2 ./4 .5,, -'2 ).4%'%2 2%&%2%.#%3 3!,%32%03 4!2'%4 $%#)-!, 3!,%3 $%#)-!, ./4 .5,,
3EVERAL OF THE MAJOR $"-3 BRANDS INCLUDING 31, 3ERVER )NFORMIX 3YBASE AND $" SUPPORT THIS SHORTHAND
#HECKõ#ONSTRAINTS !NOTHER 31, DATA INTEGRITY FEATURE THE CHECK CONSTRAINT DESCRIBED IN #HAPTER IS ALSO SPECIFIED IN THE #2%!4% 4!",% STATEMENT ! CHECK CONSTRAINT SPECIFIES A CHECK CONDITION IDENTICAL IN FORM TO A SEARCH CONDITION IN A 31, QUERY THAT IS CHECKED EVERY TIME AN ATTEMPT IS MADE TO MODIFY THE CONTENTS OF THE TABLE WITH AN ).3%24 50$!4% OR $%,%4% STATEMENT )F THE CHECK CONDITION REMAINS 425% AFTER THE MODIFICATION IT IS ALLOWED OTHERWISE THE $"-3 DISALLOWS THE ATTEMPT TO MODIFY THE DATA AND RETURNS AN ERROR 4HE FOLLOWING IS A #2%!4% 4!",% STATEMENT FOR THE /&&)#%3 TABLE WITH A VERY SIMPLE CHECK CONDITION TO MAKE SURE THE 4!2'%4 FOR THE OFFICE IS GREATER THAN
#2%!4% 4!",% /&&)#%3 /&&)#% ).4%'%2 ./4 .5,, #)49 6!2#(!2 ./4 .5,, 2%')/. 6!2#(!2 ./4 .5,, -'2 ).4%'%2 4!2'%4 $%#)-!, 3!,%3 $%#)-!, ./4 .5,, 02)-!29 +%9 /&&)#% #/.342!).4 (!3-'2 &/2%)'. +%9 -'2 2%&%2%.#%3 3!,%32%03 /. $%,%4% 3%4 .5,, #(%#+ 4!2'%4
9OU CAN OPTIONALLY SPECIFY A NAME FOR THE CHECK CONSTRAINT WHICH WILL BE USED BY THE $"-3 WHEN IT REPORTS AN ERROR IF THE CONSTRAINT IS VIOLATED (ERE IS A SLIGHTLY MORE COMPLEX CHECK CONSTRAINT FOR THE 3!,%32%03 TABLE TO ENFORCE THE RULE h3ALESPEOPLE WHOSE HIRE DATE
0!24ç)6
$ElNE THE /&&)#%3 TABLE WITH A UNIQUENESS CONSTRAINT
ç
0ARTç)6ç
$ATABASEç3TRUCTURE
IS LATER THAN *ANUARY SHALL NOT BE ASSIGNED QUOTAS HIGHER THAN v 4HE #2%!4% 4!",% STATEMENT NAMES THIS CONSTRAINT 15/4!?#!0 #2%!4% 4!",% 3!,%32%03 %-0,?.5- ).4%'%2 ./4 .5,, .!-% 6!2#(!2 ./4 .5,, #/.342!).4 7/2+3). &/2%)'. +%9 2%0?/&&)#% 2%&%2%.#%3 /&&)#%3 /. $%,%4% 3%4 .5,, #/.342!).4 15/4!?#!0 #(%#+ ()2%?$!4% g g /2 15/4!
4HIS CHECK CONSTRAINT CAPABILITY IS SUPPORTED BY MANY OF THE MAJOR $"-3 BRANDS
0HYSICALõ3TORAGEõ$EFINITION
4HE #2%!4% 4!",% STATEMENT TYPICALLY INCLUDES ONE OR MORE OPTIONAL CLAUSES THAT SPECIFY PHYSICAL STORAGE CHARACTERISTICS FOR A TABLE 'ENERALLY THESE CLAUSES ARE USED ONLY BY THE DATABASE ADMINISTRATOR TO OPTIMIZE THE PERFORMANCE OF A PRODUCTION DATABASE "Y THEIR NATURE THESE CLAUSES ARE VERY SPECIFIC TO A PARTICULAR $"-3 !LTHOUGH THEY ARE OF LITTLE PRACTICAL INTEREST TO MOST 31, USERS THE DIFFERENT PHYSICAL STORAGE STRUCTURES PROVIDED BY VARIOUS $"-3 PRODUCTS ILLUSTRATE THEIR DIFFERENT INTENDED APPLICATIONS AND LEVELS OF SOPHISTICATION -OST OF THE PERSONAL COMPUTER DATABASES PROVIDE VERY SIMPLE PHYSICAL STORAGE MECHANISMS -ANY PERSONAL COMPUTER DATABASE PRODUCTS STORE AN ENTIRE DATABASE WITHIN A SINGLE 7INDOWS FILE OR USE A SEPARATE 7INDOWS FILE FOR EACH DATABASE TABLE 4HEY MAY ALSO REQUIRE THAT THE ENTIRE TABLE OR DATABASE BE STORED ON A SINGLE PHYSICAL DISK VOLUME -ULTIUSER DATABASES TYPICALLY PROVIDE MORE SOPHISTICATED PHYSICAL STORAGE SCHEMES TO SUPPORT IMPROVED DATABASE PERFORMANCE &OR EXAMPLE )NGRES ALLOWS THE DATABASE ADMINISTRATOR TO DEFINE MULTIPLE NAMED LOCATIONS WHICH ARE PHYSICAL DIRECTORIES WHERE DATABASE DATA CAN BE STORED 4HE LOCATIONS CAN BE SPREAD ACROSS MULTIPLE DISK VOLUMES TO TAKE ADVANTAGE OF PARALLEL DISK INPUTOUTPUT OPERATIONS 9OU CAN OPTIONALLY SPECIFY ONE OR MORE LOCATIONS FOR A TABLE IN THE )NGRES #2%!4% 4!",% STATEMENT #2%!4% 4!",% /&&)#%3 TABLE DEFINITION 7)4( ,/#!4)/. !2%! !2%! !2%!
"Y SPECIFYING MULTIPLE LOCATIONS YOU CAN SPREAD A TABLES CONTENTS ACROSS SEVERAL DISK VOLUMES FOR GREATER PARALLEL ACCESS TO THE TABLE 3YBASE !3% OFFERS A SIMILAR APPROACH ALLOWING THE DATABASE ADMINISTRATOR TO SPECIFY MULTIPLE NAMED LOGICAL DATABASE DEVICES THAT ARE USED TO STORE DATA 4HE CORRESPONDENCE BETWEEN 3YBASES LOGICAL DEVICES AND THE ACTUAL PHYSICAL DISK DRIVES OF THE COMPUTER SYSTEM IS HANDLED BY A 3YBASE UTILITY PROGRAM AND NOT WITHIN THE 31, 4HE 3YBASE #2%!4% $!4!"!3% STATEMENT CAN THEN SPECIFY THAT A DATABASE SHOULD BE STORED ON ONE OR MORE DATABASE DEVICES #2%!4% $!4!"!3% /0$!4! /. $"&),% $"&),% $"&),%
#HAPTERçç
#REATINGçAç$ATABASEç
7ITHIN A GIVEN DATABASE DEVICE 3YBASE THEN ALLOWS THE DATABASE ADMINISTRATOR TO DEFINE LOGICAL SEGMENTS USING ONE OF THE 3YBASE SYSTEM PROVIDED STORED PROCEDURES &INALLY A 3YBASE #2%!4% 4!",% STATEMENT CAN SPECIFY THE SEGMENT WHERE A TABLES DATA IS TO BE STORED #2%!4% 4!",% /&&)#%3 TABLE DEFINITION /. 3%'-%.4 3%'!
$" OFFERS A SIMILARLY COMPREHENSIVE SCHEME FOR MANAGING PHYSICAL STORAGE BASED ON THE CONCEPTS OF TABLESPACES AND NODEGROUPS ! TABLESPACE IS A LOGICAL LEVEL STORAGE CONTAINER WHEREAS NODEGROUPS ARE DEFINED MORE SPECIFICALLY IN TERMS OF PHYSICAL STORAGE 7HEN YOU CREATE A $" TABLE YOU CAN OPTIONALLY ASSIGN IT TO A SPECIFIC TABLESPACE #2%!4% 4!",% /&&)#%3 TABLE DEFINITION ). !$-).$"/030!#%
5NLIKE 3YBASE $" PUTS MOST OF THE MANAGEMENT OF THESE STORAGE ENTITIES WITHIN THE 31, ITSELF THROUGH THE #2%!4% 4!",%30!#% AND #2%!4% ./$%'2/50 STATEMENTS ! CONSEQUENCE IS THAT THESE STATEMENTS INCLUDE OPERATING SYSTEMnDEPENDENT SPECIFICATIONS OF FILENAMES AND DIRECTORIES WHICH VARY FROM ONE SUPPORTED $" OPERATING SYSTEM TO ANOTHER /THER CLAUSES SPECIFY THE $" BUFFER POOL TO BE USED THE OVERHEAD AND TRANSFER RATE OF THE STORAGE MEDIUM AND OTHER CHARACTERISTICS CLOSELY RELATED TO THE PHYSICAL STORAGE MEDIUM $" USES THIS INFORMATION IN ITS PERFORMANCE OPTIMIZATION ALGORITHMS 31, 3ERVER SUPPORTS THE CREATION OF FILEGROUPS WHICH ARE LOGICAL EQUIVALENTS TO TABLESPACES %ACH FILEGROUP HAS ONE OR MORE PHYSICAL FILES ASSIGNED TO IT ! DEFAULT FILEGROUP IS ASSIGNED TO EACH DATABASE WHEN IT IS CREATED AND TABLES CREATED IN THAT DATABASE ARE STORED IN THAT FILEGROUP UNLESS OTHERWISE SPECIFIED IN THE #2%!4% 4!",% STATEMENT LIKE THIS
/RACLE SUPPORTS THE CREATION OF TABLESPACES IN A MANNER SIMILAR TO $" ! TABLESPACE HAS ONE OR MORE PHYSICAL FILES ASSIGNED TO IT ! DEFAULT TABLESPACE CAN BE ASSIGNED GLOBALLY OR FOR EACH USER SCHEMA 7HEN A TABLE IS CREATED THE TABLESPACE AND VARIOUS PHYSICAL STORAGE ATTRIBUTES SUCH AS AN INITIAL SIZE ALLOCATION THE INCREMENTAL AMOUNT TO BE ADDED WHEN MORE SPACE IS NEEDED AND A PERCENTAGE TO INCREASE EACH ADDITIONAL ALLOCATION CAN BE SPECIFIED #2%!4% 4!",% /&&)#%3 TABLE DEFINITION 4!",%30!#% TABLESPACE NAME 34/2!'% ).)4)!, INITIAL SIZE .%84 INCREMENTAL SIZE 0#4).#2%!3% GROWTH PERCENT
2EMOVINGõAõ4ABLEõ$2/0õ4!",% /VER TIME THE STRUCTURE OF A DATABASE GROWS AND CHANGES .EW TABLES ARE CREATED TO REPRESENT NEW ENTITIES AND SOME OLD TABLES ARE NO LONGER NEEDED 9OU CAN REMOVE AN UNNEEDED TABLE FROM THE DATABASE WITH THE $2/0 4!",% STATEMENT SHOWN IN &IGURE
1, Ê£ÎÎÊ $2/0 4!",%ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
0!24ç)6
#2%!4% 4!",% /&&)#%3 TABLE DEFINITION /. FILEGROUP NAME
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0ARTç)6ç
$ATABASEç3TRUCTURE
4HE TABLE NAME IN THE STATEMENT IDENTIFIES THE TABLE TO BE DROPPED .ORMALLY YOU WILL BE DROPPING ONE OF YOUR OWN TABLES AND WILL USE AN UNQUALIFIED TABLE NAME 7ITH PROPER PERMISSION YOU CAN ALSO DROP A TABLE OWNED BY ANOTHER USER BY SPECIFYING A QUALIFIED TABLE NAME (ERE ARE SOME EXAMPLES OF THE $2/0 4!",% STATEMENT 4HE #534/-%23 TABLE HAS BEEN REPLACED BY TWO NEW TABLES #534?).&/ AND !##/5.4?).&/ AND IS NO LONGER NEEDED $2/0 4!",% #534/-%23
3AM HAS GIVEN YOU PERMISSION TO DROP HIS TABLE NAMED ")24($!93 $2/0 4!",% 3!-")24($!93
7HEN THE $2/0 4!",% STATEMENT REMOVES A TABLE FROM THE DATABASE ITS DEFINITION AND ALL OF ITS CONTENTS ARE LOST )N MOST 31, PRODUCTS THERE IS NO WAY TO RECOVER THE DATA AND YOU WOULD HAVE TO USE A NEW #2%!4% 4!",% STATEMENT TO RE CREATE THE TABLE DEFINITION (OWEVER /RACLE NOW ALLOWS DROPPED TABLES TO BE RECOVERED FROM THE 2ECYCLE "IN AND OTHER VENDORS MAY SOON FOLLOW SUIT "ECAUSE OF ITS SERIOUS CONSEQUENCES YOU SHOULD USE THE $2/0 4!",% STATEMENT WITH CARE 4HE 31, STANDARD REQUIRES THAT A $2/0 4!",% STATEMENT INCLUDE EITHER #!3#!$% OR 2%342)#4 WHICH SPECIFIES THE IMPACT OF DROPPING A TABLE ON OTHER DATABASE OBJECTS SUCH AS VIEWS DESCRIBED IN #HAPTER THAT DEPEND ON THE TABLE )F #!3#!$% IS SPECIFIED THE $2/0 4!",% STATEMENT FAILS IF OTHER DATABASE OBJECTS REFERENCE THE TABLE -OST COMMERCIAL $"-3 PRODUCTS ACCEPT THE $2/0 4!",% STATEMENT WITH NO OPTION SPECIFIED (ERE ARE SOME EXCEPTIONS s -Y31, ALLOWS 2%342)#4 OR #!3#!$% TO BE SPECIFIED FOR COMPATIBILITY BUT AS OF VERSION THEY HAVE NO EFFECT s /RACLE DEFAULTS TO 2%342)#4 WHICH CANNOT BE EXPLICITLY SPECIFIED AND REQUIRES THE KEYWORDS #!3#!$% #/.342!).43 INSTEAD OF #!3#!$% s 31, 3ERVER AND $" DO NOT SUPPORT THE 2%342)#4 OR #!3#!$% OPTIONS
#HANGINGõAõ4ABLEõ$EFINITIONõ!,4%2õ4!",% !FTER A TABLE HAS BEEN IN USE FOR SOME TIME USERS OFTEN DISCOVER THAT THEY WANT TO STORE ADDITIONAL INFORMATION ABOUT THE ENTITIES REPRESENTED IN THE TABLE )N THE SAMPLE DATABASE FOR EXAMPLE YOU MIGHT WANT TO s !DD THE NAME AND PHONE NUMBER OF A KEY CONTACT PERSON TO EACH ROW OF THE #534/-%23 TABLE AS YOU BEGIN TO USE IT FOR CONTACTING CUSTOMERS s !DD A MINIMUM INVENTORY LEVEL COLUMN TO THE 02/$5#43 TABLE SO THE DATABASE CAN AUTOMATICALLY ALERT YOU WHEN STOCK OF A PARTICULAR PRODUCT IS LOW s -AKE THE 2%')/. COLUMN IN THE /&&)#%3 TABLE A FOREIGN KEY FOR A NEWLY CREATED 2%')/.3 TABLE WHOSE PRIMARY KEY IS THE REGION NAME s $ROP THE FOREIGN KEY DEFINITION LINKING THE #534 COLUMN IN THE /2$%23 TABLE TO THE #534/-%23 TABLE REPLACING IT WITH TWO FOREIGN KEY DEFINITIONS LINKING THE #534 COLUMN TO THE NEWLY CREATED #534?).&/ AND !##/5.4?).&/ TABLES
#HAPTERçç
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1, Ê£Î{Ê !,4%2 4!",%ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
%ACH OF THESE CHANGES AND SOME OTHERS CAN BE HANDLED WITH THE !,4%2 4!",% STATEMENT SHOWN IN &IGURE !S WITH THE $2/0 4!",% STATEMENT YOU WILL NORMALLY USE THE !,4%2 4!",% STATEMENT ON ONE OF YOUR OWN TABLES 7ITH PROPER PERMISSION HOWEVER YOU CAN SPECIFY A QUALIFIED TABLE NAME AND ALTER THE DEFINITION OF ANOTHER USERS TABLE !S SHOWN IN THE FIGURE THE !,4%2 4!",% STATEMENT CAN s !DD A COLUMN DEFINITION TO A TABLE s $ROP A COLUMN FROM A TABLE s #HANGE THE DEFAULT VALUE FOR A COLUMN s !DD OR DROP A NEW FOREIGN KEY FOR A TABLE s !DD OR DROP A UNIQUENESS CONSTRAINT FOR A TABLE s !DD OR DROP A CHECK CONSTRAINT FOR A TABLE 4HE CLAUSES IN &IGURE ARE SPECIFIED IN THE 31, STANDARD -ANY $"-3 BRANDS LACK SUPPORT FOR SOME OF THESE CLAUSES SUPPORT SOMEWHAT DIFFERENT SYNTAX OR OFFER CLAUSES UNIQUE TO THE $"-3 WHICH ALTERS OTHER TABLE CHARACTERISTICS 4HE 31, STANDARD RESTRICTS EACH !,4%2 4!",% STATEMENT TO A SINGLE TABLE CHANGE !DDING A COLUMN AND DEFINING A NEW FOREIGN KEY FOR EXAMPLE REQUIRE TWO SEPARATE !,4%2 4!",% STATEMENTS 3EVERAL $"-3 BRANDS RELAX THIS RESTRICTION AND ALLOW MULTIPLE ACTION CLAUSES IN A SINGLE !,4%2 4!",% STATEMENT
!DDINGõAõ#OLUMN 4HE MOST COMMON USE OF THE !,4%2 4!",% STATEMENT IS TO ADD A COLUMN TO AN EXISTING TABLE 4HE COLUMN DEFINITION CLAUSE IN THE !,4%2 4!",% STATEMENT IS JUST LIKE THE ONE IN THE #2%!4% 4!",% STATEMENT AND IT WORKS THE SAME WAY 4HE NEW COLUMN IS ADDED TO THE END OF THE COLUMN DEFINITIONS FOR THE TABLE AND IT APPEARS AS THE RIGHTMOST COLUMN IN SUBSEQUENT QUERIES 4HE $"-3 NORMALLY ASSUMES A .5,, VALUE FOR A NEWLY ADDED COLUMN IN ALL EXISTING ROWS OF THE TABLE )F THE COLUMN IS DECLARED TO BE ./4 .5,, WITH A DEFAULT VALUE THE $"-3 INSTEAD ASSUMES THE DEFAULT VALUE
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s !DD OR DROP A PRIMARY KEY FOR A TABLE
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0ARTç)6ç
$ATABASEç3TRUCTURE
.OTE THAT YOU CANNOT SIMPLY DECLARE THE NEW COLUMN ./4 .5,, BECAUSE THE $"-3 WOULD ASSUME .5,, VALUES FOR THE COLUMN IN THE EXISTING ROWS IMMEDIATELY VIOLATING THE CONSTRAINT 7HEN YOU ADD A NEW COLUMN THE $"-3 MAY NOT ACTUALLY GO THROUGH ALL OF THE EXISTING ROWS OF THE TABLE ADDING A .5,, OR DEFAULT VALUE )NSTEAD SOME $"-3 PRODUCTS DETECT THE FACT THAT AN EXISTING ROW IS TOO SHORT FOR THE NEW TABLE DEFINITION WHEN THE ROW IS RETRIEVED AND EXTEND IT WITH A .5,, OR DEFAULT VALUE BEFORE DISPLAYING IT OR PASSING IT TO YOUR PROGRAM 3OME SAMPLE !,4%2 4!",% STATEMENTS THAT ADD NEW COLUMNS ARE !DD A CONTACT NAME AND PHONE NUMBER TO THE #534/-%23 TABLE !,4%2 4!",% #534/-%23 !$$ #/.4!#4?.!-% 6!2#(!2 !,4%2 4!",% #534/-%23 !$$ #/.4!#4?0(/.% #(!2
!DD A MINIMUM INVENTORY LEVEL COLUMN TO THE 02/$5#43 TABLE !,4%2 4!",% 02/$5#43 !$$ -).?149 ).4%'%2 ./4 .5,, $%&!5,4
)N THE FIRST EXAMPLE THE NEW COLUMNS WILL HAVE .5,, VALUES FOR EXISTING CUSTOMERS )N THE SECOND EXAMPLE THE -).?149 COLUMN WILL HAVE THE VALUE ZERO FOR EXISTING PRODUCTS WHICH IS APPROPRIATE 7HEN THE !,4%2 4!",% STATEMENT FIRST APPEARED IN 31, IMPLEMENTATIONS THE ONLY MAJOR STRUCTURES WITHIN A TABLE WERE THE COLUMN DEFINITIONS AND IT WAS VERY CLEAR WHAT THE !$$ CLAUSE MEANT 3INCE THEN TABLES HAVE GROWN TO INCLUDE PRIMARY AND FOREIGN KEY DEFINITIONS AND CONSTRAINTS AND THE !$$ CLAUSES FOR THESE TYPES OF OBJECTS SPECIFY WHICH TYPE OF OBJECT IS BEING ADDED &OR CONSISTENCY WITH THESE OTHER !$$$2/0 CLAUSES THE 31, STANDARD INCLUDES THE OPTIONAL KEYWORD #/,5-. AFTER THE KEYWORD !$$ 7ITH THIS ADDITION THE PRECEDING EXAMPLE BECOMES !DD A MINIMUM INVENTORY LEVEL COLUMN TO THE 02/$5#43 TABLE !,4%2 4!",% 02/$5#43 !$$ #/,5-. -).?149 ).4%'%2 ./4 .5,, $%&!5,4
$ROPPINGõAõ#OLUMN 4HE !,4%2 4!",% STATEMENT CAN BE USED TO DROP ONE OR MORE COLUMNS FROM AN EXISTING TABLE WHEN THEY ARE NO LONGER NEEDED (ERE IS AN EXAMPLE THAT DROPS THE ()2%?$!4% COLUMN FROM THE 3!,%32%03 TABLE $ROP A COLUMN FROM THE 3!,%32%03 TABLE !,4%2 4!",% 3!,%32%03 $2/0 ()2%?$!4%
4HE 31, STANDARD FORCES YOU TO ISSUE A SEPARATE !,4%2 4!",% STATEMENT IF YOU WANT TO DROP SEVERAL COLUMNS BUT SEVERAL OF THE MAJOR $"-3 BRANDS ALLOW YOU TO DROP MULTIPLE COLUMNS WITH A SINGLE STATEMENT
#HAPTERçç
#REATINGçAç$ATABASEç
.OTE THAT DROPPING A COLUMN CAN POSE THE SAME KINDS OF DATA INTEGRITY ISSUES THAT WERE DESCRIBED IN #HAPTER FOR DATABASE UPDATE OPERATIONS &OR EXAMPLE IF YOU DROP A COLUMN THAT IS A PRIMARY KEY IN SOME RELATIONSHIP THE FOREIGN KEY COLUMNS THAT REFER TO THE DROPPED COLUMN BECOME INVALID ! SIMILAR PROBLEM CAN ARISE IF YOU DROP A COLUMN THAT IS REFERENCED IN A CHECK CONSTRAINTTHE COLUMN THAT PROVIDES THE DATA VALUE FOR CHECKING THE CONSTRAINT IS NOW GONE ! SIMILAR PROBLEM IS CREATED IN VIEWS THAT ARE DEFINED BASED ON THE DROPPED COLUMN 4HE 31, STANDARD DEALS WITH THESE ISSUES THE SAME WAY IT HANDLED THE POTENTIAL DATA INTEGRITY PROBLEMS POSED BY $%,%4% AND 50$!4% STATEMENTSWITH A DROP RULE ACTUALLY CALLED A DROP BEHAVIOR IN THE STANDARD THAT OPERATES JUST LIKE THE DELETE RULES AND UPDATE RULES 9OU CAN SPECIFY ONE OF TWO DROP RULES s 2%342)#4 )F ANY OTHER OBJECTS IN THE DATABASE FOREIGN KEYS CONSTRAINTS AND SO ON DEPEND ON THE COLUMN TO BE DROPPED THE !,4%2 4!",% STATEMENT FAILS WITH AN ERROR AND THE COLUMN IS NOT DROPPED s #!3#!$% !NY OTHER OBJECTS IN THE DATABASE FOREIGN KEYS CONSTRAINTS AND SO ON THAT DEPEND ON THE COLUMN ARE ALSO DROPPED AS A CASCADED EFFECT OF THE !,4%2 4!",% STATEMENT 4HE #!3#!$% EFFECT CAN CAUSE QUITE DRAMATIC CHANGES IN THE DATABASE THEREFORE USE IT WITH CARE )TS USUALLY A BETTER IDEA TO USE THE 2%342)#4 MODE EXPLICITLY DROP THE DEPENDENT FOREIGN KEYS AND CONSTRAINTS USING THE APPROPRIATE !,4%2 OR $2/0 STATEMENTS BEFORE DROPPING THE COLUMN
#HANGINGõ0RIMARYõANDõ&OREIGNõ+EYS
-AKE THE 2%')/. COLUMN IN THE /&&)#%3 TABLE A FOREIGN KEY FOR THE NEWLY CREATED 2%')/.3 TABLE WHOSE PRIMARY KEY IS THE REGION NAME !,4%2 4!",% /&&)#%3 !$$ #/.342!).4 ).2%')/. &/2%)'. +%9 2%')/. 2%&%2%.#%3 2%')/.3
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4HE OTHER COMMON USE FOR THE !,4%2 4!",% STATEMENT IS TO CHANGE OR ADD PRIMARY KEY AND FOREIGN KEY DEFINITIONS FOR A TABLE -ANY FIND THIS FORM OF THE !,4%2 4!",% STATEMENT IS PARTICULARLY USEFUL )T CAN BE USED TO INFORM THE $"-3 ABOUT INTERTABLE RELATIONSHIPS THAT ALREADY EXIST IN A DATABASE BUT WHICH HAVE NOT BEEN EXPLICITLY SPECIFIED BEFORE 5NLIKE COLUMN DEFINITIONS PRIMARY KEY AND FOREIGN KEY DEFINITIONS CAN BE ADDED AND DROPPED FROM A TABLE WITH THE !,4%2 4!",% STATEMENT 4HE CLAUSES THAT ADD PRIMARY KEY AND FOREIGN KEY DEFINITIONS ARE EXACTLY THE SAME AS THOSE IN THE #2%!4% 4!",% STATEMENT AND THEY WORK THE SAME WAY 4HE CLAUSES THAT DROP A PRIMARY KEY OR FOREIGN KEY ARE STRAIGHTFORWARD AS SHOWN IN THE FOLLOWING EXAMPLES .OTE THAT YOU CAN DROP A FOREIGN KEY ONLY IF THE RELATIONSHIP THAT IT CREATES WAS ORIGINALLY ASSIGNED A NAME )F THE RELATIONSHIP WAS UNNAMED AND THE $"-3 IS NOT ONE OF THOSE THAT ASSIGNS DEFAULT NAMES TO UNNAMED CONSTRAINTS THERE IS NO WAY TO SPECIFY IT IN THE !,4%2 4!",% STATEMENT )N THIS CASE YOU CANNOT DROP THE FOREIGN KEY UNLESS YOU DROP AND RE CREATE THE TABLE USING THE PROCEDURE DESCRIBED FOR DROPPING A COLUMN (ERE IS AN EXAMPLE THAT ADDS A FOREIGN KEY DEFINITION TO AN EXISTING TABLE
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$ATABASEç3TRUCTURE
(ERE IS AN EXAMPLE OF AN !,4%2 4!",% STATEMENT THAT MODIFIES A PRIMARY KEY .OTE THAT THE FOREIGN KEY CORRESPONDING TO THE ORIGINAL PRIMARY KEY MUST BE DROPPED BECAUSE IT IS NO LONGER A FOREIGN KEY FOR THE ALTERED TABLE $ROP THE PRIMARY KEY OF THE /&&)#%3 TABLE !,4%2 4!",% 3!,%32%03 $2/0 #/.342!).4 7/2+3). !,4%2 4!",% /&&)#%3 $2/0 02)-!29 +%9
#ONSTRAINTõ$EFINITIONS 4HE TABLES IN A DATABASE DEFINE ITS BASIC STRUCTURE AND IN MOST EARLY COMMERCIAL 31, PRODUCTS THE TABLE DEFINITIONS WERE THE ONLY SPECIFICATION OF DATABASE STRUCTURE 7ITH THE ADVENT OF PRIMARY KEYFOREIGN KEY SUPPORT IN $" AND IN THE 31, STANDARD THE DEFINITION OF DATABASE STRUCTURE WAS EXPANDED TO INCLUDE THE RELATIONSHIPS AMONG THE TABLES IN A DATABASE -ORE RECENTLY THROUGH THE EVOLUTION OF THE 31, STANDARD AND COMMERCIAL PRODUCTS THE DEFINITION OF DATABASE STRUCTURE HAS EXPANDED TO INCLUDE A NEW AREADATABASE CONSTRAINTS THAT RESTRICT THE DATA THAT CAN BE ENTERED INTO THE DATABASE 4HE TYPES OF CONSTRAINTS AND THE ROLE THAT THEY PLAY IN MAINTAINING DATABASE INTEGRITY ARE DESCRIBED IN #HAPTER &OUR TYPES OF DATABASE CONSTRAINTS UNIQUENESS CONSTRAINTS PRIMARY AND FOREIGN KEY CONSTRAINTS AND CHECK CONSTRAINTS ARE CLOSELY ASSOCIATED WITH A SINGLE DATABASE TABLE 4HEY ARE SPECIFIED AS PART OF THE #2%!4% 4!",% STATEMENT AND CAN BE MODIFIED OR DROPPED USING THE !,4%2 4!",% STATEMENT 4HE OTHER TWO TYPES OF DATABASE INTEGRITY CONSTRAINTS ASSERTIONS AND DOMAINS ARE CREATED AS STAND ALONE OBJECTS WITHIN A DATABASE INDEPENDENT OF ANY INDIVIDUAL TABLE DEFINITION
!SSERTIONS !N ASSERTION IS A DATABASE CONSTRAINT THAT RESTRICTS THE CONTENTS OF THE DATABASE AS A WHOLE ,IKE A CHECK CONSTRAINT AN ASSERTION IS SPECIFIED AS A SEARCH CONDITION "UT UNLIKE A CHECK CONSTRAINT THE SEARCH CONDITION IN AN ASSERTION CAN RESTRICT THE CONTENTS OF MULTIPLE TABLES AND THE DATA RELATIONSHIPS AMONG THEM &OR THAT REASON AN ASSERTION IS SPECIFIED AS PART OF THE OVERALL DATABASE DEFINITION VIA A 31, #2%!4% !33%24)/. STATEMENT 3UPPOSE YOU WANTED TO RESTRICT THE CONTENTS OF THE SAMPLE DATABASE SO THAT THE TOTAL ORDERS FOR ANY GIVEN CUSTOMER MAY NOT EXCEED THAT CUSTOMERS CREDIT LIMIT 9OU CAN IMPLEMENT THAT RESTRICTION WITH THE STATEMENT #2%!4% !33%24)/. #2%$,)-)4 #(%#+ #534/-%23#534?.5- /2$%23#534 !.$ 35- !-/5.4 #2%$)4?,)-)4
7ITH THE ASSERTION NAMED #2%$,)-)4 AS PART OF THE DATABASE DEFINITION THE $"-3 IS REQUIRED TO CHECK THAT THE ASSERTION REMAINS TRUE EACH TIME A 31, STATEMENT ATTEMPTS TO MODIFY THE #534/-%2 OR /2$%23 TABLES )F YOU LATER DETERMINE THAT THE ASSERTION IS NO LONGER NEEDED YOU CAN DROP IT USING THE $2/0 !33%24)/. STATEMENT $2/0 !33%24)/. #2%$,)-)4
#HAPTERçç
#REATINGçAç$ATABASEç
4HERE IS NO 31, !,4%2 !33%24)/. STATEMENT 4O CHANGE AN ASSERTION DEFINITION YOU MUST DROP THE OLD DEFINITION AND THEN SPECIFY THE NEW ONE WITH A NEW #2%!4% !33%24)/. STATEMENT !LTHOUGH THE SPECIFICATION FOR ASSERTIONS HAS BEEN IN THE 31, STANDARD SINCE VERY FEW 31, IMPLEMENTATIONS SUPPORT IT )N FACT AS OF THIS WRITING IT IS NOT YET SUPPORTED BY /RACLE $" 5$" 31, 3ERVER OR -Y31,
$OMAINS 4HE 31, STANDARD IMPLEMENTS THE FORMAL CONCEPT OF A DOMAIN AS A PART OF A DATABASE DEFINITION !S DESCRIBED IN #HAPTER A DOMAIN IS A NAMED COLLECTION OF DATA VALUES THAT EFFECTIVELY FUNCTIONS AS AN ADDITIONAL DATA TYPE FOR USE IN DATABASE DEFINITIONS ! DOMAIN IS CREATED WITH A #2%!4% $/-!). STATEMENT /NCE CREATED THE DOMAIN CAN BE REFERENCED AS IF IT WERE A DATA TYPE WITHIN A COLUMN DEFINITION (ERE IS A #2%!4% $/-!). STATEMENT TO DEFINE A DOMAIN NAMED 6!,)$?%-0,?)$3 WHICH CONSISTS OF VALID EMPLOYEE IDENTIFICATION NUMBERS IN THE SAMPLE DATABASE 4HESE NUMBERS ARE THREE DIGIT INTEGERS IN THE RANGE TO INCLUSIVE #2%!4% $/-!). 6!,)$?%-0,?)$3 ).4%'%2 #(%#+ 6!,5% "%47%%. !.$
)F A DOMAIN IS NO LONGER NEEDED YOU CAN DROP IT USING ONE OF THE FORMS OF THE 31, $2/0 $/-!). STATEMENT $2/0 $/-!). 6!,)$?%-0,?)$3 #!3#!$% $2/0 $/-!). 6!,)$?%-0,?)$3 2%342)#4
!LIASESõANDõ3YNONYMSõ#2%!4%$2/0õ!,)!3 0RODUCTION DATABASES ARE OFTEN ORGANIZED LIKE THE COPY OF THE SAMPLE DATABASE SHOWN IN &IGURE WITH ALL OF THEIR MAJOR TABLES COLLECTED TOGETHER AND OWNED BY AN APPLICATION )$ OR DATABASE ADMINISTRATOR 4HE DATABASE ADMINISTRATOR GIVES OTHER USERS PERMISSION TO ACCESS THE TABLES USING THE 31, SECURITY SCHEME DESCRIBED IN #HAPTER 2ECALL HOWEVER THAT YOU MUST USE QUALIFIED TABLE NAMES TO REFER TO ANOTHER USERS TABLES )N PRACTICE
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4HE #!3#!$% AND 2%342)#4 DROP RULES OPERATE JUST AS THEY DO FOR DROPPED COLUMNS )F #!3#!$% IS SPECIFIED ANY COLUMN DEFINED IN TERMS OF THE DROPPED DOMAIN WILL ALSO BE AUTOMATICALLY DROPPED FROM THE DATABASE )F 2%342)#4 IS SPECIFIED THE ATTEMPT TO DROP THE DOMAIN WILL FAIL IF ANY COLUMN DEFINITIONS ARE BASED ON IT 9OU MUST FIRST DROP OR ALTER THE COLUMN DEFINITIONS SO THAT THEY NO LONGER DEPEND ON THE DOMAIN BEFORE DROPPING IT 4HIS PROVIDES AN EXTRA MARGIN OF SAFETY AGAINST ACCIDENTALLY DROPPING COLUMNS AND MORE IMPORTANTLY THE DATA THAT THEY CONTAIN ,IKE ASSERTIONS DOMAIN DEFINITIONS HAVE BEEN SPECIFIED IN THE 31, STANDARD SINCE BUT THERE ARE VERY FEW IMPLEMENTATIONS OF THEM IN COMMERCIAL PRODUCTS 31, 3ERVER AND /RACLE HAVE #2%!4% 490% STATEMENTS THAT ARE SIMILAR IN SOME WAYS BUT THERE IS NO SUCH SUPPORT IN $" 5$" -Y31, OR ANY OTHER MAINSTREAM $"-3 PRODUCT
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THIS MEANS THAT EVERY QUERY AGAINST THE MAJOR TABLES IN &IGURE MUST USE QUALIFIED TABLE NAMES WHICH MAKES QUERIES LIKE THE FOLLOWING ONE LONG AND TEDIOUS TO TYPE ,IST THE NAME SALES OFlCE AND OFlCE SALES FOR EVERYONE 3%,%#4 .!-% /0?!$-).3!,%32%033!,%3 /&&)#% /0?!$-)./&&)#%33!,%3 &2/- /0?!$-).3!,%32%03 /0?!$-)./&&)#%3
4O ADDRESS THIS PROBLEM MANY 31, $"-3 PRODUCTS PROVIDE AN ALIAS OR SYNONYM CAPABILITY ! SYNONYM IS A NAME THAT YOU DEFINE THAT STANDS FOR THE NAME OF SOME OTHER TABLE )N $" YOU CREATE AN ALIAS USING THE #2%!4% !,)!3 STATEMENT /LDER VERSIONS OF $" ACTUALLY USED A #2%!4% 39./.9- STATEMENT AND /RACLE AND 31, 3ERVER STILL USE THIS FORM OF THE STATEMENT BUT IT HAS THE SAME EFFECT AS THE #2%!4% !,)!3 STATEMENT )F YOU WERE THE USER NAMED 'EORGE IN &IGURE FOR EXAMPLE YOU MIGHT USE THIS PAIR OF #2%!4% !,)!3 STATEMENTS #REATE ALIASES FOR TWO TABLES OWNED BY ANOTHER USER #2%!4% !,)!3 2%03 &/2 /0?!$-).3!,%32%03 #2%!4% !,)!3 /&&)#%3 &/2 /0?!$-)./&&)#%3
/NCE YOU HAVE DEFINED A SYNONYM OR ALIAS YOU CAN USE IT JUST LIKE A TABLE NAME IN 31, QUERIES 4HE PREVIOUS QUERY THUS BECOMES 3%,%#4 .!-% 2%033!,%3 /&&)#% /&&)#%33!,%3 &2/- 2%03 /&&)#%3
4HE USE OF ALIASES DOESNT CHANGE THE MEANING OF THE QUERY AND YOU MUST STILL HAVE PERMISSION TO ACCESS THE OTHER USERS TABLES .ONETHELESS SYNONYMS SIMPLIFY THE 31, STATEMENTS YOU USE AND MAKE IT APPEAR AS IF THE TABLES WERE YOUR OWN )F YOU DECIDE LATER THAT YOU NO LONGER WANT TO USE THE SYNONYMS THEY CAN BE REMOVED WITH THE $2/0 !,)!3 STATEMENT
#HAPTERçç
#REATINGçAç$ATABASEç
$ROP THE ALIASES CREATED EARLIER $2/0 !,)!3 2%03 $2/0 !,)!3 /&&)#%3
3YNONYMS OR ALIASES ARE SUPPORTED BY $" /RACLE 31, 3ERVER AND )NFORMIX (OWEVER THEY ARE NOT SPECIFIED BY THE !.3))3/ 31, STANDARD
)NDEXESõ#2%!4%$2/0õ).$%8 /NE OF THE PHYSICAL STORAGE STRUCTURES PROVIDED BY MOST 31, BASED DATABASE MANAGEMENT SYSTEMS IS AN INDEX WHICH IS A STRUCTURE THAT PROVIDES RAPID ACCESS TO THE ROWS OF A TABLE BASED ON THE VALUES OF ONE OR MORE COLUMNS &IGURE SHOWS THE 02/$5#43 TABLE AND TWO INDEXES THAT HAVE BEEN CREATED FOR IT /NE OF THE INDEXES PROVIDES ACCESS BASED ON THE $%+( #
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$ATABASEç3TRUCTURE
$%3#2)04)/. COLUMN 4HE OTHER PROVIDES ACCESS BASED ON THE PRIMARY KEY OF THE TABLE WHICH IS A COMBINATION OF THE -&2?)$ AND 02/$5#4?)$ COLUMNS 4HE $"-3 USES THE INDEX AS YOU MIGHT USE THE INDEX OF A BOOK 4HE INDEX STORES DATA VALUES AND POINTERS TO THE ROWS WHERE THOSE DATA VALUES OCCUR )N THE INDEX THE DATA VALUES ARE ARRANGED IN ASCENDING OR DESCENDING ORDER SO THAT THE $"-3 CAN QUICKLY SEARCH THE INDEX TO FIND A PARTICULAR VALUE )T CAN THEN FOLLOW THE POINTER TO LOCATE THE ROW CONTAINING THE VALUE 4HE PRESENCE OR ABSENCE OF AN INDEX IS COMPLETELY TRANSPARENT TO THE 31, USER WHO ACCESSES A TABLE &OR EXAMPLE CONSIDER THIS 3%,%#4 STATEMENT &IND THE QUANTITY AND PRICE FOR SIZE WIDGETS 3%,%#4 149?/.?(!.$ 02)#% &2/- 02/$5#43 7(%2% $%3#2)04)/. g3IZE 7IDGETg
4HE STATEMENT DOESNT SAY WHETHER THERE IS AN INDEX ON THE $%3#2)04)/. COLUMN AND THE $"-3 WILL CARRY OUT THE QUERY IN EITHER CASE )F THERE WERE NO INDEX FOR THE $%3#2)04)/. COLUMN THE $"-3 WOULD BE FORCED TO PROCESS THE QUERY BY SEQUENTIALLY SCANNING THE 02/$5#43 TABLE ROW BY ROW EXAMINING THE $%3#2)04)/. COLUMN IN EACH ROW 4O MAKE SURE IT HAD FOUND ALL OF THE ROWS THAT SATISFIED THE SEARCH CONDITION IT WOULD HAVE TO EXAMINE EVERY ROW IN THE TABLE &OR A LARGE TABLE WITH MILLIONS OF ROWS THE SCAN OF THE TABLE COULD TAKE MINUTES OR HOURS 7ITH AN INDEX FOR THE $%3#2)04)/. COLUMN THE $"-3 CAN LOCATE THE REQUESTED DATA WITH MUCH LESS EFFORT )T SEARCHES THE INDEX TO FIND THE REQUESTED VALUE h3IZE 7IDGETv AND THEN FOLLOWS THE POINTER TO FIND THE REQUESTED ROWS OF THE TABLE 4HE INDEX SEARCH IS VERY RAPID BECAUSE THE INDEX IS SORTED AND ITS ROWS ARE VERY SMALL -OVING FROM THE INDEX TO THE ROWS IS ALSO VERY RAPID BECAUSE THE INDEX TELLS THE $"-3 WHERE ON THE DISK THE ROWS ARE LOCATED !S THIS EXAMPLE SHOWS THE ADVANTAGE OF HAVING AN INDEX IS THAT IT GREATLY SPEEDS THE EXECUTION OF 31, STATEMENTS WITH SEARCH CONDITIONS THAT REFER TO THE INDEXED COLUMNS /NE DISADVANTAGE OF HAVING AN INDEX IS THAT IT CONSUMES ADDITIONAL DISK SPACE !NOTHER DISADVANTAGE IS THAT THE INDEX MUST BE UPDATED EVERY TIME A ROW IS ADDED TO THE TABLE AND EVERY TIME THE INDEXED COLUMN IS UPDATED IN AN EXISTING ROW 4HIS IMPOSES ADDITIONAL OVERHEAD ON ).3%24 AND 50$!4% STATEMENTS FOR THE TABLE )N GENERAL ITS A GOOD IDEA TO CREATE AN INDEX FOR COLUMNS THAT ARE USED FREQUENTLY IN SEARCH CONDITIONS )N ADDITION AN INDEX ON FOREIGN KEY COLUMNS CAN OFTEN ENHANCE THE PERFORMANCE OF JOINS )NDEXING IS ALSO MORE APPROPRIATE WHEN QUERIES AGAINST A TABLE ARE MORE FREQUENT THAN INSERTS AND UPDATES -OST $"-3 PRODUCTS ALWAYS ESTABLISH AN INDEX FOR THE PRIMARY KEY OF A TABLE BECAUSE THEY ANTICIPATE THAT ACCESS TO THE TABLE WILL MOST FREQUENTLY BE VIA THE PRIMARY KEY 4HE PRIMARY KEY INDEX ALSO HELPS THE $"-3 QUICKLY CHECK FOR DUPLICATE VALUES AS NEW ROWS ARE INSERTED INTO THE TABLE -OST $"-3 PRODUCTS ALSO AUTOMATICALLY ESTABLISH AN INDEX FOR ANY COLUMN OR COLUMN COMBINATION DEFINED WITH A UNIQUENESS CONSTRAINT !S WITH THE PRIMARY KEY THE $"-3 MUST CHECK THE VALUE OF SUCH A COLUMN IN ANY NEW ROW TO BE INSERTED OR IN ANY UPDATE TO AN EXISTING ROW TO MAKE CERTAIN THAT THE VALUE DOES NOT DUPLICATE A VALUE ALREADY CONTAINED IN THE TABLE 7ITHOUT AN INDEX ON THE COLUMNS THE $"-3 WOULD HAVE TO SEQUENTIALLY SEARCH THROUGH EVERY ROW OF THE TABLE TO CHECK THE CONSTRAINT 7ITH AN INDEX THE $"-3 CAN SIMPLY USE THE INDEX TO FIND A ROW IF IT EXISTS WITH THE VALUE IN QUESTION WHICH IS A MUCH FASTER OPERATION THAN A SEQUENTIAL SEARCH
#HAPTERçç
#REATINGçAç$ATABASEç
)N THE SAMPLE DATABASE THESE COLUMNS ARE GOOD CANDIDATES FOR ADDITIONAL INDEXES s 4HE #/-0!.9 COLUMN IN THE #534/-%23 TABLE SHOULD BE INDEXED IF CUSTOMER DATA IS OFTEN RETRIEVED BY COMPANY NAME s 4HE .!-% COLUMN IN THE 3!,%32%03 TABLE SHOULD BE INDEXED IF DATA ABOUT SALESPEOPLE IS OFTEN RETRIEVED BY SALESPERSON NAME s 4HE 2%0 COLUMN IN THE /2$%23 TABLE SHOULD BE INDEXED IF ORDERS ARE FREQUENTLY RETRIEVED BASED ON THE SALESPERSON WHO TOOK THEM s 4HE #534 COLUMN IN THE /2$%23 TABLE SHOULD SIMILARLY BE INDEXED IF ORDERS ARE FREQUENTLY RETRIEVED BASED ON THE CUSTOMER WHO PLACED THEM s 4HE -&2 AND 02/$5#4 COLUMNS TOGETHER IN THE /2$%23 TABLE SHOULD BE INDEXED IF ORDERS ARE FREQUENTLY RETRIEVED BASED ON THE PRODUCT ORDERED
#REATE A UNIQUE INDEX FOR THE /&&)#%3 TABLE #2%!4% 5.)15% ).$%8 /&#?-'2?)$8 /. /&&)#%3 -'2
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! DISADVANTAGE OF THIS ARCHITECTURE IS THAT THE DATABASE WILL GROW HUGE OVER TIME AS MORE AND MORE APPLICATIONS ARE ADDED TO IT ! MAINFRAME $" DATABASE WITH SEVERAL THOUSAND TABLES IS COMMON 4HE PROBLEMS OF MANAGING A DATABASE OF THAT SIZEPERFORMING BACKUPS RECOVERING DATA ANALYZING PERFORMANCE AND SO ONUSUALLY REQUIRE A FULL TIME DATABASE ADMINISTRATOR )N THE SINGLE DATABASE ARCHITECTURE GAINING ACCESS TO THE DATABASE IS VERY SIMPLE THERES ONLY ONE DATABASE SO NO CHOICES NEED TO BE MADE )N FACT IN THIS ARCHITECTURE THE DATABASE IS USUALLY ASSOCIATED WITH A SINGLE RUNNING COPY OF THE $"-3 SOFTWARE SO IN A VERY REAL SENSE THE USER IS CONNECTING TO THE $"-3 -AINFRAME $" INSTALLATIONS FREQUENTLY DO RUN TWO SEPARATE DATABASES ONE FOR PRODUCTION WORK AND ONE FOR TESTING &UNDAMENTALLY HOWEVER ALL PRODUCTION DATA IS COLLECTED INTO A SINGLE DATABASE /RACLE USES A SINGLE DATABASE ARCHITECTURE IN THAT EACH DATABASE IS ASSOCIATED WITH A SINGLE COPY OF THE $"-3 SOFTWARE 4YPICALLY /RACLE DATABASES ARE ORGANIZED BY APPLICATION OR MAJOR FUNCTION AND THUS MULTIPLE /RACLE DATABASES ARE OFTEN RUNNING ON A SINGLE HOST COMPUTER /RACLE PROVIDES A #/..%#4 COMMAND THAT PROVIDES THE COMBINATION OF USER LOGIN AND AN IDENTIFIER OF THE DATABASE WITH WHICH THE USER WISHES TO CONNECT 4HERE ARE SEVERAL METHODS FOR IDENTIFYING AND LOCATING THE DATABASE DURING THE CONNECTION PROCESS AND UNDER MOST CIRCUMSTANCES THE USER DOES NOT HAVE TO KNOW WHERE THE DATABASE IS LOCATED ON THE NETWORK
-ULTIDATABASEõ!RCHITECTURE &IGURE SHOWS A MULTIDATABASE ARCHITECTURE WHERE EACH DATABASE IS ASSIGNED A UNIQUE NAME 3YBASE -ICROSOFT 31, 3ERVER -Y31, )NGRES AND MANY OTHERS USE THIS SCHEME !S SHOWN IN THE FIGURE EACH OF THE DATABASES IN THIS ARCHITECTURE IS USUALLY DEDICATED TO A PARTICULAR APPLICATION 7HEN YOU ADD A NEW APPLICATION YOU WILL PROBABLY CREATE A NEW DATABASE .OTE THAT WE HAVE USED INDIVIDUAL USER NAMES AS OWNERS OF SETS OF TABLES FOR ILLUSTRATION PURPOSES HOWEVER IN PRODUCTION COMMERCIAL DATABASES THE OWNERS OF THE TABLES WOULD MOST LIKELY BE DATABASE ACCOUNTS SET UP BY THE $"! FOR APPLICATIONS TO USE )N ESSENCE THE DATABASES WOULD BE OWNED BY AN APPLICATION SYSTEM SUCH AS PAYROLL OR ORDER ENTRY INSTEAD OF AN INDIVIDUAL 4HE MAIN ADVANTAGE OF THE MULTIDATABASE ARCHITECTURE OVER THE SINGLE DATABASE ARCHITECTURE IS THAT IT DIVIDES THE DATA MANAGEMENT TASKS INTO SMALLER MORE MANAGEABLE PIECES %ACH PERSON RESPONSIBLE FOR AN APPLICATION CAN NOW BE THE DATABASE ADMINISTRATOR OF HIS OR HER OWN DATABASE WITH LESS WORRY ABOUT OVERALL COORDINATION 7HEN ITS TIME TO ADD A NEW APPLICATION IT CAN BE DEVELOPED IN ITS OWN DATABASE WITHOUT DISTURBING THE EXISTING DATABASES 5SERS AND PROGRAMMERS ARE ALSO MORE LIKELY TO REMEMBER THE OVERALL STRUCTURE OF THEIR OWN DATABASES 4HE MAIN DISADVANTAGE OF THE MULTIDATABASE ARCHITECTURE IS THAT THE INDIVIDUAL DATABASES MAY BECOME ISLANDS OF INFORMATION UNCONNECTED TO ONE ANOTHER 4YPICALLY A TABLE IN ONE DATABASE CANNOT CONTAIN A FOREIGN KEY REFERENCE TO A TABLE IN A DIFFERENT DATABASE /FTEN THE $"-3 DOES NOT SUPPORT QUERIES ACROSS DATABASE BOUNDARIES MAKING IT IMPOSSIBLE TO RELATE DATA FROM TWO APPLICATIONS )F CROSS DATABASE QUERIES ARE SUPPORTED THEY MAY IMPOSE SUBSTANTIAL OVERHEAD OR REQUIRE THE PURCHASE OF ADDITIONAL DISTRIBUTED $"-3 SOFTWARE FROM THE $"-3 VENDOR )F A $"-3 USES A MULTIDATABASE ARCHITECTURE AND SUPPORTS QUERIES ACROSS DATABASES IT MUST EXTEND THE 31, TABLE AND COLUMN NAMING CONVENTIONS ! QUALIFIED TABLE NAME MUST
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1, ʣΣäÊ Ê ÊÕÌ`>Ì>L>ÃiÊ >ÀV
ÌiVÌÕÀi
#REATINGçAç$ATABASEç
SPECIFY NOT ONLY THE OWNER OF THE TABLE BUT ALSO WHICH DATABASE CONTAINS THE TABLE 4YPICALLY THE $"-3 EXTENDS THE DOT NOTATION FOR TABLE NAMES BY PREFIXING THE DATABASE NAME TO THE OWNER NAME SEPARATED BY A PERIOD &OR EXAMPLE IN A 3YBASE OR 31, 3ERVER DATABASE THIS TABLE REFERENCE /0*/%/&&)#%3
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$ATABASEç3TRUCTURE
REFERS TO THE /&&)#%3 TABLE OWNED BY THE USER */% IN THE ORDER PROCESSING DATABASE NAMED /0 AND THE FOLLOWING QUERY JOINS THE 3!,%32%03 TABLE IN THE PAYROLL DATABASE WITH THAT /&&)#%3 TABLE 3%,%#4 /0*/%/&&)#%3#)49 0!92/,,'%/2'%3!,%32%03.!-% &2/- /0*/%/&&)#%3 0!92/,,'%/2'%3!,%32%03 7(%2% /0*/%/&&)#%3-'2 0!92/,,'%/2'%3!,%32%03%-0,?.5-
&ORTUNATELY SUCH CROSS DATABASE QUERIES ARE THE EXCEPTION RATHER THAN THE RULE AND DEFAULT DATABASE AND USER NAMES CAN NORMALLY BE USED 7ITH A MULTIDATABASE ARCHITECTURE GAINING ACCESS TO A DATABASE BECOMES SLIGHTLY MORE COMPLEX BECAUSE YOU MUST TELL THE $"-3 WHICH DATABASE YOU WANT TO USE 4HE $"-3 INTERACTIVE 31, PROGRAM WILL OFTEN DISPLAY A LIST OF AVAILABLE DATABASES OR ASK YOU TO ENTER THE DATABASE NAME ALONG WITH YOUR USER NAME AND PASSWORD TO GAIN ACCESS &OR PROGRAMMATIC ACCESS THE $"-3 GENERALLY EXTENDS THE EMBEDDED 31, WITH A STATEMENT THAT CONNECTS THE PROGRAM TO A PARTICULAR DATABASE 4HE )NGRES FORM FOR CONNECTING TO THE DATABASE NAMED /0 IS #/..%#4 g/0g
&OR 3YBASE -ICROSOFT 31, 3ERVER AND -Y31, THE PARALLEL STATEMENT IS 53% g/0g
-ULTILOCATIONõ!RCHITECTURE &IGURE SHOWS A MULTILOCATION ARCHITECTURE THAT SUPPORTS MULTIPLE DATABASES AND USES THE COMPUTER SYSTEMS DIRECTORY STRUCTURE TO ORGANIZE THEM 3EVERAL OF THE EARLIER MINICOMPUTER DATABASES INCLUDING 2DB6-3 AND )NFORMIX USED THIS SCHEME FOR SUPPORTING MULTIPLE DATABASES !S WITH THE MULTIDATABASE ARCHITECTURE EACH APPLICATION IS TYPICALLY ASSIGNED TO ITS OWN DATABASE !S &IGURE SHOWS EACH DATABASE HAS A NAME BUT ITS POSSIBLE FOR TWO DIFFERENT DATABASES IN TWO DIFFERENT DIRECTORIES TO HAVE THE SAME NAME 4HE MAJOR ADVANTAGE OF THE MULTILOCATION ARCHITECTURE IS FLEXIBILITY )T IS ESPECIALLY APPROPRIATE IN APPLICATIONS SUCH AS ENGINEERING AND DESIGN WHERE MANY SOPHISTICATED USERS OF THE COMPUTER SYSTEM MAY ALL WANT TO USE SEVERAL DATABASES TO STRUCTURE THEIR OWN INFORMATION 4HE DISADVANTAGES OF THE MULTILOCATION ARCHITECTURE ARE THE SAME AS THOSE OF THE MULTIDATABASE ARCHITECTURE )N ADDITION THE $"-3 TYPICALLY DOESNT KNOW ABOUT ALL OF THE DATABASES THAT HAVE BEEN CREATED WHICH MAY BE SPREAD THROUGHOUT THE SYSTEMS DIRECTORY STRUCTURE 4HERE IS NO MASTER DATABASE THAT KEEPS TRACK OF ALL THE DATABASES WHICH MAKES CENTRALIZED DATABASE ADMINISTRATION VERY DIFFICULT 4HE MULTILOCATION ARCHITECTURE MAKES GAINING ACCESS TO A DATABASE MORE COMPLEX ONCE AGAIN BECAUSE BOTH THE NAME OF THE DATABASE AND ITS LOCATION IN THE DIRECTORY HIERARCHY MUST BE SPECIFIED 4HE 6!8 31, SYNTAX FOR GAINING ACCESS TO AN 2DB6-3 DATABASE IS THE $%#,!2% $!4!"!3% STATEMENT &OR EXAMPLE THIS $%#,!2% $!4!"!3% STATEMENT ESTABLISHES A CONNECTION TO THE DATABASE NAMED /0 IN THE 6!86-3 DIRECTORY NAMED 3932//4;$%6%,/0-%.44%34= $%#,!2% $!4!"!3% &),%.!-% g3932//4;$%6%,/0-%.44%34=/0g
#HAPTERçç
#REATINGçAç$ATABASEç
1, ʣΣ£Ê ÊÕÌV>ÌÊ>ÀV
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)F THE DATABASE IS IN THE USERS CURRENT DIRECTORY WHICH IS OFTEN THE CASE THE STATEMENT SIMPLIFIES TO
3OME OF THE $"-3 BRANDS THAT USE THIS SCHEME ALLOW YOU TO HAVE ACCESS TO SEVERAL DATABASES CONCURRENTLY EVEN IF THEY DONT SUPPORT QUERIES ACROSS DATABASE BOUNDARIES !GAIN THE MOST COMMON TECHNIQUE USED TO DISTINGUISH AMONG THE MULTIPLE DATABASES IS TO USE A SUPERQUALIFIED TABLE NAME 3INCE TWO DATABASES IN TWO DIFFERENT DIRECTORIES CAN HAVE THE SAME NAME ITS ALSO NECESSARY TO INTRODUCE A DATABASE ALIAS TO ELIMINATE AMBIGUITY 4HESE 6!8 31, STATEMENTS OPEN TWO DIFFERENT 2DB6-3 DATABASES THAT HAPPEN TO HAVE THE SAME NAME $%#,!2% $!4!"!3% /0 &),%.!-% g3932//4;02/$5#4)/.<=/0g $%#,!2% $!4!"!3% /0 &),%.!-% g3932//4;$%6%,/0-%.44%34=/0g
4HE STATEMENTS ASSIGN THE ALIASES /0 AND /0 TO THE TWO DATABASES AND THESE ALIASES ARE USED TO QUALIFY TABLE NAMES IN SUBSEQUENT 6!8 31, STATEMENTS !S THIS DISCUSSION SHOWS THERE CAN BE A TREMENDOUS VARIETY IN THE WAY VARIOUS $"-3 BRANDS ORGANIZE THEIR DATABASES AND PROVIDE ACCESS TO THEM 4HIS AREA OF 31, IS ONE OF THE MOST NONSTANDARD AND YET IT IS OFTEN THE FIRST ONE THAT A USER ENCOUNTERS WHEN TRYING TO ACCESS A DATABASE FOR THE FIRST TIME 4HE INCONSISTENCIES ALSO MAKE IT IMPOSSIBLE TO TRANSPARENTLY MOVE PROGRAMS DEVELOPED FOR ONE $"-3 TO ANOTHER ALTHOUGH THE CONVERSION PROCESS IS USUALLY TEDIOUS RATHER THAN COMPLEX
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$%#,!2% $!4!"!3% &),%.!-% g/0g
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$ATABASEç3TRUCTURE
$ATABASESõONõ-ULTIPLEõ3ERVERS 7ITH THE RISE OF DATABASE SERVERS AND LOCAL AREA NETWORKS THE NOTION OF DATABASE LOCATION EMBODIED IN THE MULTILOCATION ARCHITECTURE IS NATURALLY EXTENDED TO THE NOTION OF A PHYSICAL DATABASE SERVER )N PRACTICE MOST $"-3 PRODUCTS TODAY APPEAR TO BE CONVERGING ON A MULTIDATABASE ARCHITECTURE IMPLEMENTED WITHIN A PHYSICAL SERVER !T THE HIGHEST LEVEL A DATABASE IS ASSOCIATED WITH A NAMED SERVER ON THE NETWORK 7ITHIN THE SERVER THERE CAN BE MULTIPLE NAMED DATABASES 4HE MAPPING OF SERVER NAMES TO PHYSICAL SERVER LOCATIONS IS HANDLED BY THE NETWORKING SOFTWARE 4HE MAPPING OF DATABASE NAMES TO PHYSICAL FILES OR FILE SYSTEMS ON A SERVER IS HANDLED BY THE $"-3 SOFTWARE
$ATABASEõ3TRUCTUREõANDõTHEõ!.3))3/õ3TANDARD 4HE !.3))3/ 31, STANDARD MADE A VERY STRONG DISTINCTION BETWEEN THE 31, $ATA -ANIPULATION ,ANGUAGE AND $ATA $EFINITION ,ANGUAGE DEFINING THEM EFFECTIVELY AS TWO SEPARATE LANGUAGES 4HE STANDARD DID NOT REQUIRE THAT THE $$, STATEMENTS BE ACCEPTED BY THE $"-3 DURING ITS NORMAL OPERATION /NE OF THE ADVANTAGES OF THIS SEPARATION OF THE $-, AND $$, WAS THAT THE STANDARD PERMITTED A STATIC DATABASE STRUCTURE LIKE THAT USED BY OLDER HIERARCHICAL AND NETWORK $"-3 PRODUCTS AS SHOWN IN &IGURE 4HE DATABASE STRUCTURE SPECIFIED BY THE 31, STANDARD WAS FAIRLY STRAIGHTFORWARD #OLLECTIONS OF TABLES WERE DEFINED IN A DATABASE SCHEMA ASSOCIATED WITH A SPECIFIC USER 4HE SIMPLE DATABASE SHOWN IN &IGURE HAS TWO SCHEMAS /NE SCHEMA IS ASSOCIATED WITH THE COMMON TERMINOLOGY IS OWNED BY A USER NAMED *OE AND THE OTHER IS OWNED BY -ARY *OES SCHEMA CONTAINS TWO TABLES NAMED 0%/0,% AND 0,!#%3 -ARYS SCHEMA ALSO CONTAINS TWO TABLES NAMED 4().'3 AND 0,!#%3 !LTHOUGH THE DATABASE CONTAINS TWO TABLES NAMED 0,!#%3 ITS POSSIBLE TO TELL THEM APART BECAUSE THEY HAVE DIFFERENT OWNERS 3TARTING WITH 31, THE 31, STANDARD SIGNIFICANTLY EXTENDS THE NOTION OF DATABASE DEFINITION AND DATABASE SCHEMAS !S PREVIOUSLY NOTED THE 31, STANDARD NOW REQUIRES THAT DATA DEFINITION STATEMENTS BE EXECUTABLE BY AN INTERACTIVE 31, USER OR BY A 31, PROGRAM 7ITH THIS CAPABILITY CHANGES TO THE DATABASE STRUCTURE CAN BE MADE AT ANY TIME NOT JUST WHEN THE DATABASE IS CREATED )N ADDITION THE 31, CONCEPTS OF SCHEMAS AND USERS OFFICIALLY CALLED AUTHORIZATION IDS IN THE STANDARD HAS BEEN SIGNIFICANTLY EXPANDED &IGURE SHOWS THE HIGH LEVEL DATABASE STRUCTURE SPECIFIED BY CURRENT VERSIONS OF THE 31, STANDARD 4HE HIGHEST LEVEL DATABASE STRUCTURE DESCRIBED BY THE 31, STANDARD IS THE 31, ENVIRONMENT 4HIS IS A CONCEPTUAL COLLECTION OF THE DATABASE ENTITIES ASSOCIATED WITH A $"-3 IMPLEMENTATION THAT CONFORMS TO THE 31, STANDARD 4HE STANDARD DOESNT SPECIFY HOW A 31, ENVIRONMENT IS CREATED THAT DEPENDS ON THE PARTICULAR $"-3 IMPLEMENTATION 4HE STANDARD DEFINES THESE COMPONENTS OF A 31, ENVIRONMENT s $"-3 SOFTWARE THAT CONFORMS TO THE 31, STANDARD s .AMED USERS CALLED AUTHORIZATION IDS IN THE STANDARD WHO HAVE THE PRIVILEGES TO PERFORM SPECIFIC ACTIONS ON THE DATA AND STRUCTURES WITHIN THE DATABASE s 0ROGRAM MODULES THAT ARE USED TO ACCESS THE DATABASE 4HE 31, STANDARD SPECIFIES THE ACTUAL EXECUTION OF 31, STATEMENTS IN TERMS OF A MODULE LANGUAGE WHICH IN PRACTICE IS NOT USED BY MOST MAJOR COMMERCIAL 31, PRODUCTS .O MATTER HOW THE 31, PROGRAMS ARE ACTUALLY CREATED HOWEVER THE STANDARD SAYS THAT CONCEPTUALLY THE 31, ENVIRONMENT INCLUDES THE PROGRAMS DATABASE ACCESS CODE
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1, ʣΣÓÊ Ê Ê -ÊÜÌ
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#REATINGçAç$ATABASEç
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s #ATALOGS THAT DESCRIBE THE STRUCTURE OF THE DATABASE 31, STYLE DATABASE SCHEMAS ARE CONTAINED WITHIN THESE CATALOGS s $ATABASE DATA WHICH IS MANAGED BY THE $"-3 SOFTWARE ACCESSED BY THE USERS THROUGH THE PROGRAMS AND WHOSE STRUCTURE IS DESCRIBED IN THE CATALOGS !LTHOUGH THE STANDARD CONCEPTUALLY DESCRIBES THE DATA AS OUTSIDE OF THE CATALOG STRUCTURE ITS COMMON TO THINK OF DATA AS BEING CONTAINED IN A TABLE THAT IS IN A SCHEMA WHICH IS IN A CATALOG
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#ATALOGS 7ITHIN A 31, ENVIRONMENT THE DATABASE STRUCTURE IS DEFINED BY ONE OR MORE NAMED CATALOGS 4HE WORD hCATALOGv IN THIS CASE IS USED IN THE SAME WAY THAT IT HAS HISTORICALLY BEEN USED ON MAINFRAME SYSTEMSTO DESCRIBE A COLLECTION OF OBJECTS USUALLY FILES /N MINICOMPUTER AND PERSONAL COMPUTER SYSTEMS THE CONCEPT IS ROUGHLY ANALOGOUS TO A DIRECTORY )N THE CASE OF A 31, STANDARD DATABASE THE CATALOG IS A COLLECTION OF NAMED DATABASE SCHEMAS 4HE CATALOG ALSO CONTAINS A SET OF SYSTEM TABLES CONFUSINGLY OFTEN CALLED THE SYSTEM CATALOG THAT DESCRIBES THE STRUCTURE OF THE DATABASE 4HE CATALOG IS THUS A SELF DESCRIBING ENTITY WITHIN THE DATABASE 4HIS CHARACTERISTIC OF CATALOGS WHICH IS PROVIDED BY ALL MAJOR 31, PRODUCTS IS DESCRIBED IN DETAIL IN #HAPTER 4HE 31, STANDARD DESCRIBES THE ROLE OF THE CATALOG AND SPECIFIES THAT A 31, ENVIRONMENT MAY CONTAIN ONE OR MORE ACTUALLY ZERO OR MORE CATALOGS EACH OF WHICH MUST HAVE A DISTINCT NAME )T EXPLICITLY SAYS THAT THE MECHANISM FOR CREATING AND DESTROYING CATALOGS IS IMPLEMENTATION DEFINED 4HE STANDARD ALSO SAYS THAT THE EXTENT TO WHICH A $"-3 ALLOWS ACCESS ACROSS CATALOGS IS IMPLEMENTATION DEFINED 3PECIFICALLY WHETHER A SINGLE 31, STATEMENT CAN ACCESS DATA FROM MULTIPLE CATALOGS WHETHER A SINGLE 31, TRANSACTION CAN SPAN MULTIPLE CATALOGS OR EVEN WHETHER A SINGLE USER SESSION WITH THE $"-3 CAN CROSS CATALOG BOUNDARIES ARE ALL IMPLEMENTATION DEFINED CHARACTERISTICS 4HE STANDARD SAYS THAT WHEN A USER OR PROGRAM FIRST ESTABLISHES CONTACT WITH A 31, ENVIRONMENT ONE OF ITS CATALOGS IS IDENTIFIED AS THE DEFAULT CATALOG FOR THE SESSION !GAIN THE WAY IN WHICH THIS CATALOG IS SELECTED IS IMPLEMENTATION DEFINED $URING THE COURSE OF A SESSION THE DEFAULT CATALOG CAN BE CHANGED WITH THE 3%4 #!4!,/' STATEMENT
#HAPTERçç
#REATINGçAç$ATABASEç
3CHEMAS 4HE SCHEMA IS THE KEY HIGH LEVEL CONTAINER FOR OBJECTS IN A 31, DATABASE STRUCTURE ! SCHEMA IS A NAMED ENTITY WITHIN THE DATABASE AND INCLUDES THE DEFINITIONS FOR THE FOLLOWING s 4ABLES !LONG WITH THEIR ASSOCIATED STRUCTURES COLUMNS PRIMARY AND FOREIGN KEYS TABLE CONSTRAINTS AND SO ON TABLES REMAIN THE BASIC BUILDING BLOCKS OF A DATABASE IN A SCHEMA s 6IEWS 4HESE ARE VIRTUAL TABLES DERIVED FROM THE ACTUAL TABLES DEFINED IN THE SCHEMA AS DESCRIBED IN #HAPTER s $OMAINS 4HESE FUNCTION LIKE EXTENDED DATA TYPES FOR DEFINING COLUMNS WITHIN THE TABLES OF THE SCHEMA AS DESCRIBED IN #HAPTER s !SSERTIONS 4HESE DATABASE INTEGRITY CONSTRAINTS RESTRICT THE DATA RELATIONSHIPS ACROSS TABLES WITHIN THE SCHEMA AS DESCRIBED EARLIER IN THE SECTION h!SSERTIONSv s 0RIVILEGES $ATABASE PRIVILEGES CONTROL THE CAPABILITIES THAT ARE GIVEN TO VARIOUS USERS TO ACCESS AND UPDATE DATA IN THE DATABASE AND TO MODIFY THE DATABASE STRUCTURE 4HE 31, SECURITY SCHEME CREATED BY THESE PRIVILEGES IS DESCRIBED IN #HAPTER s #HARACTER SETS $ATABASES SUPPORT INTERNATIONAL LANGUAGES AND MANAGE THE REPRESENTATION OF NON 2OMAN CHARACTERS IN THOSE LANGUAGES FOR EXAMPLE THE DIACRITICAL ACCENT MARKS USED BY MANY %UROPEAN LANGUAGES OR THE BYTE REPRESENTATIONS OF THE WORD SYMBOLS USED IN MANY !SIAN LANGUAGES THROUGH CHARACTER SETS DEFINED BY THE SCHEMA s #OLLATIONS 4HESE WORK HAND IN HAND WITH CHARACTER SETS DEFINING THE SORTING SEQUENCE FOR A CHARACTER SET
! SCHEMA IS CREATED WITH THE #2%!4% 3#(%-! STATEMENT SHOWN IN &IGURE (ERE IS A SIMPLE SCHEMA DEFINITION FOR THE BASIC TWO TABLE SCHEMA FOR *OE SHOWN IN &IGURE #2%!4% 3#(%-! *3#(%-! !54(/2):!4)/. */% #2%!4% 4!",% 0%/0,% .!-% 6!2#(!2 !'% ).4%'%2 #2%!4% 4!",% 0,!#%3 #)49 6!2#(!2 34!4% 6!2#(!2 '2!.4 !,, 02)6),%'%3 /. 0%/0,% 4/ 05",)# '2!.4 3%,%#4 /. 0,!#%3 4/ -!29
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s 4RANSLATIONS 4HESE CONTROL HOW TEXT DATA IS CONVERTED FROM ONE CHARACTER SET TO ANOTHER AND HOW COMPARISONS ARE MADE OF TEXT DATA FROM DIFFERENT CHARACTER SETS
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$ATABASEç3TRUCTURE
1, ʣΣ{Ê #2%!4% 3#(%-!ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
4HE SCHEMA DEFINES THE TWO TABLES AND GIVES CERTAIN OTHER USERS PERMISSION TO ACCESS THEM )T DOESNT DEFINE ANY ADDITIONAL STRUCTURES SUCH AS VIEWS OR ASSERTIONS .OTE THAT THE #2%!4% 4!",% STATEMENTS WITHIN THE #2%!4% 3#(%-! STATEMENT ARE LEGITIMATE 31, STATEMENTS IN THEIR OWN RIGHT )F YOU TYPE THEM INTO AN INTERACTIVE 31, PROGRAM THE $"-3 WILL CREATE THE SPECIFIED TABLES IN THE CURRENT DEFAULT SCHEMA FOR YOUR INTERACTIVE 31, SESSION ACCORDING TO THE STANDARD .OTE THAT THE SCHEMA STRUCTURE IS RELATED TO BUT INDEPENDENT OF THE USER ID STRUCTURE ! GIVEN USER CAN BE THE OWNER OF SEVERAL DIFFERENT NAMED SCHEMAS &OR BACKWARD COMPATIBILITY WITH THE 31, STANDARD HOWEVER THE CURRENT 31, STANDARD ALLOWS YOU TO CREATE A SCHEMA WITH s "OTH A SCHEMA NAME AND A USER ID AS IN THE LAST EXAMPLE s /NLY A SCHEMA NAME )N THIS CASE THE USER WHO EXECUTES THE #2%!4% 3#(%-! STATEMENT AUTOMATICALLY BECOMES THE OWNER OF THE SCHEMA s /NLY A USER ID )N THIS CASE THE SCHEMA NAME BECOMES THE USER ID 4HIS CONFORMS TO THE 31, STANDARD AND TO THE PRACTICE OF MANY COMMERCIAL $"-3 PRODUCTS WHERE THERE WAS CONCEPTUALLY ONE SCHEMA PER USER ! SCHEMA THAT IS NO LONGER NEEDED CAN BE DROPPED USING THE $2/0 3#(%-! STATEMENT SHOWN IN &IGURE 4HE STATEMENT REQUIRES THAT YOU SPECIFY ONE OF THE DROP RULES PREVIOUSLY DESCRIBED FOR DROPPING COLUMNSEITHER #!3#!$% OR 2%342)#4 )F YOU SPECIFY #!3#!$% THEN ALL OF THE STRUCTURES WITHIN THE SCHEMA DEFINITION TABLES VIEWS ASSERTIONS
#HAPTERçç
#REATINGçAç$ATABASEç
1, ʣΣxÊ $2/0 3#(%-!ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
AND SO ON ARE AUTOMATICALLY DROPPED )F YOU SPECIFY 2%342)#4 THE STATEMENT WILL NOT SUCCEED IF ANY OF THESE STRUCTURES REMAINS WITHIN THE SCHEMA %FFECTIVELY THE 2%342)#4 RULE FORCES YOU TO FIRST DROP THE INDIVIDUAL TABLES VIEWS AND OTHER STRUCTURES WITHIN THE SCHEMA BEFORE DROPPING THE SCHEMA ITSELF 4HIS IS A PROTECTION AGAINST ACCIDENTALLY DROPPING A SCHEMA THAT CONTAINS DATA OR DATABASE DEFINITIONS OF VALUE .O !,4%2 3#(%-! TABLE IS SPECIFIED BY THE 31, STANDARD )NSTEAD YOU CAN INDIVIDUALLY ALTER THE DEFINITIONS OF THE STRUCTURES WITHIN A SCHEMA USING STATEMENTS LIKE !,4%2 4!",% !T ANY TIME WHILE A USER OR PROGRAM IS ACCESSING A DATABASE ONE OF ITS SCHEMAS IS IDENTIFIED AS THE DEFAULT SCHEMA !NY $$, STATEMENTS THAT YOU EXECUTE TO CREATE DROP OR ALTER SCHEMA STRUCTURES IMPLICITLY APPLY TO THIS SCHEMA )N ADDITION ALL TABLES NAMED IN 31, DATA MANIPULATION STATEMENTS ARE ASSUMED TO BE TABLES DEFINED WITHIN THIS DEFAULT SCHEMA 4HE SCHEMA NAME IMPLICITLY QUALIFIES THE NAMES OF ALL TABLES USED IN THE 31, STATEMENTS !S NOTED IN #HAPTER YOU CAN USE A QUALIFIED TABLE NAME TO REFER TO TABLES FROM OTHER SCHEMAS !CCORDING TO THE 31, STANDARD THE NAME USED TO QUALIFY THE TABLE NAME IS THE SCHEMA NAME &OR EXAMPLE IF THE SAMPLE DATABASE WERE CREATED AS PART OF A SCHEMA NAMED 3!,%3 THE QUALIFIED TABLE NAME FOR THE /&&)#%3 TABLE WOULD BE 3!,%3/&&)#%3
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)F A SCHEMA IS CREATED WITH JUST A USER ID AS THE SCHEMA NAME THEN THE TABLE QUALIFICATION SCHEME BECOMES EXACTLY THE SIMPLE ONE DESCRIBED IN #HAPTER 4HE SCHEMA NAME IS THE USER NAME AND THE QUALIFIED TABLE NAME SPECIFIES THIS NAME BEFORE THE DOT 4HE #2%!4% 3#(%-! STATEMENT HAS ONE OTHER NONOBVIOUS ADVANTAGE 9OU MAY RECALL FROM THE EARLIER DISCUSSION OF THE #2%!4% 4!",% STATEMENT THAT YOU COULD NOT EASILY CREATE A REFERENTIAL CYCLE TWO OR MORE TABLES THAT REFER TO ONE ANOTHER USING FOREIGN KEYPRIMARY KEY RELATIONSHIPS )NSTEAD ONE OF THE TABLES HAD TO BE CREATED FIRST WITHOUT ITS FOREIGN KEY DEFINITION AND THEN THE FOREIGN KEY DEFINITION HAD TO BE ADDED WITH THE !,4%2 4!",% STATEMENT AFTER THE OTHER TABLES HAD BEEN CREATED 4HE #2%!4% 3#(%-! STATEMENT AVOIDS THIS PROBLEM SINCE THE $"-3 DOES NOT CHECK THE REFERENTIAL INTEGRITY CONSTRAINTS SPECIFIED BY THE SCHEMA UNTIL ALL OF THE TABLES IT DEFINES HAVE BEEN CREATED )N PRACTICE THE #2%!4% 3#(%-! STATEMENT IS GENERALLY USED TO CREATE A NEW SET OF INTERRELATED TABLES FOR THE FIRST TIME 3UBSEQUENTLY INDIVIDUAL TABLES ARE ADDED MODIFIED OR DROPPED USING THE #2%!4% !,4%2$2/0 4!",% CAPABILITIES -ANY OF THE MAJOR $"-3 BRANDS HAVE MOVED TO ADOPT SOME FORM OF THE #2%!4% 3#(%-! STATEMENT ALTHOUGH THERE ARE SIGNIFICANT VARIATIONS ACROSS THE BRANDS /RACLES #2%!4% 3#(%-! STATEMENT ALLOWS YOU TO CREATE TABLES VIEWS AND PRIVILEGES BUT NOT THE OTHER 31, STRUCTURES AND IT REQUIRES THAT THE SCHEMA NAME AND THE USER NAME BE ONE AND THE SAME )NFORMIX 5NIVERSAL 3ERVER FOLLOWS A SIMILAR PATTERN REQUIRING A USER ID AS THE SCHEMA NAME AND EXTENDING THE OBJECTS WITHIN THE SCHEMA TO INCLUDE INDEXES TRIGGERS AND SYNONYMS 3YBASE PROVIDES SIMILAR CAPABILITIES )N EACH CASE THE OFFERED CAPABILITIES CONFORM TO THE 31, ENTRY LEVEL IMPLEMENTATION REQUIREMENTS
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$ATABASEç3TRUCTURE
3UMMARY 4HIS CHAPTER DESCRIBED THE 31, $ATA $EFINITION ,ANGUAGE FEATURES THAT DEFINE AND CHANGE THE STRUCTURE OF A DATABASE s 4HE #2%!4% 4!",% STATEMENT CREATES A TABLE AND DEFINES ITS COLUMNS )T CAN ALSO BE USED TO DEFINE PRIMARY KEY FOREIGN KEY REFERENTIAL AND #(%#+ CONSTRAINTS AS THE TABLE IS CREATED s 4HE $2/0 4!",% STATEMENT REMOVES A PREVIOUSLY CREATED TABLE FROM THE DATABASE s 4HE !,4%2 4!",% STATEMENT CAN BE USED TO ADD CHANGE OR REMOVE A COLUMN OR A CONSTRAINT ON AN EXISTING TABLE s 4HE #2%!4% ).$%8 AND $2/0 ).$%8 STATEMENTS DEFINE INDEXES WHICH SPEED DATABASE QUERIES BUT ADD OVERHEAD TO DATABASE UPDATES s -OST $"-3 BRANDS SUPPORT OTHER #2%!4% $2/0 AND !,4%2 STATEMENTS USED WITH $"-3 SPECIFIC OBJECTS s 4HE 31, STANDARD SPECIFIES A DATABASE SCHEMA CONTAINING A COLLECTION OF TABLES AND THE DATABASE SCHEMA IS MANIPULATED WITH #2%!4% 3#(%-! AND $2/0 3#(%-! STATEMENTS s 6ARIOUS $"-3 BRANDS USE VERY DIFFERENT APPROACHES TO ORGANIZING THE ONE OR MORE DATABASES THAT THEY MANAGE AND THESE DIFFERENCES AFFECT THE WAY YOU DESIGN YOUR DATABASES AND GAIN ACCESS TO THEM
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HE TABLES OF A DATABASE DEFINE THE STRUCTURE AND ORGANIZATION OF ITS DATA (OWEVER 31, ALSO LETS YOU LOOK AT THE STORED DATA IN OTHER WAYS BY DEFINING ALTERNATIVE VIEWS OF THE DATA ! VIEW IS A 31, QUERY THAT IS PERMANENTLY STORED IN THE DATABASE AND ASSIGNED A NAME 4HE RESULTS OF THE STORED QUERY ARE VISIBLE THROUGH THE VIEW AND 31, LETS YOU ACCESS THESE QUERY RESULTS AS IF THEY WERE IN FACT A REAL TABLE IN THE DATABASE 6IEWS ARE AN IMPORTANT PART OF 31, FOR SEVERAL REASONS s 6IEWS LET YOU TAILOR THE APPEARANCE OF A DATABASE SO THAT DIFFERENT USERS SEE IT FROM DIFFERENT PERSPECTIVES s 6IEWS LET YOU RESTRICT ACCESS TO DATA ALLOWING DIFFERENT USERS TO SEE ONLY CERTAIN ROWS ANDOR CERTAIN COLUMNS OF A TABLE s 6IEWS SIMPLIFY DATABASE ACCESS BY PRESENTING THE STRUCTURE OF THE STORED DATA IN THE WAY THAT IS MOST NATURAL FOR EACH USER INCLUDING HIDING COMPLEXITIES SUCH AS JOINS 4HIS CHAPTER DESCRIBES HOW TO CREATE VIEWS AND HOW TO USE VIEWS TO SIMPLIFY PROCESSING AND ENHANCE THE SECURITY OF A DATABASE
7HATõ)SõAõ6IEW ! VIEW IS A VIRTUAL TABLE IN THE DATABASE WHOSE CONTENTS ARE DEFINED BY A QUERY AS SHOWN IN &IGURE 4O THE DATABASE USER THE VIEW APPEARS JUST LIKE A REAL TABLE WITH A SET OF NAMED COLUMNS AND ROWS OF DATA "UT UNLIKE A REAL TABLE A VIEW DOES NOT EXIST IN THE DATABASE AS A STORED SET OF DATA VALUES )NSTEAD THE ROWS AND COLUMNS OF DATA VISIBLE THROUGH THE VIEW ARE THE QUERY RESULTS PRODUCED BY THE QUERY THAT DEFINES THE VIEW 31, CREATES THE ILLUSION OF THE VIEW BY GIVING THE VIEW A NAME LIKE A TABLE NAME AND STORING THE DEFINITION OF THE VIEW IN THE DATABASE 4HE VIEW SHOWN IN &IGURE IS TYPICAL )T HAS BEEN GIVEN THE NAME 2%0$!4! AND IS DEFINED BY THIS TWO TABLE QUERY 3%,%#4 .!-% #)49 2%')/. 15/4! 3!,%32%033!,%3 &2/- 3!,%32%03 /&&)#%3 7(%2% 2%0?/&&)#% /&&)#%
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4HE DATA IN THE VIEW COMES FROM THE 3!,%32%03 AND /&&)#%3 TABLES 4HESE TABLES ARE CALLED THE SOURCE TABLES FOR THE VIEW BECAUSE THEY ARE THE SOURCE OF THE DATA THAT IS VISIBLE THROUGH THE VIEW 4HIS VIEW CONTAINS ONE ROW OF INFORMATION FOR EACH SALESPERSON EXTENDED WITH THE NAME OF THE CITY AND REGION WHERE THE SALESPERSON WORKS !S SHOWN IN THE FIGURE THE VIEW APPEARS AS A TABLE AND ITS CONTENTS LOOK JUST LIKE THE QUERY RESULTS THAT YOU WOULD OBTAIN IF YOU ACTUALLY WERE TO RUN THE QUERY /NCE A VIEW IS DEFINED YOU CAN USE IT IN A 3%,%#4 STATEMENT JUST LIKE A REAL TABLE AS IN THIS QUERY
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,IST THE SALESPEOPLE WHO ARE OVER QUOTA SHOWING THE NAME CITY AND REGION FOR EACH SALESPERSON 3%,%#4 .!-% #)49 2%')/. &2/- 2%0$!4! 7(%2% 3!,%3 15/4! .!-% #)49 2%')/.
-ARY *ONES .EW 9ORK %ASTERN 3AM #LARK .EW 9ORK %ASTERN $AN 2OBERTS #HICAGO %ASTERN 0AUL #RUZ #HICAGO %ASTERN "ILL !DAMS !TLANTA %ASTERN 3UE 3MITH ,OS !NGELES 7ESTERN ,ARRY &ITCH ,OS !NGELES 7ESTERN
4HE NAME OF THE VIEW 2%0$!4! APPEARS IN THE &2/- CLAUSE JUST LIKE A TABLE NAME AND THE COLUMNS OF THE VIEW ARE REFERENCED IN THE 3%,%#4 STATEMENT JUST LIKE THE COLUMNS OF A REAL TABLE &OR SOME VIEWS YOU CAN ALSO USE THE ).3%24 $%,%4% AND 50$!4% STATEMENTS TO MODIFY THE DATA VISIBLE THROUGH THE VIEW AS IF IT WERE A REAL TABLE 4HUS FOR ALL PRACTICAL PURPOSES THE VIEW CAN BE USED IN 31, STATEMENTS AS IF IT WERE A REAL TABLE (OWEVER IT IS ESSENTIAL TO UNDERSTAND THE IMPLICATIONS TO THE UNDERLYING TABLES BEFORE UPDATING VIEWS
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!DVANTAGESõOFõ6IEWS 6IEWS PROVIDE A VARIETY OF BENEFITS AND CAN BE USEFUL IN MANY DIFFERENT TYPES OF DATABASES )N A PERSONAL COMPUTER DATABASE VIEWS ARE USUALLY A CONVENIENCE DEFINED TO SIMPLIFY DATABASE REQUESTS )N A COMMERCIAL DATABASE INSTALLATION VIEWS PLAY A CENTRAL ROLE IN DEFINING THE STRUCTURE OF THE DATABASE FOR ITS USERS AND ENFORCING ITS SECURITY 6IEWS PROVIDE THESE MAJOR BENEFITS s 3ECURITY %ACH USER CAN BE GIVEN PERMISSION TO ACCESS THE DATABASE ONLY THROUGH A SMALL SET OF VIEWS THAT CONTAIN THE SPECIFIC DATA THE USER IS AUTHORIZED TO SEE THUS RESTRICTING THE USERS ACCESS TO STORED DATA s 1UERY SIMPLICITY ! VIEW CAN DRAW DATA FROM SEVERAL DIFFERENT TABLES AND PRESENT IT AS A SINGLE TABLE TURNING MULTITABLE QUERIES INTO SINGLE TABLE QUERIES AGAINST THE VIEW
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7HEN THE $"-3 ENCOUNTERS A REFERENCE TO A VIEW IN A 31, STATEMENT IT FINDS THE DEFINITION OF THE VIEW STORED IN THE DATABASE 4HEN THE $"-3 TRANSLATES THE REQUEST THAT REFERENCES THE VIEW INTO AN EQUIVALENT REQUEST AGAINST THE SOURCE TABLES OF THE VIEW AND CARRIES OUT THE EQUIVALENT REQUEST )N THIS WAY THE $"-3 MAINTAINS THE ILLUSION OF THE VIEW WHILE MAINTAINING THE INTEGRITY OF THE SOURCE TABLES &OR SIMPLE VIEWS THE $"-3 MAY CONSTRUCT EACH ROW OF THE VIEW ON THE FLY DRAWING THE DATA FOR THE ROW FROM THE SOURCE TABLES &OR MORE COMPLEX VIEWS THE $"-3 MUST ACTUALLY MATERIALIZE THE VIEW THAT IS THE $"-3 MUST ACTUALLY CARRY OUT THE QUERY THAT DEFINES THE VIEW AND STORE ITS RESULTS IN A TEMPORARY TABLE 4HE $"-3 FILLS YOUR REQUESTS FOR VIEW ACCESS FROM THIS TEMPORARY TABLE AND DISCARDS THE TABLE WHEN IT IS NO LONGER NEEDED 2EGARDLESS OF HOW THE $"-3 ACTUALLY HANDLES A PARTICULAR VIEW THE RESULT IS THE SAME FOR THE USERTHE VIEW CAN BE REFERENCED IN 31, STATEMENTS EXACTLY AS IF IT WERE A REAL TABLE IN THE DATABASE
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s 3TRUCTURAL SIMPLICITY 6IEWS CAN GIVE A USER A PERSONALIZED VIEW OF THE DATABASE STRUCTURE PRESENTING THE DATABASE AS A SET OF VIRTUAL TABLES THAT MAKE SENSE FOR THAT USER s )NSULATION FROM CHANGE ! VIEW CAN PRESENT A CONSISTENT UNCHANGED IMAGE OF THE STRUCTURE OF THE DATABASE EVEN IF THE UNDERLYING SOURCE TABLES ARE SPLIT RESTRUCTURED OR RENAMED .OTE HOWEVER THAT THE VIEW DEFINITION MUST BE UPDATED WHENEVER UNDERLYING TABLES OR COLUMNS REFERENCED BY THE VIEW ARE RENAMED s $ATA INTEGRITY )F DATA IS ACCESSED AND ENTERED THROUGH A VIEW THE $"-3 CAN AUTOMATICALLY CHECK THE DATA TO ENSURE THAT IT MEETS SPECIFIED INTEGRITY CONSTRAINTS
$ISADVANTAGESõOFõ6IEWS 7HILE VIEWS PROVIDE SUBSTANTIAL ADVANTAGES THERE ARE ALSO THREE MAJOR DISADVANTAGES TO USING A VIEW INSTEAD OF A REAL TABLE s 0ERFORMANCE 6IEWS CREATE THE APPEARANCE OF A TABLE BUT THE $"-3 MUST STILL TRANSLATE QUERIES AGAINST THE VIEW INTO QUERIES AGAINST THE UNDERLYING SOURCE TABLES )F THE VIEW IS DEFINED BY A COMPLEX MULTITABLE QUERY THEN EVEN A SIMPLE QUERY AGAINST THE VIEW BECOMES A COMPLICATED JOIN AND IT MAY TAKE A LONG TIME TO COMPLETE (OWEVER THE ISSUE ISNT BECAUSE THE QUERY IS IN A VIEWANY POORLY CONSTRUCTED QUERY CAN PRESENT PERFORMANCE PROBLEMSTHE HAZARD IS THAT THE COMPLEXITY IS HIDDEN IN THE VIEW AND THUS USERS ARE NOT AWARE OF HOW MUCH WORK THE QUERY IS PERFORMING s -ANAGEABILITY ,IKE ALL DATABASE OBJECTS VIEWS MUST BE MANAGED )F DEVELOPERS AND DATABASE USERS ARE ALLOWED TO FREELY CREATE VIEWS WITHOUT CONTROLS OR STANDARDS THE $"!S JOB BECOMES THAT MUCH MORE DIFFICULT 4HIS IS ESPECIALLY TRUE WHEN VIEWS ARE CREATED THAT REFERENCE OTHER VIEWS WHICH IN TURN REFERENCE EVEN MORE VIEWS 4HE MORE LAYERS BETWEEN THE BASE TABLES AND THE VIEWS THE MORE DIFFICULT IT IS TO RESOLVE PROBLEMS ATTRIBUTED TO THE VIEWS s 5PDATE RESTRICTIONS 7HEN A USER TRIES TO UPDATE ROWS OF A VIEW THE $"-3 MUST TRANSLATE THE REQUEST INTO AN UPDATE ON ROWS OF THE UNDERLYING SOURCE TABLES 4HIS IS POSSIBLE FOR SIMPLE VIEWS BUT MORE COMPLEX VIEWS CANNOT BE UPDATED THEY ARE READ ONLY 4HESE DISADVANTAGES MEAN THAT YOU CANNOT INDISCRIMINATELY DEFINE VIEWS AND USE THEM INSTEAD OF THE SOURCE TABLES )NSTEAD YOU MUST IN EACH CASE CONSIDER THE ADVANTAGES PROVIDED BY USING A VIEW AND WEIGH THEM AGAINST THE DISADVANTAGES
#REATINGõAõ6IEWõ#2%!4%õ6)%7 4HE #2%!4% 6)%7 STATEMENT SHOWN IN &IGURE IS USED TO CREATE A VIEW 4HE STATEMENT ASSIGNS A NAME TO THE VIEW AND SPECIFIES THE QUERY THAT DEFINES THE VIEW 4O CREATE THE VIEW SUCCESSFULLY YOU MUST HAVE PERMISSION TO ACCESS ALL OF THE TABLES REFERENCED IN THE QUERY )N SOME $"-3S NOTABLY /RACLE YOU MUST ALSO HAVE PERMISSION TO CREATE VIEWS 4HE #2%!4% 6)%7 STATEMENT CAN OPTIONALLY ASSIGN A NAME TO EACH COLUMN IN THE NEWLY CREATED VIEW )F A LIST OF COLUMN NAMES IS SPECIFIED IT MUST HAVE THE SAME NUMBER OF ITEMS AS THE NUMBER OF COLUMNS PRODUCED BY THE QUERY .OTE THAT ONLY THE COLUMN NAMES ARE
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SPECIFIED THE DATA TYPE LENGTH AND OTHER CHARACTERISTICS OF EACH COLUMN ARE DERIVED FROM THE DEFINITION OF THE COLUMNS IN THE SOURCE TABLES )F THE LIST OF COLUMN NAMES IS OMITTED FROM THE #2%!4% 6)%7 STATEMENT EACH COLUMN IN THE VIEW TAKES THE NAME OF THE CORRESPONDING COLUMN IN THE QUERY 4HE LIST OF COLUMN NAMES MUST BE SPECIFIED IF THE QUERY PRODUCES TWO COLUMNS WITH IDENTICAL NAMES AND IN SOME $"-3 PRODUCTS IF THE QUERY INCLUDES CALCULATED COLUMNS 7HILE SOME $"-3 PRODUCTS AUTOMATICALLY ASSIGN COLUMN NAMES TO CALCULATED COLUMNS THE NAMES ARE USUALLY NOT VERY USEFUL SO ITS A MUCH BETTER PRACTICE TO ALWAYS ASSIGN COLUMN NAMES TO CALCULATED COLUMNS !LTHOUGH ALL VIEWS ARE CREATED IN THE SAME WAY IN PRACTICE DIFFERENT TYPES OF VIEWS ARE TYPICALLY USED FOR DIFFERENT PURPOSES 4HE NEXT FEW SECTIONS EXAMINE THESE TYPES OF VIEWS AND GIVE EXAMPLES OF THE #2%!4% 6)%7 STATEMENT
(ORIZONTALõ6IEWS ! COMMON USE OF VIEWS IS TO RESTRICT A USERS ACCESS TO ONLY SELECTED ROWS OF A TABLE &OR EXAMPLE IN THE SAMPLE DATABASE YOU MAY WANT TO LET A SALES MANAGER SEE ONLY THE 3!,%32%03 ROWS FOR SALESPEOPLE IN THE MANAGERS OWN REGION 4O ACCOMPLISH THIS YOU CAN DEFINE TWO VIEWS AS FOLLOWS
#2%!4% 6)%7 %!342%03 !3 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ).
#REATE A VIEW SHOWING 7ESTERN REGION SALESPEOPLE #2%!4% 6)%7 7%342%03 !3 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ).
.OW YOU CAN GIVE EACH SALES MANAGER PERMISSION TO ACCESS EITHER THE %!342%03 OR THE 7%342%03 VIEW DENYING THEM PERMISSION TO ACCESS THE OTHER VIEW AND THE 3!,%32%03 TABLE ITSELF 4HIS EFFECTIVELY GIVES THE SALES MANAGER A CUSTOMIZED VIEW OF THE 3!,%32%03 TABLE SHOWING ONLY SALESPEOPLE IN THE APPROPRIATE REGION ! VIEW LIKE %!342%03 OR 7%342%03 IS OFTEN CALLED A HORIZONTAL VIEW !S SHOWN IN &IGURE A HORIZONTAL VIEW SLICES THE SOURCE TABLE HORIZONTALLY TO CREATE THE VIEW !LL OF THE COLUMNS OF THE SOURCE TABLE PARTICIPATE IN THE VIEW BUT ONLY SOME OF ITS ROWS ARE VISIBLE THROUGH THE VIEW (ORIZONTAL VIEWS ARE APPROPRIATE WHEN THE SOURCE TABLE CONTAINS DATA
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#REATE A VIEW SHOWING %ASTERN REGION SALESPEOPLE
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THAT RELATES TO VARIOUS ORGANIZATIONS OR USERS 4HEY PROVIDE A PRIVATE TABLE FOR EACH USER COMPOSED ONLY OF THE ROWS NEEDED BY THAT USER (ERE ARE SOME MORE EXAMPLES OF HORIZONTAL VIEWS $ElNE A VIEW CONTAINING ONLY %ASTERN REGION OFlCES #2%!4% 6)%7 %!34/&&)#%3 !3 3%,%#4 &2/- /&&)#%3 7(%2% 2%')/. g%ASTERNg
$ElNE A VIEW FOR 3UE 3MITH EMPLOYEE NUMBER CONTAINING ONLY ORDERS PLACED BY CUSTOMERS ASSIGNED TO HER #2%!4% 6)%7 35%/2$%23 !3 3%,%#4 &2/- /2$%23 7(%2% #534 ). 3%,%#4 #534?.5- &2/- #534/-%23 7(%2% #534?2%0
$ElNE A VIEW SHOWING ONLY THOSE CUSTOMERS WHO HAVE MORE THAN WORTH OF ORDERS CURRENTLY ON THE BOOKS #2%!4% 6)%7 ")'#534/-%23 !3 3%,%#4 &2/- #534/-%23 7(%2% 3%,%#4 35-!-/5.4 &2/- /2$%23 7(%2% #534 #534?.5-
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)N EACH OF THESE EXAMPLES THE VIEW IS DERIVED FROM A SINGLE SOURCE TABLE 4HE VIEW IS DEFINED BY A 3%,%#4 QUERY AND THEREFORE HAS EXACTLY THE SAME COLUMNS AS THE SOURCE TABLE 4HE 7(%2% CLAUSE DETERMINES WHICH ROWS OF THE SOURCE TABLE ARE VISIBLE IN THE VIEW
6ERTICALõ6IEWS !NOTHER COMMON USE OF VIEWS IS TO RESTRICT A USERS ACCESS TO ONLY CERTAIN COLUMNS OF A TABLE &OR EXAMPLE IN THE SAMPLE DATABASE THE ORDER PROCESSING DEPARTMENT MAY NEED ACCESS TO THE EMPLOYEE NUMBER NAME AND OFFICE ASSIGNMENT OF EACH SALESPERSON BECAUSE THIS INFORMATION MAY BE NEEDED TO PROCESS AN ORDER CORRECTLY (OWEVER THERE IS NO NEED FOR THE ORDER PROCESSING STAFF TO SEE THE SALESPERSONS YEAR TO DATE SALES OR QUOTA 4HIS SELECTIVE VIEW OF THE 3!,%32%03 TABLE CAN BE CONSTRUCTED WITH THE FOLLOWING VIEW #REATE A VIEW SHOWING SELECTED SALESPERSON INFORMATION #2%!4% 6)%7 2%0).&/ !3 3%,%#4 %-0,?.5- .!-% 2%0?/&&)#% &2/- 3!,%32%03
"Y GIVING THE ORDER PROCESSING STAFF ACCESS TO THIS VIEW AND DENYING ACCESS TO THE 3!,%32%03 TABLE ITSELF ACCESS TO SENSITIVE SALES AND QUOTA DATA IS EFFECTIVELY RESTRICTED ! VIEW LIKE THE 2%0).&/ VIEW IS OFTEN CALLED A VERTICAL VIEW !S SHOWN IN &IGURE A VERTICAL VIEW SLICES THE SOURCE TABLE VERTICALLY TO CREATE THE VIEW 6ERTICAL VIEWS ARE COMMONLY FOUND WHERE THE DATA STORED IN A TABLE IS USED BY VARIOUS USERS OR GROUPS OF USERS 4HEY PROVIDE A PRIVATE VIRTUAL TABLE FOR EACH USER COMPOSED ONLY OF THE COLUMNS NEEDED BY THAT USER (ERE ARE SOME MORE EXAMPLES OF VERTICAL VIEWS
#2%!4% 6)%7 /&&)#%).&/ !3 3%,%#4 /&&)#% #)49 2%')/. &2/- /&&)#%3
$ElNE A VIEW OF THE #534/-%23 TABLE THAT INCLUDES ONLY CUSTOMER NAMES AND THEIR ASSIGNMENT TO SALESPEOPLE #2%!4% 6)%7 #534).&/ !3 3%,%#4 #/-0!.9 #534?2%0 &2/- #534/-%23
)N EACH OF THESE EXAMPLES THE VIEW IS DERIVED FROM A SINGLE SOURCE TABLE 4HE SELECT LIST IN THE VIEW DEFINITION DETERMINES WHICH COLUMNS OF THE SOURCE TABLE ARE VISIBLE IN THE VIEW "ECAUSE THESE ARE VERTICAL VIEWS EVERY ROW OF THE SOURCE TABLE IS REPRESENTED IN THE VIEW AND THE VIEW DEFINITION DOES NOT INCLUDE A 7(%2% CLAUSE
2OW#OLUMNõ3UBSETõ6IEWS 7HEN YOU DEFINE A VIEW 31, DOES NOT RESTRICT YOU TO PURELY HORIZONTAL OR VERTICAL SLICES OF A TABLE )N FACT THE 31, DOES NOT INCLUDE THE NOTION OF HORIZONTAL AND VERTICAL VIEWS
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$ElNE A VIEW OF THE /&&)#%3 TABLE FOR THE ORDER PROCESSING STAFF THAT INCLUDES THE OFlCES CITY OFlCE NUMBER AND REGION
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4HESE CONCEPTS MERELY HELP YOU TO VISUALIZE HOW THE VIEW PRESENTS THE INFORMATION FROM THE SOURCE TABLE )TS QUITE COMMON TO DEFINE A VIEW THAT SLICES A SOURCE TABLE IN BOTH THE HORIZONTAL AND VERTICAL DIMENSIONS AS IN THIS EXAMPLE $ElNE A VIEW THAT CONTAINS THE CUSTOMER NUMBER COMPANY NAME AND CREDIT LIMIT OF ALL CUSTOMERS ASSIGNED TO "ILL !DAMS EMPLOYEE NUMBER #2%!4% 6)%7 "),,#534 !3 3%,%#4 #534?.5- #/-0!.9 #2%$)4?,)-)4 &2/- #534/-%23 7(%2% #534?2%0
4HE DATA VISIBLE THROUGH THIS VIEW IS A ROWCOLUMN SUBSET OF THE #534/-%23 TABLE /NLY THE COLUMNS EXPLICITLY NAMED IN THE SELECT LIST OF THE VIEW AND THE ROWS THAT MEET THE SEARCH CONDITION ARE VISIBLE THROUGH THE VIEW
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'ROUPEDõ6IEWS 4HE QUERY SPECIFIED IN A VIEW DEFINITION MAY INCLUDE A '2/50 "9 CLAUSE 4HIS TYPE OF VIEW IS CALLED A GROUPED VIEW BECAUSE THE DATA VISIBLE THROUGH THE VIEW IS THE RESULT OF A GROUPED QUERY 'ROUPED VIEWS PERFORM THE SAME FUNCTION AS GROUPED QUERIES THEY GROUP RELATED ROWS OF DATA AND PRODUCE ONE ROW OF QUERY RESULTS FOR EACH GROUP SUMMARIZING THE DATA IN THAT GROUP ! GROUPED VIEW MAKES THESE GROUPED QUERY RESULTS INTO A VIRTUAL TABLE ALLOWING YOU TO PERFORM FURTHER QUERIES ON THEM (ERE IS AN EXAMPLE OF A GROUPED VIEW $ElNE A VIEW THAT CONTAINS SUMMARY ORDER DATA FOR EACH SALESPERSON #2%!4% 6)%7 /2$?"9?2%0 7(/ (/7?-!.9 4/4!, ,/7 ()'( !6%2!'% !3 3%,%#4 2%0 #/5.4 35-!-/5.4 -).!-/5.4 -!8!-/5.4 !6'!-/5.4 &2/- /2$%23 '2/50 "9 2%0
!S THIS EXAMPLE SHOWS THE DEFINITION OF A GROUPED VIEW SHOULD ALWAYS INCLUDE A COLUMN NAME LIST 4HE LIST ASSIGNS NAMES TO THE COLUMNS IN THE GROUPED VIEW WHICH ARE DERIVED FROM COLUMN FUNCTIONS SUCH AS 35- AND -). )T MAY ALSO SPECIFY A MODIFIED NAME FOR A GROUPING COLUMN )N THIS EXAMPLE THE 2%0 COLUMN OF THE /2$%23 TABLE BECOMES THE 7(/ COLUMN IN THE /2$?"9?2%0 VIEW /NCE THIS GROUPED VIEW IS DEFINED IT CAN BE USED TO SIMPLIFY QUERIES &OR EXAMPLE THIS QUERY GENERATES A SIMPLE REPORT THAT SUMMARIZES THE ORDERS FOR EACH SALESPERSON 3HOW THE NAME NUMBER OF ORDERS TOTAL ORDER AMOUNT AND AVERAGE ORDER SIZE FOR EACH SALESPERSON
5NLIKE A HORIZONTAL OR VERTICAL VIEW THE ROWS IN A GROUPED VIEW DO NOT HAVE A ONE TO ONE CORRESPONDENCE WITH THE ROWS IN THE SOURCE TABLE ! GROUPED VIEW IS NOT JUST A FILTER ON ITS SOURCE TABLE THAT SCREENS OUT CERTAIN ROWS AND COLUMNS )T IS A SUMMARY OF THE SOURCE TABLES THEREFORE A SUBSTANTIAL AMOUNT OF $"-3 PROCESSING MAY BE REQUIRED TO MAINTAIN THE ILLUSION OF A VIRTUAL TABLE FOR GROUPED VIEWS
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'ROUPED VIEWS CAN BE USED IN QUERIES JUST LIKE OTHER SIMPLER VIEWS ! GROUPED VIEW CANNOT BE UPDATED HOWEVER 4HE REASON SHOULD BE OBVIOUS FROM THE EXAMPLE 7HAT WOULD IT MEAN TO UPDATE THE AVERAGE ORDER SIZE FOR SALESREP NUMBER "ECAUSE EACH ROW IN THE GROUPED VIEW CORRESPONDS TO A GROUP OF ROWS FROM THE SOURCE TABLE AND BECAUSE THE COLUMNS IN THE GROUPED VIEW GENERALLY CONTAIN CALCULATED DATA THERE IS NO WAY TO TRANSLATE THE UPDATE REQUEST INTO AN UPDATE AGAINST THE ROWS OF THE SOURCE TABLE 'ROUPED VIEWS THUS FUNCTION AS READ ONLY VIEWS WHICH CAN PARTICIPATE IN QUERIES BUT NOT IN UPDATES 'ROUPED VIEWS CAN BE USED IN QUERIES THAT THEMSELVES GROUP ROWS ACCOMPLISHING A DOUBLE GROUPING OF ROWS THAT CANNOT BE DONE WITH AN ORDINARY QUERY #ONSIDER THIS EXAMPLE &OR EACH SALES OFlCE SHOW THE RANGE OF AVERAGE ORDER SIZES FOR ALL SALESPEOPLE WHO WORK IN THE OFlCE 3%,%#4 2%0?/&&)#% -).!6%2!'% -!8!6%2!'% &2/- 3!,%32%03 /2$?"9?2%0 7(%2% %-0,?.5- 7(/ !.$ 2%0?/&&)#% )3 ./4 .5,, '2/50 "9 2%0?/&&)#%
4HIS QUERY WORKS JUST FINE IN MOST CURRENT 31, IMPLEMENTATIONS )TS A TWO TABLE QUERY THAT GROUPS THE ROWS OF THE /2$?"9?2%0 VIEW BASED ON THE OFFICE TO WHICH THE SALESPERSON IS ASSIGNED "UT RECALL THAT THE /2$?"9?2%0 VIEW ALREADY GROUPS ROWS )F YOU WERE TO ATTEMPT THIS QUERY WITHOUT USING A VIEW FOLDING THE QUERY CONTAINED IN THE /2$?"9?2%0 VIEW INTO THE NEW QUERY IT WOULD LOOK LIKE THIS 3%,%#4 2%0?/&&)#% -).!6'!-/5.4 -!8!6'!-/5.4 &2/- 3!,%32%03 /2$%23 7(%2% %-0,?.5- 2%0 '2/50 "9 2%0 '2/50 "9 2%0?/&&)#%
4HIS QUERY IS ILLEGAL BECAUSE OF THE DOUBLE '2/50 "9 !LSO IN SOME OLDER 31, IMPLEMENTATIONS NESTED FUNCTIONS SUCH AS -).!6'!-/5.4 WERE NOT SUPPORTED BUT FORTUNATELY ALL MODERN 31, IMPLEMENTATIONS NOW SUPPORT THEM
*OINEDõ6IEWS /NE OF THE MOST FREQUENT REASONS FOR USING VIEWS IS TO SIMPLIFY MULTITABLE QUERIES "Y SPECIFYING A TWO TABLE OR THREE TABLE QUERY IN THE VIEW DEFINITION YOU CAN CREATE A JOINED VIEW THAT DRAWS ITS DATA FROM TWO OR THREE DIFFERENT TABLES AND PRESENTS THE QUERY RESULTS AS A SINGLE VIRTUAL TABLE /NCE THE VIEW IS DEFINED YOU CAN OFTEN USE A SIMPLE SINGLE TABLE QUERY AGAINST THE VIEW FOR REQUESTS THAT WOULD OTHERWISE EACH REQUIRE A TWO TABLE OR THREE TABLE JOIN &OR EXAMPLE SUPPOSE THAT 3AM #LARK THE VICE PRESIDENT OF SALES OFTEN RUNS QUERIES AGAINST THE /2$%23 TABLE IN THE SAMPLE DATABASE (OWEVER 3AM DOESNT LIKE TO WORK WITH CUSTOMER AND EMPLOYEE NUMBERS )NSTEAD HED LIKE TO BE ABLE TO USE A VERSION OF THE /2$%23 TABLE THAT HAS NAMES INSTEAD OF NUMBERS (ERE IS A VIEW THAT MEETS 3AMS NEEDS #REATE A VIEW OF THE /2$%23 TABLE WITH NAMES INSTEAD OF NUMBERS #2%!4% 6)%7 /2$%2?).&/ /2$%2?.5- #/-0!.9 2%0?.!-% !-/5.4 !3 3%,%#4 /2$%2?.5- #/-0!.9 .!-% !-/5.4 &2/- /2$%23 #534/-%23 3!,%32%03 7(%2% #534 #534?.5- !.$ 2%0 %-0,?.5-
#HAPTERçç
6I E W S ç
4HIS VIEW IS DEFINED BY A THREE TABLE JOIN !S WITH A GROUPED VIEW THE PROCESSING REQUIRED TO CREATE THE ILLUSION OF A VIRTUAL TABLE FOR THIS VIEW CAN BE CONSIDERABLE %ACH ROW OF THE VIEW IS DERIVED FROM A COMBINATION OF ONE ROW FROM THE /2$%23 TABLE ONE ROW FROM THE #534/-%23 TABLE AND ONE ROW FROM THE 3!,%32%03 TABLE !LTHOUGH IT HAS A RELATIVELY COMPLEX DEFINITION THIS VIEW CAN PROVIDE SOME REAL BENEFITS (ERE IS A QUERY AGAINST THE VIEW THAT GENERATES A REPORT OF ORDERS GROUPED BY SALESPERSON AND COMPANY 3HOW THE TOTAL CURRENT ORDERS FOR EACH COMPANY FOR EACH SALESPERSON 3%,%#4 2%0?.!-% #/-0!.9 35-!-/5.4 &2/- /2$%2?).&/ '2/50 "9 2%0?.!-% #/-0!.9 2%0?.!-% #/-0!.9 35-!-/5.4
"ILL !DAMS !CME -FG "ILL !DAMS *#0 )NC $AN 2OBERTS &IRST #ORP $AN 2OBERTS (OLM ,ANDIS $AN 2OBERTS )AN 3CHMIDT ,ARRY &ITCH -IDWEST 3YSTEMS ,ARRY &ITCH /RION #ORP ,ARRY &ITCH :ETACORP
3%,%#4 .!-% #/-0!.9 35-!-/5.4 &2/- 3!,%32%03 /2$%23 #534/-%23 7(%2% 2%0 %-0,?.5- !.$ #534 #534?.5- '2/50 "9 .!-% #/-0!.9
3IMILARLY ITS EASY TO GENERATE A REPORT OF THE LARGEST ORDERS SHOWING WHO PLACED THEM AND WHO RECEIVED THEM WITH THIS QUERY AGAINST THE VIEW 3HOW THE LARGEST CURRENT ORDERS SORTED BY AMOUNT 3%,%#4 #/-0!.9 !-/5.4 2%0?.!-% &2/- /2$%2?).&/ 7(%2% !-/5.4 /2$%2 "9 !-/5.4 $%3# #/-0!.9 !-/5.4 2%0?.!-%
:ETACORP ,ARRY &ITCH *0 3INCLAIR 3AM #LARK #HEN !SSOCIATES .ANCY !NGELLI !CME -FG "ILL !DAMS !CE )NTERNATIONAL 4OM 3NYDER )AN 3CHMIDT $AN 2OBERTS
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.OTE THAT THIS QUERY IS A SINGLE TABLE 3%,%#4 STATEMENT WHICH IS CONSIDERABLY SIMPLER THAN THE EQUIVALENT THREE TABLE 3%,%#4 STATEMENT FOR THE SOURCE TABLES
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0ARTç)6ç
$ATABASEç3TRUCTURE
4HE VIEW MAKES IT MUCH EASIER TO SEE WHATS GOING ON IN THE QUERY THAN IF IT WERE EXPRESSED AS THE EQUIVALENT THREE TABLE JOIN /F COURSE THE $"-3 MUST WORK JUST AS HARD TO GENERATE THE QUERY RESULTS FOR THE SINGLE TABLE QUERY AGAINST THE VIEW AS IT WOULD TO GENERATE THE QUERY RESULTS FOR THE EQUIVALENT THREE TABLE QUERY )N FACT THE $"-3 MUST PERFORM SLIGHTLY MORE WORK TO HANDLE THE QUERY AGAINST THE VIEW (OWEVER FOR THE HUMAN USER OF THE DATABASE ITS MUCH EASIER TO WRITE AND UNDERSTAND THE SINGLE TABLE QUERY THAT REFERENCES THE VIEW
5PDATINGõAõ6IEW 7HAT DOES IT MEAN TO INSERT A ROW OF DATA INTO A VIEW DELETE A ROW FROM A VIEW OR UPDATE A ROW OF A VIEW &OR SOME VIEWS THESE OPERATIONS CAN OBVIOUSLY BE TRANSLATED INTO EQUIVALENT OPERATIONS AGAINST THE SOURCE TABLES OF THE VIEW &OR EXAMPLE CONSIDER ONCE AGAIN THE %!342%03 VIEW DEFINED EARLIER IN THIS CHAPTER #REATE A VIEW SHOWING %ASTERN REGION SALESPEOPLE #2%!4% 6)%7 %!342%03 !3 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ).
4HIS IS A STRAIGHTFORWARD HORIZONTAL VIEW DERIVED FROM A SINGLE SOURCE TABLE !S SHOWN IN &IGURE IT MAKES SENSE TO TALK ABOUT INSERTING A ROW INTO THIS VIEW IT MEANS THE NEW ROW SHOULD BE INSERTED INTO THE UNDERLYING 3!,%32%03 TABLE FROM WHICH THE VIEW IS DERIVED )T ALSO MAKES SENSE TO DELETE A ROW FROM THE %!342%03 VIEW THIS WOULD DELETE THE CORRESPONDING ROW FROM THE 3!,%32%03 TABLE &INALLY UPDATING A ROW OF THE %!342%03 VIEW MAKES SENSE THIS WOULD UPDATE THE CORRESPONDING ROW OF THE 3!,%32%03 TABLE )N EACH CASE THE ACTION CAN BE CARRIED OUT AGAINST THE CORRESPONDING ROW OF THE SOURCE TABLE PRESERVING THE INTEGRITY OF BOTH THE SOURCE TABLE AND THE VIEW
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#HAPTERçç
6I E W S ç
(OWEVER CONSIDER THE /2$?"9?2%0 GROUPED VIEW AS IT WAS DEFINED EARLIER IN THE SECTION h'ROUPED 6IEWSv $ElNE A VIEW THAT CONTAINS SUMMARY ORDER DATA FOR EACH SALESPERSON #2%!4% 6)%7 /2$?"9?2%0 7(/ (/7?-!.9 4/4!, ,/7 ()'( !6%2!'% !3 3%,%#4 2%0 #/5.4 35-!-/5.4 -).!-/5.4 -!8!-/5.4 !6'!-/5.4 &2/- /2$%23 '2/50 "9 2%0
4HERE IS NO ONE TO ONE CORRESPONDENCE BETWEEN THE ROWS OF THIS VIEW AND THE ROWS OF THE UNDERLYING /2$%23 TABLE SO IT MAKES NO SENSE TO TALK ABOUT INSERTING DELETING OR UPDATING ROWS OF THIS VIEW 4HE /2$?"9?2%0 VIEW IS NOT UPDATEABLE IT IS A READ ONLY VIEW 4HE %!342%03 VIEW AND THE /2$?"9?2%0 VIEW ARE TWO EXTREME EXAMPLES IN TERMS OF THE COMPLEXITY OF THEIR DEFINITIONS 4HERE ARE VIEWS MORE COMPLEX THAN %!342%03 WHERE IT STILL MAKES SENSE TO UPDATE THE VIEW AND THERE ARE VIEWS LESS COMPLEX THAN /2$?"9?2%0 WHERE UPDATES DO NOT MAKE SENSE )N FACT WHICH VIEWS CAN BE UPDATED AND WHICH CANNOT HAS BEEN AN IMPORTANT RELATIONAL DATABASE RESEARCH PROBLEM OVER THE YEARS
6IEWõ5PDATESõANDõTHEõ!.3))3/õ3TANDARD 4HE ORIGINAL !.3))3/ 31, STANDARD 31, SPECIFIES THE VIEWS THAT MUST BE UPDATEABLE IN A DATABASE THAT CLAIMS CONFORMANCE TO THE STANDARD 5PDATEABLE IN THIS CONTEXT REFERS TO INSERTS UPDATES AND DELETES 5NDER THE STANDARD A VIEW CAN BE UPDATED IF THE QUERY THAT DEFINES THE VIEW MEETS ALL OF THESE RESTRICTIONS s $)34).#4 MUST NOT BE SPECIFIED THAT IS DUPLICATE ROWS MUST NOT BE ELIMINATED FROM THE QUERY RESULTS
s %ACH SELECT ITEM MUST BE A SIMPLE COLUMN REFERENCE THE SELECT LIST CANNOT CONTAIN EXPRESSIONS CALCULATED COLUMNS OR COLUMN FUNCTIONS s 4HE 7(%2% CLAUSE MUST NOT INCLUDE A SUBQUERY ONLY SIMPLE ROW BY ROW SEARCH CONDITIONS MAY APPEAR s 4HE QUERY MUST NOT INCLUDE A '2/50 "9 OR A (!6).' CLAUSE 4HE BASIC CONCEPT BEHIND THE RESTRICTIONS IS EASIER TO REMEMBER THAN THE RULES THEMSELVES &OR A VIEW TO BE UPDATEABLE THE $"-3 MUST BE ABLE TO TRACE ANY ROW OF THE VIEW BACK TO ITS SOURCE ROW IN THE SOURCE TABLE 3IMILARLY THE $"-3 MUST BE ABLE TO TRACE EACH INDIVIDUAL COLUMN TO BE UPDATED BACK TO ITS SOURCE COLUMN IN THE SOURCE TABLE )F THE VIEW MEETS THIS TEST THEN ITS POSSIBLE TO DEFINE MEANINGFUL ).3%24 $%,%4% AND 50$!4% OPERATIONS FOR THE VIEW IN TERMS OF THE SOURCE TABLES (OWEVER IF A VIEW LEAVES OUT A SOURCE TABLE COLUMN THAT HAS A ./4 .5,, CONSTRAINT WITHOUT A $%&!5,4 SPECIFICATION YOU CANNOT INSERT A NEW ROW INTO THAT SOURCE TABLE USING THE VIEW 4HE REASON IS THAT THERE IS NO WAY TO SUPPLY A DATA VALUE FOR THE OMITTED COLUMN
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s 4HE &2/- CLAUSE MUST SPECIFY ONLY ONE UPDATEABLE TABLE THAT IS THE VIEW MUST HAVE A SINGLE SOURCE TABLE FOR WHICH THE USER HAS THE REQUIRED PRIVILEGES )F THE SOURCE TABLE IS ITSELF A VIEW THEN THAT VIEW MUST MEET THESE CRITERIA
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0ARTç)6ç
$ATABASEç3TRUCTURE
6IEWõ5PDATESõINõ#OMMERCIALõ31,õ0RODUCTS 4HE 31, STANDARD RULES ON VIEW UPDATES ARE VERY RESTRICTIVE -ANY VIEWS CAN BE THEORETICALLY UPDATED BUT DO NOT SATISFY ALL OF THE RESTRICTIONS )N ADDITION SOME VIEWS CAN SUPPORT SOME OF THE UPDATE OPERATIONS BUT NOT OTHERS AND SOME VIEWS CAN SUPPORT UPDATES ON CERTAIN COLUMNS BUT NOT OTHERS -OST COMMERCIAL 31, IMPLEMENTATIONS HAVE VIEW UPDATE RULES THAT ARE CONSIDERABLY MORE PERMISSIVE THAN THE 31, STANDARD &OR EXAMPLE CONSIDER THIS VIEW #REATE A VIEW SHOWING THE SALES QUOTA AND THE DIFFERENCE BETWEEN THE TWO FOR EACH SALESPERSON #2%!4% 6)%7 3!,%30%2& %-0,?.5- 3!,%3 15/4! $)&& !3 3%,%#4 %-0,?.5- 3!,%3 15/4! 3!,%3 15/4! &2/- 3!,%32%03
4HE 31, STANDARD DISALLOWS ALL UPDATES TO THIS VIEW BECAUSE ITS FOURTH COLUMN IS A CALCULATED COLUMN (OWEVER NOTE THAT EACH ROW IN THE VIEW CAN BE TRACED BACK TO A SINGLE ROW IN THE SOURCE TABLE 3!,%32%03 &OR THIS REASON $" AND MANY OTHER COMMERCIAL 31, IMPLEMENTATIONS ALLOWS $%,%4% OPERATIONS AGAINST THIS VIEW &URTHER $" ALLOWS 50$!4% OPERATIONS ON THE %-0,?.5- 3!,%3 AND 15/4! COLUMNS BECAUSE THEY ARE DIRECTLY DERIVED FROM THE SOURCE TABLE /NLY THE $)&& COLUMN CANNOT BE UPDATED $" DOES NOT ALLOW THE ).3%24 STATEMENT FOR THE VIEW BECAUSE INSERTING A VALUE FOR THE $)&& COLUMN WOULD BE MEANINGLESS 4HE SPECIFIC RULES THAT DETERMINE WHETHER A VIEW CAN BE UPDATED VARY FROM ONE BRAND OF $"-3 TO ANOTHER AND THEY ARE USUALLY FAIRLY DETAILED 3OME VIEWS SUCH AS THOSE BASED ON GROUPED QUERIES CANNOT BE UPDATED BY ANY $"-3 BECAUSE THE UPDATE OPERATIONS SIMPLY DO NOT MAKE SENSE /THER VIEWS MAY BE UPDATEABLE IN ONE BRAND OF $"-3 PARTIALLY UPDATEABLE IN ANOTHER BRAND AND NOT UPDATEABLE IN A THIRD BRAND 3UBSEQUENT VERSIONS OF THE 31, STANDARD INCLUDE A BROADER DEFINITION OF UPDATEABLE VIEWS ALONG WITH CONSIDERABLE LATITUDE FOR VARIATION AMONG $"-3 BRANDS 4HE BEST WAY TO FIND OUT ABOUT UPDATEABILITY OF VIEWS IN YOUR PARTICULAR $"-3 IS TO CONSULT THE USERS GUIDE OR EXPERIMENT WITH DIFFERENT TYPES OF VIEWS
#HECKINGõ6IEWõ5PDATESõ#(%#+õ/04)/. )F A VIEW IS DEFINED BY A QUERY THAT INCLUDES A 7(%2% CLAUSE ONLY ROWS THAT MEET THE SEARCH CONDITION ARE VISIBLE IN THE VIEW /THER ROWS MAY BE PRESENT IN THE SOURCE TABLES FROM WHICH THE VIEW IS DERIVED BUT THEY ARE NOT VISIBLE THROUGH THE VIEW &OR EXAMPLE THE %!342%03 VIEW DESCRIBED IN THE h(ORIZONTAL 6IEWSv SECTION EARLIER IN THIS CHAPTER CONTAINS ONLY THOSE ROWS OF THE 3!,%32%03 TABLE WITH SPECIFIC VALUES IN THE 2%0?/&&)#% COLUMN #REATE A VIEW SHOWING %ASTERN REGION SALESPEOPLE #2%!4% 6)%7 %!342%03 !3 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ).
4HIS IS AN UPDATEABLE VIEW FOR MOST COMMERCIAL 31, IMPLEMENTATIONS 9OU CAN ADD A NEW SALESPERSON WITH THIS ).3%24 STATEMENT ).3%24 ).4/ %!342%03 %-0,?.5- .!-% 2%0?/&&)#% !'% ()2%?$!4% 3!,%3 6!,5%3 g*AKE +IMBALLg g g
#HAPTERçç
6I E W S ç
4HE $"-3 WILL ADD THE NEW ROW TO THE UNDERLYING 3!,%32%03 TABLE AND THE ROW WILL BE VISIBLE THROUGH THE %!342%03 VIEW "UT CONSIDER WHAT HAPPENS WHEN YOU ADD A NEW SALESPERSON WITH THIS ).3%24 STATEMENT ).3%24 ).4/ %!342%03 %-0,?.5- .!-% 2%0?/&&)#% !'% ()2%?$!4% 3!,%3 6!,5%3 g&RED 2OBERTSg g g
4HIS IS A PERFECTLY LEGAL 31, STATEMENT AND THE $"-3 WILL INSERT A NEW ROW WITH THE SPECIFIED COLUMN VALUES INTO THE 3!,%32%03 TABLE (OWEVER THE NEWLY INSERTED ROW DOESNT MEET THE SEARCH CONDITION FOR THE VIEW )TS 2%0?/&&)#% VALUE SPECIFIES THE ,OS !NGELES OFFICE WHICH IS IN THE 7ESTERN REGION !S A RESULT IF YOU RUN THIS QUERY IMMEDIATELY AFTER THE ).3%24 STATEMENT 3%,%#4 %-0,?.5- .!-% 2%0?/&&)#% &2/- %!342%03 %-0,?.5- .!-% 2%0?/&&)#%
"ILL !DAMS -ARY *ONES 3AM #LARK "OB 3MITH $AN 2OBERTS 0AUL #RUZ
THE NEWLY ADDED ROW DOESNT SHOW UP IN THE VIEW 4HE SAME THING HAPPENS IF YOU CHANGE THE OFFICE ASSIGNMENT FOR ONE OF THE SALESPEOPLE CURRENTLY IN THE VIEW 4HIS 50$!4% STATEMENT
MODIFIES ONE OF THE COLUMNS FOR "OB 3MITHS ROW AND IMMEDIATELY CAUSES IT TO DISAPPEAR FROM THE VIEW /F COURSE BOTH OF THE VANISHING ROWS SHOW UP IN A QUERY AGAINST THE UNDERLYING TABLE 3%,%#4 %-0,?.5- .!-% 2%0?/&&)#% &2/- 3!,%32%03 %-0,?.5- .!-% 2%0?/&&)#%
"ILL !DAMS -ARY *ONES 3UE 3MITH 3AM #LARK "OB 3MITH $AN 2OBERTS 4OM 3NYDER .5,, ,ARRY &ITCH 0AUL #RUZ .ANCY !NGELLI &RED 2OBERTS
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50$!4% %!342%03 3%4 2%0?/&&)#% 7(%2% %-0,?.5-
ç
0ARTç)6ç
$ATABASEç3TRUCTURE
4HE FACT THAT THE ROWS VANISH FROM THE VIEW AS A RESULT OF AN ).3%24 OR 50$!4% STATEMENT IS DISCONCERTING AT BEST 9OU PROBABLY WANT THE $"-3 TO DETECT AND PREVENT THIS TYPE OF ).3%24 OR 50$!4% FROM TAKING PLACE THROUGH THE VIEW 31, ALLOWS YOU TO SPECIFY THIS KIND OF INTEGRITY CHECKING FOR VIEWS BY CREATING THE VIEW WITH A CHECK OPTION 4HE CHECK OPTION IS SPECIFIED IN THE #2%!4% 6)%7 STATEMENT AS SHOWN IN THIS REDEFINITION OF THE %!342%03 VIEW $2/0 6)%7 %!342%03 #2%!4% 6)%7 %!342%03 !3 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). 7)4( #(%#+ /04)/.
.OTE THAT A VIEW THAT ALREADY EXISTS MUST BE DROPPED AND RE CREATED IN ORDER TO APPLY A CHANGE SUCH AS THIS ONE $ROPPING VIEWS IS DISCUSSED IN THE NEXT TOPIC 7HEN THE CHECK OPTION IS REQUESTED FOR A VIEW 31, AUTOMATICALLY CHECKS EACH ).3%24 AND EACH 50$!4% OPERATION FOR THE VIEW TO MAKE SURE THAT THE RESULTING ROWS MEET THE SEARCH CRITERIA IN THE VIEW DEFINITION )F AN INSERTED OR MODIFIED ROW WOULD NOT MEET THE CONDITION THE ).3%24 OR 50$!4% STATEMENT FAILS AND THE OPERATION IS NOT CARRIED OUT 4HE 31, STANDARD SPECIFIES ONE ADDITIONAL REFINEMENT TO THE CHECK OPTION THE CHOICE OF #!3#!$%$ OR ,/#!, APPLICATION OF THE CHECK OPTION 4HIS CHOICE APPLIES WHEN A VIEW IS CREATED AND ITS DEFINITION IS BASED NOT ON AN UNDERLYING TABLE BUT ON ONE OR MORE OTHER VIEWS 4HE DEFINITIONS OF THESE UNDERLYING VIEWS MIGHT IN TURN BE BASED ON STILL OTHER VIEWS AND SO ON %ACH OF THE UNDERLYING VIEWS MIGHT OR MIGHT NOT HAVE THE CHECK OPTION SPECIFIED )F THE NEW VIEW IS CREATED 7)4( #!3#!$%$ #(%#+ /04)/. ANY ATTEMPT TO UPDATE THE VIEW CAUSES THE $"-3 TO GO DOWN THROUGH THE ENTIRE HIERARCHY OF VIEW DEFINITIONS ON WHICH IT IS BASED PROCESSING THE CHECK OPTION FOR EACH VIEW WHERE IT IS SPECIFIED )F THE NEW VIEW IS CREATED 7)4( ,/#!, #(%#+ /04)/. THEN THE $"-3 CHECKS ONLY THAT VIEW THE UNDERLYING VIEWS ARE NOT CHECKED 4HE 31, STANDARD SPECIFIES #!3#!$%$ AS THE DEFAULT IF THE 7)4( #(%#+ /04)/. CLAUSE IS USED WITHOUT SPECIFYING ,/#!, OR #!3#!$%$ )TS PROBABLY CLEAR FROM THE DISCUSSION THAT THE CHECK OPTION CAN ADD SIGNIFICANT OVERHEAD TO THE ).3%24 AND 50$!4% OPERATIONS ESPECIALLY IF YOU ARE UPDATING A VIEW THAT IS DEFINED BASED ON SEVERAL LAYERS OF UNDERLYING VIEW DEFINITIONS (OWEVER THE CHECK OPTION PLAYS AN IMPORTANT ROLE TO ENSURE THE INTEGRITY OF THE DATABASE !FTER ALL IF THE UPDATE WAS INTENDED TO APPLY TO DATA NOT VISIBLE THROUGH THE VIEW OR TO EFFECTIVELY SWITCH A ROW OF DATA FROM ONE VIEW TO ANOTHER THEN LOGICALLY THE UPDATE SHOULD BE MADE THROUGH AN UNDERLYING VIEW OR BASE TABLE 7HEN YOU CREATE AN UPDATEABLE VIEW AS PART OF A SECURITY SCHEME ITS ALMOST ALWAYS A GOOD IDEA TO SPECIFY THE CHECK OPTION )T PREVENTS MODIFICATIONS MADE THROUGH THE VIEW FROM AFFECTING DATA THAT ISNT ACCESSIBLE TO THE USER IN THE FIRST PLACE
#HAPTERçç
6I E W S ç
$ROPPINGõAõ6IEWõ$2/0õ6)%7 2ECALL THAT THE 31, STANDARD TREATED THE 31, $ATA $EFINITION ,ANGUAGE $$, AS A STATIC SPECIFICATION OF THE STRUCTURE OF A DATABASE INCLUDING ITS TABLES AND VIEWS &OR THIS REASON THE 31, STANDARD DID NOT PROVIDE THE ABILITY TO DROP A VIEW WHEN IT WAS NO LONGER NEEDED (OWEVER ALL MAJOR $"-3 BRANDS HAVE PROVIDED THIS CAPABILITY FOR SOME TIME "ECAUSE VIEWS BEHAVE LIKE TABLES AND A VIEW CANNOT HAVE THE SAME NAME AS A TABLE SOME $"-3 BRANDS USED THE $2/0 4!",% STATEMENT TO DROP VIEWS AS WELL /THER 31, IMPLEMENTATIONS PROVIDED A SEPARATE $2/0 6)%7 STATEMENT 4HE 31, STANDARD FORMALIZED SUPPORT FOR DROPPING VIEWS THROUGH A $2/0 6)%7 STATEMENT STARTING WITH THE 31, VERSION )T ALSO PROVIDES FOR DETAILED CONTROL OVER WHAT HAPPENS WHEN A USER ATTEMPTS TO DROP A VIEW WHEN THE DEFINITION OF ANOTHER VIEW DEPENDS ON IT &OR EXAMPLE SUPPOSE TWO VIEWS ON THE 3!,%32%03 TABLE HAVE BEEN CREATED BY THESE TWO #2%!4% 6)%7 STATEMENTS #2%!4% 6)%7 %!342%03 !3 3%,%#4 &2/- 3!,%32%03 7(%2% 2%0?/&&)#% ). #2%!4% 6)%7 .92%03 !3 3%,%#4 &2/- %!342%03 7(%2% 2%0?/&&)#%
$2/0 6)%7 %!342%03 #!3#!$%
4HE #!3#!$% OPTION TELLS THE $"-3 TO DELETE NOT ONLY THE NAMED VIEW BUT ALSO ANY VIEWS THAT DEPEND ON ITS DEFINITION )N CONTRAST THIS $2/0 6)%7 STATEMENT $2/0 6)%7 %!342%03 2%342)#4
FAILS WITH AN ERROR BECAUSE THE 2%342)#4 OPTION TELLS THE $"-3 TO REMOVE THE VIEW ONLY IF NO OTHER VIEWS DEPEND ON IT 4HIS PROVIDES AN ADDED PRECAUTION AGAINST UNINTENTIONAL SIDE EFFECTS OF A $2/0 6)%7 STATEMENT 4HE 31, STANDARD REQUIRES THAT EITHER 2%342)#4 OR #!3#!$% BE SPECIFIED "UT MANY COMMERCIAL 31, PRODUCTS SUPPORT A VERSION OF THE $2/0 6)%7 STATEMENT WITHOUT AN EXPLICITLY SPECIFIED OPTION FOR BACKWARD COMPATIBILITY WITH EARLIER VERSIONS OF THEIR PRODUCTS RELEASED BEFORE THE PUBLICATION OF THE 31, STANDARD 4HE SPECIFIC BEHAVIOR OF DEPENDENT VIEWS IN THIS CASE DEPENDS ON THE PARTICULAR $"-3 BRAND
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&OR PURPOSES OF ILLUSTRATION THE .92%03 VIEW IS DEFINED IN TERMS OF THE %!342%03 VIEW ALTHOUGH IT COULD JUST AS EASILY HAVE BEEN DEFINED IN TERMS OF THE UNDERLYING TABLE 5NDER THE 31, STANDARD THE FOLLOWING $2/0 6)%7 STATEMENT REMOVES BOTH OF THE VIEWS FROM THE DATABASE
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0ARTç)6ç
$ATABASEç3TRUCTURE
-ATERIALIZEDõ6IEWS
#ONCEPTUALLY A VIEW IS A VIRTUAL TABLE WITHIN A DATABASE 4HE ROWCOLUMN DATA IN THE VIEW IS NOT PHYSICALLY STORED IN THE DATABASE IT IS DERIVED FROM ACTUAL DATA IN THE UNDERLYING SOURCE TABLES )F THE VIEW DEFINITION IS RELATIVELY SIMPLE FOR EXAMPLE IF THE VIEW IS A SIMPLE ROWCOLUMN SUBSET OF A SINGLE TABLE OR A SIMPLE JOIN BASED ON FOREIGN KEY RELATIONSHIPS IT IS FAIRLY EASY FOR THE $"-3 TO TRANSLATE DATABASE OPERATIONS ON THE VIEW INTO OPERATIONS ON THE UNDERLYING TABLES )N THIS SITUATION THE $"-3 WILL PERFORM THIS TRANSLATION ON THE FLY OPERATION BY OPERATION AS IT PROCESSES DATABASE QUERIES OR UPDATES )N GENERAL OPERATIONS THAT UPDATE THE DATABASE THROUGH A VIEW ).3%24 50$!4% OR $%,%4% OPERATIONS WILL ALWAYS BE CARRIED OUT IN THIS WAYBY TRANSLATING THE OPERATION INTO ONE OR MORE OPERATIONS ON THE SOURCE TABLES )F THE VIEW DEFINITION IS MORE COMPLICATED THE $"-3 MAY NEED TO MATERIALIZE THE VIEW TO CARRY OUT A QUERY AGAINST IT 4HAT IS THE $"-3 WILL ACTUALLY CARRY OUT THE QUERY THAT DEFINES THE VIEW AND STORE THE QUERY RESULTS IN A TEMPORARY TABLE WITHIN THE DATABASE 4HEN THE $"-3 CARRIES OUT THE REQUESTED QUERY AGAINST THIS TEMPORARY TABLE TO OBTAIN THE REQUESTED RESULTS 7HEN THE QUERY PROCESSING HAS FINISHED THE $"-3 DISCARDS THE TEMPORARY TABLE &IGURE SHOWS THIS MATERIALIZATION PROCESS #LEARLY MATERIALIZING THE VIEW CONTENTS CAN BE A VERY HIGH OVERHEAD OPERATION )F THE TYPICAL DATABASE WORKLOAD CONTAINS MANY QUERIES THAT REQUIRE VIEW MATERIALIZATION THE TOTAL THROUGHPUT CAPACITY OF THE $"-3 CAN BE DRAMATICALLY REDUCED 4O ADDRESS THIS PROBLEM SOME COMMERCIAL $"-3 PRODUCTS SUPPORT MATERIALIZED VIEWS 7HEN YOU DEFINE A VIEW AS A MATERIALIZED VIEW THE $"-3 WILL CARRY OUT THE QUERY THAT
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#HAPTERçç
6I E W S ç
DEFINES THE VIEW ONCE TYPICALLY WHEN THE MATERIALIZED VIEW IS DEFINED STORE THE RESULTS IE THE DATA THAT APPEARS IN THE VIEW WITHIN THE DATABASE AND THEN PERMANENTLY MAINTAIN THIS COPY OF THE VIEW DATA 4O MAINTAIN THE ACCURACY OF THE MATERIALIZED VIEW DATA THE $"-3 MUST AUTOMATICALLY EXAMINE EVERY CHANGE TO THE DATA IN THE UNDERLYING SOURCE TABLES AND MAKE THE CORRESPONDING CHANGES IN THE MATERIALIZED VIEW DATA )N A FEW $"-3 PRODUCTS THE UPDATES TO THE MATERIALIZED VIEW OCCUR AS THE SOURCE TABLES ARE UPDATED BUT IT IS FAR MORE COMMON FOR THE $"-3 TO LOG THE TABLE CHANGES AND APPLY THEM TO THE MATERIALIZED VIEW AT A REGULARLY SCHEDULED INTERVAL 7HEN THE $"-3 MUST PROCESS A QUERY AGAINST THE MATERIALIZED VIEW IT HAS THE DATA ALREADY AT HAND AND CAN PROCESS THE QUERY VERY EFFICIENTLY &IGURE SHOWS $"-3 OPERATION WITH A MATERIALIZED VIEW -ATERIALIZED VIEWS PROVIDE A TRADE OFF BETWEEN THE EFFICIENCY OF UPDATES ON THE DATA CONTAINED IN THE VIEW AND THE EFFICIENCY OF QUERIES ON THE VIEW DATA )N A NONMATERIALIZED VIEW UPDATES TO THE SOURCE TABLES FOR A VIEW ARE UNAFFECTED BY THE VIEW DEFINITION THEY PROCEED AT NORMAL $"-3 PROCESSING SPEED (OWEVER QUERIES AGAINST A NONMATERIALIZED VIEW CAN BE MUCH LESS EFFICIENT THAN QUERIES AGAINST ORDINARY DATABASE TABLES SINCE THE $"-3 MUST DO A GREAT DEAL OF ON THE FLY WORK TO PROCESS THE QUERIES -ATERIALIZED VIEWS REVERSE THIS BALANCE OF WORK 7HEN A MATERIALIZED VIEW IS DEFINED UPDATES TO THE SOURCE TABLES FOR THE VIEW ARE MUCH LESS EFFICIENT THAN UPDATES TO ORDINARY DATABASE TABLES SINCE THE $"-3 MUST CALCULATE THE IMPACT OF THE UPDATES AND CHANGE THE MATERIALIZED VIEW DATA ACCORDINGLY (OWEVER QUERIES AGAINST A MATERIALIZED VIEW CAN PROCEED AT THE SAME SPEED AS QUERIES AGAINST ACTUAL DATABASE TABLES SINCE THE MATERIALIZED VIEW IS REPRESENTED WITHIN THE DATABASE IN THE SAME FORM AS A REAL TABLE 4HUS A MATERIALIZED VIEW IS MOST USEFUL WHEN THE VOLUME OF UPDATES TO THE UNDERLYING DATA IS RELATIVELY SMALL AND THE VOLUME OF QUERIES AGAINST THE VIEW IS RELATIVELY HIGH
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$ATABASEç3TRUCTURE
3UMMARY 6IEWS ALLOW YOU TO REDEFINE THE STRUCTURE OF A DATABASE GIVING EACH USER A PERSONALIZED VIEW OF THE DATABASE STRUCTURE AND CONTENTS s ! VIEW IS A VIRTUAL TABLE DEFINED BY A QUERY 4HE VIEW APPEARS TO CONTAIN ROWS AND COLUMNS OF DATA JUST LIKE A REAL TABLE BUT THE DATA VISIBLE THROUGH THE VIEW IS IN FACT THE RESULTS OF THE QUERY s ! VIEW CAN BE A SIMPLE ROWCOLUMN SUBSET OF A SINGLE TABLE IT CAN SUMMARIZE A TABLE A GROUPED VIEW OR IT CAN DRAW ITS DATA FROM TWO OR MORE TABLES A JOINED VIEW s ! VIEW CAN BE REFERENCED LIKE A REAL TABLE IN A 3%,%#4 ).3%24 $%,%4% OR 50$!4% STATEMENT (OWEVER MORE COMPLEX VIEWS CANNOT BE UPDATED THEY ARE READ ONLY VIEWS s 6IEWS ARE COMMONLY USED TO SIMPLIFY THE APPARENT STRUCTURE OF A DATABASE TO SIMPLIFY QUERIES AND TO PROTECT CERTAIN ROWS ANDOR COLUMNS FROM UNAUTHORIZED ACCESS s -ATERIALIZED VIEWS CAN IMPROVE THE EFFICIENCY OF DATABASE PROCESSING IN SITUATIONS WHERE THERE IS A VERY HIGH VOLUME OF QUERY ACTIVITY AND RELATIVELY LOW UPDATE ACTIVITY
#(!04%2
31,ç3ECURITY
7
HEN YOU ENTRUST YOUR DATA TO A DATABASE MANAGEMENT SYSTEM THE SECURITY OF THE STORED DATA IS A MAJOR CONCERN 3ECURITY IS ESPECIALLY IMPORTANT IN A 31, BASED $"-3 BECAUSE INTERACTIVE 31, MAKES DATABASE ACCESS VERY EASY 4HE SECURITY REQUIREMENTS OF A TYPICAL COMMERCIAL DATABASE ARE MANY AND VARIED s 4HE DATA IN ANY GIVEN TABLE SHOULD BE ACCESSIBLE TO SOME USERS BUT ACCESS BY OTHER USERS SHOULD BE PREVENTED s 3OME USERS SHOULD BE ALLOWED TO UPDATE DATA IN A PARTICULAR TABLE OTHERS SHOULD BE ALLOWED ONLY TO RETRIEVE DATA s &OR SOME TABLES ACCESS SHOULD BE RESTRICTED ON A COLUMN BY COLUMN BASIS s 3OME USERS SHOULD BE DENIED INTERACTIVE 31, ACCESS TO A TABLE BUT SHOULD BE ALLOWED TO USE APPLICATION PROGRAMS THAT UPDATE THE TABLE 4HE 31, SECURITY SCHEME DESCRIBED IN THIS CHAPTER PROVIDES THESE TYPES OF PROTECTION FOR DATA IN A RELATIONAL DATABASE
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31,õ3ECURITYõ#ONCEPTS )MPLEMENTING A SECURITY SCHEME AND ENFORCING SECURITY RESTRICTIONS ARE THE RESPONSIBILITY OF THE $"-3 SOFTWARE 4HE 31, DEFINES AN OVERALL FRAMEWORK FOR DATABASE SECURITY AND 31, STATEMENTS ARE USED TO SPECIFY SECURITY RESTRICTIONS 4HE 31, SECURITY SCHEME IS BASED ON THREE CENTRAL CONCEPTS s 5SERS 4HE ACTORS IN THE DATABASE %ACH TIME THE $"-3 RETRIEVES INSERTS DELETES OR UPDATES DATA IT DOES SO ON BEHALF OF SOME USER 4HE $"-3 PERMITS OR PROHIBITS THE ACTION DEPENDING ON WHICH USER IS MAKING THE REQUEST s $ATABASE OBJECTS 4HE ITEMS TO WHICH 31, SECURITY PROTECTION CAN BE APPLIED 3ECURITY IS USUALLY APPLIED TO TABLES AND VIEWS BUT OTHER OBJECTS SUCH AS FORMS APPLICATION PROGRAMS AND ENTIRE DATABASES CAN ALSO BE PROTECTED -OST USERS WILL HAVE PERMISSION TO USE CERTAIN DATABASE OBJECTS BUT WILL BE PROHIBITED FROM USING OTHERS s 0RIVILEGES 4HE ACTIONS THAT A USER IS PERMITTED TO CARRY OUT FOR A GIVEN DATABASE OBJECT ! USER MAY HAVE PERMISSION TO 3%,%#4 AND ).3%24 ROWS IN A CERTAIN TABLE FOR EXAMPLE BUT MAY LACK PERMISSION TO $%,%4% OR 50$!4% ROWS OF THE TABLE ! DIFFERENT USER MAY HAVE A DIFFERENT SET OF PRIVILEGES &IGURE SHOWS HOW THESE SECURITY CONCEPTS MIGHT BE USED IN A SECURITY SCHEME FOR THE SAMPLE DATABASE 4O ESTABLISH A SECURITY SCHEME FOR A DATABASE YOU USE THE 31, '2!.4 STATEMENT TO SPECIFY WHICH USERS HAVE WHICH PRIVILEGES ON WHICH DATABASE OBJECTS &OR EXAMPLE HERE IS A '2!.4 STATEMENT THAT LETS 3AM #LARK RETRIEVE AND INSERT DATA IN THE /&&)#%3 TABLE OF THE SAMPLE DATABASE ,ET 3AM #LARK RETRIEVE AND INSERT DATA IN THE /&&)#%3 TABLE '2!.4 3%,%#4 ).3%24 /. /&&)#%3 4/ 3!-
4HE '2!.4 STATEMENT SPECIFIES A COMBINATION OF A USER ID 3!- AN OBJECT THE /&&)#%3 TABLE AND PRIVILEGES 3%,%#4 AND ).3%24 /NCE GRANTED THE PRIVILEGES CAN BE RESCINDED LATER WITH THIS 2%6/+% STATEMENT 4AKE AWAY THE PRIVILEGES GRANTED EARLIER TO 3AM #LARK 2%6/+% 3%,%#4 ).3%24 /. /&&)#%3 &2/- 3!-
4HE '2!.4 AND 2%6/+% STATEMENTS ARE DESCRIBED IN DETAIL LATER IN THIS CHAPTER IN THE SECTIONS h'RANTING 0RIVILEGES '2!.4 v AND h2EVOKING 0RIVILEGES 2%6/+% v
5SER )DS %ACH USER OF A 31, BASED DATABASE IS TYPICALLY ASSIGNED A USER ID A SHORT NAME THAT IDENTIFIES THE USER TO THE $"-3 SOFTWARE 4HE USER ID IS AT THE HEART OF 31, SECURITY %VERY 31, STATEMENT EXECUTED BY THE $"-3 IS CARRIED OUT ON BEHALF OF A SPECIFIC USER ID 4HE USER ID DETERMINES
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WHETHER THE STATEMENT WILL BE PERMITTED OR PROHIBITED BY THE $"-3 )N A COMMERCIAL DATABASE USER IDS EITHER ARE ASSIGNED BY THE DATABASE ADMINISTRATOR OR FOR PRODUCTS THAT CAN USE EXTERNAL IDENTIFIERS FROM OPERATING SYSTEM ACCOUNTS BY A SECURITY ADMINISTRATOR ! PERSONAL COMPUTER DATABASE MAY HAVE ONLY A SINGLE USER ID IDENTIFYING THE USER WHO CREATED AND WHO OWNS THE DATABASE 3PECIAL PURPOSE DATABASES FOR EXAMPLE THOSE DESIGNED TO BE EMBEDDED WITHIN AN APPLICATION OR IN A SPECIAL PURPOSE SYSTEM MAY NOT NEED THE ADDITIONAL OVERHEAD ASSOCIATED WITH 31, SECURITY 4HESE DATABASES TYPICALLY OPERATE AS IF THERE WERE A SINGLE USER ID )N PRACTICE THE RESTRICTIONS ON THE NAMES THAT CAN BE CHOSEN AS USER IDS VARY FROM IMPLEMENTATION TO IMPLEMENTATION 4HE 31, STANDARD PERMITTED USER IDS OF UP TO CHARACTERS AND REQUIRED THEM TO BE VALID 31, NAMES WHICH WAS INCREASED TO UP TO CHARACTERS IN LATER VERSIONS )N SOME MAINFRAME $"-3 SYSTEMS USER IDS MAY HAVE NO MORE THAN EIGHT CHARACTERS )N 3YBASE AND 31, 3ERVER USER IDS MAY HAVE UP TO CHARACTERS )F PORTABILITY IS A CONCERN ITS BEST TO LIMIT USER IDS TO EIGHT OR FEWER CHARACTERS &IGURE SHOWS VARIOUS USERS WHO NEED ACCESS TO THE SAMPLE DATABASE AND THE TYPICAL USER IDS ASSIGNED TO THEM .OTE THAT ALL OF THE USERS IN THE ORDER PROCESSING DEPARTMENT CAN BE ASSIGNED THE SAME USER ID BECAUSE THEY ARE TO HAVE IDENTICAL PRIVILEGES IN THE DATABASE (OWEVER MOST SECURITY EXPERTS RECOMMEND AGAINST SUCH A PRACTICE BECAUSE OF
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THE DIFFICULTY IN TRACING INDIVIDUAL ACTIONS BACK TO THE INDIVIDUAL WHO PERFORMED THEM !N ALTERNATIVE TO THIS PRACTICE IS PRESENTED IN THE h2OLE "ASED 3ECURITYv SECTION LATER IN THIS CHAPTER 4HE !.3))3/ 31, STANDARD USES THE TERM AUTHORIZATION ID INSTEAD OF USER ID AND YOU WILL OCCASIONALLY FIND THIS TERM USED IN OTHER 31, DOCUMENTATION 4ECHNICALLY AUTHORIZATION ID IS A MORE ACCURATE TERM BECAUSE THE ROLE OF THE )$ IS TO DETERMINE AUTHORIZATION OR PRIVILEGES IN THE DATABASE 4HERE ARE SITUATIONS AS IN &IGURE WHERE THE SAME USER ID MIGHT BE ASSIGNED TO DIFFERENT USERS )N OTHER SITUATIONS A SINGLE PERSON MAY USE TWO OR THREE DIFFERENT USER IDS BUT USUALLY NOT IN THE SAME DATABASE )N A COMMERCIAL DATABASE AUTHORIZATION IDS MAY BE ASSOCIATED WITH PROGRAMS AND GROUPS OF PROGRAMS RATHER THAN WITH HUMAN USERS )N EACH OF THESE SITUATIONS AUTHORIZATION ID IS A MORE PRECISE AND LESS CONFUSING TERM THAN USER ID (OWEVER THE MOST COMMON PRACTICE IS TO ASSIGN A DIFFERENT USER ID TO EACH PERSON AND MOST 31, BASED $"-3S USE THE TERM USER ID IN THEIR DOCUMENTATION
5SERõ!UTHENTICATION 4HE 31, STANDARD SPECIFIES THAT USER IDS PROVIDE DATABASE SECURITY HOWEVER THE SPECIFIC MECHANISM FOR ASSOCIATING A USER ID WITH A 31, STATEMENT IS OUTSIDE THE SCOPE OF THE STANDARD BECAUSE A DATABASE CAN BE ACCESSED IN MANY DIFFERENT WAYS &OR EXAMPLE WHEN YOU TYPE 31, STATEMENTS INTO AN INTERACTIVE 31, UTILITY HOW DOES THE $"-3 DETERMINE WHICH USER ID IS ASSOCIATED WITH THE STATEMENTS )F YOU USE A FORMS BASED DATA ENTRY OR QUERY PROGRAM HOW DOES THE $"-3 DETERMINE YOUR USER ID /N A DATABASE SERVER A REPORT GENERATING PROGRAM MIGHT BE SCHEDULED TO RUN AT A PRESET TIME EVERY EVENING WHAT IS THE USER ID IN THIS SITUATION WHERE THERE IS NO HUMAN USER &INALLY HOW ARE USER IDS HANDLED WHEN YOU ACCESS A DATABASE ACROSS A NETWORK WHERE YOUR USER ID ON THE SYSTEM YOU ARE ACTIVELY WORKING FROM MIGHT BE DIFFERENT FROM THE USER ID ESTABLISHED ON THE SYSTEM WHERE THE DATABASE RESIDES
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-OST COMMERCIAL 31, IMPLEMENTATIONS ASSOCIATE A USER ID WITH EACH DATABASE SESSION )N INTERACTIVE 31, THE SESSION BEGINS WHEN YOU START THE INTERACTIVE 31, PROGRAM AND IT LASTS UNTIL YOU EXIT THE PROGRAM OR USE A COMMAND TO SWITCH TO ANOTHER USER ID )N AN APPLICATION PROGRAM USING PROGRAMMATIC 31, THE SESSION BEGINS WHEN THE APPLICATION PROGRAM CONNECTS TO THE $"-3 AND IT ENDS WHEN THE APPLICATION PROGRAM TERMINATES !LL OF THE 31, STATEMENTS USED DURING THE SESSION ARE ASSOCIATED WITH THE USER ID SPECIFIED FOR THE SESSION (OWEVER IN MODERN APPLICATION SYSTEMS IT IS ALSO POSSIBLE FOR AN APPLICATION PROGRAM TO ESTABLISH MULTIPLE CONNECTIONS TO A DATABASE AND TO SELECT THE ONE TO BE USED AS IT SUBMITS 31, STATEMENTS FOR PROCESSING 5SUALLY YOU MUST SUPPLY BOTH A USER ID AND AN ASSOCIATED PASSWORD TO ESTABLISH A CONNECTION 4HE $"-3 CHECKS THE PASSWORD TO VERIFY THAT YOU ARE IN FACT AUTHORIZED TO USE THE USER ID THAT YOU SUPPLY (OWEVER MANY PRODUCTS SUPPORT OPERATING SYSTEM AUTHENTICATION WHERE THE $"-3 ACCEPTS USER CREDENTIALS PASSED TO IT BY THE OPERATING SYSTEM WITHOUT THE NEED FOR A PASSWORD OR OTHER AUTHENTICATION !LTHOUGH USER IDS AND PASSWORDS ARE COMMON ACROSS MOST 31, PRODUCTS THE SPECIFIC TECHNIQUES USED TO SPECIFY THE USER ID AND PASSWORD VARY FROM ONE PRODUCT TO ANOTHER 3OME $"-3 BRANDS ESPECIALLY THOSE THAT ARE AVAILABLE ON MANY DIFFERENT OPERATING SYSTEM PLATFORMS IMPLEMENT THEIR OWN USER IDPASSWORD SECURITY &OR EXAMPLE WHEN YOU USE /RACLES INTERACTIVE 31, PROGRAM CALLED 31,0,53 YOU SPECIFY A USER NAME AND ASSOCIATED PASSWORD IN THE COMMAND THAT STARTS THE PROGRAM LIKE THIS 31,0,53 3#/444)'%2
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)N EACH CASE THE $"-3 VALIDATES THE USER ID 3#/44 AND THE PASSWORD 4)'%2 BEFORE BEGINNING THE INTERACTIVE 31, SESSION !GAIN ITS BETTER TO OMIT THE PASSWORD AND WAIT FOR )31, TO PROMPT YOU FOR IT /LDER VERSIONS OF 31, 3ERVER ALSO SUPPORT )31, BUT NEWER VERSIONS USE A SLIGHTLY DIFFERENT TOOL NAMED /31, FOR COMMAND LINE ACCESS TO $"-3 COMMANDS -ANY OTHER $"-3 BRANDS INCLUDING )NGRES AND )NFORMIX USE THE USER NAMES OF THE HOST COMPUTERS OPERATING SYSTEM AS DATABASE USER IDS &OR EXAMPLE WHEN YOU LOG INTO A 5.)8 BASED COMPUTER SYSTEM YOU MUST SUPPLY A VALID 5.)8 USER NAME AND PASSWORD TO GAIN ACCESS 4O START THE )NGRES INTERACTIVE 31, UTILITY YOU SIMPLY GIVE THE COMMAND )31, 3!,%3$"
WHERE 3!,%3$" IS THE NAME OF THE )NGRES DATABASE YOU WANT TO USE )NGRES AUTOMATICALLY OBTAINS YOUR 5.)8 USER NAME AND MAKES IT YOUR )NGRES USER ID FOR THE SESSION 4HUS YOU DONT HAVE TO SPECIFY A SEPARATE DATABASE USER ID AND PASSWORD $"S INTERACTIVE 31, RUNNING UNDER -6343/ USES A SIMILAR TECHNIQUE 9OUR 43/ LOGIN NAME AUTOMATICALLY BECOMES YOUR $" USER ID FOR THE INTERACTIVE 31, SESSION
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(OWEVER TYPING YOUR PASSWORD ON A COMMAND LINE IS NOT RECOMMENDED BECAUSE THE PASSWORD IS NOT ENCRYPTED AND CAN BE EASILY EXPOSED BY ANYONE ELSE ON THE SYSTEM )T IS FAR BETTER TO OMIT THE PASSWORD AND THE SEPARATING SLASH AND LET 31,0,53 PROMPT YOU FOR THE PASSWORD 4HE 3YBASE INTERACTIVE 31, PROGRAM CALLED )31, ALSO ACCEPTS A USER NAME AND PASSWORD USING THIS COMMAND FORMAT
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-OST MODERN $"-3 PRODUCTS ALSO HAVE '5) TOOLS FOR DATABASE ACCESS SUCH AS THE 31, 3ERVER -ANAGEMENT 3TUDIO THE $" 5$" #OMMAND %DITOR AND THE /RACLE 31, $EVELOPER 4HESE TOOLS PROMPT FOR THE USER ID AND PASSWORD WHEN CONNECTIONS ARE INITIALLY ESTABLISHED 31, SECURITY ALSO APPLIES TO PROGRAMMATIC ACCESS TO A DATABASE SO THE $"-3 MUST DETERMINE AND AUTHENTICATE THE USER ID FOR EVERY APPLICATION PROGRAM THAT TRIES TO ACCESS THE DATABASE !GAIN THE TECHNIQUES AND RULES FOR ESTABLISHING THE USER ID VARY FROM ONE BRAND OF $"-3 TO ANOTHER &OR WIDELY USED UTILITY PROGRAMS SUCH AS A DATA ENTRY OR AN INQUIRY PROGRAM IT IS COMMON FOR THE PROGRAM TO ASK THE USER FOR A USER ID AND PASSWORD AT THE BEGINNING OF THE SESSION VIA A SCREEN DIALOG &OR MORE SPECIALIZED OR CUSTOM WRITTEN PROGRAMS THE APPROPRIATE USER ID MAY BE OBVIOUS FROM THE APPLICATION TO BE PERFORMED AND MAY BE HARD WIRED INTO THE PROGRAM 4HE 31, STANDARD ALSO ALLOWS A PROGRAM TO USE AN AUTHORIZATION ID ASSOCIATED WITH A SPECIFIC SET OF 31, STATEMENTS CALLED A MODULE RATHER THAN THE USER ID OF THE PARTICULAR PERSON RUNNING THE PROGRAM 7ITH THIS MECHANISM A PROGRAM MAY BE GIVEN THE ABILITY TO PERFORM VERY SPECIFIC OPERATIONS ON A DATABASE ON BEHALF OF MANY DIFFERENT USERS EVEN IF THOSE USERS ARE NOT OTHERWISE AUTHORIZED TO ACCESS THE TARGET DATA 4HIS IS A CONVENIENT CAPABILITY THAT IS FINDING ITS WAY INTO MAINSTREAM 31, IMPLEMENTATIONS 4HE SPECIFICS OF 31, SECURITY FOR DATABASE ACCESS PROGRAMS ARE DESCRIBED IN #HAPTER WHICH COVERS PROGRAMMATIC 31,
5SERõ'ROUPS ! LARGE PRODUCTION DATABASE OFTEN HAS GROUPS OF USERS WITH SIMILAR NEEDS )N THE SAMPLE DATABASE FOR EXAMPLE THE THREE PEOPLE IN THE ORDER PROCESSING DEPARTMENT FORM A NATURAL USER GROUP AND THE TWO PEOPLE IN THE ACCOUNTS RECEIVABLE DEPARTMENT FORM ANOTHER NATURAL GROUP 7ITHIN EACH GROUP ALL OF THE USERS HAVE IDENTICAL NEEDS FOR DATA ACCESS AND SHOULD HAVE IDENTICAL PRIVILEGES 5NDER THE !.3))3/ 31, SECURITY SCHEME YOU CAN HANDLE GROUPS OF USERS WITH SIMILAR NEEDS IN ONE OF THREE WAYS s 9OU CAN ASSIGN THE SAME USER ID TO EVERY PERSON IN THE GROUP AS SHOWN IN &IGURE 4HIS SCHEME SIMPLIFIES SECURITY ADMINISTRATION BECAUSE IT ALLOWS YOU TO SPECIFY DATA ACCESS PRIVILEGES ONCE FOR THE SINGLE USER ID (OWEVER UNDER THIS SCHEME IT IS MORE DIFFICULT TO DISTINGUISH THE PEOPLE SHARING THE USER ID FROM ONE ANOTHER IN SYSTEM OPERATOR DISPLAYS AND $"-3 REPORTS s 9OU CAN ASSIGN A DIFFERENT USER ID TO EVERY PERSON IN THE GROUP AND SPECIFY PRIVILEGES FOR EACH USER INDIVIDUALLY 4HIS SCHEME LETS YOU DIFFERENTIATE BETWEEN THE USERS IN REPORTS PRODUCED BY THE $"-3 AND IT LETS YOU ESTABLISH DIFFERENT PRIVILEGES FOR THE INDIVIDUAL USERS LATER BUT SECURITY ADMINISTRATION IS MORE TEDIOUS AND ERROR PRONE s &OR $"-3 PRODUCTS THAT SUPPORT IT MOST MODERN ONES DO YOU CAN CREATE A ROLE THAT CONTAINS THE REQUIRED PRIVILEGES ! ROLE IS A NAMED COLLECTION OF PRIVILEGES 9OU CAN ASSIGN EACH PERSON HIS OR HER OWN USER ID AND ASSOCIATE THE ROLE WITH HIS OR HER USER ID /BVIOUSLY THIS IS THE BEST ALTERNATIVE BECAUSE YOU CAN DIFFERENTIATE BETWEEN THE USERS WITHOUT COMPLICATING ADMINISTRATION 2OLES ARE PRESENTED IN DETAIL IN THE h2OLE "ASED 3ECURITYv SECTION LATER IN THIS CHAPTER 4HE SCHEME YOU CHOOSE DEPENDS ON THE SECURITY SUPPORT AND TRADE OFFS IN YOUR PARTICULAR DATABASE AND APPLICATION
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0RIOR TO IMPLEMENTING SUPPORT FOR ROLES SEVERAL $"-3 BRANDS INCLUDING 3YBASE AND 31, 3ERVER OFFERED A THIRD ALTERNATIVE FOR DEALING WITH GROUPS OF SIMILAR USERS 4HEY SUPPORT GROUP IDS WHICH IDENTIFY GROUPS OF RELATED USER IDS 0RIVILEGES CAN BE GRANTED BOTH TO INDIVIDUAL USER IDS AND TO GROUP IDS AND A USER MAY CARRY OUT A DATABASE ACTION IF IT IS PERMITTED BY EITHER THE USER ID OR GROUP ID PRIVILEGES 'ROUP IDS THUS SIMPLIFY THE ADMINISTRATION OF PRIVILEGES GIVEN TO GROUPS OF USERS (OWEVER THEY ARE NONSTANDARD AND A DATABASE DESIGN USING THEM MAY NOT BE PORTABLE TO ANOTHER $"-3 BRAND 3OME VERSIONS OF $" ALSO SUPPORT GROUPS OF USERS BUT TAKE A DIFFERENT APPROACH 4HE $" DATABASE ADMINISTRATOR CAN CONFIGURE $" SO THAT WHEN YOU FIRST CONNECT TO $" AND SUPPLY YOUR USER ID KNOWN AS YOUR PRIMARY AUTHORIZATION ID $" AUTOMATICALLY LOOKS UP A SET OF ADDITIONAL USER IDS KNOWN AS SECONDARY AUTHORIZATION IDS THAT YOU MAY USE 7HEN $" LATER CHECKS YOUR PRIVILEGES IT CHECKS THE PRIVILEGES FOR ALL OF YOUR AUTHORIZATION IDS PRIMARY AND SECONDARY /N AN )"- MAINFRAME SYSTEM THE $" DATABASE ADMINISTRATOR NORMALLY SETS UP THE SECONDARY AUTHORIZATION IDS SO THAT THEY ARE THE SAME AS THE USER GROUP NAMES USED BY 2ESOURCE !CCESS #ONTROL &ACILITY 2!#& THE )"- MAINFRAME SECURITY FACILITY 4HUS THE $" APPROACH EFFECTIVELY PROVIDES GROUP IDS BUT DOES SO WITHOUT ADDING TO THE USER ID MECHANISM
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0RIVILEGES 4HE SET OF ACTIONS THAT A USER CAN CARRY OUT AGAINST A DATABASE OBJECT ARE CALLED THE PRIVILEGES FOR THE OBJECT 4HE 31, STANDARD SPECIFIES FOUR BASIC PRIVILEGES FOR TABLES AND VIEWS s 4HE 3%,%#4 PRIVILEGE ALLOWS YOU TO RETRIEVE DATA FROM A TABLE OR VIEW 7ITH THIS PRIVILEGE YOU CAN SPECIFY THE TABLE OR VIEW IN THE &2/- CLAUSE OF A 3%,%#4 STATEMENT OR SUBQUERY s 4HE ).3%24 PRIVILEGE ALLOWS YOU TO INSERT NEW ROWS INTO A TABLE OR VIEW 7ITH THIS PRIVILEGE YOU CAN SPECIFY THE TABLE OR VIEW IN THE ).4/ CLAUSE OF AN ).3%24 STATEMENT
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31, SECURITY PROTECTIONS APPLY TO SPECIFIC OBJECTS CONTAINED IN A DATABASE 4HE 31, STANDARD SPECIFIED TWO TYPES OF SECURITY OBJECTSTABLES AND VIEWS 4HUS EACH TABLE AND VIEW CAN BE INDIVIDUALLY PROTECTED !CCESS TO A TABLE OR VIEW CAN BE PERMITTED FOR CERTAIN USER IDS AND PROHIBITED FOR OTHER USER IDS 3UBSEQUENT VERSIONS OF THE 31, STANDARD EXPAND SECURITY PROTECTIONS TO INCLUDE OTHER OBJECTS INCLUDING DOMAINS AND USER DEFINED CHARACTER SETS AND ADD A NEW TYPE OF PROTECTION FOR TABLE OR VIEW ACCESS -OST COMMERCIAL 31, PRODUCTS SUPPORT ADDITIONAL TYPES OF OBJECTS THAT ARE SUBJECT TO SECURITY CONTROLS )N A 31, 3ERVER DATABASE FOR EXAMPLE A STORED PROCEDURE IS AN IMPORTANT DATABASE OBJECT 4HE 31, SECURITY SCHEME DETERMINES WHICH USERS CAN CREATE AND DROP STORED PROCEDURES AND WHICH USERS ARE ALLOWED TO EXECUTE THEM )N )"-S $" THE PHYSICAL TABLESPACES WHERE TABLES ARE STORED ARE TREATED AS SECURITY OBJECTS 4HE DATABASE ADMINISTRATOR CAN GIVE SOME USER IDS PERMISSION TO CREATE NEW TABLES IN A PARTICULAR TABLESPACE AND DENY THAT PERMISSION TO OTHER USER IDS /THER 31, IMPLEMENTATIONS SUPPORT OTHER SECURITY OBJECTS (OWEVER THE UNDERLYING 31, SECURITY SCHEMEOF SPECIFIC PRIVILEGES APPLIED TO SPECIFIC OBJECTS GRANTED OR REVOKED THROUGH THE SAME 31, STATEMENTSIS ALMOST UNIVERSALLY APPLIED
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s 4HE $%,%4% PRIVILEGE ALLOWS YOU TO DELETE ROWS OF DATA FROM A TABLE OR VIEW 7ITH THIS PRIVILEGE YOU CAN SPECIFY THE TABLE OR VIEW IN THE &2/- CLAUSE OF A $%,%4% STATEMENT s 4HE 50$!4% PRIVILEGE ALLOWS YOU TO MODIFY ROWS OF DATA IN A TABLE OR VIEW 7ITH THIS PRIVILEGE YOU CAN SPECIFY THE TABLE OR VIEW AS THE TARGET TABLE IN AN 50$!4% STATEMENT 4HE 50$!4% PRIVILEGE CAN BE RESTRICTED TO SPECIFIC COLUMNS OF THE TABLE OR VIEW ALLOWING UPDATES TO THESE COLUMNS BUT DISALLOWING UPDATES TO ANY OTHER COLUMNS 4HESE FOUR PRIVILEGES ARE SUPPORTED BY VIRTUALLY ALL COMMERCIAL 31, PRODUCTS
31,õ%XTENDEDõ0RIVILEGES 3UBSEQUENT VERSIONS OF THE STANDARD EXPANDED THE BASIC 31, PRIVILEGES IN SEVERAL DIMENSIONS .EW CAPABILITIES WERE ADDED TO THE 31, 3%,%#4 ).3%24 AND 50$!4% PRIVILEGES ! NEW 2%&%2%.#%3 PRIVILEGE WAS ADDED THAT RESTRICTS A USERS ABILITY TO CREATE A REFERENCE TO A TABLE FROM A FOREIGN KEY IN ANOTHER TABLE !LSO A NEW 53!'% PRIVILEGE WAS ADDED THAT CONTROLS ACCESS TO THE NEW 31, DATABASE STRUCTURES OF DOMAINS CHARACTER SETS COLLATION SEQUENCES AND TRANSLATIONS 4HE 31, EXTENSIONS TO THE 3%,%#4 ).3%24 AND 50$!4% PRIVILEGES ARE STRAIGHTFORWARD 4HESE PRIVILEGES MAY NOW BE GRANTED FOR A SPECIFIC COLUMN OR COLUMNS WITHIN A TABLE INSTEAD OF APPLYING TO THE ENTIRE TABLE 4HE SAMPLE DATABASE PROVIDES A SIMPLE EXAMPLE OF HOW THIS CAPABILITY CAN BE USEFUL 3UPPOSE YOU WANTED TO GIVE YOUR HUMAN RESOURCES MANAGER THE RESPONSIBILITY TO INSERT NEW EMPLOYEES INTO THE 3!,%32%03 TABLE ONCE THE HIRING PAPERWORK IS COMPLETE 4HE (2 MANAGER SHOULD SUPPLY THE EMPLOYEE NUMBER NAME AND SIMILAR INFORMATION "UT IT SHOULD BE THE RESPONSIBILITY OF THE SALES 60 TO SET THE 15/4! COLUMN FOR THE NEW EMPLOYEE !DJUSTMENTS TO THE 3!,%3 COLUMN FOR EXISTING EMPLOYEES WOULD BE SIMILARLY RESTRICTED 5SING THE NEWER 31, CAPABILITIES YOU COULD IMPLEMENT THIS SCHEME BY GIVING THE (2 MANAGER ).3%24 PRIVILEGES ON THE APPROPRIATE COLUMNS 4HE OTHER COLUMNS SUCH AS 3!,%3 AND 15/4! FOR ANY NEWLY INSERTED EMPLOYEES WOULD INITIALLY HAVE .5,, VALUES 7ITH THE 50$!4% PRIVILEGE ON THE OTHER COLUMNS THE SALES 60 CAN THEN SET THE APPROPRIATE QUOTA 7ITHOUT THE ABILITY TO SPECIFY THESE PRIVILEGES ON SPECIFIC COLUMNS YOU WOULD HAVE TO EITHER RELAX THE RESTRICTIONS ON COLUMN ACCESS OR DEFINE EXTRANEOUS VIEWS ON THE TABLE SIMPLY TO RESTRICT ACCESS 4HE 31, 2%&%2%.#%3 PRIVILEGE DEALS WITH A MORE SUBTLE 31, SECURITY ISSUE POSED BY FOREIGN KEYS AND CHECK CONSTRAINTS 5SING THE SAMPLE DATABASE AS AN EXAMPLE SUPPOSE AN EMPLOYEE HAS THE ABILITY TO CREATE A NEW TABLE IN THE DATABASE FOR EXAMPLE A TABLE CONTAINING NEW PRODUCT INFORMATION BUT DOES NOT HAVE ANY ACCESS TO THE EMPLOYEE INFORMATION IN THE 3!,%32%03 TABLE 9OU MIGHT ASSUME GIVEN THIS SECURITY SCHEME THAT THERE IS NO WAY FOR HIM TO DETERMINE THE EMPLOYEE NUMBERS BEING USED OR WHETHER A NEW EMPLOYEE HAS BEEN HIRED (OWEVER THIS ISNT STRICTLY TRUE 4HE EMPLOYEE COULD CREATE A NEW TABLE WITH A COLUMN THAT IS DEFINED AS A FOREIGN KEY TO THE 3!,%32%03 TABLE 2ECALL THAT THIS MEANS THE ONLY LEGAL VALUES FOR THIS COLUMN ARE PRIMARY KEY VALUES FOR THE 3!,%32%03 TABLETHAT IS VALID EMPLOYEE NUMBERS 7ITH THIS NEW TABLE THE EMPLOYEE CAN SIMPLY TRY TO INSERT NEW ROWS WITH DIFFERENT VALUES IN THE FOREIGN KEY COLUMN 4HE ).3%24 STATEMENTS THAT SUCCEED TELL THE EMPLOYEE THAT HE HAS DISCOVERED A VALID EMPLOYEE NUMBER THOSE THAT FAIL REPRESENT INVALID EMPLOYEE NUMBERS
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%VEN MORE SERIOUS PROBLEMS CAN BE CREATED BY A NEW TABLE DEFINED WITH A CHECK CONSTRAINT ON A COLUMN &OR EXAMPLE SUPPOSE THE EMPLOYEE TRIES TO EXECUTE THIS #2%!4% 4!",% STATEMENT #2%!4% 4!",% 89: 429)4 $%#)-!, #(%#+ 3%,%#4 15/4! &2/- 3!,%32%03 7(%2% 4)4,% g60 3ALESg "%47%%. !.$
/WNERSHIPõ0RIVILEGES 7HEN YOU CREATE A TABLE WITH THE #2%!4% 4!",% STATEMENT YOU BECOME ITS OWNER AND RECEIVE FULL PRIVILEGES FOR THE TABLE 3%,%#4 ).3%24 $%,%4% 50$!4% AND ANY OTHER PRIVILEGES SUPPORTED BY THE $"-3 /THER USERS INITIALLY HAVE NO PRIVILEGES ON THE NEWLY CREATED TABLE )F THEY ARE TO BE GIVEN ACCESS TO THE TABLE YOU MUST EXPLICITLY GRANT PRIVILEGES TO THEM BY USING THE '2!.4 STATEMENT 7HEN YOU CREATE A VIEW WITH THE #2%!4% 6)%7 STATEMENT YOU BECOME THE OWNER OF THE VIEW BUT YOU DO NOT NECESSARILY RECEIVE FULL PRIVILEGES ON IT 4O CREATE THE VIEW SUCCESSFULLY YOU MUST ALREADY HAVE THE 3%,%#4 PRIVILEGE ON EACH OF THE SOURCE TABLES FOR THE VIEW THEREFORE THE $"-3 GIVES YOU THE 3%,%#4 PRIVILEGE FOR THE VIEW AUTOMATICALLY &OR EACH OF THE OTHER PRIVILEGES ).3%24 $%,%4% AND 50$!4% THE $"-3 GIVES YOU THE PRIVILEGE ON THE VIEW ONLY IF YOU HOLD THAT SAME PRIVILEGE ON EVERY SOURCE TABLE FOR THE VIEW
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"ECAUSE OF THE COLUMN CONSTRAINT LINKED TO A VALUE FROM THE 3!,%32%03 TABLE IF THIS STATEMENT SUCCEEDS IT MEANS THE 60 OF SALES HAS A QUOTA IN THE SPECIFIED RANGE )F IT DOESNT THE EMPLOYEE CAN KEEP TRYING SIMILAR #2%!4% 4!",% STATEMENTS UNTIL HE HAS DETERMINED THE APPROPRIATE QUOTA .OTE HOWEVER THAT VERY FEW 31, IMPLEMENTATIONS SUPPORT CHECK CONSTRAINTS THAT REFERENCE OTHER TABLES !S OF THIS WRITING -Y31, OFFERS SUCH SUPPORT BUT $" 31, 3ERVER AND /RACLE DO NOT 4O ELIMINATE THIS BACKDOOR ACCESS TO DATA THE 31, STANDARD SPECIFIES A NEW 2%&%2%.#%3 PRIVILEGE ,IKE THE 3%,%#4 ).3%24 AND 50$!4% PRIVILEGES THE 2%&%2%.#%3 PRIVILEGE CAN BE GRANTED FOR SPECIFIC COLUMNS OF A TABLE /NLY IF A USER HAS THE 2%&%2%.#%3 PRIVILEGE FOR A COLUMN IS HE OR SHE ALLOWED TO CREATE A NEW TABLE THAT REFERS TO THAT EXISTING COLUMN IN ANY WAY FOR EXAMPLE AS THE TARGET OF A FOREIGN KEY REFERENCE OR IN A CHECK CONSTRAINT AS IN THE PREVIOUS EXAMPLES )N DATABASES THAT DONT YET IMPLEMENT THE 2%&%2%.#%3 PRIVILEGE BUT DO SUPPORT FOREIGN KEYS OR CHECK CONSTRAINTS THE 3%,%#4 PRIVILEGE IS SOMETIMES USED FOR THIS PURPOSE &INALLY THE 31, STANDARD SPECIFIES THE 53!'% PRIVILEGE TO CONTROL ACCESS TO DOMAINS SETS OF LEGAL COLUMN VALUES USER DEFINED CHARACTER SETS COLLATING SEQUENCES AND TRANSLATIONS 4HE 53!'% PRIVILEGE IS A SIMPLE ONOFF SWITCH THAT EITHER ALLOWS OR DISALLOWS THE USE OF THESE DATABASE OBJECTS BY NAME FOR INDIVIDUAL USER IDS &OR EXAMPLE WITH THE 53!'% PRIVILEGE ON A DOMAIN YOU CAN DEFINE A NEW TABLE WITH A COLUMN WHOSE DATA TYPE IS DEFINED AS THAT DOMAIN 7ITHOUT THE PRIVILEGE YOU CANNOT CREATE SUCH A COLUMN DEFINITION 4HESE PRIVILEGES ARE DIRECTED MOSTLY TOWARD SIMPLIFYING ADMINISTRATION OF LARGE COMMERCIAL DATABASES THAT ARE USED AND MODIFIED BY MANY DIFFERENT DEVELOPMENT TEAMS 4HEY TYPICALLY DO NOT PRESENT THE SAME KINDS OF SECURITY ISSUES AS THE TABLE AND COLUMN ACCESS PRIVILEGES
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/THERõ0RIVILEGES -ANY COMMERCIAL $"-3 PRODUCTS OFFER ADDITIONAL TABLE AND VIEW PRIVILEGES BEYOND THE BASIC 3%,%#4 ).3%24 $%,%4% AND 50$!4% PRIVILEGES &OR EXAMPLE /RACLE AND THE )"- MAINFRAME DATABASES SUPPORT AN !,4%2 AND AN ).$%8 PRIVILEGE FOR TABLES ! USER WITH THE !,4%2 PRIVILEGE ON A PARTICULAR TABLE CAN USE THE !,4%2 4!",% STATEMENT TO MODIFY THE DEFINITION OF THE TABLE A USER WITH THE ).$%8 PRIVILEGE CAN CREATE AN INDEX FOR THE TABLE WITH THE #2%!4% ).$%8 STATEMENT )N $"-3 BRANDS THAT DO NOT SUPPORT THE !,4%2 AND ).$%8 PRIVILEGES ONLY THE OWNER MAY USE THE !,4%2 4!",% AND #2%!4% ).$%8 STATEMENTS !DDITIONAL PRIVILEGES ARE FREQUENTLY SUPPORTED FOR $"-3 SECURITY OBJECTS OTHER THAN TABLES AND VIEWS &OR EXAMPLE /RACLE 3YBASE AND 31, 3ERVER SUPPORT AN %8%#54% PRIVILEGE FOR STORED PROCEDURES WHICH DETERMINES WHETHER A USER IS ALLOWED TO EXECUTE A STORED PROCEDURE $" SUPPORTS A 53% PRIVILEGE FOR TABLESPACES WHICH DETERMINES WHETHER A USER CAN CREATE TABLES IN A SPECIFIC TABLESPACE
6IEWSõANDõ31,õ3ECURITY )N ADDITION TO THE RESTRICTIONS ON TABLE ACCESS PROVIDED BY THE 31, PRIVILEGES VIEWS ALSO PLAY A KEY ROLE IN 31, SECURITY "Y CAREFULLY DEFINING A VIEW AND GIVING A USER PERMISSION TO ACCESS THE VIEW BUT NOT ITS SOURCE TABLES YOU CAN EFFECTIVELY RESTRICT THE USERS ACCESS TO ONLY SELECTED COLUMNS AND ROWS 6IEWS THUS OFFER A WAY TO EXERCISE VERY PRECISE CONTROL OVER WHAT DATA IS MADE VISIBLE TO WHICH USERS &OR EXAMPLE SUPPOSE YOU WANTED TO ENFORCE THIS SECURITY RULE IN THE SAMPLE DATABASE !CCOUNTS RECEIVABLE PERSONNEL SHOULD BE ABLE TO RETRIEVE EMPLOYEE NUMBERS NAMES AND OFlCE NUMBERS FROM THE 3!,%32%03 TABLE BUT DATA ABOUT SALES AND QUOTAS SHOULD NOT BE AVAILABLE TO THEM 9OU CAN IMPLEMENT THIS SECURITY RULE BY DEFINING A VIEW AS FOLLOWS #2%!4% 6)%7 2%0).&/ !3 3%,%#4 %-0,?.5- .!-% 2%0?/&&)#% &2/- 3!,%32%03
AND GIVING THE 3%,%#4 PRIVILEGE FOR THE VIEW TO THE !253%2 USER ID AS SHOWN IN &IGURE 4HIS EXAMPLE USES A VERTICAL VIEW TO RESTRICT ACCESS TO SPECIFIC COLUMNS (ORIZONTAL VIEWS ARE ALSO EFFECTIVE FOR ENFORCING SECURITY RULES SUCH AS THIS ONE 4HE SALES MANAGERS IN EACH REGION SHOULD HAVE FULL ACCESS TO 3!,%32%03 DATA FOR THE SALESPEOPLE ASSIGNED TO THAT REGION !S SHOWN IN &IGURE YOU CAN DEFINE TWO VIEWS %!342%03 AND 7%342%03 CONTAINING 3!,%32%03 DATA FOR EACH OF THE TWO REGIONS AND THEN GRANT EACH OFFICE MANAGER ACCESS TO THE APPROPRIATE VIEW /F COURSE VIEWS CAN BE MUCH MORE COMPLEX THAN THE SIMPLE ROW AND COLUMN SUBSETS OF A SINGLE TABLE SHOWN IN THESE EXAMPLES "Y DEFINING A VIEW WITH A GROUPED QUERY YOU CAN GIVE A USER ACCESS TO SUMMARY DATA BUT NOT TO THE DETAILED ROWS IN THE UNDERLYING TABLE ! VIEW CAN ALSO COMBINE DATA FROM TWO OR MORE TABLES PROVIDING PRECISELY THE DATA NEEDED BY A PARTICULAR USER AND DENYING ACCESS TO ALL OTHER DATA 4HE USEFULNESS OF VIEWS FOR
#HAPTERçç
31,ç3ECURITYç
1, Ê£xÎÊ 1Ã}Ê>ÊÛiÜÊÌÊÀiÃÌÀVÌÊVÕÊ>VViÃÃ
IMPLEMENTING 31, SECURITY IS LIMITED BY THE TWO FUNDAMENTAL RESTRICTIONS DESCRIBED EARLIER IN #HAPTER s 5PDATE RESTRICTIONS 4HE 3%,%#4 PRIVILEGE CAN BE USED WITH READ ONLY VIEWS TO LIMIT DATA RETRIEVAL BUT THE ).3%24 $%,%4% AND 50$!4% PRIVILEGES ARE MEANINGLESS FOR THESE VIEWS )F A USER MUST UPDATE THE DATA VISIBLE IN A READ ONLY VIEW THE USER MUST BE GIVEN PERMISSION TO UPDATE THE UNDERLYING TABLES AND MUST USE ).3%24 $%,%4% AND 50$!4% STATEMENTS THAT REFERENCE THOSE TABLES s 0ERFORMANCE !NY POORLY WRITTEN 31, QUERY CAN ADD SIGNIFICANT OVERHEAD TO DATABASE OPERATIONS AND OF COURSE THIS CAN BE TRUE OF QUERIES INCLUDED IN VIEW DEFINITIONS (OWEVER DATABASE USERS MAY REFERENCE VIEWS WITHOUT CONSIDERING THE COMPLEXITY OF THE UNDERLYING ACCESSES AGAINST THE SOURCE TABLES 6IEWS CANNOT BE USED INDISCRIMINATELY TO RESTRICT DATABASE ACCESS WITHOUT REGARD FOR THE OVERALL PERFORMANCE IMPLICATIONS OF THE QUERIES WITHIN THEM
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$ATABASEç3TRUCTURE
%'' ! (, +/*)", (' +&
* (%-$ )* "+-, .'+.0
%'' ! (, +/*)", ."(%-$ (' +&
* (%-$ )* "+-, *()/!"+ ++/%- $ .'+.0 ) / )#"''%
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1, Ê£x{Ê 1Ã}ÊÛiÜÃÊÌÊÀiÃÌÀVÌÊÀÜÊ>VViÃÃ
'RANTINGõ0RIVILEGESõ'2!.4 4HE BASIC '2!.4 STATEMENT SHOWN IN &IGURE IS USED TO GRANT SECURITY PRIVILEGES ON DATABASE OBJECTS TO SPECIFIC USERS OR ROLES .ORMALLY THE '2!.4 STATEMENT IS USED BY THE OWNER OF A TABLE OR VIEW TO GIVE OTHER USERS ACCESS TO THE DATA !S SHOWN IN THE FIGURE THE '2!.4 STATEMENT INCLUDES A SPECIFIC LIST OF THE PRIVILEGES TO BE GRANTED THE NAME OF THE TABLE OR OTHER OBJECT TO WHICH THE PRIVILEGES APPLY AN OBJECT TYPE IS REQUIRED FOR ALL OBJECTS EXCEPT TABLES AND VIEWS AND THE USER ID OR ROLE TO WHICH THE PRIVILEGES ARE GRANTED )N MOST 31, IMPLEMENTATIONS USER ACCOUNTS MUST EXIST BEFORE PRIVILEGES CAN BE GRANTED TO THEM 4HE '2!.4 STATEMENT SHOWN IN THE SYNTAX DIAGRAM CONFORMS TO THE !.3))3/ 31, STANDARD -ANY $"-3 BRANDS FOLLOW THE $" '2!.4 STATEMENT SYNTAX WHICH IS MORE FLEXIBLE 4HE $" SYNTAX ALLOWS YOU TO SPECIFY A LIST OF USER IDS AND A LIST OF OBJECT NAMES MAKING IT SIMPLER TO GRANT MANY PRIVILEGES AT ONCE (ERE ARE SOME EXAMPLES OF SIMPLE '2!.4 STATEMENTS FOR THE SAMPLE DATABASE 'IVE ORDER PROCESSING USERS FULL ACCESS TO THE /2$%23 TABLE '2!.4 3%,%#4 ).3%24 $%,%4% 50$!4% /. /2$%23 4/ /053%2
#HAPTERçç
31,ç3ECURITYç
1, Ê£xxÊ /
iÊ'2!.4ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
,ET ACCOUNTS RECEIVABLE USERS RETRIEVE CUSTOMER DATA AND ADD NEW CUSTOMERS TO THE #534/-%23 TABLE BUT GIVE ORDER PROCESSING USERS READ ONLY ACCESS
!LLOW 3AM #LARK TO INSERT OR DELETE AN OFlCE '2!.4 ).3%24 $%,%4% /. /&&)#%3 4/ 3!-
&OR CONVENIENCE THE '2!.4 STATEMENT PROVIDES TWO SHORTCUTS THAT YOU CAN USE WHEN GRANTING MANY PRIVILEGES OR WHEN GRANTING PRIVILEGES TO MANY USERS )NSTEAD OF SPECIFICALLY LISTING ALL OF THE PRIVILEGES AVAILABLE FOR A PARTICULAR OBJECT YOU CAN USE THE KEYWORDS !,, 02)6),%'%3 4HIS '2!.4 STATEMENT GIVES 3AM #LARK THE VICE PRESIDENT OF SALES FULL ACCESS TO THE 3!,%32%03 TABLE 'IVE ALL PRIVILEGES ON THE 3!,%32%03 TABLE TO 3AM #LARK '2!.4 !,, 02)6),%'%3 /. 3!,%32%03 4/ 3!-
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'2!.4 3%,%#4 ).3%24 /. #534/-%23 4/ !253%2 '2!.4 3%,%#4 /. #534/-%23 4/ /053%2
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0ARTç)6ç
$ATABASEç3TRUCTURE
)NSTEAD OF GIVING PRIVILEGES TO EVERY USER OF THE DATABASE ONE BY ONE YOU CAN USE THE KEYWORD 05",)# TO GRANT A PRIVILEGE TO EVERY DATABASE USER AUTHORIZED TO CONNECT TO THE DATABASE /BVIOUSLY THIS OPTION MUST BE USED JUDICIOUSLY 4HIS '2!.4 STATEMENT LETS ANYONE RETRIEVE DATA FROM THE /&&)#%3 TABLE 'IVE ALL USERS 3%,%#4 ACCESS TO THE /&&)#%3 TABLE '2!.4 3%,%#4 /. /&&)#%3 4/ 05",)#
.OTE THAT THIS STATEMENT GRANTS ACCESS TO ALL PRESENT AND FUTURE AUTHORIZED USERS NOT JUST TO THE USER IDS CURRENTLY KNOWN TO THE $"-3 4HIS ELIMINATES THE NEED FOR YOU TO EXPLICITLY GRANT PRIVILEGES TO NEW USERS AS THEY ARE AUTHORIZED TO CONNECT TO THE DATABASE
#OLUMNõ0RIVILEGES 4HE 31, STANDARD ALLOWED YOU TO GRANT THE 50$!4% PRIVILEGE FOR INDIVIDUAL COLUMNS OF A TABLE OR VIEW AND NEWER VERSIONS ALLOW A COLUMN LIST FOR 3%,%#4 ).3%24 AND 2%&%2%.#%3 PRIVILEGES AS WELL 4HE COLUMNS ARE LISTED AFTER THE 3%,%#4 50$!4% ).3%24 OR 2%&%2%.#%3 KEYWORD AND ENCLOSED IN PARENTHESES (ERE IS A '2!.4 STATEMENT THAT ALLOWS THE ORDER PROCESSING DEPARTMENT TO UPDATE ONLY THE COMPANY NAME #/-0!.9 AND ASSIGNED SALESPERSON #534?2%0 COLUMNS OF THE #534/-%23 TABLE ,ET ORDER PROCESSING USERS CHANGE COMPANY NAMES AND SALESPERSON ASSIGNMENTS '2!.4 50$!4% #/-0!.9 #534?2%0 /. #534/-%23 4/ /053%2
)F THE COLUMN LIST IS OMITTED THE PRIVILEGE APPLIES TO ALL COLUMNS OF THE TABLE OR VIEW AS IN THIS EXAMPLE ,ET ACCOUNTS RECEIVABLE USERS CHANGE ANY CUSTOMER INFORMATION '2!.4 50$!4% /. #534/-%23 4/ !253%2
31, STANDARD VERSIONS BEYOND 31, SUPPORT GRANTING THE 3%,%#4 PRIVILEGE FOR LISTS AS COLUMNS AS WITH THIS EXAMPLE 'IVE ACCOUNTS RECEIVABLE USERS READ ONLY ACCESS TO THE EMPLOYEE NUMBER NAME AND SALES OFlCE COLUMNS OF THE 3!,%32%03 TABLE '2!.4 3%,%#4 %-0,?.5- .!-% 2%0?/&&)#% /. 3!,%32%03 4/ !253%2
4HIS '2!.4 STATEMENT ELIMINATES THE NEED FOR THE 2%0).&/ VIEW DEFINED IN &IGURE AND IN PRACTICE IT CAN ELIMINATE THE NEED FOR MANY VIEWS IN A COMMERCIAL DATABASE (OWEVER COLUMN LEVEL 3%,%#4 PRIVILEGES ARENT YET SUPPORTED BY ALL THE MAJOR $"-3 VENDORS
#HAPTERçç
31,ç3ECURITYç
0ASSINGõ0RIVILEGESõ'2!.4õ/04)/. 7HEN YOU CREATE A DATABASE OBJECT AND BECOME ITS OWNER YOU ARE THE ONLY PERSON WHO CAN GRANT PRIVILEGES TO USE THE OBJECT 7HEN YOU GRANT PRIVILEGES TO OTHER USERS THEY ARE ALLOWED TO USE THE OBJECT BUT BY DEFAULT THEY CANNOT PASS THOSE PRIVILEGES ON TO OTHER USERS )N THIS WAY THE OWNER OF AN OBJECT MAINTAINS VERY TIGHT CONTROL BOTH OVER WHO HAS PERMISSION TO USE THE OBJECT AND OVER WHICH FORMS OF ACCESS ARE ALLOWED /CCASIONALLY YOU MAY WANT TO ALLOW OTHER USERS TO GRANT PRIVILEGES ON AN OBJECT THAT YOU OWN &OR EXAMPLE CONSIDER AGAIN THE %!342%03 AND 7%342%03 VIEWS IN THE SAMPLE DATABASE 3AM #LARK THE VICE PRESIDENT OF SALES CREATED THESE VIEWS AND OWNS THEM (E CAN GIVE THE ,OS !NGELES OFFICE MANAGER ,ARRY &ITCH PERMISSION TO USE THE 7%342%03 VIEW WITH THIS '2!.4 STATEMENT '2!.4 3%,%#4 /. 7%342%03 4/ ,!229
7HAT HAPPENS IF ,ARRY WANTS TO GIVE 3UE 3MITH USER ID 35% PERMISSION TO ACCESS THE 7%342%03 DATA BECAUSE SHE IS DOING SOME SALES FORECASTING FOR THE ,OS !NGELES OFFICE "ASED ON THE PRECEDING '2!.4 STATEMENT HE CANNOT GIVE HER THE REQUIRED PRIVILEGE /NLY 3AM #LARK CAN GRANT THE PRIVILEGE BECAUSE HE OWNS THE VIEW )F 3AM WANTS TO GIVE ,ARRY DISCRETION OVER WHO MAY USE THE 7%342%03 VIEW HE CAN USE THIS VARIATION OF THE PREVIOUS '2!.4 STATEMENT '2!.4 3%,%#4 /. 7%342%03 4/ ,!229 7)4( '2!.4 /04)/.
'2!.4 3%,%#4 /. 7%342%03 4/ 35%
WHICH ALLOWS 3UE 3MITH TO RETRIEVE DATA FROM THE 7%342%03 VIEW &IGURE GRAPHICALLY ILLUSTRATES THE FLOW OF PRIVILEGES FIRST FROM 3AM TO ,ARRY AND THEN FROM ,ARRY TO 3UE "ECAUSE THE '2!.4 STATEMENT ISSUED BY ,ARRY DID NOT INCLUDE THE 7)4( '2!.4 /04)/. CLAUSE THE CHAIN OF PERMISSIONS ENDS WITH 3UE SHE CAN RETRIEVE THE 7%342%03 DATA BUT CANNOT GRANT ACCESS TO ANOTHER USER (OWEVER IF ,ARRYS GRANT OF PRIVILEGES TO 3UE HAD INCLUDED THE '2!.4 /04)/. THE CHAIN COULD CONTINUE TO ANOTHER LEVEL ALLOWING 3UE TO GRANT ACCESS TO OTHER USERS )TS VERY EASY TO LOSE CONTROL OF WHO HAS WHICH PRIVILEGES WHEN THE '2!.4 /04)/. IS OVERUSED &OR THIS REASON USE OF THIS OPTION IS OFTEN EITHER FORBIDDEN OR DISCOURAGED BY CORPORATE SECURITY ADMINISTRATORS
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"ECAUSE OF THE 7)4( '2!.4 /04)/. CLAUSE THIS '2!.4 STATEMENT CONVEYS ALONG WITH THE SPECIFIED PRIVILEGES THE RIGHT TO GRANT THOSE PRIVILEGES TO OTHER USERS ,ARRY CAN NOW ISSUE THIS '2!.4 STATEMENT
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$ATABASEç3TRUCTURE
1, Ê£xÈÊ Ê 1Ã}ÊÌ
iÊ'2!.4 /04)/.
!LTERNATIVELY ,ARRY MIGHT CONSTRUCT A VIEW FOR 3UE INCLUDING ONLY THE SALESPEOPLE IN THE ,OS !NGELES OFFICE AND GIVE HER ACCESS TO THAT VIEW #2%!4% 6)%7 ,!2%03 !3 3%,%#4 &2/- 7%342%03 7(%2% 2%0?/&&)#% '2!.4 !,, 02)6),%'%3 /. ,!2%03 4/ 35%
,ARRY IS THE OWNER OF THE ,!2%03 VIEW BUT HE DOES NOT OWN THE 7%342%03 VIEW FROM WHICH THIS NEW VIEW IS DERIVED 4O MAINTAIN EFFECTIVE SECURITY THE $"-3 REQUIRES THAT ,ARRY NOT ONLY HAVE THE 3%,%#4 PRIVILEGE ON 7%342%03 BUT ALSO REQUIRES THAT HE HAVE THE '2!.4 /04)/. FOR THAT PRIVILEGE BEFORE ALLOWING HIM TO GRANT THE 3%,%#4 PRIVILEGE ON ,!2%03 TO 3UE /NCE A USER HAS BEEN GRANTED CERTAIN PRIVILEGES WITH THE '2!.4 /04)/. THAT USER MAY GRANT THOSE PRIVILEGES AND THE '2!.4 /04)/. TO OTHER USERS 4HOSE OTHER USERS CAN IN TURN CONTINUE TO GRANT BOTH THE PRIVILEGES AND THE '2!.4 /04)/. &OR THIS REASON YOU SHOULD USE GREAT CARE WHEN GIVING OTHER USERS THE '2!.4 /04)/. .OTE THAT THE '2!.4 /04)/. APPLIES ONLY TO THE SPECIFIC PRIVILEGES NAMED IN THE '2!.4 STATEMENT )F YOU WANT TO GRANT CERTAIN PRIVILEGES WITH THE '2!.4 /04)/. AND GRANT OTHER PRIVILEGES WITHOUT IT YOU MUST USE TWO SEPARATE '2!.4 STATEMENTS AS IN THIS EXAMPLE ,ET ,ARRY &ITCH RETRIEVE INSERT UPDATE AND DELETE DATA FROM THE 7%342%03 TABLE AND LET HIM GRANT RETRIEVAL PERMISSION TO OTHER USERS '2!.4 3%,%#4 /. 7%342%03 4/ ,!229 7)4( '2!.4 /04)/. '2!.4 ).3%24 $%,%4% 50$!4% /. 7%342%03 4/ ,!229
#HAPTERçç
31,ç3ECURITYç
2EVOKINGõ0RIVILEGESõ2%6/+% )N MOST 31, BASED DATABASES THE PRIVILEGES THAT YOU HAVE GRANTED WITH THE '2!.4 STATEMENT CAN BE TAKEN AWAY WITH THE 2%6/+% STATEMENT SHOWN IN &IGURE 4HE 2%6/+% STATEMENT HAS A STRUCTURE THAT CLOSELY PARALLELS THE '2!.4 STATEMENT SPECIFYING A SPECIFIC SET OF PRIVILEGES TO BE TAKEN AWAY FOR A SPECIFIC DATABASE OBJECT FROM ONE OR MORE USER IDS ! 2%6/+% STATEMENT MAY TAKE AWAY ALL OR SOME OF THE PRIVILEGES THAT YOU PREVIOUSLY GRANTED TO A USER ID &OR EXAMPLE CONSIDER THIS STATEMENT SEQUENCE 'RANT AND THEN REVOKE SOME 3!,%32%03 TABLE PRIVILEGES '2!.4 3%,%#4 ).3%24 50$!4% /. 3!,%32%03 4/ !253%2 /053%2 2%6/+% ).3%24 50$!4% /. 3!,%32%03 &2/- /053%2
4HE ).3%24 AND 50$!4% PRIVILEGES ON THE 3!,%32%03 TABLE ARE FIRST GIVEN TO THE TWO USERS AND THEN REVOKED FROM ONE OF THEM (OWEVER THE 3%,%#4 PRIVILEGE REMAINS FOR BOTH USER IDS 3OME OTHER EXAMPLES OF THE 2%6/+% STATEMENT ARE SHOWN NEXT
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iÊ2%6/+%ÊÃÌ>ÌiiÌÊÃÞÌ>ÝÊ`>}À>
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$ATABASEç3TRUCTURE
4AKE AWAY ALL PRIVILEGES GRANTED EARLIER ON THE /&&)#%3 TABLE 2%6/+% !,, 02)6),%'%3 /. /&&)#%3 &2/- !253%2
4AKE AWAY 50$!4% AND $%,%4% PRIVILEGES FOR TWO USER IDS 2%6/+% 50$!4% $%,%4% /. /&&)#%3 &2/- !253%2 /053%2
4AKE AWAY ALL PRIVILEGES ON THE /&&)#%3 TABLE THAT WERE FORMERLY GRANTED TO ALL USERS 2%6/+% !,, 02)6),%'%3 /. /&&)#%3 &2/- 05",)#
7HEN YOU ISSUE A 2%6/+% STATEMENT YOU CAN TAKE AWAY ONLY THOSE PRIVILEGES THAT YOU PREVIOUSLY GRANTED TO ANOTHER USER 4HAT USER MAY ALSO HAVE PRIVILEGES THAT WERE GRANTED BY OTHER USERS THOSE PRIVILEGES ARE NOT AFFECTED BY YOUR 2%6/+% STATEMENT .OTE SPECIFICALLY THAT IF TWO DIFFERENT USERS GRANT THE SAME PRIVILEGE ON THE SAME OBJECT TO A USER AND ONE OF THEM LATER REVOKES THE PRIVILEGE THE SECOND USERS GRANT WILL STILL ALLOW THE USER TO ACCESS THE OBJECT 4HIS HANDLING OF OVERLAPPING GRANTS OF PRIVILEGES IS ILLUSTRATED IN THE FOLLOWING EXAMPLE SEQUENCE 3UPPOSE THAT 3AM #LARK THE SALES VICE PRESIDENT GIVES ,ARRY &ITCH 3%,%#4 PRIVILEGES FOR THE 3!,%32%03 TABLE AND 3%,%#4 AND 50$!4% PRIVILEGES FOR THE /2$%23 TABLE USING THE FOLLOWING STATEMENTS '2!.4 3%,%#4 /. 3!,%32%03 4/ ,!229 '2!.4 3%,%#4 50$!4% /. /2$%23 4/ ,!229
! FEW DAYS LATER 'EORGE 7ATKINS THE MARKETING VICE PRESIDENT GIVES ,ARRY THE 3%,%#4 AND $%,%4% PRIVILEGES FOR THE /2$%23 TABLE AND THE 3%,%#4 PRIVILEGE FOR THE #534/-%23 TABLE USING THESE STATEMENTS '2!.4 3%,%#4 $%,%4% /. /2$%23 4/ ,!229 '2!.4 3%,%#4 /. #534/-%23 4/ ,!229
#HAPTERçç
31,ç3ECURITYç
.OTE THAT ,ARRY HAS RECEIVED PRIVILEGES ON THE /2$%23 TABLE FROM TWO DIFFERENT SOURCES )N FACT THE 3%,%#4 PRIVILEGE ON THE /2$%23 TABLE HAS BEEN GRANTED BY BOTH SOURCES ! FEW DAYS LATER 3AM REVOKES THE PRIVILEGES HE PREVIOUSLY GRANTED TO ,ARRY FOR THE /2$%23 TABLE 2%6/+% 3%,%#4 50$!4% /. /2$%23 &2/- ,!229
!FTER THE $"-3 PROCESSES THE 2%6/+% STATEMENT ,ARRY STILL RETAINS THE 3%,%#4 PRIVILEGE ON THE 3!,%32%03 TABLE THE 3%,%#4 AND $%,%4% PRIVILEGES ON THE /2$%23 TABLE AND THE 3%,%#4 PRIVILEGE ON THE #534/-%23 TABLE BUT HE HAS LOST THE 50$!4% PRIVILEGE ON THE /2$%23 TABLE
2%6/+%õANDõTHEõ'2!.4õ/04)/. 7HEN YOU GRANT PRIVILEGES WITH THE '2!.4 /04)/. AND LATER REVOKE THESE PRIVILEGES MOST $"-3 BRANDS WILL AUTOMATICALLY REVOKE ALL PRIVILEGES DERIVED FROM THE ORIGINAL GRANT #ONSIDER AGAIN THE CHAIN OF PRIVILEGES IN &IGURE FROM 3AM #LARK THE SALES VICE PRESIDENT TO ,ARRY &ITCH THE ,OS !NGELES OFFICE MANAGER AND THEN TO 3UE 3MITH )F 3AM NOW REVOKES ,ARRYS PRIVILEGES FOR THE 7%342%03 VIEW 3UES PRIVILEGE IS AUTOMATICALLY REVOKED AS WELL 4HE SITUATION GETS MORE COMPLICATED IF TWO OR MORE USERS HAVE GRANTED PRIVILEGES AND ONE OF THEM LATER REVOKES THE PRIVILEGES #ONSIDER &IGURE A SLIGHT VARIATION ON THE LAST EXAMPLE (ERE ,ARRY RECEIVES THE 3%,%#4 PRIVILEGE WITH THE '2!.4 /04)/. FROM BOTH 3AM THE SALES VICE PRESIDENT AND 'EORGE THE MARKETING VICE PRESIDENT AND THEN GRANTS PRIVILEGES TO 3UE 4HIS TIME WHEN 3AM REVOKES ,ARRYS PRIVILEGES THE GRANT OF PRIVILEGES FROM 'EORGE REMAINS &URTHERMORE 3UES PRIVILEGES ALSO REMAIN BECAUSE THEY CAN BE DERIVED FROM 'EORGES GRANT
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$ATABASEç3TRUCTURE
1, Ê£xÊ Ê ,iÛ}Ê«ÀÛi}iÃÊÊ >Ê`vviÀiÌÊÃiµÕiVi
(OWEVER CONSIDER ANOTHER VARIATION ON THE CHAIN OF PRIVILEGES WITH THE EVENTS SLIGHTLY REARRANGED AS SHOWN IN &IGURE (ERE ,ARRY RECEIVES THE PRIVILEGE WITH THE '2!.4 /04)/. FROM 3AM GRANTS THE PRIVILEGE TO 3UE AND THEN RECEIVES THE GRANT WITH THE '2!.4 /04)/. FROM 'EORGE 4HIS TIME WHEN 3AM REVOKES ,ARRYS PRIVILEGES THE RESULTS ARE SLIGHTLY DIFFERENT AND THEY MAY VARY FROM ONE $"-3 TO ANOTHER !S IN &IGURE ,ARRY RETAINS THE 3%,%#4 PRIVILEGE ON THE 7%342%03 VIEW BECAUSE THE GRANT FROM 'EORGE IS STILL INTACT "UT IN A $" OR 31,$3 DATABASE 3UE AUTOMATICALLY LOSES HER 3%,%#4 PRIVILEGE ON THE TABLE 7HY "ECAUSE THE GRANT FROM ,ARRY TO 3UE WAS CLEARLY DERIVED FROM THE GRANT FROM 3AM TO ,ARRY WHICH HAS JUST BEEN REVOKED )T COULD NOT HAVE BEEN DERIVED FROM 'EORGES GRANT TO ,ARRY BECAUSE THAT GRANT HAD NOT YET TAKEN PLACE WHEN THE GRANT FROM ,ARRY TO 3UE WAS MADE )N A DIFFERENT BRAND OF $"-3 3UES PRIVILEGES MIGHT REMAIN INTACT BECAUSE THE GRANT FROM 'EORGE TO ,ARRY REMAINS INTACT 4HUS THE TIME SEQUENCE OF '2!.4 AND 2%6/+% STATEMENTS RATHER THAN JUST THE PRIVILEGES THEMSELVES CAN DETERMINE HOW FAR THE EFFECTS OF A 2%6/+% STATEMENT WILL CASCADE 'RANTING AND REVOKING PRIVILEGES WITH THE '2!.4 /04)/. MUST BE HANDLED VERY CAREFULLY TO ENSURE THAT THE RESULTS ARE THOSE YOU INTEND !NOTHER CONSIDERATION IS THE PROCESSING OVERHEAD REQUIRED TO HANDLE THE CASCADING REVOKES )F THE '2!.4 /04)/. IS OVERUSED REVOKES OF PRIVILEGES CAN CAUSE SIGNIFICANT PERFORMANCE PROBLEMS
2%6/+%õANDõTHEõ!.3))3/õ3TANDARD 4HE 31, STANDARD SPECIFIED THE '2!.4 STATEMENT AS PART OF THE 31, $ATA $EFINITION ,ANGUAGE $$, 2ECALL FROM #HAPTER THAT THE 31, STANDARD TREATED THE $$, AS A SEPARATE STATIC DEFINITION OF A DATABASE AND DID NOT REQUIRE THAT THE $"-3 PERMIT DYNAMIC CHANGES TO DATABASE STRUCTURE 4HIS APPROACH APPLIES TO DATABASE SECURITY AS WELL 5NDER THE 31, STANDARD ACCESSIBILITY TO TABLES AND VIEWS IN THE DATABASE IS DETERMINED BY A SERIES OF '2!.4
#HAPTERçç
31,ç3ECURITYç
STATEMENTS INCLUDED IN THE DATABASE SCHEMA 4HERE IS NO MECHANISM FOR CHANGING THE SECURITY SCHEME ONCE THE DATABASE STRUCTURE IS DEFINED 4HE 2%6/+% STATEMENT IS THEREFORE ABSENT FROM THE 31, STANDARD JUST AS THE $2/0 4!",% STATEMENT IS MISSING FROM THE STANDARD $ESPITE ITS ABSENCE FROM THE 31, STANDARD THE 2%6/+% STATEMENT WAS PROVIDED BY VIRTUALLY ALL COMMERCIAL 31, BASED $"-3 PRODUCTS SINCE THEIR EARLIEST VERSIONS !S WITH THE $2/0 AND !,4%2 STATEMENTS THE $" DIALECT OF 31, HAS EFFECTIVELY SET THE STANDARD FOR THE 2%6/+% STATEMENT 3TARTING WITH 31, THE STANDARD INCLUDES A SPECIFICATION FOR THE 2%6/+% STATEMENT BASED ON THE $" STATEMENT WITH SOME EXTENSIONS /NE OF THE EXTENSIONS GIVES THE USER MORE EXPLICIT CONTROL OVER HOW PRIVILEGES ARE REVOKED WHEN THE PRIVILEGES HAVE IN TURN BEEN GRANTED TO OTHERS 4HE OTHER PROVIDES A WAY TO REVOKE THE '2!.4 /04)/. WITHOUT REVOKING THE PRIVILEGES THEMSELVES 4O SPECIFY HOW THE $"-3 SHOULD HANDLE THE REVOKING OF PRIVILEGES THAT HAVE BEEN IN TURN GRANTED TO OTHERS THE 31, STANDARD SUPPORTS A #!3#!$% OR 2%342)#4 OPTION IN A 2%6/+% STATEMENT ! SIMILAR REQUIREMENT APPLIES TO MANY OF THE $2/0 STATEMENTS IN THE 31, STANDARD AS DESCRIBED IN #HAPTER 3UPPOSE THAT 3%,%#4 AND 50$!4% PRIVILEGES HAVE PREVIOUSLY BEEN GRANTED TO ,ARRY ON THE /2$%23 TABLE WITH THE '2!.4 /04)/. AND THAT ,ARRY HAS FURTHER GRANTED THESE OPTIONS TO "ILL 4HEN THIS 2%6/+% STATEMENT 2%6/+% 3%,%#4 50$!4% /. /2$%23 &2/- ,!229 #!3#!$%
REVOKES NOT ONLY ,ARRYS PRIVILEGES BUT ALSO "ILLS 4HE EFFECT OF THE 2%6/+% STATEMENT THUS CASCADES TO ALL OTHER USERS WHOSE PRIVILEGES HAVE FLOWED FROM THE ORIGINAL '2!.4 .OW ASSUME THE SAME CIRCUMSTANCES AND THIS 2%6/+% STATEMENT
)N THIS CASE THE 2%6/+% FAILS 4HE 2%342)#4 OPTION TELLS THE $"-3 NOT TO EXECUTE THE STATEMENT IF IT WILL AFFECT ANY OTHER PRIVILEGES IN THE DATABASE 4HE RESULTING ERROR CALLS THE USERS ATTENTION TO THE FACT THAT THERE ARE POSSIBLY UNINTENTIONAL SIDE EFFECTS OF THE 2%6/+% STATEMENT AND ALLOWS THE USER TO RECONSIDER THE ACTION )F THE USER WANTS TO GO AHEAD AND REVOKE THE PRIVILEGES THE #!3#!$% OPTION CAN BE SPECIFIED 4HE NEWER VERSION OF THE 2%6/+% STATEMENT ALSO GIVES A USER MORE EXPLICIT SEPARATE CONTROL OVER PRIVILEGES AND THE '2!.4 /04)/. FOR THOSE PRIVILEGES 3UPPOSE AGAIN THAT ,ARRY HAS BEEN GRANTED PRIVILEGES ON THE /2$%23 TABLE WITH THE '2!.4 /04)/. FOR THOSE PRIVILEGES 4HE USUAL 2%6/+% STATEMENT FOR THOSE PRIVILEGES 2%6/+% 3%,%#4 50$!4% /. /2$%23 &2/- ,!229
TAKES AWAY BOTH THE PRIVILEGES AND THE ABILITY TO GRANT THOSE PRIVILEGES TO OTHERS 4HE 31, STANDARD PERMITS THIS VERSION OF THE 2%6/+% STATEMENT 2%6/+% '2!.4 /04)/. &/2 3%,%#4 50$!4% /. /2$%23 &2/- ,!229 #!3#!$%
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2%6/+% 3%,%#4 50$!4% /. /2$%23 &2/- ,!229 2%342)#4
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$ATABASEç3TRUCTURE
)F THE STATEMENT IS SUCCESSFUL ,ARRY WILL LOSE THE ABILITY TO GRANT THESE PRIVILEGES TO OTHER USERS BUT HE WILL NOT LOSE THE PRIVILEGES THEMSELVES !S BEFORE THE 31, STANDARD SUPPORTS THE #!3#!$% OR THE 2%342)#4 OPTION FOR SPECIFYING HOW THE $"-3 SHOULD HANDLE THE STATEMENT IF ,ARRY HAS IN TURN GRANTED THE '2!.4 /04)/. TO OTHER USERS
2OLE "ASEDõ3ECURITY 4HE MANAGEMENT OF PRIVILEGES ON AN INDIVIDUAL USER BASIS CAN BE QUITE TEDIOUS !S A RESULT THE CONCEPT OF ROLES WAS ADDED TO THE 31, STANDARD 2ECALL THAT A ROLE IS SIMPLY A NAMED COLLECTION OF PRIVILEGES )N MOST MODERN 31, IMPLEMENTATIONS ROLES CAN BE GRANTED TO USER IDS IN EXACTLY THE SAME WAY AS INDIVIDUAL PRIVILEGES &URTHERMORE MOST 31, IMPLEMENTATIONS COME WITH PREDEFINED ROLES &OR EXAMPLE THE PRIVILEGES NORMALLY REQUIRED BY A $"! ARE OFTEN PROVIDED BY THE $"-3 VENDOR IN A ROLE OF THE SAME NAME 2OLES PROVIDE THE FOLLOWING ADVANTAGES s 2OLES CAN EXIST BEFORE USER ACCOUNTS DO &OR EXAMPLE WE CAN CREATE A ROLE FOR THE /RDER 0ROCESSING DEPARTMENT TO USE INSTEAD OF HAVING THEM SHARE THE USER ID /053%2 AS SHOWN IN &IGURE 7HEN EMPLOYEES JOIN THAT DEPARTMENT ONE '2!.4 USING THE ROLE GIVES THEM ALL THE PRIVILEGES THEY NEED TO WORK IN THE DEPARTMENT s 2OLES SURVIVE WHEN USER ACCOUNTS ARE DROPPED !N ADMINISTRATOR NO LONGER HAS TO WORRY ABOUT LOSING TRACK OF ACCESS PRIVILEGES WHEN A USER ACCOUNT USER ID IS DROPPED &OR EXAMPLE IF 3AM #LARKS PRIVILEGES AS 60 SALES WERE ASSIGNED TO HIM VIA A ROLE THE LIST OF PRIVILEGES WOULD REMAIN WITH THE ROLE IF 3AMS ACCOUNT WAS TERMINATED BECAUSE HE WAS NO LONGER WITH THE COMPANY 4HE ROLE COULD BE EASILY GRANTED TO THE NEXT PERSON TO HOLD THE POSITION s 2OLES PROMOTE STANDARD PRIVILEGES 7HEN ROLES ARE USED BY AN ORGANIZATION IT IS EASY TO ENSURE THAT PEOPLE DOING THE SAME JOB HAVE THE SAME PRIVILEGES s 2OLES RELIEVE THE TEDIUM OF MANAGING PRIVILEGES ON AN INDIVIDUAL USER BASIS -ANY PRIVILEGES CAN BE GRANTED WITH A SINGLE COMMAND WHEN ROLES ARE USED !S PRIVILEGES ARE GRANTED TO OR REVOKED FROM ROLES THOSE CHANGES ARE IMMEDIATELY EFFECTIVE FOR ALL USERS WHO HAVE BEEN GRANTED THE ROLE #REATING AND ASSIGNING PRIVILEGES VIA ROLES IS VERY STRAIGHTFORWARD ONCE YOU UNDERSTAND THE '2!.4 AND 2%6/+% STATEMENTS .OTE THAT IN &IGURE THE '2!.4 STATEMENT ALLOWS THE SPECIFICATION OF A ROLE NAME IN THE 4/ CLAUSE INSTEAD OF A USER ID OR THE KEYWORD 05",)#
#HAPTERçç
31,ç3ECURITYç
3IMILARLY A ROLE NAME CAN BE USED IN THE &2/- CLAUSE OF A 2%6/+% STATEMENT AS SHOWN IN &IGURE (ERE ARE SOME EXAMPLES #REATE ROLE /053%2 TO ORGANIZE THE PRIVILEGES REQUIRED BY USERS IN THE /RDER 0ROCESSING DEPARTMENT #2%!4% 2/,% /053%2
!SSIGN PRIVILEGES NEEDED BY ALL DEPARTMENT USERS TO THE ROLE '2!.4 3%,%#4 ).3%24 $%,%4% 50$!4% /. /2$%23 4/ /053%2 '2!.4 3%,%#4 /. #534/-%23 4/ /053%2 '2!.4 50$!4% #/-0!.9 #534?2%0 /. #534/-%23 4/ /053%2 '2!.4 3%,%#4 /. 3!,%32%03 4/ /053%2
'RANT THE ROLE TO *ULIO 3UMIT AND 9OLANDA THE THREE CURRENT CLERKS IN THE /RDER 0ROCESSING DEPARTMENT '2!.4 /053%2 4/ *5,)/ 35-)4 9/,!.$!
'2!.4 50$!4% /. 3!,%32%03 4/ /053%2
! NEW EMPLOYEE &RANCOIS HAS JOINED THE /RDER 0ROCESSING DEPARTMENT 'RANT THE /053%2 ROLE TO HIM .OTE THAT HE IMMEDIATELY ACQUIRES ALL THE PRIVILEGES IN THE ROLE '2!.4 /053%2 4/ &2!.#/)3
9OLANDA HAS TRANSFERRED TO ANOTHER DEPARTMENT 2EVOKE THE /053%2 ROLE FROM HER ACCOUNT 2%6/+% /053%2 &2/- 9/,!.$!
.OTE THAT SUPPORT FOR ROLES VARIES ACROSS 31, IMPLEMENTATIONS &OR EXAMPLE AS OF THIS WRITING -Y31, DOES NOT APPEAR TO SUPPORT ROLES !ND IN /RACLE A USER NEEDS THE #2%!4% 2/,% PRIVILEGE BEFORE HE OR SHE CAN CREATE NEW ROLES
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'RANT 50$!4% ON THE 3!,%32%03 TABLE TO ROLE /053%2 .OTE THAT ALL THREE USERS CURRENTLY GRANTED THE ROLE IMMEDIATELY ACQUIRE THE NEW PRIVILEGE
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$ATABASEç3TRUCTURE
3UMMARY 4HE 31, IS USED TO SPECIFY THE SECURITY RESTRICTIONS FOR A 31, BASED DATABASE s 4HE 31, SECURITY SCHEME IS BUILT AROUND PRIVILEGES PERMITTED ACTIONS THAT CAN BE GRANTED ON SPECIFIC DATABASE OBJECTS SUCH AS TABLES AND VIEWS TO SPECIFIC USER IDS USERS OR GROUPS OF USERS s 6IEWS ALSO PLAY A KEY ROLE IN 31, SECURITY BECAUSE THEY CAN BE USED TO RESTRICT ACCESS TO SPECIFIC ROWS OR SPECIFIC COLUMNS OF A TABLE s 4HE '2!.4 STATEMENT IS USED TO GRANT PRIVILEGES PRIVILEGES THAT YOU GRANT TO A USER WITH THE '2!.4 /04)/. CAN IN TURN BE GRANTED BY THAT USER TO OTHERS s 4HE 2%6/+% STATEMENT IS USED TO REVOKE PRIVILEGES PREVIOUSLY GRANTED WITH THE '2!.4 STATEMENT s 2OLES CAN BE USED TO ASSEMBLE LISTS OF PRIVILEGES THAT CAN BE GRANTED TO OR REVOKED FROM USERS WITH A SINGLE COMMAND
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4HEç3YSTEMç#ATALOG
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DATABASE MANAGEMENT SYSTEM MUST KEEP TRACK OF A GREAT DEAL OF INFORMATION ABOUT THE STRUCTURE OF A DATABASE TO PERFORM ITS DATA MANAGEMENT FUNCTIONS )N A RELATIONAL DATABASE THIS INFORMATION IS TYPICALLY STORED IN THE SYSTEM CATALOG A COLLECTION OF SYSTEM TABLES THAT THE $"-3 MAINTAINS FOR ITS OWN USE 4HE INFORMATION IN THE SYSTEM CATALOG DESCRIBES THE TABLES VIEWS COLUMNS PRIVILEGES AND OTHER STRUCTURAL FEATURES OF THE DATABASE !LTHOUGH THE $"-3 MAINTAINS THE SYSTEM CATALOG PRIMARILY FOR ITS OWN INTERNAL PURPOSES THE SYSTEM TABLES OR VIEWS BASED ON THEM ARE USUALLY ACCESSIBLE TO DATABASE USERS AS WELL THROUGH STANDARD 31, QUERIES OR SPECIAL COMMANDS SUPPORTED BY THE $"-3 ! RELATIONAL DATABASE IS THUS SELF DESCRIBING USING QUERIES AGAINST THE SYSTEM TABLES YOU CAN ASK THE DATABASE TO DESCRIBE ITS OWN STRUCTURE 'ENERAL PURPOSE DATABASE FRONT ENDS SUCH AS QUERY TOOLS AND REPORT WRITERS USE THIS SELF DESCRIBING FEATURE TO GENERATE LISTS OF TABLES AND COLUMNS FOR USER SELECTION SIMPLIFYING DATABASE ACCESS 4HIS CHAPTER DESCRIBES THE SYSTEM CATALOGS PROVIDED BY SEVERAL POPULAR 31, BASED $"-3 PRODUCTS AND THE INFORMATION THAT THE CATALOGS CONTAIN )T ALSO DESCRIBES THE SYSTEM CATALOG CAPABILITIES SPECIFIED BY THE !.3))3/ 31, STANDARD
7HATõ)SõTHEõ3YSTEMõ#ATALOG 4HE SYSTEM CATALOG IS A COLLECTION OF SPECIAL DATABASE TABLES THAT ARE OWNED CREATED AND MAINTAINED BY THE $"-3 ITSELF 4HESE SYSTEM TABLES CONTAIN DATA THAT DESCRIBES THE STRUCTURE OF THE DATABASE 4HE TABLES IN THE SYSTEM CATALOG ARE AUTOMATICALLY CREATED WHEN THE DATABASE IS CREATED 4HEY ARE USUALLY GATHERED UNDER A SPECIAL SYSTEM USER ID WITH A NAME LIKE 3934%- 393)"- -!34%2 OR $"! 4HE $"-3 CONSTANTLY REFERS TO THE DATA IN THE SYSTEM CATALOG WHILE PROCESSING 31, STATEMENTS &OR EXAMPLE TO PROCESS A TWO TABLE 3%,%#4 STATEMENT THE $"-3 MUST s 6ERIFY THAT THE TWO NAMED TABLES ACTUALLY EXIST s %NSURE THAT THE USER HAS PERMISSION TO ACCESS THEM s #HECK WHETHER THE COLUMNS REFERENCED IN THE QUERY EXIST s 2ESOLVE ANY UNQUALIFIED COLUMN NAMES TO ONE OF THE TABLES s $ETERMINE THE DATA TYPE OF EACH COLUMN
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$ATABASEç3TRUCTURE
"Y STORING STRUCTURAL INFORMATION IN SYSTEM TABLES THE $"-3 CAN USE ITS OWN ACCESS METHODS AND LOGIC TO RAPIDLY AND EFFICIENTLY RETRIEVE THE INFORMATION IT NEEDS TO PERFORM THESE TASKS )F THE SYSTEM TABLES WERE USED ONLY INTERNALLY TO THE $"-3 THEY WOULD BE OF LITTLE INTEREST TO DATABASE USERS (OWEVER THE $"-3 GENERALLY MAKES THE SYSTEM TABLES AVAILABLE FOR USER ACCESS AS WELL )F THE SYSTEM TABLES THEMSELVES ARE NOT MADE AVAILABLE THE $"-3 GENERALLY PROVIDES VIEWS BASED ON THE SYSTEM TABLES THAT OFFER A SET OF USER RETRIEVABLE CATALOG INFORMATION 5SER QUERIES AGAINST THE SYSTEM CATALOGS OR VIEWS ARE ALMOST ALWAYS PERMITTED BY PERSONAL COMPUTER AND WORKGROUP CLASS DATABASES 4HESE QUERIES ARE ALSO SUPPORTED BY MAINFRAME AND ENTERPRISE $"-3 PRODUCTS BUT THE DATABASE ADMINISTRATOR MAY RESTRICT SYSTEM CATALOG ACCESS TO PROVIDE AN ADDITIONAL MEASURE OF DATABASE SECURITY "Y QUERYING THE SYSTEM CATALOGS YOU CAN DISCOVER INFORMATION ABOUT THE STRUCTURE OF A DATABASE EVEN IF YOU HAVE NEVER USED IT BEFORE 5SER ACCESS TO THE SYSTEM CATALOG IS READ ONLY 4HE $"-3 PREVENTS USERS FROM DIRECTLY UPDATING OR MODIFYING THE SYSTEM TABLES BECAUSE SUCH MODIFICATIONS WOULD DESTROY THE INTEGRITY OF THE DATABASE )NSTEAD THE $"-3 ITSELF TAKES CARE OF INSERTING DELETING AND UPDATING ROWS OF THE SYSTEM TABLES AS IT MODIFIES THE STRUCTURE OF A DATABASE $ATA $EFINITION ,ANGUAGE $$, STATEMENTS SUCH AS #2%!4% !,4%2 AND $2/0 AND SECURITY MANAGEMENT STATEMENTS SUCH AS '2!.4 AND 2%6/+% PRODUCE CHANGES IN THE SYSTEM TABLES AS A RESULT OF THEIR ACTIONS )N SOME $"-3 PRODUCTS EVEN $-, STATEMENTS THAT MODIFY THE DATABASE SUCH AS ).3%24 AND $%,%4% MAY PRODUCE CHANGES IN THE SYSTEM TABLES WHICH MIGHT FOR EXAMPLE KEEP TRACK OF HOW MANY ROWS ARE IN EACH TABLE
4HEõ#ATALOGõANDõ1UERYõ4OOLS /NE OF THE MOST IMPORTANT BENEFITS OF THE SYSTEM CATALOG IS THAT IT MAKES POSSIBLE USER FRIENDLY QUERY TOOLS SUCH AS THE 1UERY "UILDER TOOL THAT IS PART OF /RACLE !PPLICATION %XPRESS THAT COMES WITH /RACLE %XPRESS %DITION AS SHOWN IN &IGURE 4HE OBJECTIVE OF SUCH TOOLS IS TO LET USERS SIMPLY AND TRANSPARENTLY ACCESS THE DATABASE WITHOUT LEARNING THE 31, LANGUAGE 4YPICALLY A TOOL LEADS THE USER THROUGH A SERIES OF STEPS SUCH AS
4HE USER GIVES A NAME AND PASSWORD FOR DATABASE ACCESS
4HE QUERY TOOL DISPLAYS A LIST OF AVAILABLE TABLES
4HE USER CHOOSES A TABLE CAUSING THE QUERY TOOL TO DISPLAY A LIST OF THE COLUMNS IT CONTAINS
4HE USER CHOOSES COLUMNS OF INTEREST PERHAPS BY CLICKING THEIR NAMES AS THEY APPEAR ON A 0# SCREEN
4HE USER CHOOSES COLUMNS FROM OTHER TABLES OR RESTRICTS THE DATA TO BE RETRIEVED WITH A SEARCH CONDITION
4HE QUERY TOOL RETRIEVES THE REQUESTED DATA AND DISPLAYS IT ON THE USERS SCREEN
! GENERAL PURPOSE QUERY TOOL LIKE THE ONE IN &IGURE WILL BE USED BY MANY DIFFERENT PEOPLE AND IT WILL BE USED TO ACCESS MANY DIFFERENT DATABASES 4HE TOOL CANNOT POSSIBLY KNOW IN ADVANCE THE STRUCTURE OF THE DATABASE THAT IT WILL ACCESS DURING ANY GIVEN SESSION 4HUS IT MUST BE ABLE TO DYNAMICALLY LEARN ABOUT THE TABLES AND COLUMNS OF A DATABASE 4HE TOOL USES SYSTEM CATALOG QUERIES FOR THIS PURPOSE
#HAPTERçç
4HEç3YSTEMç#ATALOGç
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4HEõ#ATALOGõANDõTHEõ!.3))3/õ3TANDARD
#ATALOGõ#ONTENTS %ACH TABLE IN THE SYSTEM CATALOG CONTAINS INFORMATION ABOUT A SINGLE KIND OF STRUCTURAL ELEMENT IN THE DATABASE !LTHOUGH THE DETAILS VARY ALMOST ALL COMMERCIAL 31, PRODUCTS INCLUDE SYSTEM TABLES THAT DESCRIBE EACH OF THESE FIVE ENTITIES s 4ABLES 4HE TABLES CATALOG DESCRIBES EACH TABLE IN THE DATABASE IDENTIFYING ITS TABLE NAME ITS OWNER THE NUMBER OF COLUMNS IT CONTAINS ITS SIZE AND SO ON s #OLUMNS 4HE COLUMNS CATALOG DESCRIBES EACH COLUMN IN THE DATABASE GIVING THE COLUMNS NAME THE TABLE TO WHICH IT BELONGS ITS DATA TYPE ITS SIZE WHETHER .5,,S ARE ALLOWED AND SO ON s 5SERS 4HE USERS CATALOG DESCRIBES EACH AUTHORIZED DATABASE USER INCLUDING THE USERS NAME AN ENCRYPTED FORM OF THE USERS PASSWORD AND OTHER DATA
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4HE !.3))3/ 31, STANDARD DOES NOT SPECIFY THE STRUCTURE AND CONTENTS OF THE SYSTEM CATALOG )N FACT THE 31, STANDARD DOES NOT REQUIRE A SYSTEM CATALOG AT ALL (OWEVER ALL OF THE MAJOR 31, BASED $"-3 PRODUCTS PROVIDE A SYSTEM CATALOG IN ONE FORM OR ANOTHER 4HE STRUCTURE OF THE CATALOG AND THE TABLES IT CONTAINS VARY CONSIDERABLY FROM ONE BRAND OF $"-3 TO ANOTHER "ECAUSE OF THE GROWING IMPORTANCE OF GENERAL PURPOSE DATABASE TOOLS THAT MUST ACCESS THE SYSTEM CATALOG THE 31, STANDARD STARTING WITH 31, INCLUDES A SPECIFICATION OF A SET OF VIEWS THAT PROVIDE STANDARDIZED ACCESS TO INFORMATION TYPICALLY FOUND IN THE SYSTEM CATALOG ! $"-3 SYSTEM THAT CONFORMS TO THE 31, STANDARD MUST SUPPORT THESE VIEWS WHICH ARE COLLECTIVELY CALLED THE ).&/2-!4)/.?3#(%-! "ECAUSE THIS SCHEMA IS MORE COMPLEX THAN THE ACTUAL SYSTEM CATALOGS USED BY MOST COMMERCIAL $"-3 PRODUCTS IT IS DESCRIBED IN A SEPARATE SECTION NEAR THE END OF THIS CHAPTER h4HE 31, )NFORMATION 3CHEMAv
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s 6IEWS 4HE VIEWS CATALOG DESCRIBES EACH VIEW DEFINED IN THE DATABASE INCLUDING ITS NAME THE NAME OF ITS OWNER THE QUERY THAT DEFINES THE VIEW AND SO ON s 0RIVILEGES 4HE PRIVILEGES CATALOG DESCRIBES EACH SET OF PRIVILEGES GRANTED IN THE DATABASE INCLUDING THE NAMES OF THE GRANTOR AND GRANTEE THE PRIVILEGES GRANTED THE OBJECT ON WHICH THE PRIVILEGES HAVE BEEN GRANTED AND SO ON 4ABLE SHOWS THE NAMES OF THE SYSTEM TABLES ANDOR VIEWS THAT PROVIDE THIS INFORMATION IN EACH OF THE MAJOR 31, BASED $"-3 PRODUCTS .OTE THAT -Y31, SUPPORTS THE -
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4HEç3YSTEMç#ATALOGç
)NFORMATION 3CHEMA DESCRIBED LATER IN THIS CHAPTER 4HE REMAINDER OF THIS TOPIC DESCRIBES SOME TYPICAL SYSTEM TABLES IN MORE DETAIL AND GIVES EXAMPLES OF SYSTEM CATALOG ACCESS "ECAUSE OF THE WIDE VARIATIONS IN SYSTEM CATALOGS AMONG $"-3 BRANDS A COMPLETE DESCRIPTION OF THE SYSTEM CATALOGS AND COMPLETE EXAMPLES FOR ALL OF THE MAJOR $"-3 BRANDS IS BEYOND THE SCOPE OF THIS BOOK 7ITH THE INFORMATION PROVIDED HERE YOU SHOULD BE ABLE TO CONSULT THE SYSTEM DOCUMENTATION FOR YOUR $"-3 BRAND AND CONSTRUCT THE APPROPRIATE SYSTEM CATALOG QUERIES
4ABLEõ)NFORMATION %ACH OF THE MAJOR 31, PRODUCTS HAS A SYSTEM TABLE OR VIEW THAT KEEPS TRACK OF THE TABLES IN THE DATABASE )N $" FOR EXAMPLE THIS INFORMATION IS PROVIDED BY A SYSTEM CATALOG VIEW NAMED 393#!44!",%3 !LL OF THE $" SYSTEM CATALOG VIEWS ARE PART OF A SCHEMA NAMED 393#!4 SO THEY ALL HAVE QUALIFIED TABLEVIEW NAMES OF THE FORM 393#!4888 4ABLE SHOWS SOME OF THE COLUMNS OF THE 393#!44!",%3 VIEW )T CONTAINS ONE ROW FOR EACH TABLE VIEW OR ALIAS DEFINED IN THE DATABASE 4HE INFORMATION IN THIS VIEW IS TYPICAL OF THAT PROVIDED BY THE CORRESPONDING VIEWS IN OTHER MAJOR $"-3 PRODUCTS
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6IEWõ)NFORMATION 4HE DEFINITIONS OF THE VIEWS IN A DATABASE ARE USUALLY STORED BY THE $"-3 IN THE SYSTEM CATALOG 4HE $" CATALOG CONTAINS TWO SYSTEM TABLES THAT KEEP TRACK OF VIEWS 4HE 393#!4 6)%73 TABLE DESCRIBED IN 4ABLE CONTAINS THE 31, TEXT DEFINITION OF EACH VIEW /LDER VERSIONS OF $" SUPPORTED 31, TEXT UP TO CHARACTERS AND DEFINITIONS EXCEEDING THAT SIZE WERE STORED IN MULTIPLE ROWS WITH SEQUENCE NUMBERS AND SO ON .EWER VERSIONS OF $" USE A #,/" COLUMN THAT ACCOMMODATES VIEW DEFINITIONS UP TO + IN SIZE SO ONLY ONE ROW IN THE 393#!46)%73 TABLE IS REQUIRED FOR EACH VIEW
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.OTE THE USE OF $)34).#4 TO ELIMINATE DUPLICATE ROWS THAT WOULD BE PRESENT FOR VIEWS WITH LONG TEXT DEFINITIONS IN OLDER VERSIONS OF $" 0ERHAPS AN EASIER WAY TO OBTAIN THE SAME INFORMATION IS TO QUERY THE $" 4!",%3 SYSTEM TABLE DIRECTLY SELECTING ONLY ROWS REPRESENTING VIEWS AS INDICATED BY THE 490% VALUE ,IST THE VIEWS DElNED IN THE DATABASE 3%,%#4 4!"3#(%-! 4!".!-% $%&).%2 &2/- 393#!44!",%3 7(%2% 490% g6g
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.OTE THAT MOST INTERACTIVE 31, PRODUCTS INCLUDING /RACLES TRUNCATE THE DISPLAYED TEXT CONTAINING THE VIEW DEFINITION IF IT IS TOO LONG TO BE DISPLAYED EFFECTIVELY 4HE ACTUAL TEXT STORED IN THE DATABASE IS COMPLETE
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-OST OF THE MAJOR $"-3 PRODUCTS TREAT VIEWS IN THIS SAME WAY WITHIN THEIR SYSTEM CATALOG STRUCTURE )NFORMIX 5NIVERSAL 3ERVER FOR EXAMPLE HAS A SYSTEM TABLE NAMED 3936)%73 THAT CONTAINS VIEW DEFINITIONS %ACH OF ITS ROWS HOLDS A CHARACTER CHUNK OF THE 31, 3%,%#4 STATEMENT THAT DEFINES A VIEW 6IEW DEFINITIONS THAT SPAN MULTIPLE ROWS ARE HANDLED BY SEQUENCE NUMBERS AS WITH $" 4HE )NFORMIX 3936)%73 TABLE INCLUDES ONLY ONE OTHER COLUMNTHE TABLE ID THAT LINKS THE 3936)%73 TABLE TO THE CORRESPONDING ROW IN THE 3934!",%3 TABLE 4HUS )NFORMIX DUPLICATES LESS INFORMATION BETWEEN THE 3934!",%3 AND 3936)%73 TABLES BUT YOU MUST EXPLICITLY JOIN THE TABLES FOR THE MOST COMMON VIEW INFORMATION REQUESTS /RACLE TAKES A SIMILAR APPROACH BY MAKING THE 31, TEXT THAT DEFINES A VIEW AVAILABLE VIA SYSTEM VIEWS !S WITH TABLE AND COLUMN INFORMATION THREE SYSTEM VIEWS ARE OF INTEREST 53%2?6)%73 WHICH CONTAINS INFORMATION ABOUT ALL VIEWS CREATED AND OWNED BY THE CURRENT USER !,,?6)%73 WHICH CONTAINS INFORMATION ABOUT VIEWS ACCESSIBLE TO THE CURRENT USER AND $"!?6)%73 WHICH CONTAINS INFORMATION ABOUT ALL THE VIEWS IN THE DATABASE 4HE 31, TEXT DEFINING THE VIEW IS HELD IN A ,/.' /RACLE PROPRIETARY LARGE TEXT OBJECT DATA TYPE COLUMN AND CAN CONCEIVABLY RUN TO MANY THOUSANDS OF CHARACTERS ! LENGTH COLUMN TELLS THE LENGTH OF THE STORED 31, TEXT DEFINITION OF THE VIEW (ERE IS A QUERY TO OBTAIN /RACLE VIEW INFORMATION
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2EMARKS )"-S $" PRODUCTS ALLOW YOU TO ASSOCIATE UP TO CHARACTERS OF REMARKS WITH EACH TABLE VIEW AND COLUMN DEFINED IN THE DATABASE 4HE REMARKS ALLOW YOU TO STORE A BRIEF DESCRIPTION OF THE TABLE OR DATA ITEM IN THE SYSTEM CATALOG 4HE REMARKS ARE STORED IN THE 393#!44!",%3 AND 393#!4#/,5-.3 SYSTEM TABLES OF THE SYSTEM CATALOG 5NLIKE THE OTHER ELEMENTS OF TABLE AND COLUMN DEFINITIONS THE REMARKS AND LABELS ARE NOT SPECIFIED BY THE #2%!4% 4!",% STATEMENT )NSTEAD THE #/--%.4 STATEMENT IS USED )TS SYNTAX IS SHOWN IN &IGURE (ERE ARE SOME EXAMPLES $ElNE REMARKS FOR THE /&&)#%3 TABLE #/--%.4 /. 4!",% /&&)#%3 )3 g4HIS TABLE STORES DATA ABOUT OUR SALES OFFICESg
!SSOCIATE SOME REMARKS WITH THE 4!2'%4 AND 3!,%3 COLUMNS OF THE /&&)#%3 TABLE #/--%.4 /. /&&)#%3 4!2'%4 )3 g4HIS IS THE ANNUAL SALES TARGET FOR THE OFFICEg 3!,%3 )3 g4HIS IS THE YEAR TO DATE SALES FOR THE OFFICEg
"ECAUSE THIS IS A CAPABILITY CARRIED FORWARD FROM SOME OF THE EARLIEST )"- 31, PRODUCTS /RACLE ALSO SUPPORTS THE #/--%.4 /. STATEMENT FOR ATTACHING COMMENTS TO TABLES AND COLUMNS 4HE COMMENTS ARE NOT STORED INLINE WITH OTHER TABLE AND COLUMN INFORMATION HOWEVER 4HEY ARE ACCESSIBLE VIA THE /RACLE SYSTEM VIEWS 53%2?4!"?#/--%.43 AND 53%2?#/,?#/--%.43 4HE $" #/--%.4 CAPABILITY HAS BEEN EXPANDED OVER THE YEARS TO ALLOW COMMENTS ON CONSTRAINTS STORED PROCEDURES SCHEMAS TABLESPACES TRIGGERS AND OTHER $" DATABASE OBJECTS 4HIS CAPABILITY IS NOT PART OF THE 31, STANDARD AND HAS GENERALLY NOT BEEN ADOPTED BY OTHER MAJOR $"-3 PRODUCTS
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4HE NAMES OF THE FOREIGN KEY COLUMNS AND THE CORRESPONDING PRIMARY KEY COLUMNS ARE LISTED AS TEXT IN THE &+?#/,.!-%3 AND 0+?#/,.!-%3 COLUMNS OF THE 2%&%2%.#%3 SYSTEM TABLE ! SECOND SYSTEM TABLE 393#!4+%9#/,53% SHOWN IN 4ABLE PROVIDES A SOMEWHAT MORE USEFUL FORM OF THE INFORMATION 4HERE IS ONE ROW IN THIS SYSTEM TABLE FOR EACH COLUMN IN EACH FOREIGN KEY PRIMARY KEY OR UNIQUENESS CONSTRAINT DEFINED IN THE DATABASE ! SEQUENCE NUMBER DEFINES THE ORDER OF THE COLUMNS IN A COMPOUND KEY 9OU CAN USE THIS SYSTEM TABLE TO FIND OUT THE NAMES OF THE COLUMNS THAT LINK A TABLE TO ITS PARENT BY USING A QUERY LIKE THIS ONE ,IST THE COLUMNS THAT LINK /2$%23 TO 02/$5#43 IN THE RELATIONSHIP NAMED )3&/2 3%,%#4 #/,.!-% #/,3%1 &2/- 393#!4+%9#/,53% 7(%2% #/.34.!-% g)3&/2g /2$%2 "9 #/,3%1
4HE PRIMARY KEY OF A TABLE AND THE PARENTCHILD RELATIONSHIPS IN WHICH IT PARTICIPATES ARE ALSO SUMMARIZED IN THE 393#!44!",%3 AND 393#!4#/,5-.3 SYSTEM TABLES SHOWN PREVIOUSLY IN 4ABLES AND )F A TABLE HAS A PRIMARY KEY THE +%9#/,5-.3 COLUMN IN ITS ROW OF THE 393#!44!",%3 SYSTEM TABLE IS NONZERO AND TELLS HOW MANY COLUMNS MAKE UP THE PRIMARY KEY ONE FOR A SIMPLE KEY AND TWO OR MORE FOR A COMPOSITE KEY )N THE 393#!4#/,5-.3 SYSTEM TABLE THE ROWS FOR THE COLUMNS THAT MAKE UP THE PRIMARY KEY HAVE A NONZERO VALUE IN THEIR +%93%1 COLUMN 4HE VALUE IN THIS COLUMN INDICATES THE POSITION AND SO ON OF THE PRIMARY KEY COLUMN WITHIN THE PRIMARY KEY
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4HEç3YSTEMç#ATALOGç
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5SERõ)NFORMATION 4HE SYSTEM CATALOG GENERALLY CONTAINS A TABLE THAT IDENTIFIES THE USERS WHO ARE AUTHORIZED TO ACCESS THE DATABASE 4HE $"-3 MAY USE THIS SYSTEM TABLE TO VALIDATE THE USER NAME AND PASSWORD WHEN A USER FIRST ATTEMPTS TO CONNECT TO THE DATABASE 4HE TABLE MAY ALSO STORE OTHER DATA ABOUT THE USER 31, 3ERVER STORES USER INFORMATION IN ITS 393$!4!"!3%?02).#)0!,3 CATALOG VIEW SHOWN IN 4ABLE %ACH ROW OF THIS TABLE DESCRIBES A SINGLE USER OR USER GROUP IN THE 31, 3ERVER SECURITY SCHEME )NFORMIX TAKES A SIMILAR APPROACH WITH A SYSTEM TABLE THAT IS ALSO
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/THERõ#ATALOGõ)NFORMATION 4HE SYSTEM CATALOG IS A REFLECTION OF THE CAPABILITIES AND FEATURES OF THE $"-3 THAT USES IT "ECAUSE OF THE MANY 31, EXTENSIONS AND ADDITIONAL FEATURES OFFERED BY POPULAR $"-3 PRODUCTS THEIR SYSTEM CATALOGS ALWAYS CONTAIN SEVERAL TABLES UNIQUE TO THE $"-3 (ERE ARE JUST A FEW EXAMPLES
s 31, 3ERVER SUPPORTS MULTIPLE NAMED DATABASES )T HAS A CATALOG VIEW CALLED 393 $!4!"!3%3 THAT IDENTIFIES THE DATABASES MANAGED BY A SINGLE SERVER s -ANY $"-3 BRANDS NOW SUPPORT STORED PROCEDURES AND THE CATALOG CONTAINS ONE OR MORE TABLES THAT DESCRIBE THEM 3YBASE STORES INFORMATION ABOUT STORED PROCEDURES IN ITS 39302/#%$52%3 SYSTEM TABLE s )NGRES SUPPORTS TABLES THAT ARE DISTRIBUTED ACROSS SEVERAL DISK VOLUMES )TS ))-5,4)?,/#!4)/.3 SYSTEM TABLE KEEPS TRACK OF THE LOCATIONS OF MULTIVOLUME TABLES
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s $" AND /RACLE SUPPORT ALIASES AND SYNONYMS ALTERNATE NAMES FOR TABLES $" STORES ALIAS INFORMATION WITH OTHER TABLE INFORMATION IN THE 393#!44!",%3 SYSTEM TABLE /RACLE MAKES SYNONYM INFORMATION AVAILABLE THROUGH ITS $"!?39./.9-3 SYSTEM VIEW
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3UMMARY 4HE SYSTEM CATALOG IS A COLLECTION OF SYSTEM TABLES THAT DESCRIBE THE STRUCTURE OF A RELATIONAL DATABASE s 4HE $"-3 MAINTAINS THE DATA IN THE SYSTEM TABLES UPDATING IT AS THE STRUCTURE OF THE DATABASE CHANGES s ! USER CAN QUERY THE SYSTEM TABLES TO FIND OUT INFORMATION ABOUT TABLES COLUMNS AND PRIVILEGES IN THE DATABASE s &RONT END QUERY TOOLS USE THE SYSTEM TABLES TO HELP USERS NAVIGATE THEIR WAY THROUGH THE DATABASE IN A USER FRIENDLY WAY s 4HE NAMES AND ORGANIZATION OF THE SYSTEM TABLES DIFFER WIDELY FROM ONE BRAND OF $"-3 TO ANOTHER THERE EVEN ARE DIFFERENCES AMONG DIFFERENT $"-3 PRODUCTS FROM THE SAME VENDOR REFLECTING THE DIFFERENT INTERNAL STRUCTURES AND CAPABILITIES OF THE PRODUCTS s 4HE 31, STANDARD DOES NOT REQUIRE THAT A $"-3 ACTUALLY HAVE A SET OF SYSTEM CATALOG TABLES BUT IT DOES DEFINE A SET OF STANDARD CATALOG VIEWS FOR PRODUCTS THAT CLAIM HIGHER LEVELS OF 31, CONFORMANCE
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N ADDITION TO ITS ROLE AS AN INTERACTIVE DATA ACCESS LANGUAGE 31, SUPPORTS DATABASE ACCESS BY APPLICATION PROGRAMS #HAPTERS n DESCRIBE THE SPECIAL 31, FEATURES AND TECHNIQUES THAT APPLY TO PROGRAMMATIC 31, #HAPTER DESCRIBES EMBEDDED 31, THE OLDEST PROGRAMMATIC 31, TECHNIQUE AND ONE STILL SUPPORTED BY MANY 31, PRODUCTS $YNAMIC 31, AN ADVANCED FORM OF EMBEDDED 31, THAT IS USED TO BUILD GENERAL PURPOSE DATABASE TOOLS IS DESCRIBED IN #HAPTER #HAPTER DESCRIBES AN ALTERNATIVE TO EMBEDDED 31,THE FUNCTION CALL INTERFACE PROVIDED BY SEVERAL POPULAR $"-3 PRODUCTS WHICH HAS BEEN GAINING IN POPULARITY
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1, IS A DUAL MODE LANGUAGE )T IS BOTH AN INTERACTIVE DATABASE LANGUAGE USED FOR AD HOC QUERIES AND UPDATES AND A PROGRAMMATIC DATABASE LANGUAGE USED BY APPLICATION PROGRAMS FOR DATABASE ACCESS &OR THE MOST PART THE 31, LANGUAGE IS IDENTICAL IN BOTH MODES 4HE DUAL MODE NATURE OF 31, HAS SEVERAL ADVANTAGES s )T IS RELATIVELY EASY FOR PROGRAMMERS TO LEARN HOW TO WRITE PROGRAMS THAT ACCESS THE DATABASE s #APABILITIES AVAILABLE THROUGH THE INTERACTIVE QUERY LANGUAGE ARE ALSO AUTOMATICALLY AVAILABLE TO APPLICATION PROGRAMS s 4HE 31, STATEMENTS TO BE USED IN A PROGRAM CAN BE TRIED FIRST USING INTERACTIVE 31, AND THEN CAN BE CODED INTO THE PROGRAM s 0ROGRAMS CAN WORK WITH TABLES OF DATA AND QUERY RESULTS INSTEAD OF NAVIGATING THEIR WAY THROUGH THE DATABASE 4HIS CHAPTER SUMMARIZES THE TYPES OF PROGRAMMATIC 31, OFFERED BY THE LEADING 31, BASED PRODUCTS AND THEN DESCRIBES THE PROGRAMMATIC 31, USED BY THE )"- 31, PRODUCTS WHICH IS CALLED EMBEDDED 31,
0ROGRAMMATICõ31,õ4ECHNIQUES 31, IS A LANGUAGE AND CAN BE USED PROGRAMMATICALLY BUT IT WOULD BE INCORRECT TO CALL 31, A PROGRAMMING LANGUAGE 31, LACKS EVEN THE MOST PRIMITIVE FEATURES OF REAL PROGRAMMING LANGUAGES )T HAS NO PROVISION FOR DECLARING VARIABLES NO '/4/ STATEMENT NO )& STATEMENT FOR TESTING CONDITIONS NO &/2 $/ OR 7(),% STATEMENTS TO CONSTRUCT LOOPS NO BLOCK STRUCTURE AND SO ON 31, IS A DATABASE SUBLANGUAGE THAT HANDLES SPECIAL PURPOSE DATABASE MANAGEMENT TASKS 4O WRITE A PROGRAM THAT ACCESSES A DATABASE YOU MUST START WITH A CONVENTIONAL PROGRAMMING LANGUAGE SUCH AS #/"/, 0,) &/242!. 0ASCAL # # OR *AVA OR A SCRIPTING LANGUAGE SUCH AS 0ERL 0(0 OR 2UBY AND THEN ADD 31, TO THE PROGRAM
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4HE INITIAL !.3))3/ 31, STANDARD WAS CONCERNED EXCLUSIVELY WITH THIS PROGRAMMATIC USE OF 31, )N FACT THE STANDARD DID NOT EVEN INCLUDE THE INTERACTIVE 3%,%#4 STATEMENT DESCRIBED IN #HAPTERS THROUGH )T ONLY SPECIFIED THE PROGRAMMATIC 3%,%#4 STATEMENT DESCRIBED LATER IN THE SECTION h$ATA 2ETRIEVAL IN %MBEDDED 31,v 4HE 31, STANDARD PUBLISHED IN EXPANDED ITS FOCUS TO INCLUDE INTERACTIVE 31, CALLED DIRECT INVOCATION OF 31, IN THE STANDARD AND MORE ADVANCED FORMS OF PROGRAMMATIC 31, THE DYNAMIC 31, CAPABILITIES DESCRIBED IN #HAPTER #OMMERCIAL 31, DATABASE VENDORS OFFER TWO BASIC TECHNIQUES FOR USING 31, WITHIN AN APPLICATION PROGRAM s %MBEDDED 31, )N THIS APPROACH 31, STATEMENTS ARE EMBEDDED DIRECTLY INTO THE PROGRAMS SOURCE CODE INTERMIXED WITH THE OTHER PROGRAMMING LANGUAGE STATEMENTS 3PECIAL EMBEDDED 31, STATEMENTS ARE USED TO RETRIEVE DATA INTO THE PROGRAM ! SPECIAL 31, PRECOMPILER ACCEPTS THE COMBINED SOURCE CODE AND ALONG WITH OTHER PROGRAMMING TOOLS CONVERTS IT INTO AN EXECUTABLE PROGRAM s !PPLICATION PROGRAM INTERFACE )N THIS APPROACH THE PROGRAM COMMUNICATES WITH THE $"-3 THROUGH A SET OF FUNCTION CALLS CALLED AN APPLICATION PROGRAM INTERFACE !0) 4HE PROGRAM PASSES 31, STATEMENTS TO THE $"-3 THROUGH THE !0) CALLS AND USES !0) CALLS TO RETRIEVE QUERY RESULTS 4HIS APPROACH DOES NOT REQUIRE A SPECIAL PRECOMPILER 4HE INITIAL )"- 31, PRODUCTS USED AN EMBEDDED 31, APPROACH AND MOST COMMERCIAL 31, PRODUCTS ADOPTED IT IN THE S 4HE ORIGINAL !.3))3/ 31, STANDARD SPECIFIED ONLY AN AWKWARD MODULE LANGUAGE FOR PROGRAMMATIC 31, BUT COMMERCIAL 31, PRODUCTS CONTINUED TO FOLLOW THE )"- DE FACTO STANDARD )N THE !.3))3/ STANDARD WAS EXTENDED TO INCLUDE A DEFINITION OF HOW TO EMBED 31, STATEMENTS WITHIN THE !DA # #/"/, &/242!. 0ASCAL AND 0,) PROGRAMMING LANGUAGES THIS TIME FOLLOWING THE )"- APPROACH 4HE 31, STANDARD AND SUBSEQUENT REVISIONS CONTINUED THIS SPECIFICATION )N PARALLEL WITH THIS EVOLUTION OF EMBEDDED 31, SEVERAL $"-3 VENDORS WHO WERE FOCUSED ON MINICOMPUTER SYSTEMS INTRODUCED CALLABLE DATABASE !0)S IN THE S 7HEN THE 3YBASE $"-3 WAS INTRODUCED IT OFFERED ONLY A CALLABLE !0) -ICROSOFTS 31, 3ERVER DERIVED FROM THE 3YBASE $"-3 ALSO USED THE !0) APPROACH EXCLUSIVELY 3OON AFTER THE DEBUT OF 31, 3ERVER -ICROSOFT INTRODUCED /PEN $ATABASE #ONNECTIVITY /$"# ANOTHER CALLABLE !0) /$"# IS ROUGHLY BASED ON THE 31, 3ERVER !0) BUT WITH THE ADDITIONAL GOALS OF BEING DATABASE INDEPENDENT AND PERMITTING CONCURRENT ACCESS TO TWO OR MORE DIFFERENT $"-3 BRANDS THROUGH A COMMON !0) *AVA $ATABASE #ONNECTIVITY *$"# HAS EMERGED AS AN IMPORTANT !0) FOR ACCESSING A RELATIONAL DATABASE FROM WITHIN PROGRAMS WRITTEN IN *AVA 7ITH THE GROWING POPULARITY OF CALLABLE !0)S THE CALLABLE AND EMBEDDED APPROACHES ARE BOTH IN ACTIVE USE TODAY )N GENERAL PROGRAMMERS USING OLDER LANGUAGES SUCH AS #/"/, AND !SSEMBLER WILL TEND TO FAVOR THE EMBEDDED 31, APPROACH 0ROGRAMMERS USING LANGUAGES SUCH AS # AND *AVA WILL TEND TO FAVOR THE CALLABLE !0) APPROACH 3PECIFICATIONS FOR EMBEDDED 31, IN *AVA WERE ADDED TO THE 31, STANDARD IN AND REVISED IN SEVERAL SUBSEQUENT RELEASES 4HE STANDARD WAS ORIGINALLY CALLED 31,* LATER 31,*24 AND SEVERAL VENDORS IMPLEMENTED SOLUTIONS KNOWN AS *31, -OST OF THESE *31, IMPLEMENTATIONS USE A PREPROCESSOR TO TRANSLATE 31, EMBEDDED IN THE *AVA PROGRAM TO *$"# !0) CALLS
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4HE FOLLOWING TABLE SUMMARIZES THE PROGRAMMATIC INTERFACES OFFERED BY SOME OF THE LEADING 31, BASED $"-3 PRODUCTS
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4HE BASIC TECHNIQUES OF EMBEDDED 31, CALLED STATIC 31, ARE DESCRIBED IN THIS CHAPTER 3OME ADVANCED FEATURES OF EMBEDDED 31, CALLED DYNAMIC 31, ARE DISCUSSED IN #HAPTER #ALLABLE 31, !0)S INCLUDING THE 3YBASE31, 3ERVER !0) /$"# AND *$"# ARE DISCUSSED IN #HAPTER
$"-3õ3TATEMENTõ0ROCESSING 4O UNDERSTAND ANY OF THE PROGRAMMATIC 31, TECHNIQUES IT HELPS TO UNDERSTAND A LITTLE BIT MORE ABOUT HOW THE $"-3 PROCESSES 31, STATEMENTS 4O PROCESS A 31, STATEMENT THE $"-3 GOES THROUGH A SERIES OF FIVE STEPS SHOWN IN &IGURE 4HE $"-3 BEGINS BY PARSING THE 31, STATEMENT )T BREAKS UP THE STATEMENT INTO INDIVIDUAL WORDS MAKING SURE THAT THE STATEMENT HAS A VALID VERB LEGAL CLAUSES AND SO ON 3YNTAX ERRORS AND MISSPELLINGS CAN BE DETECTED IN THIS STEP
4HE $"-3 VALIDATES THE STATEMENT )T CHECKS THE STATEMENT AGAINST THE SYSTEM CATALOG $O ALL THE TABLES NAMED IN THE STATEMENT EXIST IN THE DATABASE $O ALL OF THE COLUMNS EXIST AND ARE THE COLUMN NAMES UNAMBIGUOUS $OES THE USER HAVE THE REQUIRED PRIVILEGES TO EXECUTE THE STATEMENT 3EMANTIC ERRORS ARE DETECTED IN THIS STEP
4HE $"-3 OPTIMIZES THE STATEMENT )T EXPLORES VARIOUS WAYS TO CARRY OUT THE STATEMENT #AN AN INDEX BE USED TO SPEED A SEARCH 3HOULD THE $"-3 FIRST APPLY A SEARCH CONDITION TO 4ABLE ! AND THEN JOIN IT TO 4ABLE " OR SHOULD IT BEGIN WITH THE JOIN AND USE THE SEARCH CONDITION AFTERWARD #AN A SEQUENTIAL SEARCH THROUGH A TABLE BE AVOIDED OR REDUCED TO A SUBSET OF THE TABLE #AN AN INDEX BE USED TO AVOID A SORT !FTER EXPLORING ALTERNATIVES THE $"-3 CHOOSES ONE OF THEM
4HE $"-3 THEN GENERATES AN APPLICATION PLAN FOR THE STATEMENT 4HE APPLICATION PLAN IS A BINARY REPRESENTATION OF THE STEPS THAT ARE REQUIRED TO CARRY OUT THE STATEMENT IT IS THE $"-3 EQUIVALENT OF EXECUTABLE CODE
&INALLY THE $"-3 CARRIES OUT THE STATEMENT BY EXECUTING THE APPLICATION PLAN
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.OTE THAT THE DEFINITIONS OF THE TERMS USED IN THE PRECEDING DESCRIPTION VARY FROM ONE $"-3 PRODUCT TO ANOTHER 4HE STEPS IN &IGURE VARY IN THE AMOUNT OF DATABASE ACCESS THEY REQUIRE AND THE AMOUNT OF #05 TIME THEY TAKE 0ARSING A 31, STATEMENT DOES NOT REQUIRE ACCESS TO THE DATABASE AND TYPICALLY CAN BE DONE VERY QUICKLY /PTIMIZATION ON THE OTHER HAND IS A VERY #05 INTENSIVE PROCESS AND REQUIRES ACCESS TO THE DATABASES SYSTEM CATALOG &OR A COMPLEX MULTITABLE QUERY THE OPTIMIZER MAY EXPLORE MORE THAN A DOZEN DIFFERENT WAYS OF CARRYING OUT THE QUERY (OWEVER THE COST IN COMPUTER PROCESSING TIME OF DOING THE QUERY THE WRONG WAY IS USUALLY SO HIGH COMPARED WITH THE COST OF DOING IT THE RIGHT WAY OR AT LEAST A BETTER WAY THAT THE TIME SPENT IN OPTIMIZATION IS MORE THAN GAINED BACK IN INCREASED QUERY EXECUTION SPEED 7HEN YOU TYPE A 31, STATEMENT TO INTERACTIVE 31, THE $"-3 GOES THROUGH ALL FIVE STEPS WHILE YOU WAIT FOR ITS RESPONSE 4HE $"-3 HAS LITTLE CHOICE IN THE MATTERIT DOESNT KNOW WHICH STATEMENT YOU ARE GOING TO TYPE UNTIL YOU TYPE IT SO NONE OF THE PROCESSING CAN BE DONE AHEAD OF TIME (OWEVER SOME PRODUCTS SUCH AS /RACLE AUTOMATICALLY MAINTAIN A 31, CACHE THAT STORES RECENTLY EXECUTED STATEMENTS IN MEMORY )F THE SAME STATEMENT IS SUBMITTED TO THE 31, ENGINE ADDITIONAL TIMES THE PARSE STEP AND IN SOME CASES THE BIND STEP CAN BE SKIPPED &URTHERMORE IF RESULTS OF A PREVIOUS IDENTICAL QUERY ARE STILL IN MEMORY REEXECUTION OF THE QUERY MAY NOT BE NECESSARY
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)N CONTRAST THE SITUATION IS QUITE DIFFERENT IN PROGRAMMATIC 31, 3OME OF THE EARLY STEPS CAN BE DONE AT COMPILE TIME WHEN THE PROGRAMMER IS DEVELOPING THE PROGRAM 4HIS LEAVES ONLY THE LATER STEPS TO BE DONE AT RUNTIME WHEN THE PROGRAM IS EXECUTED BY A USER 7HEN YOU USE PROGRAMMATIC 31, ALL $"-3 PRODUCTS TRY TO MOVE AS MUCH PROCESSING AS POSSIBLE TO COMPILE TIME BECAUSE ONCE THE FINAL VERSION OF THE PROGRAM IS DEVELOPED IT MAY BE EXECUTED THOUSANDS OF TIMES BY USERS IN A PRODUCTION APPLICATION )N PARTICULAR THE GOAL IS TO MOVE OPTIMIZATION TO COMPILE TIME IF AT ALL POSSIBLE
%MBEDDEDõ31,õ#ONCEPTS 4HE CENTRAL IDEA OF EMBEDDED 31, IS TO BLEND 31, LANGUAGE STATEMENTS DIRECTLY INTO A PROGRAM WRITTEN IN A HOST PROGRAMMING LANGUAGE SUCH AS # *AVA 0ASCAL #/"/, &/242!. 0,) OR !SSEMBLER %MBEDDED 31, USES THE FOLLOWING TECHNIQUES TO EMBED THE 31, STATEMENTS s 31, STATEMENTS ARE INTERMIXED WITH STATEMENTS OF THE HOST LANGUAGE IN THE SOURCE PROGRAM 4HIS EMBEDDED 31, SOURCE PROGRAM IS SUBMITTED TO A 31, PRECOMPILER OR IN THE CASE OF *AVA A PREPROCESSOR WHICH PROCESSES THE 31, STATEMENTS s 6ARIABLES OF THE HOST PROGRAMMING LANGUAGE CAN BE REFERENCED IN THE EMBEDDED 31, STATEMENTS ALLOWING VALUES CALCULATED BY THE PROGRAM TO BE USED BY THE 31, STATEMENTS s 0ROGRAM LANGUAGE VARIABLES ARE ALSO USED BY THE EMBEDDED 31, STATEMENTS TO RECEIVE THE RESULTS OF 31, QUERIES ALLOWING THE PROGRAM TO USE AND PROCESS THE RETRIEVED VALUES s 3PECIAL PROGRAM VARIABLES ARE USED TO ASSIGN .5,, VALUES TO DATABASE COLUMNS AND TO SUPPORT THE RETRIEVAL OF .5,, VALUES FROM THE DATABASE s 3EVERAL NEW 31, STATEMENTS THAT ARE UNIQUE TO EMBEDDED 31, ARE ADDED TO THE INTERACTIVE 31, LANGUAGE TO PROVIDE FOR ROW BY ROW PROCESSING OF QUERY RESULTS
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&IGURE SHOWS A SIMPLE EMBEDDED 31, PROGRAM WRITTEN IN # 4HE PROGRAM ILLUSTRATES MANY BUT NOT ALL OF THE EMBEDDED 31, TECHNIQUES 4HE PROGRAM PROMPTS THE USER FOR AN OFFICE NUMBER RETRIEVES THE CITY REGION SALES AND TARGET FOR THE OFFICE AND DISPLAYS THEM ON THE SCREEN $ONT WORRY IF THE PROGRAM APPEARS STRANGE OR IF YOU CANT UNDERSTAND ALL OF THE STATEMENTS THAT IT CONTAINS BEFORE READING THE REST OF THIS CHAPTER /NE OF THE DISADVANTAGES OF THE EMBEDDED 31, APPROACH IS THAT THE SOURCE CODE FOR A PROGRAM BECOMES AN IMPURE BLEND OF TWO DIFFERENT LANGUAGES MAKING THE PROGRAM HARD TO UNDERSTAND WITHOUT TRAINING IN BOTH 31, AND THE PROGRAMMING LANGUAGE !NOTHER DISADVANTAGE IS THAT EMBEDDED 31, USES 31, LANGUAGE CONSTRUCTS NOT USED IN INTERACTIVE 31, SUCH AS THE 7(%.%6%2 STATEMENT AND THE ).4/ CLAUSE OF THE 3%,%#4 STATEMENTBOTH USED IN THIS PROGRAM
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FIGURE ARE ACTUALLY THOSE USED BY THE )"- MAINFRAME DATABASES $" AND 31,$3 BUT ALL PRODUCTS THAT SUPPORT EMBEDDED 31, USE A SIMILAR PROCESS 4HE EMBEDDED 31, SOURCE PROGRAM IS SUBMITTED TO THE 31, PRECOMPILER A PROGRAMMING TOOL 4HE PRECOMPILER SCANS THE PROGRAM FINDS THE EMBEDDED 31, STATEMENTS AND PROCESSES THEM ! DIFFERENT PRECOMPILER IS REQUIRED FOR EACH PROGRAMMING LANGUAGE SUPPORTED BY THE $"-3 #OMMERCIAL 31, PRODUCTS TYPICALLY OFFER PRECOMPILERS FOR ONE OR MORE LANGUAGES INCLUDING # 0ASCAL #/"/, &/242!. !DA 0,) 20' AND VARIOUS ASSEMBLY LANGUAGES
4HE PRECOMPILER PRODUCES TWO FILES AS ITS OUTPUT 4HE FIRST FILE IS THE SOURCE PROGRAM STRIPPED OF ITS EMBEDDED 31, STATEMENTS )N THEIR PLACE THE PRECOMPILER SUBSTITUTES CALLS TO THE PRIVATE $"-3 ROUTINES THAT PROVIDE THE RUNTIME LINK BETWEEN THE PROGRAM AND THE $"-3 4YPICALLY THE NAMES AND CALLING SEQUENCES OF THESE ROUTINES ARE KNOWN ONLY TO THE PRECOMPILER AND THE $"-3 THEY ARE NOT A PUBLIC INTERFACE TO THE $"-3 4HE SECOND FILE IS A COPY OF ALL THE EMBEDDED 31, STATEMENTS USED IN THE PROGRAM 4HIS FILE IS SOMETIMES CALLED A DATABASE REQUEST MODULE $"2-
4HE SOURCE FILE OUTPUT FROM THE PRECOMPILER IS SUBMITTED TO THE STANDARD COMPILER FOR THE HOST PROGRAMMING LANGUAGE SUCH AS A # OR #/"/, COMPILER 4HE COMPILER PROCESSES THE SOURCE CODE AND PRODUCES OBJECT CODE AS ITS OUTPUT .OTE THAT THIS STEP HAS NOTHING IN PARTICULAR TO DO WITH THE $"-3 OR WITH 31,
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4HE LINKER ACCEPTS THE OBJECT MODULES GENERATED BY THE COMPILER LINKS THEM WITH VARIOUS LIBRARY ROUTINES AND PRODUCES AN EXECUTABLE PROGRAM 4HE LIBRARY ROUTINES LINKED INTO THE EXECUTABLE PROGRAM INCLUDE THE PRIVATE $"-3 ROUTINES DESCRIBED IN 3TEP
4HE DATABASE REQUEST MODULE GENERATED BY THE PRECOMPILER IS SUBMITTED TO A SPECIAL ").$ PROGRAM 4HIS PROGRAM EXAMINES THE 31, STATEMENTS PARSES VALIDATES AND OPTIMIZES THEM AND PRODUCES AN APPLICATION PLAN FOR EACH STATEMENT 4HE RESULT IS A COMBINED APPLICATION PLAN FOR THE ENTIRE PROGRAM REPRESENTING A $"-3 EXECUTABLE VERSION OF ITS EMBEDDED 31, STATEMENTS 4HE ").$ PROGRAM STORES THE PLAN IN THE DATABASE USUALLY ASSIGNING IT THE NAME OF THE APPLICATION PROGRAM THAT CREATED IT
31,* PROGRAMS FOLLOW A SIMPLER PROCESS LARGELY BECAUSE *AVA IS NOT LINKED PRIOR TO EXECUTION
4HE *AVA PROGRAM WITH EMBEDDED 31, IS SUBMITTED TO AN 31,* PREPROCESSOR ALSO CALLED A TRANSLATOR 4HE TRANSLATOR ALSO WRITTEN IN *AVA PRODUCES A JAVA FILE WHICH CONTAINS THE *AVA SOURCE PROGRAM WITH THE 31, STATEMENTS TRANSLATED INTO STANDARD *AVA CODE USUALLY IN THE FORM OF *$"# !0) CALLS AND ONE OR MORE 31,* PROFILES WHICH CONTAIN INFORMATION ABOUT THE 31, OPERATIONS
4HE *AVA COMPILER PROCESSES THE JAVA FILE AND PRODUCES CLASS FILES
4HE LINK AND BIND STEPS ARE NOT REQUIRED
! RUNTIME COMPONENT IS INVOKED AUTOMATICALLY EACH TIME THE APPLICATION IS RUN )T USES THE 31,* PROFILES TO ASSIST IN COMPLETING THE 31, COMMANDS INCLUDED IN THE ORIGINAL SOURCE PROGRAM
4HE PROGRAM DEVELOPMENT STEPS IN &IGURE CORRELATE WITH THE $"-3 STATEMENT PROCESSING STEPS IN &IGURE )N PARTICULAR THE PRECOMPILER USUALLY HANDLES STATEMENT PARSING THE FIRST STEP AND THE ").$ UTILITY HANDLES VERIFICATION OPTIMIZATION AND PLAN GENERATION RESPECTIVELY THE SECOND THIRD AND FOURTH STEPS 4HUS THE FIRST FOUR STEPS OF &IGURE ALL TAKE PLACE AT COMPILE TIME WHEN YOU USE EMBEDDED 31, /NLY THE FIFTH STEP THE ACTUAL EXECUTION OF THE APPLICATION PLAN REMAINS TO BE DONE AT RUNTIME 4HE EMBEDDED 31, DEVELOPMENT PROCESS TURNS THE ORIGINAL EMBEDDED 31, SOURCE PROGRAM INTO TWO EXECUTABLE PARTS s !N EXECUTABLE PROGRAM 3TORED IN A FILE ON THE COMPUTER IN THE SAME FORMAT AS ANY EXECUTABLE PROGRAM s !N EXECUTABLE APPLICATION PLAN 3TORED WITHIN THE DATABASE IN THE FORMAT EXPECTED BY THE $"-3 4HE EMBEDDED 31, DEVELOPMENT CYCLE MAY SEEM CUMBERSOME AND IT IS MORE AWKWARD THAN DEVELOPING A STANDARD # OR #/"/, PROGRAM )N MOST CASES ALL OF THE STEPS IN &IGURE ARE AUTOMATED BY A SINGLE COMMAND PROCEDURE SO THE INDIVIDUAL STEPS ARE
#HAPTERçç
%MBEDDEDç31,ç
MADE INVISIBLE TO THE APPLICATION PROGRAMMER 4HE PROCESS DOES HAVE SEVERAL MAJOR ADVANTAGES FROM A $"-3 POINT OF VIEW AS FOLLOWS s 4HE BLENDING OF 31, AND PROGRAMMING LANGUAGE STATEMENTS IN THE EMBEDDED 31, SOURCE PROGRAM IS AN EFFECTIVE WAY TO MERGE THE TWO LANGUAGES 4HE HOST PROGRAMMING LANGUAGE PROVIDES FLOW OF CONTROL VARIABLES BLOCK STRUCTURE AND INPUTOUTPUT FUNCTIONS 31, HANDLES DATABASE ACCESS AND DOES NOT HAVE TO PROVIDE THESE OTHER CONSTRUCTS s 4HE USE OF A PRECOMPILER MEANS THAT THE COMPUTE INTENSIVE WORK OF PARSING AND OPTIMIZATION CAN TAKE PLACE DURING THE DEVELOPMENT CYCLE 4HE RESULTING EXECUTABLE PROGRAM IS VERY EFFICIENT IN ITS USE OF #05 RESOURCES s 4HE DATABASE REQUEST MODULE PRODUCED BY THE PRECOMPILER PROVIDES PORTABILITY OF APPLICATIONS !N APPLICATION PROGRAM CAN BE WRITTEN AND TESTED ON ONE SYSTEM AND THEN ITS EXECUTABLE PROGRAM AND $"2- CAN BE MOVED TO ANOTHER SYSTEM !FTER THE ").$ PROGRAM ON THE NEW SYSTEM CREATES THE APPLICATION PLAN AND INSTALLS IT IN THE DATABASE THE APPLICATION PROGRAM CAN USE IT WITHOUT BEING RECOMPILED ITSELF s 4HE PROGRAMS ACTUAL RUNTIME INTERFACE TO THE PRIVATE $"-3 ROUTINES IS COMPLETELY HIDDEN FROM THE APPLICATION PROGRAMMER 4HE PROGRAMMER WORKS WITH EMBEDDED 31, AT THE SOURCE CODE LEVEL AND DOES NOT HAVE TO WORRY ABOUT OTHER MORE COMPLEX INTERFACES
2UNNINGõANõ%MBEDDEDõ31,õ0ROGRAM 2ECALL FROM &IGURE THAT THE EMBEDDED 31, DEVELOPMENT PROCESS PRODUCES TWO EXECUTABLE COMPONENTS THE EXECUTABLE PROGRAM ITSELF AND THE PROGRAMS APPLICATION PLAN STORED IN THE DATABASE 7HEN YOU RUN AN EMBEDDED 31, PROGRAM THESE TWO COMPONENTS ARE BROUGHT TOGETHER TO DO THE WORK OF THE APPLICATION 7HEN YOU ASK THE COMPUTER SYSTEM TO RUN THE PROGRAM THE COMPUTER LOADS THE EXECUTABLE PROGRAM IN THE USUAL WAY AND BEGINS TO EXECUTE ITS INSTRUCTIONS
/NE OF THE FIRST CALLS GENERATED BY THE PRECOMPILER IS A CALL TO A $"-3 ROUTINE THAT FINDS AND LOADS THE APPLICATION PLAN FOR THE PROGRAM
&OR EACH EMBEDDED 31, STATEMENT THE PROGRAM CALLS ONE OR MORE PRIVATE $"-3 ROUTINES REQUESTING EXECUTION OF THE CORRESPONDING STATEMENT IN THE APPLICATION PLAN 4HE $"-3 FINDS THE STATEMENT EXECUTES THAT PART OF THE PLAN AND THEN RETURNS CONTROL TO THE PROGRAM
%XECUTION CONTINUES IN THIS WAY WITH THE EXECUTABLE PROGRAM AND THE $"-3 COOPERATING TO CARRY OUT THE TASK DEFINED BY THE ORIGINAL EMBEDDED 31, SOURCE PROGRAM
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2UNTIMEõ3ECURITY 7HEN YOU USE INTERACTIVE 31, THE $"-3 ENFORCES ITS SECURITY BASED ON THE USER ID YOU SUPPLY TO THE INTERACTIVE 31, PROGRAM 9OU CAN TYPE ANY 31, STATEMENT YOU WANT BUT THE PRIVILEGES GRANTED TO YOUR USER ID DETERMINE WHETHER THE $"-3 WILL OR WILL NOT EXECUTE THE STATEMENT YOU TYPE 7HEN YOU RUN A PROGRAM THAT USES EMBEDDED 31, THERE ARE TWO USER IDS TO CONSIDER s 4HE USER ID OF THE PERSON WHO DEVELOPED THE PROGRAM OR MORE SPECIFICALLY THE PERSON WHO RAN THE ").$ PROGRAM TO CREATE THE APPLICATION PLAN s 4HE USER ID OF THE PERSON WHO IS NOW EXECUTING THE PROGRAM AND THE CORRESPONDING APPLICATION PLAN )T MAY SEEM STRANGE TO CONSIDER THE USER ID OF THE PERSON WHO RAN THE ").$ PROGRAM OR MORE GENERALLY THE PERSON WHO DEVELOPED THE APPLICATION PROGRAM OR INSTALLED IT ON THE COMPUTER SYSTEM BUT $" AND SEVERAL OTHER COMMERCIAL 31, PRODUCTS USE BOTH USER IDS IN THEIR SECURITY SCHEME 4O UNDERSTAND HOW THE SECURITY SCHEME WORKS SUPPOSE THAT USER */% RUNS THE /2$-!).4 ORDER MAINTENANCE PROGRAM WHICH UPDATES THE /2$%23 3!,%3 AND /&&)#%3 TABLES 4HE APPLICATION PLAN FOR THE /2$-!).4 PROGRAM WAS ORIGINALLY BOUND BY USER ID /0!$-). WHICH BELONGS TO THE ORDER PROCESSING ADMINISTRATOR )N THE $" SCHEME EACH APPLICATION PLAN IS A DATABASE OBJECT PROTECTED BY $" SECURITY 4O EXECUTE A PLAN */% MUST HAVE THE %8%#54% PRIVILEGE FOR IT )F HE DOES NOT EXECUTION FAILS IMMEDIATELY !S THE /2$-!).4 PROGRAM EXECUTES ITS EMBEDDED ).3%24 50$!4% AND $%,%4% STATEMENTS UPDATE THE DATABASE 4HE PRIVILEGES OF THE /0!$-). USER DETERMINE WHETHER THE PLAN WILL BE ALLOWED TO PERFORM THESE UPDATES .OTE THAT THE PLAN MAY UPDATE THE TABLES EVEN IF */% DOES NOT HAVE THE REQUIRED PRIVILEGES (OWEVER THE UPDATES THAT CAN BE PERFORMED ARE ONLY THOSE THAT HAVE BEEN EXPLICITLY CODED INTO THE EMBEDDED 31, STATEMENTS OF THE PROGRAM 4HUS $" PROVIDES VERY FINE CONTROL OVER DATABASE SECURITY 4HE PRIVILEGES OF USERS TO ACCESS TABLES CAN BE VERY LIMITED WITHOUT DIMINISHING THEIR ABILITY TO USE CANNED PROGRAMS .OT ALL $"-3 PRODUCTS PROVIDE SECURITY PROTECTION FOR APPLICATION PLANS &OR THOSE THAT DO NOT THE PRIVILEGES OF THE USER EXECUTING AN EMBEDDED 31, PROGRAM DETERMINE THE PRIVILEGES OF THE PROGRAMS APPLICATION PLAN 5NDER THIS SCHEME THE USER MUST HAVE PRIVILEGES TO PERFORM ALL OF THE ACTIONS PERFORMED BY THE PLAN OR THE PROGRAM WILL FAIL )F THE USER IS NOT TO HAVE THESE SAME PERMISSIONS IN AN INTERACTIVE 31, ENVIRONMENT ACCESS TO THE INTERACTIVE 31, PROGRAM ITSELF MUST BE RESTRICTED WHICH IS A DISADVANTAGE OF THIS APPROACH
!UTOMATICõ2EBINDING .OTE THAT AN APPLICATION PLAN IS OPTIMIZED FOR THE DATABASE STRUCTURE AS IT EXISTS AT THE TIME THE PLAN IS PLACED IN THE DATABASE BY THE ").$ PROGRAM )F THE STRUCTURE CHANGES LATER FOR EXAMPLE IF AN INDEX IS DROPPED OR A COLUMN IS DELETED FROM A TABLE ANY APPLICATION PLAN THAT REFERENCES THE CHANGED STRUCTURES MAY BECOME INVALID 4O HANDLE THIS SITUATION THE $"-3 USUALLY STORES ALONG WITH THE APPLICATION PLAN A COPY OF THE ORIGINAL 31, STATEMENTS THAT PRODUCED IT 4HE $"-3 ALSO KEEPS TRACK OF ALL THE DATABASE OBJECTS UPON WHICH EACH APPLICATION PLAN DEPENDS )F ANY OF THESE OBJECTS ARE MODIFIED BY A $$, STATEMENT THE $"-3 CAN FIND THE PLANS THAT DEPEND ON IT AND AUTOMATICALLY MARK THOSE PLANS AS INVALID 4HE NEXT TIME THE PROGRAM TRIES TO USE THE PLAN THE $"-3 CAN DETECT THE SITUATION IN MOST CASES IT WILL AUTOMATICALLY REBIND THE STATEMENTS TO PRODUCE A NEW BIND IMAGE "ECAUSE THE $"-3 HAS
#HAPTERçç
%MBEDDEDç31,ç
MAINTAINED A GREAT DEAL OF INFORMATION ABOUT THE APPLICATION PLAN IT CAN MAKE THIS AUTOMATIC REBINDING COMPLETELY TRANSPARENT TO THE APPLICATION PROGRAM (OWEVER A 31, STATEMENT MAY TAKE MUCH LONGER TO EXECUTE WHEN ITS PLAN IS REBOUND THAN WHEN THE PLAN IS SIMPLY EXECUTED !LTHOUGH THE $"-3 CAN AUTOMATICALLY REBIND A PLAN WHEN ONE OF THE STRUCTURES UPON WHICH IT DEPENDS IS CHANGED THE $"-3 WILL USUALLY NOT AUTOMATICALLY DETECT CHANGES IN THE DATABASE THAT MAY MAKE A BETTER PLAN POSSIBLE &OR EXAMPLE SUPPOSE A PLAN USES A SEQUENTIAL SCAN OF A TABLE TO LOCATE PARTICULAR ROWS BECAUSE NO APPROPRIATE INDEX EXISTED WHEN IT WAS BOUND )TS POSSIBLE THAT A SUBSEQUENT #2%!4% ).$%8 STATEMENT WILL CREATE AN APPROPRIATE INDEX 4O TAKE ADVANTAGE OF THE NEW STRUCTURE YOU MUST EXPLICITLY RUN THE ").$ PROGRAM TO REBIND THE PLAN
3IMPLEõ%MBEDDEDõ31,õ3TATEMENTS 4HE SIMPLEST 31, STATEMENTS TO EMBED IN A PROGRAM ARE THOSE THAT ARE SELF CONTAINED AND DO NOT PRODUCE ANY QUERY RESULTS &OR EXAMPLE CONSIDER THIS INTERACTIVE 31, STATEMENT $ELETE ALL SALESPEOPLE WITH SALES UNDER $%,%4% &2/- 3!,%32%03 7(%2% 3!,%3
&IGURES AND SHOW THREE PROGRAMS USING EMBEDDED 31, THAT PERFORM THE SAME TASK AS THIS INTERACTIVE 31, STATEMENT 4HE PROGRAM IN &IGURE IS WRITTEN IN #
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THE PROGRAM IN &IGURE IS WRITTEN IN #/"/, AND THE PROGRAM IN &IGURE IS WRITTEN IN &/242!. !LTHOUGH THE PROGRAMS ARE EXTREMELY SIMPLE THEY ILLUSTRATE THE MOST BASIC FEATURES OF EMBEDDED 31, s 4HE EMBEDDED 31, STATEMENTS APPEAR IN THE MIDST OF HOST PROGRAMMING LANGUAGE STATEMENTS )T USUALLY DOESNT MATTER WHETHER THE 31, STATEMENT IS WRITTEN IN UPPERCASE OR LOWERCASE THE MOST COMMON PRACTICE IS TO FOLLOW THE STYLE OF THE HOST LANGUAGE s %VERY EMBEDDED 31, STATEMENT BEGINS WITH AN INTRODUCER THAT FLAGS IT AS A 31, STATEMENT 4HE )"- 31, PRODUCTS USE THE INTRODUCER %8%# 31, FOR MOST HOST LANGUAGES AND THE !.3))3/ 31, STANDARD SPECIFIES IT AS WELL 3OME EMBEDDED 31, PRODUCTS STILL SUPPORT OTHER INTRODUCERS FOR BACKWARD COMPATIBILITY WITH THEIR EARLIER VERSIONS s )F AN EMBEDDED 31, STATEMENT EXTENDS OVER MULTIPLE LINES THE HOST LANGUAGE STRATEGY FOR STATEMENT CONTINUATION IS USED &OR #/"/, 0,) AND # PROGRAMS NO SPECIAL CONTINUATION CHARACTER IS REQUIRED &OR &/242!. PROGRAMS THE SECOND AND SUBSEQUENT LINES OF THE STATEMENT MUST HAVE A CONTINUATION CHARACTER IN COLUMN
#HAPTERçç
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s %VERY EMBEDDED 31, STATEMENT ENDS WITH A TERMINATOR THAT SIGNALS THE END OF THE 31, STATEMENT 4HE TERMINATOR VARIES WITH THE STYLE OF THE HOST LANGUAGE )N #/"/, THE TERMINATOR IS THE STRING %.$ %8%# WHICH ENDS IN A PERIOD LIKE OTHER #/"/, STATEMENTS &OR 0,) AND # THE TERMINATOR IS A SEMICOLON WHICH IS ALSO THE STATEMENT TERMINATION CHARACTER IN THOSE LANGUAGES )N &/242!. THE EMBEDDED 31, STATEMENT ENDS WHEN NO MORE CONTINUATION LINES ARE INDICATED
$ECLARINGõ4ABLES )N THE )"- 31, PRODUCTS THE EMBEDDED $%#,!2% 4!",% STATEMENT SHOWN IN &IGURE DECLARES A TABLE THAT WILL BE REFERENCED BY ONE OR MORE EMBEDDED 31, STATEMENTS IN YOUR PROGRAM 4HIS IS AN OPTIONAL STATEMENT THAT AIDS THE PRECOMPILER IN ITS TASK OF PARSING AND VALIDATING THE EMBEDDED 31, STATEMENTS "Y USING THE $%#,!2% 4!",% STATEMENT YOUR PROGRAM EXPLICITLY SPECIFIES ITS ASSUMPTIONS ABOUT THE COLUMNS IN THE TABLE AND THEIR DATA TYPES AND SIZES 4HE PRECOMPILER CHECKS THE TABLE AND COLUMN REFERENCES IN YOUR PROGRAM TO MAKE SURE THEY CONFORM TO YOUR TABLE DECLARATION
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4HE EMBEDDING TECHNIQUE SHOWN IN THE THREE FIGURES WORKS FOR ANY 31, STATEMENT THAT A DOES NOT DEPEND ON THE VALUES OF HOST LANGUAGE VARIABLES FOR ITS EXECUTION AND B DOES NOT RETRIEVE DATA FROM THE DATABASE &OR EXAMPLE THE # PROGRAM IN &IGURE CREATES A NEW 2%')/.3 TABLE AND INSERTS TWO ROWS INTO IT USING EXACTLY THE SAME EMBEDDED 31, FEATURES AS THE PROGRAM IN &IGURE &OR CONSISTENCY ALL OF THE REMAINING PROGRAM EXAMPLES IN THE BOOK WILL USE THE # PROGRAMMING LANGUAGE EXCEPT WHEN A PARTICULAR HOST LANGUAGE FEATURE IS BEING ILLUSTRATED
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#HAPTERçç
%MBEDDEDç31,ç
%RRORõ(ANDLING 7HEN YOU TYPE AN INTERACTIVE 31, STATEMENT THAT CAUSES AN ERROR THE INTERACTIVE 31, PROGRAM DISPLAYS AN ERROR MESSAGE ABORTS THE STATEMENT AND PROMPTS YOU TO TYPE A NEW STATEMENT )N EMBEDDED 31, ERROR HANDLING BECOMES THE RESPONSIBILITY OF THE APPLICATION PROGRAM !CTUALLY EMBEDDED 31, STATEMENTS CAN PRODUCE TWO DISTINCT TYPES OF ERRORS s #OMPILE TIME ERRORS -ISPLACED COMMAS MISSPELLED 31, KEYWORDS AND SIMILAR ERRORS IN EMBEDDED 31, STATEMENTS ARE DETECTED BY THE 31, PRECOMPILER AND REPORTED TO THE PROGRAMMER 4HE PROGRAMMER CAN FIX THE ERRORS AND RECOMPILE THE APPLICATION PROGRAM s 2UNTIME ERRORS !N ATTEMPT TO INSERT AN INVALID DATA VALUE OR LACK OF PERMISSION TO UPDATE A TABLE CAN BE DETECTED ONLY AT RUNTIME %RRORS SUCH AS THESE MUST BE DETECTED AND HANDLED BY THE APPLICATION PROGRAM )N EMBEDDED 31, PROGRAMS THE $"-3 REPORTS RUNTIME ERRORS TO THE APPLICATION PROGRAM THROUGH A RETURNED ERROR CODE )F AN ERROR IS DETECTED A FURTHER DESCRIPTION OF THE ERROR AND OTHER INFORMATION ABOUT THE STATEMENT JUST EXECUTED IS AVAILABLE THROUGH ADDITIONAL DIAGNOSTIC INFORMATION 4HE EARLIEST )"- EMBEDDED 31, IMPLEMENTATIONS DEFINED AN ERROR REPORTING MECHANISM THAT WAS ADOPTED WITH VARIATIONS BY MOST OF THE MAJOR $"-3 VENDORS 4HE CENTRAL PART OF THIS SCHEMEAN ERROR STATUS VARIABLE NAMED 31,#/$%WAS ALSO DEFINED IN THE ORIGINAL !.3))3/ 31, STANDARD 4HE 31, STANDARD PUBLISHED IN DEFINED AN ENTIRELY NEW PARALLEL ERROR REPORTING MECHANISM BUILT AROUND AN ERROR STATUS VARIABLE NAMED 31,34!4% 4HESE MECHANISMS ARE DESCRIBED IN THE NEXT TWO SECTIONS
%RRORõ(ANDLINGõWITHõ31,#/
%$s ! 31,#/$% OF ZERO INDICATES SUCCESSFUL COMPLETION OF THE STATEMENT WITHOUT ANY ERRORS OR WARNINGS s ! NEGATIVE 31,#/$% VALUE INDICATES A SERIOUS ERROR THAT PREVENTED THE STATEMENT FROM EXECUTING CORRECTLY &OR EXAMPLE AN ATTEMPT TO UPDATE A READ ONLY VIEW WOULD PRODUCE A NEGATIVE 31,#/$% VALUE ! SEPARATE NEGATIVE VALUE IS ASSIGNED TO EACH RUNTIME ERROR THAT CAN OCCUR
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5NDER THIS SCHEME PIONEERED BY THE EARLIEST )"- PRODUCTS THE $"-3 COMMUNICATES STATUS INFORMATION TO THE EMBEDDED 31, PROGRAM THROUGH AN AREA OF PROGRAM STORAGE CALLED THE 31, #OMMUNICATIONS !REA 31,#! 4HE 31,#! IS A DATA STRUCTURE THAT CONTAINS ERROR VARIABLES AND STATUS INDICATORS "Y EXAMINING THE 31,#! THE APPLICATION PROGRAM CAN DETERMINE THE SUCCESS OR FAILURE OF ITS EMBEDDED 31, STATEMENTS AND ACT ACCORDINGLY .OTICE THAT IN &IGURES AND THE FIRST EMBEDDED 31, STATEMENT IN THE PROGRAM IS ).#,5$% 31,#! 4HIS STATEMENT TELLS THE 31, PRECOMPILER TO INCLUDE A 31, #OMMUNICATIONS !REA IN THIS PROGRAM 4HE SPECIFIC CONTENTS OF THE 31,#! VARY SLIGHTLY FROM ONE BRAND OF $"-3 TO ANOTHER BUT THE 31,#! ALWAYS PROVIDES THE SAME TYPE OF INFORMATION &IGURE SHOWS THE # LANGUAGE DEFINITION OF THE 31,#! USED BY THE )"- DATABASES 4HE MOST IMPORTANT PART OF THE 31,#! THE 31,#/$% VARIABLE IS SUPPORTED BY ALL OF THE MAJOR EMBEDDED 31, PRODUCTS AND WAS SPECIFIED BY THE !.3))3/ 31, STANDARD !S THE $"-3 EXECUTES EACH EMBEDDED 31, STATEMENT IT SETS THE VALUE OF THE VARIABLE 31,#/$% IN THE 31,#! TO INDICATE THE COMPLETION STATUS OF THE STATEMENT
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s ! POSITIVE 31,#/$% VALUE INDICATES A WARNING CONDITION &OR EXAMPLE TRUNCATION OR ROUNDING OF A DATA ITEM RETRIEVED BY THE PROGRAM WOULD PRODUCE A WARNING ! SEPARATE POSITIVE VALUE IS ASSIGNED TO EACH RUNTIME WARNING THAT CAN OCCUR 4HE MOST COMMON WARNING WITH A VALUE OF IN MOST IMPLEMENTATIONS AND IN THE 31, STANDARD IS THE OUT OF DATA WARNING RETURNED WHEN A PROGRAM TRIES TO RETRIEVE THE NEXT ROW OF QUERY RESULTS AND NO MORE ROWS ARE LEFT TO RETRIEVE "ECAUSE EVERY EXECUTABLE EMBEDDED 31, STATEMENT CAN POTENTIALLY GENERATE AN ERROR A WELL WRITTEN PROGRAM WILL CHECK THE 31,#/$% VALUE AFTER EVERY EXECUTABLE EMBEDDED 31, STATEMENT &IGURE SHOWS A # PROGRAM EXCERPT THAT CHECKS THE 31,#/$% VALUE &IGURE SHOWS A SIMILAR EXCERPT FROM A #/"/, PROGRAM
%RRORõ(ANDLINGõWITHõ31,34!4% "Y THE TIME THE 31, STANDARD WAS BEING WRITTEN VIRTUALLY ALL COMMERCIAL 31, PRODUCTS WERE USING THE 31,#/$% VARIABLE TO REPORT ERROR CONDITIONS IN AN EMBEDDED 31, PROGRAM (OWEVER THE DIFFERENT PRODUCTS USED DIFFERENT ERROR NUMBERS TO REPORT THE SAME OR SIMILAR
#HAPTERçç
%MBEDDEDç31,ç
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ERROR CONDITIONS &URTHER BECAUSE OF THE SIGNIFICANT DIFFERENCES AMONG 31, IMPLEMENTATIONS PERMITTED BY THE 31, STANDARD CONSIDERABLE DIFFERENCES IN THE ERRORS COULD OCCUR FROM ONE IMPLEMENTATION TO ANOTHER &INALLY THE DEFINITION OF THE 31,#! VARIED IN SIGNIFICANT WAYS FROM ONE $"-3 BRAND TO ANOTHER AND ALL OF THE MAJOR BRANDS HAD A LARGE INSTALLED BASE OF APPLICATIONS THAT WOULD BE BROKEN BY ANY CHANGE TO THEIR 31,#! STRUCTURE )NSTEAD OF TACKLING THE IMPOSSIBLE TASK OF GETTING ALL OF THE $"-3 VENDORS TO AGREE TO CHANGE THEIR 31,#/$% VALUES TO SOME STANDARD THE WRITERS OF THE 31, STANDARD TOOK A DIFFERENT APPROACH 4HEY INCLUDED THE 31,#/$% ERROR VALUE BUT IDENTIFIED IT AS A DEPRECATED FEATURE MEANING THAT IT WAS CONSIDERED OBSOLETE AND WOULD BE REMOVED FROM THE STANDARD AT SOME FUTURE TIME 4O TAKE ITS PLACE THEY INTRODUCED A NEW ERROR VARIABLE CALLED 31,34!4% 4HE STANDARD ALSO SPECIFIES IN DETAIL THE ERROR CONDITIONS THAT CAN BE REPORTED THROUGH THE 31,34!4% VARIABLE AND THE ERROR CODE ASSIGNED TO EACH ERROR 4O CONFORM TO THE 31, STANDARD A 31, PRODUCT MUST REPORT ERRORS USING BOTH THE 31,#/$% AND 31,34!4% ERROR VARIABLES )N THIS WAY EXISTING PROGRAMS THAT USE 31,#/$% WILL STILL FUNCTION BUT NEW PROGRAMS CAN BE WRITTEN TO USE THE STANDARDIZED 31,34!4% ERROR CODES 4HE 31,34!4% VARIABLE CONSISTS OF TWO PARTS s ! TWO CHARACTER ERROR CLASS THAT IDENTIFIES THE GENERAL CLASSIFICATION OF THE ERROR SUCH AS A CONNECTION ERROR AN INVALID DATA ERROR OR A WARNING s ! THREE CHARACTER ERROR SUBCLASS THAT IDENTIFIES A SPECIFIC TYPE OF ERROR WITHIN A GENERAL ERROR CLASS &OR EXAMPLE WITHIN THE INVALID DATA CLASS THE ERROR SUBCLASS MIGHT IDENTIFY A DIVIDE BY ZERO ERROR AN INVALID NUMERIC VALUE ERROR OR AN INVALID DATETIME DATA ERROR %RRORS SPECIFIED IN THE 31, STANDARD HAVE AN ERROR CLASS CODE THAT BEGINS WITH A DIGIT FROM ZERO TO FOUR INCLUSIVE OR A LETTER BETWEEN ! AND ( INCLUSIVE &OR EXAMPLE DATA ERRORS ARE INDICATED BY ERROR CLASS ! VIOLATION OF AN INTEGRITY CONSTRAINT SUCH AS A FOREIGN KEY DEFINITION IS INDICATED BY ERROR CLASS ! TRANSACTION ROLLBACK IS INDICATED BY ERROR CLASS 7ITHIN EACH ERROR CLASS THE STANDARD SUBCLASS CODES ALSO FOLLOW THE SAME INITIAL NUMBER LETTER RESTRICTIONS &OR EXAMPLE WITHIN ERROR CLASS TRANSACTION ROLLBACK THE SUBCLASS CODES ARE FOR SERIALIZATION FAILURE THAT IS YOUR PROGRAM WAS CHOSEN AS THE LOSER IN A DEADLOCK FOR AN INTEGRITY CONSTRAINT VIOLATION AND FOR ERRORS WHERE THE COMPLETION STATUS OF THE 31, STATEMENT IS UNKNOWN FOR EXAMPLE WHEN A NETWORK CONNECTION BREAKS OR A SERVER CRASHES BEFORE THE STATEMENT COMPLETES &IGURE SHOWS THE SAME # PROGRAM AS &IGURE BUT USES THE 31,34!4% VARIABLE FOR ERROR CHECKING INSTEAD OF 31,#/$% 4HE STANDARD SPECIFICALLY RESERVES ERROR CLASS CODES THAT BEGIN WITH DIGITS FROM FIVE TO NINE INCLUSIVE AND LETTERS BETWEEN ) AND : INCLUSIVE AS IMPLEMENTATION SPECIFIC ERRORS THAT ARE NOT STANDARDIZED 7HILE THIS ALLOWS DIFFERENCES AMONG $"-3 BRANDS TO CONTINUE ALL OF THE MOST COMMON ERRORS CAUSED BY 31, STATEMENTS ARE INCLUDED IN THE STANDARDIZED ERROR CLASS CODES !S COMMERCIAL $"-3 IMPLEMENTATIONS MOVE TO SUPPORT THE 31,34!4% VARIABLE ONE OF THE MOST TROUBLESOME INCOMPATIBILITIES BETWEEN DIFFERENT 31, PRODUCTS IS GRADUALLY BEING ELIMINATED 4HE 31, STANDARD PROVIDES ADDITIONAL ERROR AND DIAGNOSTICS INFORMATION THROUGH A NEW '%4 $)!'./34)#3 STATEMENT SHOWN IN &IGURE 4HE STATEMENT ALLOWS AN EMBEDDED 31, PROGRAM TO RETRIEVE ONE OR MORE ITEMS OF INFORMATION ABOUT THE 31, STATEMENT JUST EXECUTED OR ABOUT AN ERROR CONDITION THAT WAS JUST RAISED 3UPPORT FOR THE '%4 $)!'./34)#3 STATEMENT IS REQUIRED FOR )NTERMEDIATE 31, OR &ULL 31, CONFORMANCE TO THE
#HAPTERçç
%MBEDDEDç31,ç
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STANDARD BUT IS NOT REQUIRED OR ALLOWED IN %NTRY 31, &IGURE SHOWS A # PROGRAM EXCERPT LIKE THAT IN &IGURE EXTENDED TO INCLUDE THE '%4 $)!'./34)#3 STATEMENT
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s 7(%.%6%2 31,%22/2 TELLS THE PRECOMPILER TO GENERATE CODE TO HANDLE ERRORS NEGATIVE 31,#/$%S s 7(%.%6%2 31,7!2.).' TELLS THE PRECOMPILER TO GENERATE CODE TO HANDLE WARNINGS POSITIVE 31,#/$%S s 7(%.%6%2 ./4 &/5.$ TELLS THE PRECOMPILER TO GENERATE CODE THAT HANDLES A PARTICULAR WARNINGTHE WARNING GENERATED BY THE $"-3 WHEN YOUR PROGRAM TRIES TO RETRIEVE QUERY RESULTS WHEN NO MORE ARE REMAINING 4HIS USE OF THE 7(%.%6%2 STATEMENT IS SPECIFIC TO THE SINGLETON 3%,%#4 AND THE &%4#( STATEMENTS AND IS DESCRIBED IN THE SECTION h3INGLE 2OW 1UERIESv LATER IN THIS CHAPTER
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)T QUICKLY BECOMES TEDIOUS FOR A PROGRAMMER TO WRITE PROGRAMS THAT EXPLICITLY CHECK THE 31,#/$% VALUE AFTER EACH EMBEDDED 31, STATEMENT 4O SIMPLIFY ERROR HANDLING EMBEDDED 31, SUPPORTS THE 7(%.%6%2 STATEMENT SHOWN IN &IGURE 4HE 7(%.%6%2 STATEMENT IS A DIRECTIVE TO THE 31, PRECOMPILER NOT AN EXECUTABLE STATEMENT )T TELLS THE PRECOMPILER TO AUTOMATICALLY GENERATE ERROR HANDLING CODE FOLLOWING EVERY EXECUTABLE EMBEDDED 31, STATEMENT AND SPECIFIES WHAT THE GENERATED CODE SHOULD DO 9OU CAN USE THE 7(%.%6%2 STATEMENT TO TELL THE PRECOMPILER HOW TO HANDLE THREE DIFFERENT EXCEPTION CONDITIONS
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s 7(%.%6%2'/4/ TELLS THE PRECOMPILER TO GENERATE A BRANCH TO THE SPECIFIED LABEL WHICH MUST BE A STATEMENT LABEL OR STATEMENT NUMBER IN THE PROGRAM s 7(%.%6%2#/.4).5% TELLS THE PRECOMPILER TO LET THE PROGRAMS FLOW OF CONTROL PROCEED TO THE NEXT HOST LANGUAGE STATEMENT
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&OR ANY OF THESE THREE CONDITIONS YOU CAN TELL THE PRECOMPILER TO GENERATE CODE THAT TAKES ONE OF TWO ACTIONS
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4HE 7(%.%6%2 STATEMENT IS A DIRECTIVE TO THE PRECOMPILER AND ITS EFFECT CAN BE SUPERSEDED BY ANOTHER 7(%.%6%2 STATEMENT APPEARING LATER IN THE PROGRAM TEXT &IGURE SHOWS A PROGRAM EXCERPT WITH THREE 7(%.%6%2 STATEMENTS AND FOUR EXECUTABLE 31, STATEMENTS )N THIS PROGRAM AN ERROR IN EITHER OF THE TWO $%,%4% STATEMENTS RESULTS IN A BRANCH TO ERROR BECAUSE OF THE FIRST 7(%.%6%2 STATEMENT !N ERROR IN THE EMBEDDED 50$!4% STATEMENT FLOWS DIRECTLY INTO THE FOLLOWING STATEMENTS OF THE PROGRAM !N ERROR IN THE EMBEDDED ).3%24 STATEMENT RESULTS IN A BRANCH TO ERROR !S THIS EXAMPLE SHOWS THE MAIN USE OF THE 7(%.%6%2#/.4).5% FORM OF THE STATEMENT IS TO CANCEL THE EFFECT OF A PREVIOUS 7(%.%6%2 STATEMENT 4HE 7(%.%6%2 STATEMENT MAKES EMBEDDED 31, ERROR HANDLING MUCH SIMPLER AND IT IS MORE COMMON FOR AN APPLICATION PROGRAM TO USE IT THAN FOR IT TO CHECK 31,#/$% OR 31,34!4% DIRECTLY 2EMEMBER HOWEVER THAT AFTER A 7(%.%6%2'/4/ STATEMENT APPEARS
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THE PRECOMPILER WILL GENERATE A TEST AND A BRANCH TO THE SPECIFIED LABEL FOR EVERY EMBEDDED 31, STATEMENT THAT FOLLOWS IT 9OU MUST ARRANGE YOUR PROGRAM SO THAT THE SPECIFIED LABEL IS A VALID TARGET FOR BRANCHING FROM THESE EMBEDDED 31, STATEMENTS OR USE ANOTHER 7(%.%6%2 STATEMENT TO SPECIFY A DIFFERENT DESTINATION OR TO CANCEL THE EFFECTS OF THE 7(%.%6%2'/4/
5SINGõ(OSTõ6ARIABLES 4HE EMBEDDED 31, PROGRAMS IN THE PREVIOUS FIGURES DONT PROVIDE ANY REAL INTERACTION BETWEEN THE PROGRAMMING STATEMENTS AND THE EMBEDDED 31, STATEMENTS )N MOST APPLICATIONS YOU WILL WANT TO USE THE VALUE OF ONE OR MORE PROGRAM VARIABLES IN THE EMBEDDED 31, STATEMENTS &OR EXAMPLE SUPPOSE YOU WANTED TO WRITE A PROGRAM TO ADJUST ALL SALES QUOTAS UP OR DOWN BY SOME DOLLAR AMOUNT 4HE PROGRAM SHOULD PROMPT THE USER FOR THE AMOUNT AND THEN USE AN EMBEDDED 50$!4% STATEMENT TO CHANGE THE 15/4! COLUMN IN THE 3!,%32%03 TABLE %MBEDDED 31, SUPPORTS THIS CAPABILITY THROUGH THE USE OF HOST VARIABLES ! HOST VARIABLE IS A PROGRAM VARIABLE DECLARED IN THE HOST LANGUAGE FOR EXAMPLE A #/"/, OR # VARIABLE THAT IS REFERENCED IN AN EMBEDDED 31, STATEMENT 4O IDENTIFY THE HOST VARIABLE THE VARIABLE NAME IS PREFIXED BY A COLON WHEN IT APPEARS IN AN EMBEDDED 31, STATEMENT 4HE COLON ALLOWS THE PRECOMPILER TO DISTINGUISH EASILY BETWEEN HOST VARIABLES AND DATABASE OBJECTS SUCH AS TABLES OR COLUMNS THAT MAY HAVE THE SAME NAME &IGURE SHOWS A # PROGRAM THAT IMPLEMENTS THE QUOTA ADJUSTMENT APPLICATION USING A HOST VARIABLE 4HE PROGRAM PROMPTS THE USER FOR THE ADJUSTMENT AMOUNT AND STORES
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THE ENTERED VALUE IN THE VARIABLE NAMED AMOUNT 4HIS HOST VARIABLE IS REFERENCED IN THE EMBEDDED 50$!4% STATEMENT #ONCEPTUALLY WHEN THE 50$!4% STATEMENT IS EXECUTED THE VALUE OF THE AMOUNT VARIABLE IS OBTAINED AND THAT VALUE IS SUBSTITUTED FOR THE HOST VARIABLE IN THE 31, STATEMENT &OR EXAMPLE IF YOU ENTER THE AMOUNT IN RESPONSE TO THE PROMPT THE $"-3 EFFECTIVELY EXECUTES THIS 50$!4% STATEMENT EXEC SQL UPDATE SALESREPS SET QUOTA QUOTA
! HOST VARIABLE CAN APPEAR IN AN EMBEDDED 31, STATEMENT WHEREVER A CONSTANT CAN APPEAR )N PARTICULAR A HOST VARIABLE CAN BE USED IN AN ASSIGNMENT EXPRESSION EXEC SQL UPDATE SALESREPS SET QUOTA QUOTA AMOUNT
! HOST VARIABLE CAN APPEAR IN A SEARCH CONDITION EXEC SQL DELETE FROM SALESREPS WHERE QUOTA AMOUNT
! HOST VARIABLE CAN ALSO BE USED IN THE 6!,5%3 CLAUSE OF AN ).3%24 STATEMENT EXEC SQL INSERT INTO SALESREPS EMPL?NUM NAME QUOTA VALUES g"ILL 2OBERTSg AMOUNT
)N EACH CASE NOTE THAT THE HOST VARIABLE IS PART OF THE PROGRAMS INPUT TO THE $"-3 IT FORMS PART OF THE 31, STATEMENT SUBMITTED TO THE $"-3 FOR EXECUTION ,ATER IN THE SECTION h$ATA 2ETRIEVAL IN %MBEDDED 31, v YOU WILL SEE HOW HOST VARIABLES ARE ALSO USED TO RECEIVE OUTPUT FROM THE $"-3 THEY RECEIVE QUERY RESULTS RETURNED FROM THE $"-3 TO THE PROGRAM .OTE THAT A HOST VARIABLE CANNOT BE USED INSTEAD OF A 31, IDENTIFIER 4HIS ATTEMPTED USE OF THE HOST VARIABLE COLNAME IS ILLEGAL CHAR COLNAME QUOTA EXEC SQL INSERT INTO SALESREPS EMPL?NUM NAME COLNAME VALUES g"ILL 2OBERTSg
$ECLARINGõ(OSTõ6ARIABLES 7HEN YOU USE A HOST VARIABLE IN AN EMBEDDED 31, STATEMENT YOU MUST DECLARE THE VARIABLE USING THE NORMAL METHOD FOR DECLARING VARIABLES IN THE HOST PROGRAMMING LANGUAGE &OR EXAMPLE IN &IGURE THE HOST VARIABLE AMOUNT IS DECLARED USING THE NORMAL # LANGUAGE SYNTAX FLOAT AMOUNT 7HEN THE PRECOMPILER PROCESSES THE SOURCE CODE FOR THE PROGRAM IT NOTES THE NAME OF EACH VARIABLE IT ENCOUNTERS ALONG WITH ITS DATA TYPE AND SIZE 4HE PRECOMPILER USES THIS INFORMATION TO GENERATE CORRECT CODE LATER WHEN IT ENCOUNTERS A USE OF THE VARIABLE AS A HOST VARIABLE IN A 31, STATEMENT 4HE TWO EMBEDDED 31, STATEMENTS "%'). $%#,!2% 3%#4)/. AND %.$ $%#,!2% 3%#4)/. BRACKET THE HOST VARIABLE DECLARATIONS AS SHOWN IN &IGURE 4HESE TWO STATEMENTS ARE UNIQUE TO EMBEDDED 31, AND THEY ARE NOT EXECUTABLE 4HEY ARE DIRECTIVES TO THE PRECOMPILER TELLING IT WHEN IT MUST PAY ATTENTION TO VARIABLE DECLARATIONS AND WHEN IT CAN IGNORE THEM
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)N A SIMPLE EMBEDDED 31, PROGRAM IT MAY BE POSSIBLE TO GATHER TOGETHER ALL OF THE HOST VARIABLE DECLARATIONS INTO ONE DECLARE SECTION 5SUALLY HOWEVER THE HOST VARIABLES MUST BE DECLARED AT VARIOUS POINTS WITHIN THE PROGRAM ESPECIALLY IN BLOCK STRUCTURED LANGUAGES SUCH AS # 0ASCAL AND 0,) )N THIS CASE EACH DECLARATION OF HOST VARIABLES MUST BE BRACKETED WITH A "%'). $%#,!2% 3%#4)/.%.$ $%#,!2% 3%#4)/. STATEMENT PAIR 4HE "%'). $%#,!2% 3%#4)/. AND %.$ $%#,!2% 3%#4)/. STATEMENTS ARE RELATIVELY NEW TO THE EMBEDDED 31, 4HEY ARE SPECIFIED IN THE !.3))3/ 31, STANDARD AND $" REQUIRES THEM IN ITS NEWER EMBEDDED 31, IMPLEMENTATIONS (OWEVER $" AND MANY OTHER $"-3 BRANDS DID NOT HISTORICALLY REQUIRE DECLARE SECTIONS AND SOME 31, PRECOMPILERS DO NOT YET SUPPORT THE "%'). $%#,!2% 3%#4)/. AND %.$ $%#,!2% 3%#4)/. STATEMENTS )N THIS CASE THE PRECOMPILER SCANS AND PROCESSES ALL VARIABLE DECLARATIONS IN THE HOST PROGRAM 7HEN YOU USE A HOST VARIABLE THE PRECOMPILER MAY LIMIT YOUR FLEXIBILITY IN DECLARING THE VARIABLE IN THE HOST PROGRAMMING LANGUAGE &OR EXAMPLE CONSIDER THE FOLLOWING # LANGUAGE SOURCE CODE DEFINE ")'"5&3):% EXEC SQL BEGIN DECLARE SECTION CHAR BIGBUFFER;")'"5&3):% = EXEC SQL END DECLARE SECTION
4HIS IS A VALID # DECLARATION OF THE VARIABLE BIGBUFFER (OWEVER IF YOU TRY TO USE BIGBUFFER AS A HOST VARIABLE IN AN EMBEDDED 31, STATEMENT LIKE THIS EXEC SQL UPDATE SALESREPS SET QUOTA WHERE NAME BIGBUFFER
MANY PRECOMPILERS WILL GENERATE AN ERROR MESSAGE COMPLAINING ABOUT AN ILLEGAL DECLARATION OF BIGBUFFER 4HE PROBLEM IS THAT SOME PRECOMPILERS DONT RECOGNIZE SYMBOLIC CONSTANTS LIKE ")'"5&3):% 4HIS IS JUST ONE EXAMPLE OF THE SPECIAL CONSIDERATIONS THAT APPLY WHEN USING EMBEDDED 31, AND A PRECOMPILER &ORTUNATELY THE PRECOMPILERS OFFERED BY THE MAJOR $"-3 VENDORS ARE HIGHLY DEVELOPED AND SPECIAL CASE PROBLEMS ARE FEW 4HE DATA TYPES SUPPORTED BY A 31, BASED $"-3 AND THE DATA TYPES SUPPORTED BY A PROGRAMMING LANGUAGE SUCH AS # OR &/242!. ARE OFTEN QUITE DIFFERENT 4HESE DIFFERENCES IMPACT HOST VARIABLES BECAUSE THEY PLAY A DUAL ROLE /N THE ONE HAND A HOST VARIABLE IS A PROGRAM VARIABLE DECLARED USING THE DATA TYPES OF THE PROGRAMMING LANGUAGE AND MANIPULATED BY PROGRAMMING LANGUAGE STATEMENTS /N THE OTHER HAND A HOST VARIABLE IS USED IN EMBEDDED 31, STATEMENTS TO CONTAIN DATABASE DATA #ONSIDER THE FOUR EMBEDDED 50$!4% STATEMENTS IN &IGURE )N THE FIRST 50$!4% STATEMENT THE -!.!'%2 COLUMN HAS AN ).4%'%2 DATA TYPE SO HOSTVAR SHOULD BE DECLARED AS A # INTEGER VARIABLE )N THE SECOND STATEMENT THE .!-% COLUMN HAS A 6!2#(!2 DATA TYPE SO HOSTVAR SHOULD CONTAIN STRING DATA 4HE PROGRAM SHOULD DECLARE HOSTVAR AS AN ARRAY OF # CHARACTER DATA AND MOST $"-3 PRODUCTS WILL EXPECT THE DATA IN THE ARRAY TO
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(OST LANGUAGE DOES NOT SUPPORT PACKED DECIMAL DATA CONVERSION TO OR FROM FLOATING POINT DATA MAY CAUSE TRUNCATION OR ROUND OFF ERRORS 4HE 31, STANDARD SPECIFIES A # STRING WITH A NULL TERMINATOR OLDER $"-3 IMPLEMENTATIONS RETURNED A SEPARATE LENGTH VALUE IN A DATA STRUCTURE 4HE LENGTH OF THE HOST CHARACTER STRING L IS THE NUMBER OF BITS N DIVIDED BY THE BITS PER CHARACTER FOR THE HOST LANGUAGE TYPICALLY ROUNDED UP (OST LANGUAGE DOES NOT SUPPORT VARIABLE LENGTH STRINGS MOST $"-3 BRANDS WILL CONVERT TO FIXED LENGTH STRINGS (OST LANGUAGES DO NOT SUPPORT NATIVE DATETIME DATA TYPES REQUIRES CONVERSION TOFROM HOST LANGUAGE CHARACTER STRING DATA TYPES WITH TEXT DATE TIME AND INTERVAL REPRESENTATIONS
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(OSTõ6ARIABLESõANDõ.5,,õ6ALUES -OST PROGRAMMING LANGUAGES DO NOT PROVIDE 31, STYLE SUPPORT FOR UNKNOWN OR MISSING VALUES ! VARIABLE IN #/"/, # OR &/242!. FOR EXAMPLE ALWAYS HAS A VALUE 4HERE IS NO CONCEPT OF THE VALUE BEING .5,, OR MISSING 4HIS CAUSES A PROBLEM WHEN YOU WANT TO STORE .5,, VALUES IN THE DATABASE OR RETRIEVE .5,, VALUES FROM THE DATABASE USING PROGRAMMATIC 31, %MBEDDED 31, SOLVES THIS PROBLEM BY ALLOWING EACH HOST VARIABLE TO HAVE A COMPANION HOST INDICATOR VARIABLE )N AN EMBEDDED 31, STATEMENT THE HOST VARIABLE AND THE INDICATOR VARIABLE TOGETHER SPECIFY A SINGLE 31, STYLE VALUE AS FOLLOWS s !N INDICATOR VALUE OF ZERO MEANS THAT THE HOST VARIABLE CONTAINS A VALID VALUE AND THAT THIS VALUE IS TO BE USED s ! NEGATIVE INDICATOR VALUE MEANS THAT THE HOST VARIABLE SHOULD BE ASSUMED TO HAVE A .5,, VALUE THE ACTUAL VALUE OF THE HOST VARIABLE IS IRRELEVANT AND SHOULD BE DISREGARDED s ! POSITIVE INDICATOR VALUE MEANS THAT THE HOST VARIABLE CONTAINS A VALID VALUE WHICH MAY HAVE BEEN ROUNDED OFF OR TRUNCATED 4HIS SITUATION OCCURS ONLY WHEN DATA IS RETRIEVED FROM THE DATABASE AND IS DESCRIBED LATER IN THE SECTION h2ETRIEVING .5,, 6ALUESv 7HEN YOU SPECIFY A HOST VARIABLE IN AN EMBEDDED 31, STATEMENT YOU CAN FOLLOW IT IMMEDIATELY WITH THE NAME OF THE CORRESPONDING INDICATOR VARIABLE "OTH VARIABLE NAMES ARE PRECEDED BY A COLON (ERE IS AN EMBEDDED 50$!4% STATEMENT THAT USES THE HOST VARIABLE AMOUNT WITH THE COMPANION INDICATOR VARIABLE AMOUNT?IND EXEC SQL UPDATE SALESREPS SET QUOTA AMOUNT AMOUNT?IND SALES AMOUNT WHERE QUOTA
)F AMOUNT?IND HAS A NONNEGATIVE VALUE WHEN THE 50$!4% STATEMENT IS EXECUTED THE $"-3 TREATS THE STATEMENT AS IF IT READ EXEC SQL UPDATE SALESREPS SET QUOTA AMOUNT SALES AMOUNT WHERE QUOTA
)F AMOUNT?IND HAS A NEGATIVE VALUE WHEN THE 50$!4% STATEMENT IS EXECUTED THE $"-3 TREATS THE STATEMENT AS IF IT READ EXEC SQL UPDATE SALESREPS SET QUOTA .5,, SALES AMOUNT WHERE QUOTA
! HOST VARIABLEINDICATOR VARIABLE PAIR CAN APPEAR IN THE ASSIGNMENT CLAUSE OF AN EMBEDDED 50$!4% STATEMENT AS SHOWN HERE OR IN THE VALUES CLAUSE OF AN EMBEDDED ).3%24 STATEMENT 9OU CANNOT USE AN INDICATOR VARIABLE IN A SEARCH CONDITION SO THIS EMBEDDED 31, STATEMENT IS ILLEGAL EXEC SQL DELETE FROM SALESREPS WHERE QUOTA AMOUNT AMOUNT?IND
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%MBEDDEDç31,ç
4HIS PROHIBITION EXISTS FOR THE SAME REASON THAT THE .5,, KEYWORD IS NOT ALLOWED IN THE SEARCH CONDITIONIT MAKES NO SENSE TO TEST WHETHER 15/4! AND .5,, ARE EQUAL BECAUSE THE ANSWER WILL ALWAYS BE .5,, UNKNOWN )NSTEAD OF USING THE INDICATOR VARIABLE YOU MUST USE AN EXPLICIT )3 .5,, TEST 4HIS PAIR OF EMBEDDED 31, STATEMENTS ACCOMPLISHES THE INTENDED TASK OF THE PRECEDING ILLEGAL STATEMENT IF AMOUNT?IND [ EXEC SQL DELETE FROM SALESREPS WHERE QUOTA IS NULL ] ELSE [ EXEC SQL DELETE FROM SALESREPS WHERE QUOTA AMOUNT ]
)NDICATOR VARIABLES ARE ESPECIALLY USEFUL WHEN YOU ARE RETRIEVING DATA FROM THE DATABASE INTO YOUR PROGRAM AND THE RETRIEVED DATA VALUES MAY BE .5,, 4HIS USE OF INDICATOR VARIABLES IS DESCRIBED LATER IN THE SECTION h2ETRIEVING .5,, 6ALUESv
$ATAõ2ETRIEVALõINõ%MBEDDEDõ31, 5SING THE EMBEDDED 31, FEATURES DESCRIBED THUS FAR YOU CAN EMBED ANY INTERACTIVE 31, STATEMENT EXCEPT THE 3%,%#4 STATEMENT IN AN APPLICATION PROGRAM 2ETRIEVING DATA WITH AN EMBEDDED 31, PROGRAM REQUIRES SOME SPECIAL EXTENSIONS TO THE 3%,%#4 STATEMENT 4HE REASON FOR THESE EXTENSIONS IS THAT THERE IS A FUNDAMENTAL MISMATCH BETWEEN THE 31, LANGUAGE AND PROGRAMMING LANGUAGES SUCH AS # AND #/"/, A 31, QUERY PRODUCES AN ENTIRE TABLE OF QUERY RESULTS BUT MOST PROGRAMMING LANGUAGES CAN MANIPULATE ONLY INDIVIDUAL DATA ITEMS OR INDIVIDUAL RECORDS ROWS OF DATA %MBEDDED 31, MUST BUILD A BRIDGE BETWEEN THE TABLE LEVEL LOGIC OF THE 31, 3%,%#4 STATEMENT AND THE ROW BY ROW PROCESSING OF # #/"/, AND OTHER HOST PROGRAMMING LANGUAGES &OR THIS REASON EMBEDDED 31, DIVIDES 31, QUERIES INTO TWO GROUPS s 3INGLE ROW QUERIES 9OU EXPECT THE QUERY RESULTS TO CONTAIN A SINGLE ROW OF DATA ,OOKING UP A CUSTOMERS CREDIT LIMIT OR RETRIEVING THE SALES AND QUOTA FOR A PARTICULAR SALESPERSON ARE EXAMPLES OF THIS TYPE OF QUERY
)NTERACTIVE 31, DOES NOT DISTINGUISH BETWEEN THESE TWO TYPES OF QUERIES THE SAME INTERACTIVE 3%,%#4 STATEMENT HANDLES THEM BOTH )N EMBEDDED 31, HOWEVER THE TWO TYPES OF QUERIES ARE HANDLED VERY DIFFERENTLY 3INGLE ROW QUERIES ARE SIMPLER TO HANDLE AND ARE DISCUSSED IN THE NEXT SECTION -ULTIROW QUERIES ARE DISCUSSED SHORTLY
3INGLE 2OWõ1UERIES -ANY USEFUL 31, QUERIES RETURN A SINGLE ROW OF QUERY RESULTS 3INGLE ROW QUERIES ARE ESPECIALLY COMMON IN TRANSACTION PROCESSING PROGRAMS WHERE A USER ENTERS A CUSTOMER NUMBER OR AN ORDER NUMBER AND THE PROGRAM RETRIEVES RELEVANT DATA ABOUT THE CUSTOMER OR ORDER
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s -ULTIROW QUERIES 9OU EXPECT THAT THE QUERY RESULTS MAY CONTAIN ZERO ONE OR MANY ROWS OF DATA ,ISTING THE ORDERS WITH AMOUNTS OVER OR RETRIEVING THE NAMES OF ALL SALESPEOPLE WHO ARE OVER QUOTA ARE EXAMPLES OF THIS TYPE OF QUERY
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)N EMBEDDED 31, SINGLE ROW QUERIES ARE HANDLED BY THE SINGLETON 3%,%#4 STATEMENT SHOWN IN &IGURE 4HE SINGLETON 3%,%#4 STATEMENT HAS SYNTAX MUCH LIKE THAT OF THE INTERACTIVE 3%,%#4 STATEMENT )T HAS A 3%,%#4 CLAUSE A &2/- CLAUSE AND AN OPTIONAL 7(%2% CLAUSE "ECAUSE THE SINGLETON 3%,%#4 STATEMENT RETURNS A SINGLE ROW OF DATA THERE IS NO NEED FOR A '2/50 "9 (!6).' OR /2$%2 "9 CLAUSE 4HE ).4/ CLAUSE SPECIFIES THE HOST VARIABLES THAT ARE TO RECEIVE THE DATA RETRIEVED BY THE STATEMENT &IGURE SHOWS A SIMPLE PROGRAM WITH A SINGLETON 3%,%#4 STATEMENT 4HE PROGRAM PROMPTS THE USER FOR AN EMPLOYEE NUMBER AND THEN RETRIEVES THE NAME QUOTA AND SALES OF THE CORRESPONDING SALESPERSON 4HE $"-3 PLACES THE THREE RETRIEVED DATA ITEMS INTO THE HOST VARIABLES REPNAME REPQUOTA AND REPSALES RESPECTIVELY 2ECALL THAT THE HOST VARIABLES USED IN THE ).3%24 $%,%4% AND 50$!4% STATEMENTS IN THE PREVIOUS EXAMPLES WERE INPUT HOST VARIABLES )N CONTRAST THE HOST VARIABLES SPECIFIED IN THE ).4/ CLAUSE OF THE SINGLETON 3%,%#4 STATEMENT ARE OUTPUT HOST VARIABLES %ACH HOST VARIABLE NAMED IN THE ).4/ CLAUSE RECEIVES A SINGLE COLUMN FROM THE ROW OF QUERY RESULTS 4HE SELECT LIST ITEMS AND THE CORRESPONDING HOST VARIABLES ARE PAIRED IN SEQUENCE AS THEY APPEAR IN THEIR RESPECTIVE CLAUSES AND THE NUMBER OF QUERY RESULTS COLUMNS MUST BE THE SAME AS THE NUMBER OF HOST VARIABLES )N ADDITION THE DATA TYPE OF EACH HOST VARIABLE MUST BE COMPATIBLE WITH THE DATA TYPE OF THE CORRESPONDING COLUMN OF QUERY RESULTS -OST $"-3 BRANDS WILL AUTOMATICALLY HANDLE REASONABLE CONVERSIONS BETWEEN $"-3 DATA TYPES AND THE DATA TYPES SUPPORTED BY THE PROGRAMMING LANGUAGE &OR EXAMPLE MOST $"-3 PRODUCTS WILL CONVERT $%#)-!, DATA RETRIEVED FROM THE DATABASE INTO PACKED DECIMAL #/-0 DATA BEFORE STORING IT IN A #/"/, VARIABLE OR INTO FLOATING POINT DATA BEFORE STORING IT IN A # VARIABLE 4HE PRECOMPILER USES ITS KNOWLEDGE OF THE HOST VARIABLES DATA TYPE TO HANDLE THE CONVERSION CORRECTLY
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6ARIABLE LENGTH TEXT DATA MUST ALSO BE CONVERTED BEFORE BEING STORED IN A HOST VARIABLE 4YPICALLY A $"-3 CONVERTS 6!2#(!2 DATA INTO A NULL TERMINATED STRING FOR # PROGRAMS AND INTO A VARIABLE LENGTH STRING WITH A LEADING CHARACTER COUNT FOR 0ASCAL PROGRAMS &OR #/"/, AND &/242!. PROGRAMS THE HOST VARIABLE MUST GENERALLY BE DECLARED AS A DATA STRUCTURE WITH AN INTEGER COUNT FIELD AND A CHARACTER ARRAY OR AS A FIXED LENGTH CHARACTER VARIABLE THE SAME SIZE AS THE MAXIMUM LENGTH FOR THE DATABASE COLUMN 4HE $"-3 RETURNS THE ACTUAL CHARACTERS OF DATA IN THE CHARACTER ARRAY AND IT RETURNS THE LENGTH OF THE DATA IN THE COUNT FIELD OF THE DATA STRUCTURE )F A $"-3 SUPPORTS DATETIME DATA OR OTHER DATA TYPES OTHER CONVERSIONS ARE NECESSARY 3OME $"-3 PRODUCTS RETURN THEIR INTERNAL DATETIME REPRESENTATIONS INTO AN INTEGER HOST VARIABLE /THERS CONVERT THE DATETIME DATA TO TEXT FORMAT AND RETURN IT INTO A STRING HOST VARIABLE 4ABLE SUMMARIZED THE DATA TYPE CONVERSIONS TYPICALLY PROVIDED BY $"-3 PRODUCTS BUT YOU MUST CONSULT THE EMBEDDED 31, DOCUMENTATION FOR YOUR PARTICULAR $"-3 BRAND FOR SPECIFIC INFORMATION
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4HEõ./4õ&/5.$õ#ONDITION ,IKE ALL EMBEDDED 31, STATEMENTS THE SINGLETON 3%,%#4 STATEMENT SETS THE VALUES OF THE 31,#/$% AND 31,34!4% VARIABLES TO INDICATE ITS COMPLETION STATUS s )F A SINGLE ROW OF QUERY RESULTS IS SUCCESSFULLY RETRIEVED 31,#/$% IS SET TO ZERO AND 31,34!4% IS SET TO THE HOST VARIABLES NAMED IN THE ).4/ CLAUSE CONTAIN THE RETRIEVED VALUES s )F THE QUERY PRODUCED AN ERROR 31,#/$% IS SET TO A NEGATIVE VALUE AND 31,34!4% IS SET TO A NONZERO ERROR CLASS THE FIRST TWO CHARACTERS OF THE FIVE DIGIT 31,34!4% STRING THE HOST VARIABLES DO NOT CONTAIN RETRIEVED VALUES (OWEVER THE HOST VARIABLES MIGHT CONTAIN VALUES LEFT OVER FROM THE LAST SUCCESSFUL EXECUTION OF A 3%,%#4 THAT REFERENCES THEM SO DEVELOPERS MUST BE SURE TO TEST 31,#/$% OR 31,34!4% BEFORE REFERENCING THE HOST VARIABLES s )F THE QUERY PRODUCED NO ROWS OF QUERY RESULTS A SPECIAL ./4 &/5.$ WARNING VALUE IS RETURNED IN 31,#/$% AND 31,34!4% RETURNS A ./ $!4! ERROR CLASS s )F THE QUERY PRODUCED MORE THAN ONE ROW OF QUERY RESULTS IT IS TREATED AS AN ERROR AND A NEGATIVE 31,#/$% IS RETURNED 4HE 31, STANDARD SPECIFIES THE ./4 &/5.$ WARNING CONDITION BUT IT DOES NOT SPECIFY A PARTICULAR VALUE TO BE RETURNED $" USES THE VALUE AND MOST OTHER 31, PRODUCTS FOLLOW THIS CONVENTION INCLUDING THE OTHER )"- 31, PRODUCTS )NGRES AND 31,"ASE 4HIS VALUE IS ALSO SPECIFIED IN THE 31, STANDARD BUT AS NOTED PREVIOUSLY THE STANDARD STRONGLY ENCOURAGES THE USE OF THE NEWER 31,34!4% ERROR VARIABLE INSTEAD OF THE OLDER 31,#/$% VALUES
2ETRIEVINGõ.5,,õ6ALUES )F THE DATA TO BE RETRIEVED FROM A DATABASE MAY CONTAIN .5,, VALUES THE SINGLETON 3%,%#4 STATEMENT MUST PROVIDE A WAY FOR THE $"-3 TO COMMUNICATE THE .5,, VALUES TO THE APPLICATION PROGRAM 4O HANDLE .5,, VALUES EMBEDDED 31, USES INDICATOR VARIABLES IN THE ).4/ CLAUSE JUST AS THEY ARE USED IN THE 6!,5%3 CLAUSE OF THE ).3%24 STATEMENT AND THE 3%4 CLAUSE OF THE 50$!4% STATEMENT 7HEN YOU SPECIFY A HOST VARIABLE IN THE ).4/ CLAUSE YOU CAN FOLLOW IT IMMEDIATELY WITH THE NAME OF A COMPANION HOST INDICATOR VARIABLE &IGURE SHOWS A REVISED VERSION OF THE PROGRAM IN &IGURE THAT USES THE INDICATOR VARIABLE REPQUOTA?IND WITH THE HOST VARIABLE REPQUOTA "ECAUSE THE .!-% AND 3!,%3 COLUMNS ARE DECLARED ./4 .5,, IN THE DEFINITION OF THE 3!,%32%03 TABLE THEY CANNOT PRODUCE .5,, OUTPUT VALUES AND NO INDICATOR VARIABLE IS NEEDED FOR THOSE COLUMNS !FTER THE 3%,%#4 STATEMENT HAS BEEN EXECUTED THE VALUE OF THE INDICATOR VARIABLE TELLS THE PROGRAM HOW TO INTERPRET THE RETURNED DATA s !N INDICATOR VALUE OF ZERO MEANS THE HOST VARIABLE HAS BEEN ASSIGNED A RETRIEVED VALUE BY THE $"-3 4HE APPLICATION PROGRAM CAN USE THE VALUE OF THE HOST VARIABLE IN ITS PROCESSING s ! NEGATIVE INDICATOR VALUE MEANS THE RETRIEVED VALUE WAS .5,, 4HE VALUE OF THE HOST VARIABLE IS IRRELEVANT AND SHOULD NOT BE USED BY THE APPLICATION PROGRAM s ! POSITIVE INDICATOR VALUE INDICATES A WARNING CONDITION OF SOME KIND SUCH AS A ROUNDING ERROR OR STRING TRUNCATION
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"ECAUSE YOU CANNOT TELL IN ADVANCE WHEN A .5,, VALUE WILL BE RETRIEVED YOU SHOULD ALWAYS SPECIFY AN INDICATOR VARIABLE IN THE ).4/ CLAUSE FOR ANY COLUMN OF QUERY RESULTS THAT MAY CONTAIN A .5,, VALUE )F THE 3%,%#4 STATEMENT PRODUCES A COLUMN CONTAINING A .5,, VALUE AND YOU HAVE NOT SPECIFIED AN INDICATOR VARIABLE FOR THE COLUMN THE $"-3 WILL TREAT THE STATEMENT AS AN ERROR AND RETURN A NEGATIVE 31,#/$% 4HUS INDICATOR VARIABLES MUST BE USED TO SUCCESSFULLY RETRIEVE ROWS CONTAINING .5,, DATA &URTHERMORE HOST VARIABLE VALUES ARE NOT CHANGED WHEN .5,, VALUES ARE RETURNED BY THE DATABASE SO THE DEVELOPER MUST TEST THE INDICATOR VARIABLE FOR .5,, DATA BEFORE REFERENCING THE VALUES IN THE HOST VARIABLES OTHERWISE VALUES RETURNED BY A DIFFERENT QUERY COULD BE PROCESSED AS IF THEY WERE RETURNED BY THE ONE THAT JUST COMPLETED
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!LTHOUGH THE MAJOR USE OF INDICATOR VARIABLES IS FOR HANDLING .5,, VALUES THE $"-3 ALSO USES INDICATOR VARIABLES TO SIGNAL WARNING CONDITIONS &OR EXAMPLE IF AN ARITHMETIC OVERFLOW OR DIVISION BY ZERO MAKES ONE OF THE QUERY RESULTS COLUMNS INVALID $" RETURNS A WARNING 31,#/$% OF AND SETS THE INDICATOR VARIABLE FOR THE AFFECTED COLUMN TO 4HE APPLICATION PROGRAM CAN RESPOND TO THE 31,#/$% AND EXAMINE THE INDICATOR VARIABLES TO DETERMINE WHICH COLUMN CONTAINS INVALID DATA $" ALSO USES INDICATOR VARIABLES TO SIGNAL STRING TRUNCATION )F THE QUERY RESULTS CONTAIN A COLUMN OF CHARACTER DATA THAT IS TOO LARGE FOR THE CORRESPONDING HOST VARIABLE $" COPIES THE FIRST PART OF THE CHARACTER STRING INTO THE HOST VARIABLE AND SETS THE CORRESPONDING INDICATOR VARIABLE TO THE FULL LENGTH OF THE STRING 4HE APPLICATION PROGRAM CAN EXAMINE THE INDICATOR VARIABLE AND MAY WANT TO RETRY THE 3%,%#4 STATEMENT WITH A DIFFERENT HOST VARIABLE THAT CAN HOLD A LARGER STRING 4HESE ADDITIONAL USES OF INDICATOR VARIABLES ARE FAIRLY COMMON IN COMMERCIAL 31, PRODUCTS BUT THE SPECIFIC WARNING CODE VALUES VARY FROM ONE PRODUCT TO ANOTHER 4HEY ARE NOT SPECIFIED BY THE !.3))3/ 31, STANDARD )NSTEAD THE 31, STANDARD SPECIFIES ERROR CLASSES AND SUBCLASSES TO INDICATE THESE AND SIMILAR CONDITIONS AND THE PROGRAM MUST USE THE '%4 $)!'./34)#3 STATEMENT TO DETERMINE MORE SPECIFIC INFORMATION ABOUT THE HOST VARIABLE CAUSING THE ERROR
2ETRIEVALõ5SINGõ$ATAõ3TRUCTURES 3OME PROGRAMMING LANGUAGES SUPPORT DATA STRUCTURES WHICH ARE NAMED COLLECTIONS OF VARIABLES &OR THESE LANGUAGES A 31, PRECOMPILER MAY ALLOW YOU TO TREAT THE ENTIRE DATA STRUCTURE AS A SINGLE COMPOSITE HOST VARIABLE IN THE ).4/ CLAUSE )NSTEAD OF SPECIFYING A SEPARATE HOST VARIABLE AS THE DESTINATION FOR EACH COLUMN OF QUERY RESULTS YOU CAN SPECIFY A DATA STRUCTURE AS THE DESTINATION FOR THE ENTIRE ROW &IGURE SHOWS THE PROGRAM FROM &IGURE REWRITTEN TO USE A # DATA STRUCTURE 7HEN THE PRECOMPILER ENCOUNTERS A DATA STRUCTURE REFERENCE IN THE ).4/ CLAUSE IT REPLACES THE STRUCTURE REFERENCE WITH A LIST OF THE INDIVIDUAL VARIABLES IN THE STRUCTURE IN THE ORDER THEY ARE DECLARED WITHIN THE STRUCTURE 4HUS THE NUMBER OF ITEMS IN THE STRUCTURE AND THEIR DATA TYPES MUST CORRESPOND TO THE COLUMNS OF QUERY RESULTS 4HE USE OF DATA STRUCTURES IN THE ).4/ CLAUSE IS IN EFFECT A SHORTCUT )T DOES NOT FUNDAMENTALLY CHANGE THE WAY THE ).4/ CLAUSE WORKS 3UPPORT FOR THE USE OF DATA STRUCTURES AS HOST VARIABLES VARIES WIDELY AMONG $"-3 BRANDS )T IS ALSO RESTRICTED TO CERTAIN PROGRAMMING LANGUAGES $" SUPPORTS # AND 0,) STRUCTURES BUT DOES NOT SUPPORT #/"/, OR ASSEMBLY LANGUAGE STRUCTURES FOR EXAMPLE
)NPUTõANDõ/UTPUTõ(OSTõ6ARIABLES (OST VARIABLES PROVIDE TWO WAY COMMUNICATION BETWEEN THE PROGRAM AND THE $"-3 )N THE PROGRAM SHOWN IN &IGURE THE HOST VARIABLES REPNUM AND REPNAME ILLUSTRATE THE TWO DIFFERENT ROLES PLAYED BY HOST VARIABLES s 4HE REPNUM HOST VARIABLE IS AN INPUT HOST VARIABLE USED TO PASS DATA FROM THE PROGRAM TO THE $"-3 4HE PROGRAM ASSIGNS A VALUE TO THE VARIABLE BEFORE EXECUTING THE EMBEDDED STATEMENT AND THAT VALUE BECOMES PART OF THE 3%,%#4 STATEMENT TO BE EXECUTED BY THE $"-3 4HE $"-3 DOES NOTHING TO ALTER THE VALUE OF THE VARIABLE s 4HE REPNAME HOST VARIABLE IS AN OUTPUT HOST VARIABLE USED TO PASS DATA BACK FROM THE $"-3 TO THE PROGRAM 4HE $"-3 ASSIGNS A VALUE TO THIS VARIABLE AS IT EXECUTES THE EMBEDDED 3%,%#4 STATEMENT !FTER THE STATEMENT HAS BEEN EXECUTED THE PROGRAM CAN USE THE RESULTING VALUE
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-ULTIROWõ1UERIES 7HEN A QUERY PRODUCES AN ENTIRE TABLE OF QUERY RESULTS EMBEDDED 31, MUST PROVIDE A WAY FOR THE APPLICATION PROGRAM TO PROCESS THE QUERY RESULTS ONE ROW AT A TIME %MBEDDED 31, SUPPORTS THIS CAPABILITY BY DEFINING A NEW 31, CONCEPT CALLED A CURSOR AND ADDING SEVERAL STATEMENTS TO THE INTERACTIVE 31, LANGUAGE (ERE IS AN OVERVIEW OF EMBEDDED 31, TECHNIQUES FOR MULTIROW QUERY PROCESSING AND THE NEW STATEMENTS IT REQUIRES
4HE $%#,!2% #523/2 STATEMENT SPECIFIES THE QUERY TO BE PERFORMED AND ASSOCIATES A CURSOR NAME WITH THE QUERY
4HE /0%. STATEMENT ASKS THE $"-3 TO START EXECUTING THE QUERY AND GENERATING QUERY RESULTS )T POSITIONS THE CURSOR BEFORE THE FIRST ROW OF QUERY RESULTS
4HE &%4#( STATEMENT ADVANCES THE CURSOR TO THE FIRST ROW OF QUERY RESULTS AND RETRIEVES ITS DATA INTO HOST VARIABLES FOR USE BY THE APPLICATION PROGRAM 3UBSEQUENT &%4#( STATEMENTS MOVE THROUGH THE QUERY RESULTS ROW BY ROW ADVANCING THE CURSOR TO THE NEXT ROW OF QUERY RESULTS AND RETRIEVING ITS DATA INTO THE HOST VARIABLES
4HE #,/3% STATEMENT ENDS ACCESS TO THE QUERY RESULTS AND BREAKS THE ASSOCIATION BETWEEN THE CURSOR AND THE QUERY RESULTS
&IGURE SHOWS A PROGRAM THAT USES EMBEDDED 31, TO PERFORM A SIMPLE MULTIROW QUERY 4HE NUMBERED CALLOUTS IN THE FIGURE CORRESPOND TO THE NUMBERS IN THE PRECEDING STEPS 4HE PROGRAM RETRIEVES AND DISPLAYS IN ALPHABETICAL ORDER THE NAME QUOTA AND YEAR TO DATE SALES OF EACH SALESPERSON WHOSE SALES EXCEED QUOTA 4HE INTERACTIVE 31, QUERY THAT PRINTS THIS INFORMATION IS 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% 3!,%3 15/4! /2$%2 "9 .!-%
.OTICE THAT THIS QUERY APPEARS WORD FOR WORD IN THE EMBEDDED $%#,!2% #523/2 STATEMENT IN &IGURE 4HE STATEMENT ALSO ASSOCIATES THE CURSOR NAME REPCURS WITH THE QUERY 4HIS CURSOR NAME IS USED LATER IN THE /0%. #523/2 STATEMENT TO START THE QUERY AND POSITION THE CURSOR BEFORE THE FIRST ROW OF QUERY RESULTS 4HE &%4#( STATEMENT INSIDE THE FOR LOOP FETCHES THE NEXT ROW OF QUERY RESULTS EACH TIME THE LOOP IS EXECUTED 4HE ).4/ CLAUSE OF THE &%4#( STATEMENT WORKS JUST LIKE THE ).4/ CLAUSE OF THE SINGLETON 3%,%#4 STATEMENT )T SPECIFIES THE HOST VARIABLES THAT ARE TO RECEIVE THE FETCHED DATA ITEMSONE HOST VARIABLE FOR EACH COLUMN OF QUERY RESULTS !S IN PREVIOUS EXAMPLES A HOST INDICATOR VARIABLE REPQUOTA?IND IS USED WHEN A FETCHED DATA ITEM MAY CONTAIN .5,, VALUES 7HEN NO MORE ROWS OF QUERY RESULTS ARE TO BE FETCHED THE $"-3 RETURNS THE ./4 &/5.$ WARNING IN RESPONSE TO THE &%4#( STATEMENT 4HIS IS EXACTLY THE SAME WARNING CODE THAT IS RETURNED WHEN THE SINGLETON 3%,%#4 STATEMENT DOES NOT RETRIEVE A ROW OF DATA )N THIS PROGRAM THE 7(%.%6%2 ./4 &/5.$ STATEMENT CAUSES THE PRECOMPILER TO GENERATE CODE THAT CHECKS THE 31,#/$% VALUE AFTER THE &%4#( STATEMENT 4HIS GENERATED CODE BRANCHES TO THE LABEL DONE WHEN THE ./4 &/5.$ CONDITION ARISES AND TO THE LABEL ERROR IF AN ERROR OCCURS !T THE END OF THE PROGRAM THE #,/3% STATEMENT ENDS THE QUERY AND TERMINATES THE PROGRAMS ACCESS TO THE QUERY RESULTS
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#URSORS !S THE PROGRAM IN &IGURE ILLUSTRATES AN EMBEDDED 31, CURSOR BEHAVES MUCH LIKE A FILENAME OR FILE HANDLE IN A PROGRAMMING LANGUAGE SUCH AS # OR #/"/, *UST AS A PROGRAM OPENS A FILE TO ACCESS THE FILES CONTENTS IT OPENS A CURSOR TO GAIN ACCESS TO THE QUERY RESULTS 3IMILARLY THE PROGRAM CLOSES A FILE TO END ITS ACCESS AND CLOSES A CURSOR TO END ACCESS TO THE QUERY RESULTS &INALLY JUST AS A FILE HANDLE KEEPS TRACK OF THE PROGRAMS CURRENT POSITION WITHIN AN OPEN FILE A CURSOR KEEPS TRACK OF THE PROGRAMS CURRENT POSITION WITHIN THE QUERY RESULTS 4HESE PARALLELS BETWEEN FILE INPUTOUTPUT AND 31, CURSORS MAKE THE CURSOR CONCEPT RELATIVELY EASY FOR APPLICATION PROGRAMMERS TO UNDERSTAND $ESPITE THE PARALLELS BETWEEN FILES AND CURSORS THERE ARE ALSO SOME DIFFERENCES /PENING A 31, CURSOR USUALLY INVOLVES MUCH MORE OVERHEAD THAN OPENING A FILE BECAUSE OPENING THE CURSOR ACTUALLY CAUSES THE $"-3 TO BEGIN CARRYING OUT THE ASSOCIATED QUERY )N ADDITION 31, CURSORS SUPPORT ONLY SEQUENTIAL MOTION THROUGH THE QUERY RESULTS LIKE SEQUENTIAL FILE PROCESSING )N MOST CURRENT 31, IMPLEMENTATIONS THERE IS NO CURSOR ANALOG TO THE RANDOM ACCESS PROVIDED TO THE INDIVIDUAL RECORDS OF A FILE #URSORS PROVIDE A GREAT DEAL OF FLEXIBILITY FOR PROCESSING QUERIES IN AN EMBEDDED 31, PROGRAM "Y DECLARING AND OPENING MULTIPLE CURSORS THE PROGRAM CAN PROCESS SEVERAL SETS OF QUERY RESULTS IN PARALLEL &OR EXAMPLE THE PROGRAM MIGHT RETRIEVE SOME ROWS OF QUERY RESULTS DISPLAY THEM ON THE SCREEN FOR ITS USER AND THEN RESPOND TO A USERS REQUEST FOR MORE DETAILED DATA BY LAUNCHING A SECOND QUERY 4HE FOLLOWING SECTIONS DESCRIBE IN DETAIL THE FOUR EMBEDDED 31, STATEMENTS THAT DEFINE AND MANIPULATE CURSORS
4HEõ$%#,!2%õ#523/2õ3TATEMENT 4HE $%#,!2% #523/2 STATEMENT SHOWN IN &IGURE DEFINES A QUERY TO BE PERFORMED 4HE STATEMENT ALSO ASSOCIATES A CURSOR NAME WITH THE QUERY 4HE CURSOR NAME MUST BE A VALID 31, IDENTIFIER )T IS USED TO IDENTIFY THE QUERY AND ITS RESULTS IN OTHER EMBEDDED 31, STATEMENTS 4HE CURSOR NAME IS SPECIFICALLY NOT A HOST LANGUAGE VARIABLE IT IS DECLARED BY THE $%#,!2% #523/2 STATEMENT NOT IN A HOST LANGUAGE DECLARATION 4HE 3%,%#4 STATEMENT IN THE $%#,!2% #523/2 STATEMENT DEFINES THE QUERY ASSOCIATED WITH THE CURSOR 4HE 3%,%#4 STATEMENT CAN BE ANY VALID INTERACTIVE 31, 3%,%#4 STATEMENT AS DESCRIBED IN #HAPTERS THROUGH )N PARTICULAR THE 3%,%#4 STATEMENT MUST INCLUDE A &2/- CLAUSE AND MAY OPTIONALLY INCLUDE 7(%2% '2/50 "9 (!6).' AND /2$%2 "9 CLAUSES 4HE 3%,%#4 STATEMENT MAY ALSO INCLUDE THE 5.)/. OPERATOR AS DESCRIBED IN #HAPTER 4HUS AN EMBEDDED 31, QUERY CAN USE ANY OF THE QUERY CAPABILITIES THAT ARE AVAILABLE IN THE INTERACTIVE 31, 4HE QUERY SPECIFIED IN THE $%#,!2% #523/2 STATEMENT MAY ALSO INCLUDE INPUT HOST VARIABLES 4HESE HOST VARIABLES PERFORM EXACTLY THE SAME FUNCTION AS IN THE EMBEDDED ).3%24 $%,%4% 50$!4% AND SINGLETON 3%,%#4 STATEMENTS !N INPUT HOST VARIABLE CAN APPEAR WITHIN THE QUERY ANYWHERE THAT A CONSTANT CAN APPEAR .OTE THAT OUTPUT HOST VARIABLES CANNOT APPEAR IN THE QUERY 5NLIKE THE SINGLETON 3%,%#4 STATEMENT THE 3%,%#4 STATEMENT WITHIN THE $%#,!2% #523/2 STATEMENT HAS NO ).4/ CLAUSE AND DOES NOT RETRIEVE ANY DATA 4HE ).4/ CLAUSE APPEARS AS PART OF THE &%4#( STATEMENT DESCRIBED SHORTLY
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!S ITS NAME IMPLIES THE $%#,!2% #523/2 STATEMENT IS A DECLARATION OF THE CURSOR )N MOST 31, IMPLEMENTATIONS INCLUDING THE )"- 31, PRODUCTS THIS STATEMENT IS A DIRECTIVE FOR THE 31, PRECOMPILER IT IS NOT AN EXECUTABLE STATEMENT AND THE PRECOMPILER DOES NOT PRODUCE ANY CODE FOR IT ,IKE ALL DECLARATIONS THE $%#,!2% #523/2 STATEMENT MUST PHYSICALLY APPEAR IN THE PROGRAM BEFORE ANY STATEMENTS THAT REFERENCE THE CURSOR THAT IT DECLARES -OST 31, IMPLEMENTATIONS TREAT THE CURSOR NAME AS A GLOBAL NAME THAT CAN BE REFERENCED INSIDE ANY PROCEDURES FUNCTIONS OR SUBROUTINES THAT APPEAR AFTER THE $%#,!2% #523/2 STATEMENT )TS WORTH NOTING THAT NOT ALL 31, IMPLEMENTATIONS TREAT THE $%#,!2% #523/2 STATEMENT STRICTLY AS A DECLARATIVE STATEMENT AND THIS CAN LEAD TO SUBTLE PROBLEMS 3OME 31, PRECOMPILERS ACTUALLY GENERATE CODE FOR THE $%#,!2% #523/2 STATEMENT EITHER HOST LANGUAGE DECLARATIONS OR CALLS TO THE $"-3 OR BOTH GIVING IT SOME OF THE QUALITIES OF AN EXECUTABLE STATEMENT &OR THESE PRECOMPILERS THE $%#,!2% #523/2 STATEMENT MUST NOT ONLY PHYSICALLY PRECEDE THE /0%. &%4#( AND #,/3% STATEMENTS THAT REFERENCE ITS CURSOR BUT IT ALSO MUST SOMETIMES PRECEDE THESE STATEMENTS IN THE FLOW OF EXECUTION OR BE PLACED IN THE SAME BLOCK AS THE OTHER STATEMENTS )N GENERAL YOU CAN AVOID PROBLEMS WITH THE $%#,!2% #523/2 STATEMENT BY FOLLOWING THESE GUIDELINES s 0LACE THE $%#,!2% #523/2 STATEMENT RIGHT BEFORE THE /0%. STATEMENT FOR THE CURSOR 4HIS PLACEMENT ENSURES THE CORRECT PHYSICAL STATEMENT SEQUENCE IT PUTS THE $%#,!2% #523/2 AND THE /0%. STATEMENTS IN THE SAME BLOCK AND IT ENSURES THAT THE FLOW OF CONTROL PASSES THROUGH THE $%#,!2% #523/2 STATEMENT IF NECESSARY )T ALSO HELPS TO DOCUMENT JUST WHAT QUERY IS BEING REQUESTED BY THE /0%. STATEMENT s -AKE SURE THAT THE &%4#( AND #,/3% STATEMENTS FOR THE CURSOR FOLLOW THE /0%. STATEMENT PHYSICALLY AS WELL AS IN THE FLOW OF CONTROL
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4HE /0%. STATEMENT SHOWN IN &IGURE CONCEPTUALLY OPENS THE TABLE OF QUERY RESULTS FOR ACCESS BY THE APPLICATION PROGRAM )N PRACTICE THE /0%. STATEMENT ACTUALLY CAUSES THE $"-3 TO PROCESS THE QUERY OR AT LEAST TO BEGIN PROCESSING IT 4HE /0%. STATEMENT THUS CAUSES THE $"-3 TO PERFORM THE SAME WORK AS AN INTERACTIVE 3%,%#4 STATEMENT STOPPING JUST SHORT OF THE POINT WHERE IT PRODUCES THE FIRST ROW OF QUERY RESULTS 4HE SINGLE PARAMETER OF THE /0%. STATEMENT IS THE NAME OF THE CURSOR TO BE OPENED 4HIS CURSOR MUST HAVE BEEN PREVIOUSLY DECLARED BY A $%#,!2% #523/2 STATEMENT )F THE QUERY ASSOCIATED WITH THE CURSOR CONTAINS AN ERROR THE /0%. STATEMENT WILL PRODUCE A NEGATIVE 31,#/$% VALUE -OST QUERY PROCESSING ERRORS SUCH AS A REFERENCE TO AN UNKNOWN TABLE AN AMBIGUOUS COLUMN NAME OR AN ATTEMPT TO RETRIEVE DATA FROM A TABLE WITHOUT THE PROPER PERMISSION WILL BE REPORTED AS A RESULT OF THE /0%. STATEMENT )N PRACTICE VERY FEW ERRORS OCCUR DURING THE SUBSEQUENT &%4#( STATEMENTS
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/NCE OPENED A CURSOR REMAINS IN THE OPEN STATE UNTIL IT IS CLOSED WITH THE #,/3% STATEMENT 4HE $"-3 ALSO CLOSES ALL OPEN CURSORS AUTOMATICALLY AT THE END OF A TRANSACTION THAT IS WHEN THE $"-3 EXECUTES A #/--)4 OR 2/,,"!#+ STATEMENT !FTER THE CURSOR HAS BEEN CLOSED IT CAN BE REOPENED BY EXECUTING THE /0%. STATEMENT A SECOND TIME .OTE THAT THE $"-3 RESTARTS THE QUERY FROM SCRATCH EACH TIME IT EXECUTES THE /0%. STATEMENT
4HEõ&%4#(õ3TATEMENT 4HE &%4#( STATEMENT SHOWN IN &IGURE RETRIEVES THE NEXT ROW OF QUERY RESULTS FOR USE BY THE APPLICATION PROGRAM 4HE CURSOR NAMED IN THE &%4#( STATEMENT SPECIFIES WHICH ROW OF QUERY RESULTS IS TO BE FETCHED )T MUST IDENTIFY A CURSOR PREVIOUSLY OPENED BY THE /0%. STATEMENT 4HE &%4#( STATEMENT FETCHES THE ROW OF DATA ITEMS INTO A LIST OF HOST VARIABLES WHICH ARE SPECIFIED IN THE ).4/ CLAUSE OF THE STATEMENT !N INDICATOR VARIABLE CAN BE ASSOCIATED WITH EACH HOST VARIABLE TO HANDLE RETRIEVAL OF .5,, DATA 4HE BEHAVIOR OF THE INDICATOR VARIABLE AND THE VALUES THAT IT CAN ASSUME ARE IDENTICAL TO THOSE DESCRIBED EARLIER IN THE h3INGLE 2OW 1UERIESv SECTION FOR THE SINGLETON 3%,%#4 STATEMENT 4HE NUMBER OF HOST VARIABLES IN THE LIST MUST BE THE SAME AS THE NUMBER OF COLUMNS IN THE QUERY RESULTS AND THE DATA TYPES OF THE HOST VARIABLES MUST BE COMPATIBLE COLUMN BY COLUMN WITH THE COLUMNS OF QUERY RESULTS !S SHOWN IN &IGURE THE &%4#( STATEMENT MOVES THE CURSOR THROUGH THE QUERY RESULTS ROW BY ROW ACCORDING TO THESE RULES s 4HE /0%. STATEMENT POSITIONS THE CURSOR BEFORE THE FIRST ROW OF QUERY RESULTS )N THIS STATE THE CURSOR HAS NO CURRENT ROW s 4HE &%4#( STATEMENT ADVANCES THE CURSOR TO THE NEXT AVAILABLE ROW OF QUERY RESULTS IF THERE IS ONE 4HIS ROW BECOMES THE CURRENT ROW OF THE CURSOR s )F A &%4#( STATEMENT ADVANCES THE CURSOR PAST THE LAST ROW OF QUERY RESULTS THE &%4#( STATEMENT RETURNS A ./4 &/5.$ WARNING )N THIS STATE THE CURSOR AGAIN HAS NO CURRENT ROW s 4HE #,/3% STATEMENT ENDS ACCESS TO THE QUERY RESULTS AND PLACES THE CURSOR IN A CLOSED STATE )F THERE ARE NO ROWS OF QUERY RESULTS THE /0%. STATEMENT STILL POSITIONS THE CURSOR BEFORE THE EMPTY QUERY RESULTS AND RETURNS SUCCESSFULLY 4HE PROGRAM CANNOT DETECT THAT THE /0%. STATEMENT HAS PRODUCED AN EMPTY SET OF QUERY RESULTS (OWEVER THE VERY FIRST &%4#( STATEMENT PRODUCES THE ./4 &/5.$ WARNING AND POSITIONS THE CURSOR AFTER THE END OF THE EMPTY QUERY RESULTS
4HEõ#,/3%õ3TATEMENT 4HE #,/3% STATEMENT SHOWN IN &IGURE CONCEPTUALLY CLOSES THE TABLE OF QUERY RESULTS CREATED BY THE /0%. STATEMENT ENDING ACCESS BY THE APPLICATION PROGRAM )TS SINGLE PARAMETER IS THE NAME OF THE CURSOR ASSOCIATED WITH THE QUERY RESULTS WHICH MUST BE
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A CURSOR PREVIOUSLY OPENED BY AN /0%. STATEMENT 4HE #,/3% STATEMENT CAN BE EXECUTED AT ANY TIME AFTER THE CURSOR HAS BEEN OPENED )N PARTICULAR IT IS NOT NECESSARY TO &%4#( ALL ROWS OF QUERY RESULTS BEFORE CLOSING THE CURSOR ALTHOUGH THIS WILL USUALLY BE THE CASE !LL CURSORS ARE AUTOMATICALLY CLOSED AT THE END OF A TRANSACTION /NCE A CURSOR IS CLOSED ITS QUERY RESULTS ARE NO LONGER AVAILABLE TO THE APPLICATION PROGRAM
3CROLLõ#URSORS 4HE 31, STANDARD SPECIFIES THAT A CURSOR CAN ONLY MOVE FORWARD THROUGH THE QUERY RESULTS &OR A NUMBER OF YEARS MOST COMMERCIAL 31, PRODUCTS ALSO SUPPORTED ONLY THIS FORM OF FORWARD SEQUENTIAL CURSOR MOTION )F A PROGRAM WANTS TO RE RETRIEVE A ROW ONCE THE CURSOR HAS MOVED PAST IT THE PROGRAM MUST #,/3% THE CURSOR AND RE/0%. IT CAUSING THE $"-3 TO PERFORM THE QUERY AGAIN AND THEN &%4#( THROUGH THE ROWS UNTIL THE DESIRED ROW IS REACHED )N THE EARLY S A FEW COMMERCIAL 31, PRODUCTS EXTENDED THE CURSOR CONCEPT WITH THE CONCEPT OF A SCROLL CURSOR 5NLIKE STANDARD CURSORS A SCROLL CURSOR PROVIDES RANDOM ACCESS TO THE ROWS OF QUERY RESULTS 4HE PROGRAM SPECIFIES WHICH ROW IT WANTS TO RETRIEVE THROUGH AN EXTENSION OF THE &%4#( STATEMENT SHOWN IN &IGURE s &%4#( &)234 RETRIEVES THE FIRST ROW OF QUERY RESULTS s &%4#( ,!34 RETRIEVES THE LAST ROW OF QUERY RESULTS
s &%4#( .%84 RETRIEVES THE ROW OF QUERY RESULTS THAT IMMEDIATELY FOLLOWS THE CURRENT ROW OF THE CURSOR 4HIS IS THE DEFAULT BEHAVIOR IF NO MOTION IS SPECIFIED AND CORRESPONDS TO THE STANDARD CURSOR MOTION s &%4#( !"3/,54% RETRIEVES A SPECIFIC ROW BY ITS ROW NUMBER s &%4#( 2%,!4)6% MOVES THE CURSOR FORWARD OR BACKWARD A SPECIFIC NUMBER OF ROWS RELATIVE TO ITS CURRENT POSITION
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s &%4#( 02)/2 RETRIEVES THE ROW OF QUERY RESULTS THAT IMMEDIATELY PRECEDES THE CURRENT ROW OF THE CURSOR
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3CROLL CURSORS CAN BE ESPECIALLY USEFUL IN PROGRAMS THAT ALLOW A USER TO BROWSE DATABASE CONTENTS )N RESPONSE TO THE USERS REQUEST TO MOVE FORWARD OR BACKWARD THROUGH THE DATA A ROW OR A SCREENFUL AT A TIME THE PROGRAM CAN SIMPLY FETCH THE REQUIRED ROWS OF THE QUERY RESULTS (OWEVER SCROLL CURSORS ARE ALSO A GREAT DEAL HARDER FOR THE $"-3 TO IMPLEMENT THAN A NORMAL UNIDIRECTIONAL CURSOR 4O SUPPORT A SCROLL CURSOR THE $"-3 MUST KEEP TRACK OF THE PREVIOUS QUERY RESULTS THAT IT PROVIDED FOR A PROGRAM AND OF THE ORDER IN WHICH IT SUPPLIED THOSE ROWS OF RESULTS 4HE $"-3 MUST ALSO ENSURE THAT NO OTHER CONCURRENTLY EXECUTING TRANSACTION MODIFIES ANY DATA THAT HAS BECOME VISIBLE TO A PROGRAM THROUGH A SCROLL CURSOR BECAUSE THE PROGRAM CAN USE THE EXTENDED &%4#( STATEMENT TO RE RETRIEVE THE ROW EVEN AFTER THE CURSOR HAS MOVED PAST THE ROW )F YOU USE A SCROLL CURSOR YOU SHOULD BE AWARE THAT CERTAIN &%4#( STATEMENTS ON A SCROLL CURSOR MAY HAVE A VERY HIGH OVERHEAD FOR SOME $"-3 BRANDS )F THE $"-3 BRAND NORMALLY CARRIES OUT A QUERY STEP BY STEP AS YOUR PROGRAM &%4#(ES ITS WAY DOWN THROUGH THE QUERY RESULTS YOUR PROGRAM MAY WAIT A MUCH LONGER TIME THAN NORMAL IF YOU REQUEST A &%4#( .%84 OPERATION WHEN THE CURSOR IS POSITIONED AT THE FIRST ROW OF QUERY RESULTS )TS BEST TO UNDERSTAND THE PERFORMANCE CHARACTERISTICS OF YOUR PARTICULAR $"-3 BRAND BEFORE WRITING PROGRAMS THAT DEPEND ON SCROLL CURSOR FUNCTIONALITY FOR PRODUCTION APPLICATIONS "ECAUSE OF THE USEFULNESS OF SCROLL CURSORS AND BECAUSE A FEW $"-3 VENDORS HAD BEGUN TO SHIP SCROLL CURSOR IMPLEMENTATIONS THAT WERE SLIGHTLY DIFFERENT FROM ONE ANOTHER THE 31, STANDARD WAS EXPANDED TO INCLUDE SUPPORT FOR SCROLL CURSORS 4HE %NTRY 31, LEVEL OF THE STANDARD REQUIRES ONLY THE OLDER STYLE SEQUENTIAL FORWARD CURSOR BUT CONFORMANCE AT THE )NTERMEDIATE 31, OR &ULL 31, LEVELS REQUIRES FULL SUPPORT FOR THE SCROLL CURSOR SYNTAX SHOWN IN &IGURE 4HE STANDARD ALSO SPECIFIES THAT IF ANY MOTION OTHER THAN &%4#( .%84 THE DEFAULT IS USED ON A CURSOR ITS $%#,!2% #523/2 STATEMENT MUST EXPLICITLY IDENTIFY IT AS A SCROLL CURSOR 5SING THE STANDARD SYNTAX THE CURSOR DECLARATION IN &IGURE WOULD APPEAR AS EXEC SQL DECLARE REPCURS SCROLL CURSOR FOR SELECT NAME QUOTA SALES FROM SALESREPS WHERE SALES QUOTA ORDER BY NAME
#URSOR "ASEDõ$ELETESõANDõ5PDATES !PPLICATION PROGRAMS OFTEN USE CURSORS TO ALLOW THE USER TO BROWSE THROUGH A TABLE OF DATA ROW BY ROW &OR EXAMPLE THE USER MAY ASK TO SEE ALL OF THE ORDERS PLACED BY A PARTICULAR CUSTOMER 4HE PROGRAM DECLARES A CURSOR FOR A QUERY OF THE /2$%23 TABLE AND DISPLAYS EACH
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ORDER ON THE SCREEN POSSIBLY IN A COMPUTER GENERATED FORM WAITING FOR A SIGNAL FROM THE USER TO ADVANCE TO THE NEXT ROW "ROWSING CONTINUES IN THIS FASHION UNTIL THE USER REACHES THE END OF THE QUERY RESULTS 4HE CURSOR SERVES AS A POINTER TO THE CURRENT ROW OF QUERY RESULTS )F THE QUERY DRAWS ITS DATA FROM A SINGLE TABLE AND IT IS NOT A SUMMARY QUERY AS IN THIS EXAMPLE THE CURSOR IMPLICITLY POINTS TO A ROW OF A DATABASE TABLE BECAUSE EACH ROW OF QUERY RESULTS IS DRAWN FROM A SINGLE ROW OF THE TABLE 7HILE BROWSING THE DATA THE USER MAY SPOT DATA THAT SHOULD BE CHANGED &OR EXAMPLE THE ORDER QUANTITY IN ONE OF THE ORDERS MAY BE INCORRECT OR THE CUSTOMER MAY WANT TO DELETE ONE OF THE ORDERS )N THIS SITUATION THE USER WANTS TO UPDATE OR DELETE THIS ORDER 4HE ROW IS NOT IDENTIFIED BY THE USUAL 31, SEARCH CONDITION RATHER THE PROGRAM USES THE CURSOR AS A POINTER TO INDICATE WHICH ROW IS TO BE UPDATED OR DELETED %MBEDDED 31, SUPPORTS THIS CAPABILITY THROUGH SPECIAL VERSIONS OF THE $%,%4% AND 50$!4% STATEMENTS CALLED THE POSITIONED $%,%4% AND POSITIONED 50$!4% STATEMENTS RESPECTIVELY 4HE POSITIONED $%,%4% STATEMENT SHOWN IN &IGURE DELETES A SINGLE ROW FROM A TABLE 4HE DELETED ROW IS THE CURRENT ROW OF A CURSOR THAT REFERENCES THE TABLE 4O PROCESS THE STATEMENT THE $"-3 LOCATES THE ROW OF THE BASE TABLE THAT CORRESPONDS TO THE CURRENT ROW OF THE CURSOR AND DELETES THAT ROW FROM THE BASE TABLE !FTER THE ROW IS DELETED THE CURSOR HAS NO CURRENT ROW )NSTEAD THE CURSOR IS EFFECTIVELY POSITIONED IN THE EMPTY SPACE LEFT BY THE DELETED ROW WAITING TO BE ADVANCED TO THE NEXT ROW BY A SUBSEQUENT &%4#( STATEMENT 4HE POSITIONED 50$!4% STATEMENT SHOWN IN &IGURE UPDATES A SINGLE ROW OF A TABLE 4HE UPDATED ROW IS THE CURRENT ROW OF A CURSOR THAT REFERENCES THE TABLE 4O PROCESS THE STATEMENT THE $"-3 LOCATES THE ROW OF THE BASE TABLE THAT CORRESPONDS TO THE CURRENT ROW OF THE CURSOR AND UPDATES THAT ROW AS SPECIFIED IN THE 3%4 CLAUSE !FTER THE ROW IS UPDATED IT REMAINS THE CURRENT ROW OF THE CURSOR &IGURE SHOWS AN ORDER BROWSING PROGRAM THAT USES THE POSITIONED 50$!4% AND $%,%4% STATEMENTS 4HE PROGRAM FIRST PROMPTS THE USER FOR A CUSTOMER NUMBER AND THEN QUERIES THE /2$%23 TABLE TO LOCATE ALL OF THE ORDERS PLACED BY THAT CUSTOMER
!S IT RETRIEVES EACH ROW OF QUERY RESULTS IT DISPLAYS THE ORDER INFORMATION ON THE SCREEN AND ASKS THE USER WHAT TO DO NEXT
)F THE USER TYPES AN . THE PROGRAM DOES NOT MODIFY THE CURRENT ORDER BUT MOVES DIRECTLY TO THE NEXT ORDER
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)F THE USER TYPES AN 8 THE PROGRAM HALTS THE QUERY AND TERMINATES
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!LTHOUGH IT IS PRIMITIVE COMPARED WITH A REAL APPLICATION PROGRAM THE EXAMPLE IN &IGURE SHOWS ALL OF THE LOGIC AND EMBEDDED 31, STATEMENTS REQUIRED TO IMPLEMENT A BROWSING APPLICATION WITH CURSOR BASED DATABASE UPDATES 4HE 31, STANDARD SPECIFIED THAT THE POSITIONED $%,%4% AND 50$!4% STATEMENTS CAN BE USED ONLY WITH CURSORS THAT MEET THESE VERY STRICT CRITERIA s 4HE QUERY ASSOCIATED WITH THE CURSOR MUST DRAW ITS DATA FROM A SINGLE SOURCE TABLE THAT IS THERE MUST BE ONLY ONE TABLE NAMED IN THE &2/- CLAUSE OF THE QUERY SPECIFIED IN THE $%#,!2% #523/2 STATEMENT s 4HE QUERY CANNOT SPECIFY AN /2$%2 "9 CLAUSE THE CURSOR MUST NOT IDENTIFY A SORTED SET OF QUERY RESULTS s 4HE QUERY CANNOT SPECIFY THE $)34).#4 KEYWORD s 4HE QUERY MUST NOT INCLUDE A '2/50 "9 OR A (!6).' CLAUSE s 4HE USER MUST HAVE THE 50$!4% OR $%,%4% PRIVILEGE AS APPROPRIATE ON THE BASE TABLE 4HE )"- DATABASES $" AND 31,$3 EXTENDED THE 31, RESTRICTIONS A STEP FURTHER 4HEY REQUIRE THAT THE CURSOR BE EXPLICITLY DECLARED AS AN UPDATEABLE CURSOR IN THE $%#,!2% #523/2 STATEMENT 4HE EXTENDED )"- FORM OF THE $%#,!2% #523/2 STATEMENT IS SHOWN IN &IGURE )N ADDITION TO DECLARING AN UPDATEABLE CURSOR THE &/2 50$!4% CLAUSE CAN OPTIONALLY SPECIFY PARTICULAR COLUMNS THAT MAY BE UPDATED THROUGH THE CURSOR )F THE COLUMN LIST IS SPECIFIED IN THE CURSOR DECLARATIONS POSITIONED 50$!4% STATEMENTS FOR THE CURSOR MAY UPDATE ONLY THOSE COLUMNS )N PRACTICE ALL COMMERCIAL 31, IMPLEMENTATIONS THAT SUPPORT POSITIONED $%,%4% AND 50$!4% STATEMENTS FOLLOW THE )"- 31, APPROACH )T IS A GREAT ADVANTAGE FOR THE $"-3 TO KNOW IN ADVANCE WHETHER A CURSOR WILL BE USED FOR UPDATES OR WHETHER ITS DATA WILL BE READ ONLY BECAUSE READ ONLY PROCESSING IS SIMPLER 4HE &/2 50$!4% CLAUSE PROVIDES THIS ADVANCE NOTICE AND CAN BE CONSIDERED A DE FACTO STANDARD OF THE EMBEDDED 31, "ECAUSE OF ITS WIDESPREAD USE SUBSEQUENT VERSIONS OF THE 31, STANDARD INCLUDE THE )"- STYLE &/2 50$!4% CLAUSE AS AN OPTION IN ITS $%#,!2% #523/2 STATEMENT (OWEVER UNLIKE THE )"- PRODUCTS THE 31, STANDARD AUTOMATICALLY ASSUMES THAT A CURSOR IS OPENED FOR UPDATE UNLESS IT IS A SCROLL CURSOR OR IT IS EXPLICITLY DECLARED &/2 2%!$ /.,9 4HE &/2 2%!$ /.,9 SPECIFICATION IN THE $%#,!2% #523/2 STATEMENT APPEARS IN EXACTLY THE SAME POSITION AS THE &/2 50$!4% CLAUSE AND EXPLICITLY TELLS THE $"-3 THAT THE PROGRAM WILL NOT
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ATTEMPT A POSITIONED $%,%4% OR 50$!4% OPERATION USING THE CURSOR "ECAUSE UPDATEABLE CURSORS CAN SIGNIFICANTLY AFFECT DATABASE OVERHEAD AND PERFORMANCE IT IS VERY IMPORTANT TO UNDERSTAND THE SPECIFIC ASSUMPTIONS THAT YOUR PARTICULAR $"-3 BRAND MAKES ABOUT THE UPDATEABILITY OF CURSORS AND THE CLAUSES OR STATEMENTS THAT CAN BE USED TO OVERRIDE THEM )N ADDITION PROGRAMS THAT EXPLICITLY DECLARE WHETHER THEIR INTENTION IS TO ALLOW UPDATES VIA AN OPENED CURSOR ARE MORE MAINTAINABLE
#URSORSõANDõ4RANSACTIONõ0ROCESSING 4HE WAY YOUR PROGRAM HANDLES ITS CURSORS CAN HAVE A MAJOR IMPACT ON DATABASE PERFORMANCE 2ECALL FROM #HAPTER THAT THE 31, TRANSACTION MODEL GUARANTEES THE CONSISTENCY OF DATA DURING A TRANSACTION )N CURSOR TERMS THIS MEANS THAT YOUR PROGRAM CAN DECLARE A CURSOR OPEN IT FETCH THE QUERY RESULTS CLOSE IT REOPEN IT AND FETCH THE QUERY RESULTS AGAINAND BE GUARANTEED THAT THE QUERY RESULTS WILL BE IDENTICAL BOTH TIMES 4HE PROGRAM CAN ALSO FETCH THE SAME ROW THROUGH TWO DIFFERENT CURSORS AND BE GUARANTEED THAT THE RESULTS WILL BE IDENTICAL )N FACT THE DATA IS GUARANTEED TO REMAIN CONSISTENT UNTIL YOUR PROGRAM ISSUES A #/--)4 OR 2/,,"!#+ TO END THE TRANSACTION "ECAUSE THE CONSISTENCY IS NOT GUARANTEED ACROSS TRANSACTIONS BOTH THE #/--)4 AND 2/,,"!#+ STATEMENTS AUTOMATICALLY CLOSE ALL OPEN CURSORS "EHIND THE SCENES THE $"-3 PROVIDES THIS CONSISTENCY GUARANTEE BY LOCKING ALL OF THE ROWS OF QUERY RESULTS PREVENTING OTHER USERS FROM MODIFYING THEM )F THE QUERY PRODUCES MANY ROWS OF DATA A MAJOR PORTION OF A TABLE MAY BE LOCKED BY THE CURSOR &URTHERMORE IF YOUR PROGRAM WAITS FOR USER INPUT AFTER FETCHING EACH ROW FOR EXAMPLE TO LET THE USER VERIFY DATA DISPLAYED ON THE SCREEN PARTS OF THE DATABASE MAY BE LOCKED FOR A VERY LONG TIME )N AN EXTREME CASE THE USER MIGHT LEAVE FOR LUNCH IN MID TRANSACTION LOCKING OUT OTHER USERS FOR AN HOUR OR MORE 4O MINIMIZE THE AMOUNT OF LOCKING REQUIRED YOU SHOULD FOLLOW THESE GUIDELINES WHEN WRITING INTERACTIVE QUERY PROGRAMS s +EEP TRANSACTIONS AS SHORT AS POSSIBLE s )SSUE A #/--)4 STATEMENT AT REASONABLE INTERVALS DURING PROCESSING )T IS SOMETIMES TEMPTING TO ISSUE A #/--)4 AFTER EVERY ).3%24 50$!4% AND $%,%4% BUT PROCESSING A COMMIT ADDS TO OVERHEAD SO THERES A TRADE OFF BETWEEN RELEASING LOCKS IN A TIMELY MANNER AND PROCESSING EFFICIENCY
s )F YOU KNOW THAT THE PROGRAM WILL NOT TRY TO REFETCH A ROW OF DATA AFTER THE CURSOR HAS MOVED PAST IT USE ONE OF THE LESS RESTRICTIVE ISOLATION MODES DESCRIBED IN #HAPTER 4HIS ALLOWS THE $"-3 TO UNLOCK A ROW AS SOON AS THE NEXT &%4#( STATEMENT IS ISSUED s !VOID THE USE OF SCROLL CURSORS UNLESS YOU HAVE TAKEN OTHER ACTIONS TO ELIMINATE OR MINIMIZE THE EXTRA DATABASE LOCKING THEY WILL CAUSE s %XPLICITLY SPECIFY A 2%!$ /.,9 CURSOR IF POSSIBLE
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3UMMARY )N ADDITION TO ITS ROLE AS AN INTERACTIVE DATABASE LANGUAGE 31, IS USED FOR PROGRAMMATIC ACCESS TO RELATIONAL DATABASES s 4HE MOST COMMON TECHNIQUE FOR PROGRAMMATIC USE OF 31, IS EMBEDDED 31, WHERE 31, STATEMENTS ARE EMBEDDED INTO THE APPLICATION PROGRAM INTERMIXED WITH THE STATEMENTS OF A HOST PROGRAMMING LANGUAGE SUCH AS # OR #/"/, s %MBEDDED 31, STATEMENTS ARE PROCESSED BY A SPECIAL 31, PRECOMPILER 4HEY BEGIN WITH A SPECIAL INTRODUCER USUALLY %8%# 31, AND END WITH A TERMINATOR WHICH VARIES FROM ONE HOST LANGUAGE TO ANOTHER s 6ARIABLES FROM THE APPLICATION PROGRAM CALLED HOST VARIABLES CAN BE USED IN EMBEDDED 31, STATEMENTS WHEREVER A CONSTANT CAN APPEAR 4HESE INPUT HOST VARIABLES TAILOR THE EMBEDDED 31, STATEMENT TO THE PARTICULAR SITUATION s (OST VARIABLES ARE ALSO USED TO RECEIVE THE RESULTS OF DATABASE QUERIES 4HE VALUES OF THESE OUTPUT HOST VARIABLES CAN THEN BE PROCESSED BY THE APPLICATION PROGRAM s 1UERIES THAT PRODUCE A SINGLE ROW OF DATA ARE HANDLED WITH THE SINGLETON 3%,%#4 STATEMENT OF EMBEDDED 31, WHICH SPECIFIES BOTH THE QUERY AND THE HOST VARIABLES TO RECEIVE THE RETRIEVED DATA s 1UERIES THAT PRODUCE MULTIPLE ROWS OF QUERY RESULTS ARE HANDLED WITH CURSORS IN EMBEDDED 31, 4HE $%#,!2% #523/2 STATEMENT DEFINES THE QUERY THE /0%. STATEMENT BEGINS QUERY PROCESSING THE &%4#( STATEMENT RETRIEVES SUCCESSIVE ROWS OF QUERY RESULTS AND THE #,/3% STATEMENT ENDS QUERY PROCESSING &OR APPLICATIONS THAT NEED TO MOVE THROUGH THE CURSOR RESULTS IN A NONSEQUENTIAL MANNER A SCROLLABLE CURSOR CAN BE USED IF SUPPORTED BY THE $"-3 PRODUCT s 4HE POSITIONED 50$!4% AND $%,%4% STATEMENTS CAN BE USED TO UPDATE OR DELETE THE ROW CURRENTLY SELECTED BY A CURSOR
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HE EMBEDDED 31, PROGRAMMING FEATURES DESCRIBED IN #HAPTER ARE COLLECTIVELY KNOWN AS STATIC 31, 3TATIC 31, IS ADEQUATE FOR WRITING ALL OF THE PROGRAMS TYPICALLY REQUIRED IN A DATA PROCESSING APPLICATION &OR EXAMPLE IN THE ORDER PROCESSING APPLICATION OF THE SAMPLE DATABASE YOU CAN USE STATIC 31, TO WRITE PROGRAMS THAT HANDLE ORDER ENTRY ORDER UPDATES ORDER INQUIRIES CUSTOMER INQUIRIES CUSTOMER FILE MAINTENANCE AND PROGRAMS THAT PRODUCE ALL TYPES OF REPORTS )N EVERY ONE OF THESE PROGRAMS THE PATTERN OF DATABASE ACCESS IS DECIDED BY THE PROGRAMMER AND HARD CODED INTO THE PROGRAM AS A SERIES OF EMBEDDED 31, STATEMENTS 4HERE IS AN IMPORTANT CLASS OF APPLICATIONS HOWEVER WHERE THE PATTERN OF DATABASE ACCESS CANNOT BE DETERMINED IN ADVANCE ! GRAPHIC QUERY TOOL OR A REPORT WRITER FOR EXAMPLE MUST BE ABLE TO DECIDE AT RUNTIME WHICH 31, STATEMENTS IT WILL USE TO ACCESS THE DATABASE ! PERSONAL COMPUTER SPREADSHEET THAT SUPPORTS HOST DATABASE ACCESS MUST ALSO BE ABLE TO SEND A QUERY TO THE HOST $"-3 FOR EXECUTION ON THE FLY 4HESE PROGRAMS AND OTHER GENERAL PURPOSE DATABASE FRONT ENDS CANNOT BE WRITTEN USING STATIC 31, TECHNIQUES 4HEY REQUIRE AN ADVANCED FORM OF EMBEDDED 31, CALLED DYNAMIC 31, DESCRIBED IN THIS CHAPTER
,IMITATIONSõOFõ3TATICõ31, !S THE NAME STATIC 31, IMPLIES A PROGRAM BUILT USING THE EMBEDDED 31, FEATURES DESCRIBED IN #HAPTER HOST VARIABLES CURSORS AND THE $%#,!2% #523/2 /0%. &%4#( AND #,/3% STATEMENTS HAS A RELATIVELY STABLE PATTERN OF DATABASE ACCESS &OR EACH EMBEDDED 31, STATEMENT IN THE PROGRAM THE TABLES AND COLUMNS REFERENCED BY THAT STATEMENT ARE DETERMINED IN ADVANCE BY THE PROGRAMMER AND HARD CODED INTO THE EMBEDDED 31, STATEMENT )NPUT HOST VARIABLES PROVIDE SOME FLEXIBILITY IN STATIC 31, BUT THEY DONT FUNDAMENTALLY ALTER ITS STATIC NATURE 2ECALL THAT A HOST VARIABLE CAN APPEAR ANYWHERE A CONSTANT IS ALLOWED IN A 31, STATEMENT 9OU CAN USE A HOST VARIABLE TO ALTER A SEARCH CONDITION EXEC SQL SELECT NAME QUOTA SALES FROM SALESREPS WHERE QUOTA CUTOFF?AMOUNT
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9OU CAN ALSO USE A HOST VARIABLE TO CHANGE THE DATA INSERTED OR UPDATED IN A DATABASE EXEC SQL UPDATE SALESREPS SET QUOTA QUOTA INCREASE WHERE QUOTA CUTOFF?AMOUNT
(OWEVER YOU CANNOT USE A HOST VARIABLE IN PLACE OF A TABLE NAME OR A COLUMN REFERENCE 4HE ATTEMPTED USE OF THE HOST VARIABLES WHICH?TABLE AND WHICH?COLUMN IN THESE STATEMENTS IS ILLEGAL EXEC SQL UPDATE WHICH?TABLE SET WHICH?COLUMN EXEC SQL DECLARE CURSOR CURSOR FOR SELECT FROM WHICH?TABLE
%VEN IF YOU COULD USE A HOST VARIABLE IN THIS WAY AND YOU CANNOT ANOTHER PROBLEM WOULD IMMEDIATELY ARISE 4HE NUMBER OF COLUMNS PRODUCED BY THE QUERY IN THE SECOND STATEMENT WOULD VARY DEPENDING ON WHICH TABLE WAS SPECIFIED BY THE HOST VARIABLE &OR THE /&&)#%3 TABLE THE QUERY RESULTS WOULD HAVE SIX COLUMNS FOR THE 3!,%32%03 TABLE THEY WOULD HAVE NINE COLUMNS &URTHERMORE THE DATA TYPES OF THE COLUMNS WOULD BE DIFFERENT FOR THE TWO TABLES "UT TO WRITE A &%4#( STATEMENT FOR THE QUERY YOU MUST KNOW IN ADVANCE HOW MANY COLUMNS OF QUERY RESULTS THERE WILL BE AND THEIR DATA TYPES BECAUSE YOU MUST SPECIFY A HOST VARIABLE TO RECEIVE EACH COLUMN EXEC SQL FETCH CURSOR INTO VAR VAR VAR
!S THIS DISCUSSION ILLUSTRATES IF A PROGRAM MUST BE ABLE TO DETERMINE AT RUNTIME WHICH 31, STATEMENTS IT WILL USE OR WHICH TABLES AND COLUMNS IT WILL REFERENCE STATIC 31, IS INADEQUATE FOR THE TASK $YNAMIC 31, OVERCOMES THESE LIMITATIONS $YNAMIC 31, HAS BEEN SUPPORTED BY THE )"- 31, PRODUCTS SINCE THEIR INTRODUCTION AND IT HAS BEEN SUPPORTED FOR MANY YEARS BY THE MINICOMPUTER BASED AND 5.)8 BASED COMMERCIAL 2$"-3 PRODUCTS (OWEVER DYNAMIC 31, WAS NOT SPECIFIED BY THE ORIGINAL !.3))3/ 31, STANDARD THE STANDARD DEFINED ONLY STATIC 31, 4HE ABSENCE OF DYNAMIC 31, FROM THE 31, STANDARD IS IRONIC GIVEN THE POPULAR NOTION THAT THE STANDARD ALLOWED YOU TO BUILD FRONT END DATABASE TOOLS THAT ARE PORTABLE ACROSS MANY DIFFERENT $"-3 BRANDS )N FACT SUCH FRONT END TOOLS MUST ALMOST ALWAYS BE BUILT USING DYNAMIC 31, )N THE ABSENCE OF AN !.3))3/ STANDARD $" SET THE DE FACTO STANDARD FOR DYNAMIC 31, 4HE OTHER )"- DATABASES OF THE DAY 31,$3 AND /3 %XTENDED %DITION WERE NEARLY IDENTICAL TO $" IN THEIR DYNAMIC 31, SUPPORT AND MOST OTHER 31, PRODUCTS ALSO FOLLOWED THE $" STANDARD /FFICIAL SUPPORT FOR DYNAMIC 31, WAS ADDED TO THE 31, STANDARD IN VERSION 31, MOSTLY FOLLOWING THE PATH SET BY )"- 4HE 31, STANDARD DOES NOT REQUIRE DYNAMIC 31, SUPPORT AT THE LOWEST LEVEL OF COMPLIANCE %NTRY BUT DYNAMIC 31, SUPPORT IS REQUIRED FOR PRODUCTS CLAIMING THE )NTERMEDIATE OR &ULL COMPLIANCE LEVELS TO THE 31, STANDARD
#HAPTERçç
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$YNAMICõ31,õ#ONCEPTS 4HE CENTRAL CONCEPT OF DYNAMIC 31, IS SIMPLE DONT HARD CODE AN EMBEDDED 31, STATEMENT INTO THE PROGRAMS SOURCE CODE )NSTEAD LET THE PROGRAM BUILD THE TEXT OF A 31, STATEMENT IN ONE OF ITS DATA AREAS AT RUNTIME 4HE PROGRAM THEN PASSES THE STATEMENT TEXT TO THE $"-3 FOR EXECUTION ON THE FLY !LTHOUGH THE DETAILS GET QUITE COMPLEX ALL OF DYNAMIC 31, IS BUILT ON THIS SIMPLE CONCEPT AND ITS A GOOD IDEA TO KEEP IT IN MIND 4O UNDERSTAND DYNAMIC 31, AND HOW IT COMPARES WITH STATIC 31, ITS USEFUL TO CONSIDER ONCE AGAIN THE PROCESS THE $"-3 GOES THROUGH TO EXECUTE A 31, STATEMENT ORIGINALLY SHOWN IN &IGURE AND REPEATED HERE IN &IGURE 2ECALL FROM #HAPTER THAT A STATIC 31, STATEMENT GOES THROUGH THE FIRST FOUR STEPS OF THE PROCESS AT COMPILE TIME 4HE ").$ UTILITY OR THE EQUIVALENT PART OF THE $"-3 RUNTIME SYSTEM ANALYZES THE 31, STATEMENT DETERMINES THE BEST WAY TO CARRY IT OUT AND STORES THE APPLICATION PLAN FOR THE STATEMENT IN THE DATABASE AS PART OF THE PROGRAM DEVELOPMENT PROCESS 7HEN THE STATIC 31, STATEMENT IS EXECUTED AT RUNTIME THE $"-3 SIMPLY EXECUTES THE STORED APPLICATION PLAN )N DYNAMIC 31, THE SITUATION IS QUITE DIFFERENT 4HE 31, STATEMENT TO BE EXECUTED ISNT KNOWN UNTIL RUNTIME SO THE $"-3 CANNOT PREPARE FOR THE STATEMENT IN ADVANCE 7HEN THE PROGRAM IS ACTUALLY EXECUTED THE $"-3 RECEIVES THE TEXT OF THE STATEMENT TO BE DYNAMICALLY EXECUTED CALLED THE STATEMENT STRING AND GOES THROUGH ALL FIVE OF THE STEPS SHOWN IN &IGURE AT RUNTIME
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!S YOU MIGHT EXPECT DYNAMIC 31, IS LESS EFFICIENT THAN STATIC 31, &OR THIS REASON STATIC 31, IS USED WHENEVER POSSIBLE AND MANY APPLICATION PROGRAMMERS NEVER NEED TO LEARN ABOUT DYNAMIC 31, (OWEVER DYNAMIC 31, HAS GROWN IN IMPORTANCE AS MORE AND MORE DATABASE ACCESS MOVED TO A CLIENTSERVER FRONT ENDBACK END ARCHITECTURE $ATABASE ACCESS FROM WITHIN PERSONAL COMPUTER APPLICATIONS SUCH AS SPREADSHEETS AND WORD PROCESSORS HAS GROWN DRAMATICALLY AND AN ENTIRE SET OF 0# BASED FRONT END DATA ENTRY AND DATA ACCESS TOOLS HAS EMERGED !LL OF THESE APPLICATIONS REQUIRE THE FEATURES OF DYNAMIC 31, 4HE EMERGENCE OF )NTERNET BASED THREE TIER ARCHITECTURESWITH APPLICATIONS LOGIC EXECUTING ON ONE MID TIER SYSTEM OFTEN COMPOSED OF ONE OR MORE APPLICATION SERVERS AND THE DATABASE LOGIC EXECUTING ON ANOTHER BACK END SYSTEMHAS ADDED NEW IMPORTANCE TO CAPABILITIES THAT HAVE GROWN OUT OF DYNAMIC 31, )N MOST OF THESE THREE TIER ENVIRONMENTS THE APPLICATIONS LOGIC RUNNING IN THE MIDDLE TIER IS QUITE DYNAMIC )T MUST BE CHANGED FREQUENTLY TO RESPOND TO NEW BUSINESS CONDITIONS AND TO IMPLEMENT NEW BUSINESS RULES 4HIS FREQUENTLY CHANGING ENVIRONMENT IS AT ODDS WITH THE VERY TIGHT COUPLING OF APPLICATIONS PROGRAMS AND DATABASE CONTENTS IMPLIED BY STATIC 31, !S A RESULT MOST THREE TIER ARCHITECTURES USE A CALLABLE 31, !0) DESCRIBED IN #HAPTER TO LINK THE MIDDLE TIER TO BACK END DATABASES 4HESE !0)S EXPLICITLY BORROW THE KEY CONCEPTS OF DYNAMIC 31, FOR EXAMPLE SEPARATE 02%0!2% AND %8%#54% STEPS AND THE %8%#54% )--%$)!4% CAPABILITY TO PROVIDE THEIR DATABASE ACCESS ! SOLID UNDERSTANDING OF DYNAMIC 31, CONCEPTS IS THUS IMPORTANT TO HELP A PROGRAMMER UNDERSTAND WHATS GOING ON BEHIND THE SCENES OF THE 31, !0) )N PERFORMANCE SENSITIVE APPLICATIONS THIS UNDERSTANDING CAN MAKE ALL THE DIFFERENCE BETWEEN AN APPLICATION DESIGN THAT PROVIDES GOOD PERFORMANCE AND RESPONSE TIMES AND ONE THAT DOES NOT
$YNAMICõ3TATEMENTõ%XECUTIONõ%8%#54%õ)--%$)!4% 4HE SIMPLEST FORM OF DYNAMIC 31, IS PROVIDED BY THE %8%#54% )--%$)!4% STATEMENT SHOWN IN &IGURE 4HIS STATEMENT PASSES THE TEXT OF A DYNAMIC 31, STATEMENT TO THE $"-3 AND ASKS THE $"-3 TO EXECUTE THE DYNAMIC STATEMENT IMMEDIATELY 4O USE THIS STATEMENT YOUR PROGRAM GOES THROUGH THE FOLLOWING STEPS
4HE PROGRAM CONSTRUCTS A 31, STATEMENT AS A STRING OF TEXT IN ONE OF ITS DATA AREAS STORING IT IN MEMORY AS A NAMED VARIABLE 2ECALL THAT PROGRAM LANGUAGE VARIABLES USED TO PASS INFORMATION TO OR FROM THE $"-3 ARE KNOWN AS HOST VARIABLES 4HE STATEMENT CAN BE ALMOST ANY 31, STATEMENT THAT DOES NOT RETRIEVE DATA
4HE PROGRAM PASSES THE 31, STATEMENT TO THE $"-3 WITH THE %8%#54% )--%$)!4% STATEMENT
4HE $"-3 EXECUTES THE STATEMENT AND SETS THE 31,#/$%31,34!4% VALUES TO INDICATE THE COMPLETION STATUS EXACTLY AS IF THE STATEMENT HAD BEEN HARD CODED USING STATIC 31,
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&IGURE SHOWS A SIMPLE # PROGRAM THAT FOLLOWS THESE STEPS 4HE PROGRAM PROMPTS THE USER FOR A TABLE NAME AND A 31, SEARCH CONDITION AND BUILDS THE TEXT OF A $%,%4% STATEMENT BASED ON THE USERS RESPONSES 4HE PROGRAM THEN USES THE %8%#54% )--%$)!4% STATEMENT TO EXECUTE THE $%,%4% STATEMENT 4HIS PROGRAM CANNOT USE A STATIC 31, EMBEDDED $%,%4% STATEMENT BECAUSE NEITHER THE TABLE NAME NOR THE SEARCH CONDITION IS KNOWN UNTIL THE USER ENTERS THEM AT RUNTIME )T MUST USE DYNAMIC 31, )F YOU RUN THE PROGRAM IN &IGURE WITH THESE INPUTS %NTER TABLE NAME STAFF %NTER SEARCH CONDITION QUOTA $ELETE FROM STAFF SUCCESSFUL
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THE PROGRAM PASSES THIS STATEMENT TEXT TO THE $"-3 DELETE FROM STAFF WHERE QUOTA
)F YOU RUN THE PROGRAM WITH THESE INPUTS %NTER TABLE NAME ORDERS %NTER SEARCH CONDITION CUST $ELETE FROM ORDERS SUCCESSFUL
THE PROGRAM PASSES THIS STATEMENT TEXT TO THE $"-3 DELETE FROM ORDERS WHERE CUST
4HE %8%#54% )--%$)!4% STATEMENT THUS GIVES THE PROGRAM GREAT FLEXIBILITY IN THE TYPE OF $%,%4% STATEMENT THAT IT EXECUTES 4HE %8%#54% )--%$)!4% STATEMENT USES EXACTLY ONE HOST VARIABLETHE VARIABLE CONTAINING THE ENTIRE 31, STATEMENT STRING 4HE STATEMENT STRING ITSELF CANNOT INCLUDE HOST VARIABLE REFERENCES BUT THERES NO NEED FOR THEM )NSTEAD OF USING A STATIC 31, STATEMENT WITH A HOST VARIABLE LIKE THIS EXEC SQL DELETE FROM ORDERS WHERE CUST CUST?NUM
A DYNAMIC 31, PROGRAM ACHIEVES THE SAME EFFECT BY BUILDING THE ENTIRE STATEMENT IN A BUFFER AND EXECUTING IT SPRINTFBUFFER DELETE FROM ORDERS WHERE CUST D CUST?NUM EXEC SQL EXECUTE IMMEDIATE BUFFER
4HE %8%#54% )--%$)!4% STATEMENT IS THE SIMPLEST FORM OF DYNAMIC 31, BUT IT IS VERY VERSATILE 9OU CAN USE IT TO DYNAMICALLY EXECUTE MOST $-, STATEMENTS INCLUDING ).3%24 $%,%4% 50$!4% #/--)4 AND 2/,,"!#+ 9OU CAN ALSO USE %8%#54% )--%$)!4% TO DYNAMICALLY EXECUTE MOST $$, STATEMENTS INCLUDING THE #2%!4% $2/0 '2!.4 AND 2%6/+% STATEMENTS 4HE %8%#54% )--%$)!4% STATEMENT DOES HAVE ONE SIGNIFICANT LIMITATION HOWEVER 9OU CANNOT USE IT TO DYNAMICALLY EXECUTE A 3%,%#4 STATEMENT BECAUSE IT DOES NOT PROVIDE A MECHANISM TO PROCESS THE QUERY RESULTS *UST AS STATIC 31, REQUIRES CURSORS AND SPECIAL PURPOSE STATEMENTS $%#,!2% #523/2 /0%. &%4#( AND #,/3% FOR PROGRAMMATIC QUERIES DYNAMIC 31, USES CURSORS AND SOME NEW SPECIAL PURPOSE STATEMENTS TO HANDLE DYNAMIC QUERIES 4HE DYNAMIC 31, FEATURES THAT SUPPORT DYNAMIC QUERIES ARE DISCUSSED LATER IN THE SECTION h$YNAMIC 1UERIESv !S A NOTE OF CAUTION USER INPUT SHOULD NOT BE PLACED DIRECTLY INTO 31, STATEMENTS AS SHOWN IN THE PRECEDING SIMPLIFIED EXAMPLES WITHOUT FIRST PARSING THEM FOR ESCAPE AND TERMINATION CHARACTERS $OING SO WOULD PERMIT A HACKER TO INCLUDE CHARACTERS IN THE INPUT THAT WOULD TERMINATE THE INTENDED 31, STATEMENT AND APPEND ANOTHER ONE TO THE END OF IT ALLOWING UNAUTHORIZED ACCESS TO OTHER DATA IN THE DATABASEA TECHNIQUE KNOWN AS SQL INJECTION
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$YNAMICç31, ç
4WO 3TEPõ$YNAMICõ%XECUTION 4HE %8%#54% )--%$)!4% STATEMENT PROVIDES ONE STEP SUPPORT FOR DYNAMIC STATEMENT EXECUTION !S DESCRIBED PREVIOUSLY THE $"-3 GOES THROUGH ALL FIVE STEPS OF &IGURE FOR THE DYNAMICALLY EXECUTED STATEMENT 4HE OVERHEAD OF THIS PROCESS CAN BE VERY SIGNIFICANT IF YOUR PROGRAM EXECUTES MANY DYNAMIC STATEMENTS AND ITS WASTEFUL IF THE STATEMENTS TO BE EXECUTED ARE IDENTICAL OR VERY SIMILAR )N PRACTICE THE %8%#54% )--%$)!4% STATEMENT SHOULD BE USED ONLY FOR ONE TIME STATEMENTS THAT WILL BE EXECUTED ONCE BY A PROGRAM AND THEN NEVER EXECUTED AGAIN 4O DEAL WITH THE LARGE OVERHEAD OF THE ONE STEP APPROACH DYNAMIC 31, OFFERS AN ALTERNATIVE TWO STEP METHOD FOR EXECUTING 31, STATEMENTS DYNAMICALLY )N PRACTICE THIS TWO STEP APPROACH SEPARATING STATEMENT PREPARATION AND STATEMENT EXECUTION IS USED FOR ALL 31, STATEMENTS IN A PROGRAM THAT IS EXECUTED MORE THAN ONCE AND ESPECIALLY FOR THOSE THAT ARE EXECUTED REPEATEDLY HUNDREDS OR THOUSANDS OF TIMES IN RESPONSE TO USER INTERACTION (ERE IS AN OVERVIEW OF THE TWO STEP TECHNIQUE 4HE PROGRAM CONSTRUCTS A 31, STATEMENT STRING IN A BUFFER JUST AS IT DOES FOR THE %8%#54% )--%$)!4% STATEMENT ! QUESTION MARK CAN BE SUBSTITUTED FOR A CONSTANT ANYWHERE IN THE STATEMENT TEXT TO INDICATE THAT A VALUE FOR THE CONSTANT WILL BE SUPPLIED LATER 4HE QUESTION MARK IS CALLED A PARAMETER MARKER BUT DEVELOPERS OFTEN USE THE TERM PLACEHOLDER
4HE 02%0!2% STATEMENT ASKS THE $"-3 TO PARSE VALIDATE AND OPTIMIZE THE STATEMENT AND TO GENERATE AN APPLICATION PLAN FOR IT 4HIS IS 3TEP OF THE $"-3 INTERACTION 4HE $"-3 SETS THE 31,#/$%31,34!4% VALUES TO INDICATE ANY ERRORS FOUND IN THE STATEMENT AND RETAINS THE APPLICATION PLAN FOR LATER EXECUTION .OTE THAT THE $"-3 DOES NOT EXECUTE THE PLAN IN RESPONSE TO THE 02%0!2% STATEMENT
7HEN THE PROGRAM WANTS TO EXECUTE THE PREVIOUSLY PREPARED STATEMENT IT USES THE %8%#54% STATEMENT AND PASSES A VALUE FOR EACH PARAMETER MARKER TO THE $"-3 4HIS IS 3TEP OF THE $"-3 INTERACTION 4HE $"-3 SUBSTITUTES THE PARAMETER VALUES EXECUTES THE PREVIOUSLY GENERATED APPLICATION PLAN AND SETS THE 31,#/$%31,34!4% VALUES TO INDICATE ITS COMPLETION STATUS
4HE PROGRAM CAN USE THE %8%#54% STATEMENT REPEATEDLY SUPPLYING DIFFERENT PARAMETER VALUES EACH TIME THE DYNAMIC STATEMENT IS EXECUTED 4HE $"-3 CAN SIMPLY REPEAT 3TEP OF THE INTERACTION SINCE THE WORK IN 3TEP HAS ALREADY BEEN DONE AND THE RESULTS OF THAT WORK THE APPLICATION PLAN FOR EXECUTION WILL STILL BE VALID
&IGURE SHOWS A # PROGRAM THAT USES THESE STEPS WHICH ARE LABELED BY THE CALLOUT NUMBERS IN THE FIGURE 4HE PROGRAM IS A GENERAL PURPOSE TABLE UPDATE PROGRAM )T PROMPTS THE USER FOR A TABLE NAME AND TWO COLUMN NAMES AND CONSTRUCTS AN 50$!4% STATEMENT FOR THE TABLE THAT LOOKS LIKE THIS UPDATE TABLE NAME SET SECOND COLUMN NAME WHERE FIRST COLUMN NAME
4HE USERS INPUT THUS DETERMINES THE TABLE TO BE UPDATED THE COLUMN TO BE UPDATED AND THE SEARCH CONDITION TO BE USED 4HE SEARCH COMPARISON VALUE AND THE UPDATED DATA VALUE ARE SPECIFIED AS PARAMETERS TO BE SUPPLIED LATER WHEN THE 50$!4% STATEMENT IS ACTUALLY EXECUTED
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!FTER BUILDING THE 50$!4% STATEMENT TEXT IN ITS BUFFER THE PROGRAM ASKS THE $"-3 TO COMPILE IT WITH THE 02%0!2% STATEMENT 4HE PROGRAM THEN ENTERS A LOOP PROMPTING THE USER TO ENTER PAIRS OF PARAMETER VALUES TO PERFORM A SEQUENCE OF TABLE UPDATES 4HIS USER DIALOG SHOWS HOW YOU COULD USE THE PROGRAM IN &IGURE TO UPDATE THE QUOTAS FOR SELECTED SALESPEOPLE %NTER NAME OF TABLE TO BE UPDATED STAFF %NTER NAME OF COLUMN TO BE SEARCHED EMPL?NUM %NTER NAME OF COLUMN TO BE UPDATED QUOTA %NTER SEARCH VALUE FOR EMPL?NUM %NTER NEW VALUE FOR QUOTA !NOTHER YN Y %NTER SEARCH VALUE FOR EMPL?NUM %NTER NEW VALUE FOR QUOTA !NOTHER YN Y %NTER SEARCH VALUE FOR EMPL?NUM %NTER NEW VALUE FOR QUOTA !NOTHER YN N 5PDATES COMPLETE
4HIS PROGRAM IS A GOOD EXAMPLE OF A SITUATION WHERE TWO STEP DYNAMIC EXECUTION IS APPROPRIATE 4HE $"-3 COMPILES THE DYNAMIC 50$!4% STATEMENT ONLY ONCE BUT EXECUTES IT THREE TIMES ONCE FOR EACH SET OF PARAMETER VALUES ENTERED BY THE USER )F THE PROGRAM HAD BEEN WRITTEN USING %8%#54% )--%$)!4% INSTEAD THE DYNAMIC 50$!4% STATEMENT WOULD HAVE BEEN COMPILED THREE TIMES AND EXECUTED THREE TIMES 4HUS THE TWO STEP DYNAMIC EXECUTION OF 02%0!2% AND %8%#54% HELPS TO ELIMINATE SOME OF THE PERFORMANCE DISADVANTAGE OF DYNAMIC 31, !S MENTIONED EARLIER THIS SAME TWO STEP APPROACH IS USED BY ALL OF THE CALLABLE 31, !0)S DESCRIBED IN #HAPTER
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4HE 02%0!2% STATEMENT SHOWN IN &IGURE IS UNIQUE TO DYNAMIC 31, )T ACCEPTS A HOST VARIABLE CONTAINING A 31, STATEMENT STRING AND PASSES THE STATEMENT TO THE $"-3 4HE $"-3 COMPILES THE STATEMENT TEXT AND PREPARES IT FOR EXECUTION BY GENERATING AN APPLICATION PLAN 4HE $"-3 SETS THE 31,#/$%31,34!4% VARIABLES TO INDICATE ANY ERRORS DETECTED IN THE STATEMENT TEXT !S DESCRIBED PREVIOUSLY THE STATEMENT STRING CAN CONTAIN A PARAMETER MARKER INDICATED BY A QUESTION MARK ANYWHERE THAT A CONSTANT CAN APPEAR 4HE PARAMETER MARKER SIGNALS THE $"-3 THAT A VALUE FOR THE PARAMETER WILL BE SUPPLIED LATER WHEN THE STATEMENT IS ACTUALLY EXECUTED
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0ROGRAMMINGçWITHç31,
!S A RESULT OF THE 02%0!2% STATEMENT THE $"-3 ASSIGNS THE SPECIFIED STATEMENT NAME TO THE PREPARED STATEMENT 4HE STATEMENT NAME IS A 31, IDENTIFIER LIKE A CURSOR NAME 9OU SPECIFY THE STATEMENT NAME IN SUBSEQUENT %8%#54% STATEMENTS WHEN YOU WANT TO EXECUTE THE STATEMENT $"-3 BRANDS DIFFER IN HOW LONG THEY RETAIN THE PREPARED STATEMENT AND THE ASSOCIATED STATEMENT NAME &OR SOME BRANDS THE PREPARED STATEMENT CAN BE REEXECUTED ONLY UNTIL THE END OF THE CURRENT TRANSACTION THAT IS UNTIL THE NEXT #/--)4 OR 2/,,"!#+ STATEMENT )F YOU WANT TO EXECUTE THE SAME DYNAMIC STATEMENT LATER DURING ANOTHER TRANSACTION YOU MUST PREPARE IT AGAIN /THER BRANDS RELAX THIS RESTRICTION AND RETAIN THE PREPARED STATEMENT THROUGHOUT THE CURRENT SESSION WITH THE $"-3 4HE !.3))3/ 31, STANDARD ACKNOWLEDGES THESE DIFFERENCES AND EXPLICITLY SAYS THAT THE VALIDITY OF A PREPARED STATEMENT OUTSIDE OF THE CURRENT TRANSACTION IS IMPLEMENTATION DEPENDENT 4HE 02%0!2% STATEMENT CAN BE USED TO PREPARE ALMOST ANY EXECUTABLE $-, OR $$, STATEMENT INCLUDING THE 3%,%#4 STATEMENT %MBEDDED 31, STATEMENTS THAT ARE ACTUALLY PRECOMPILER DIRECTIVES SUCH AS THE 7(%.%6%2 OR $%#,!2% #523/2 STATEMENTS CANNOT BE PREPARED OF COURSE BECAUSE THEY ARE NOT EXECUTABLE
4HEõ%8%#54%õ3TATEMENT 4HE %8%#54% STATEMENT SHOWN IN &IGURE IS UNIQUE TO DYNAMIC 31, )T ASKS THE $"-3 TO EXECUTE A STATEMENT PREVIOUSLY PREPARED WITH THE 02%0!2% STATEMENT 9OU CAN EXECUTE ANY STATEMENT THAT CAN BE PREPARED WITH ONE EXCEPTION ,IKE THE %8%#54% )--%$)!4% STATEMENT THE %8%#54% STATEMENT CANNOT BE USED TO EXECUTE A 3%,%#4 STATEMENT BECAUSE IT LACKS A MECHANISM FOR HANDLING QUERY RESULTS )F THE DYNAMIC STATEMENT TO BE EXECUTED CONTAINS ONE OR MORE PARAMETER MARKERS THE %8%#54% STATEMENT MUST PROVIDE A VALUE FOR EACH OF THE PARAMETERS 4HE VALUES CAN BE PROVIDED IN TWO DIFFERENT WAYS DESCRIBED IN THE NEXT TWO SECTIONS 4HE !.3))3/ 31, STANDARD INCLUDES BOTH OF THESE METHODS
%8%#54%õWITHõ(OSTõ6ARIABLES 4HE EASIEST WAY TO PASS PARAMETER VALUES TO THE %8%#54% STATEMENT IS BY SPECIFYING A LIST OF HOST VARIABLES IN THE 53).' CLAUSE 4HE %8%#54% STATEMENT SUBSTITUTES THE VALUES OF THE HOST VARIABLES IN SEQUENCE FOR THE PARAMETER MARKERS IN THE PREPARED STATEMENT TEXT 4HE HOST VARIABLES THUS SERVE AS INPUT HOST VARIABLES FOR THE DYNAMICALLY EXECUTED STATEMENT 4HIS TECHNIQUE WAS USED IN THE PROGRAM SHOWN IN &IGURE )T IS SUPPORTED BY ALL OF THE POPULAR $"-3 BRANDS THAT SUPPORT DYNAMIC 31, AND IS INCLUDED IN THE !.3))3/ 31, STANDARD FOR DYNAMIC 31,
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#HAPTERçç
$YNAMICç31, ç
4HE NUMBER OF HOST VARIABLES IN THE 53).' CLAUSE MUST MATCH THE NUMBER OF PARAMETER MARKERS IN THE DYNAMIC STATEMENT AND THE DATA TYPE OF EACH HOST VARIABLE MUST BE COMPATIBLE WITH THE DATA TYPE REQUIRED FOR THE CORRESPONDING PARAMETER %ACH HOST VARIABLE IN THE LIST MAY ALSO HAVE A COMPANION HOST INDICATOR VARIABLE )F THE INDICATOR VARIABLE CONTAINS A NEGATIVE VALUE WHEN THE %8%#54% STATEMENT IS PROCESSED THE CORRESPONDING PARAMETER MARKER IS ASSIGNED THE .5,, VALUE
%8%#54%õWITHõ31,$! 4HE SECOND WAY TO PASS PARAMETERS TO THE %8%#54% STATEMENT IS WITH A SPECIAL DYNAMIC 31, DATA STRUCTURE CALLED A 31, $ATA !REA 31,$! 9OU MUST USE A 31,$! TO PASS PARAMETERS WHEN YOU DONT KNOW THE NUMBER OF PARAMETERS TO BE PASSED AND THEIR DATA TYPES AT THE TIME THAT YOU WRITE THE PROGRAM &OR EXAMPLE SUPPOSE YOU WANTED TO MODIFY THE GENERAL PURPOSE UPDATE PROGRAM IN &IGURE SO THAT THE USER COULD SELECT MORE THAN ONE COLUMN TO BE UPDATED 9OU COULD EASILY MODIFY THE PROGRAM TO GENERATE AN 50$!4% STATEMENT WITH A VARIABLE NUMBER OF ASSIGNMENTS BUT THE LIST OF HOST VARIABLES IN THE %8%#54% STATEMENT POSES A PROBLEM IT MUST BE REPLACED WITH A VARIABLE LENGTH LIST 4HE 31,$! PROVIDES A WAY TO SPECIFY SUCH A VARIABLE LENGTH PARAMETER LIST &IGURE SHOWS THE LAYOUT OF THE 31,$! USED BY THE )"- DATABASES INCLUDING $" WHICH SET THE DE FACTO STANDARD FOR DYNAMIC 31, -OST OTHER $"-3 PRODUCTS ALSO USE THIS )"- 31,$! FORMAT OR ONE VERY SIMILAR TO IT 4HE !.3))3/ 31, STANDARD PROVIDES A SIMILAR STRUCTURE CALLED A 31, $ESCRIPTOR !REA 4HE TYPES OF INFORMATION CONTAINED IN THE !.3))3/ 31, $ESCRIPTOR !REA AND THE $" STYLE 31,$! ARE THE SAME AND BOTH STRUCTURES PLAY THE SAME ROLE IN DYNAMIC 31, PROCESSING (OWEVER THE DETAILS OF USEHOW PROGRAM LOCATIONS ARE ASSOCIATED WITH 31, STATEMENT PARAMETERS HOW INFORMATION IS PLACED INTO THE DESCRIPTOR AREA AND RETRIEVED FROM IT AND SO ONARE QUITE DIFFERENT )N PRACTICE THE $" STYLE 31,$! IS THE MORE IMPORTANT BECAUSE DYNAMIC 31, SUPPORT APPEARED IN MOST MAJOR $"-3 BRANDS MODELED ON THE $" IMPLEMENTATION LONG BEFORE DYNAMIC 31, WAS WRITTEN INTO THE 31, STANDARD
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4HE 31,$! IS A VARIABLE SIZE DATA STRUCTURE WITH TWO DISTINCT PARTS s 4HE FIXED PART IS LOCATED AT THE BEGINNING OF THE 31,$! )TS FIELDS IDENTIFY THE DATA STRUCTURE AS A 31,$! AND SPECIFY THE SIZE OF THIS PARTICULAR 31,$! s 4HE VARIABLE PART IS AN ARRAY OF ONE OR MORE 31,6!2 DATA STRUCTURES 7HEN YOU USE A 31,$! TO PASS PARAMETERS TO AN %8%#54% STATEMENT THERE MUST BE ONE 31,6!2 STRUCTURE FOR EACH PARAMETER 4HE FIELDS IN THE 31,6!2 STRUCTURE DESCRIBE THE DATA BEING PASSED TO THE %8%#54% STATEMENT AS A PARAMETER VALUE s 4HE 31,490% FIELD CONTAINS AN INTEGER DATA TYPE CODE THAT SPECIFIES THE DATA TYPE OF THE PARAMETER BEING PASSED &OR EXAMPLE THE $" DATA TYPE CODE IS FOR A BYTE INTEGER FOR A BYTE INTEGER AND FOR A VARIABLE LENGTH CHARACTER STRING s 4HE 31,,%. FIELD SPECIFIES THE LENGTH OF THE DATA BEING PASSED )T WILL CONTAIN A FOR A BYTE INTEGER AND A FOR A BYTE INTEGER 7HEN YOU PASS A CHARACTER STRING AS A PARAMETER 31,,%. CONTAINS THE NUMBER OF CHARACTERS IN THE STRING s 4HE 31,$!4! FIELD IS A POINTER TO THE DATA AREA WITHIN YOUR PROGRAM THAT CONTAINS THE PARAMETER VALUE 4HE $"-3 USES THIS POINTER TO FIND THE DATA VALUE AS IT EXECUTES THE DYNAMIC 31, STATEMENT 4HE 31,490% AND 31,,%. FIELDS TELL THE $"-3 WHICH TYPE OF DATA IS BEING POINTED TO AND ITS LENGTH s 4HE 31,).$ FIELD IS A POINTER TO A BYTE INTEGER THAT IS USED AS AN INDICATOR VARIABLE FOR THE PARAMETER 4HE $"-3 CHECKS THE INDICATOR VARIABLE TO DETERMINE WHETHER YOU ARE PASSING A .5,, VALUE )F YOU ARE NOT USING AN INDICATOR VARIABLE FOR A PARTICULAR PARAMETER THE 31,).$ FIELD MUST BE SET TO ZERO 4HE OTHER FIELDS IN THE 31,6!2 AND 31,$! STRUCTURES ARE NOT USED TO PASS PARAMETER VALUES TO THE %8%#54% STATEMENT 4HEY ARE USED WHEN YOU USE A 31,$! TO RETRIEVE DATA FROM THE DATABASE AS DESCRIBED LATER IN THE h$YNAMIC 1UERIESv SECTION &IGURE SHOWS A DYNAMIC 31, PROGRAM THAT USES A 31,$! TO SPECIFY INPUT PARAMETERS 4HE PROGRAM UPDATES THE 3!,%32%03 TABLE BUT IT ALLOWS THE USER TO SELECT THE COLUMNS THAT ARE TO BE UPDATED AT THE BEGINNING OF THE PROGRAM 4HEN IT ENTERS A LOOP PROMPTING THE USER FOR AN EMPLOYEE NUMBER AND THEN PROMPTING FOR A NEW VALUE FOR EACH COLUMN TO BE UPDATED )F THE USER TYPES AN ASTERISK IN RESPONSE TO THE NEW VALUE PROMPT THE PROGRAM ASSIGNS THE CORRESPONDING COLUMN A .5,, VALUE "ECAUSE THE USER CAN SELECT DIFFERENT COLUMNS EACH TIME THE PROGRAM IS RUN THIS PROGRAM MUST USE A 31,$! TO PASS THE PARAMETER VALUES TO THE %8%#54% STATEMENT 4HE PROGRAM ILLUSTRATES THE GENERAL TECHNIQUE FOR USING A 31,$! INDICATED BY CALLOUT NUMBERS IN &IGURE
4HE PROGRAM ALLOCATES A 31,$! LARGE ENOUGH TO HOLD A 31,6!2 STRUCTURE FOR EACH PARAMETER TO BE PASSED )T SETS THE 31,. FIELD TO INDICATE HOW MANY 31,6!2S CAN BE ACCOMMODATED
&OR EACH PARAMETER TO BE PASSED THE PROGRAM FILLS IN ONE OF THE 31,6!2 STRUCTURES WITH INFORMATION DESCRIBING THE PARAMETER
4HE PROGRAM DETERMINES THE DATA TYPE OF A PARAMETER AND PLACES THE CORRECT DATA TYPE CODE IN THE 31,490% FIELD
#HAPTERçç
$YNAMICç31, ç
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B:01>DCC78B2>;D<= ?A8=C5+?30C4B2>;D<=H = 2>;D<=B,8. =0<4 64CB8=1D5 858=1D5, .KHKI 2>;D<=B,8. B4;42C43KHK ?0A<2=C J J ;;>20C40)'" BCAD2CDA4C>?0BB?0A0<4C4AE0;D4B
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#HAPTERçç
$YNAMICç31, ç
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0ARTç6ç
0ROGRAMMINGçWITHç31,
4HE PROGRAM DETERMINES THE LENGTH OF THE PARAMETER AND PLACES IT IN THE 31,,%. FIELD
4HE PROGRAM ALLOCATES MEMORY TO HOLD THE PARAMETER VALUE AND PUTS THE ADDRESS OF THE ALLOCATED MEMORY IN THE 31,$!4! FIELD
4HE PROGRAM ALLOCATES MEMORY TO HOLD AN INDICATOR VARIABLE FOR THE PARAMETER AND PUTS THE ADDRESS OF THE INDICATOR VARIABLE IN THE 31,).$ FIELD
4HE PROGRAM SETS THE 31,$ FIELD IN THE 31,$! HEADER TO INDICATE HOW MANY PARAMETERS ARE BEING PASSED 4HIS TELLS THE $"-3 HOW MANY 31,6!2 STRUCTURES WITHIN THE 31,$! CONTAIN VALID DATA
4HE PROGRAM PROMPTS THE USER FOR DATA VALUES AND PLACES THEM INTO THE DATA AREAS ALLOCATED IN 3TEPS AND
4HE PROGRAM USES AN %8%#54% STATEMENT WITH THE 53).' CLAUSE TO PASS PARAMETER VALUES VIA THE 31,$!
.OTE THAT THIS PARTICULAR PROGRAM COPIES THE PROMPT STRING FOR EACH PARAMETER VALUE INTO THE 31,.!-% STRUCTURE 4HE PROGRAM DOES THIS SOLELY FOR ITS OWN CONVENIENCE THE $"-3 IGNORES THE 31,.!-% STRUCTURE WHEN YOU USE THE 31,$! TO PASS PARAMETERS (ERE IS A SAMPLE USER DIALOG WITH THE PROGRAM IN &IGURE
3ALESPERSON 5PDATE 0ROGRAM
5PDATE .AME COLUMN YN Y 5PDATE /FFICE COLUMN YN Y 5PDATE -ANAGER COLUMN YN N 5PDATE (IRE $ATE COLUMN YN N 5PDATE 1UOTA COLUMN YN Y 5PDATE 3ALES COLUMN YN N %NTER 3ALESPERSONgS %MPLOYEE .UMBER %NTER NEW VALUE FOR .AME 3UE *ACKSON %NTER NEW VALUE FOR /FFICE %NTER NEW VALUE FOR 1UOTA %NTER 3ALESPERSONgS %MPLOYEE .UMBER %NTER NEW VALUE FOR .AME *OE 3MITH %NTER NEW VALUE FOR /FFICE %NTER NEW VALUE FOR 1UOTA %NTER 3ALESPERSONgS %MPLOYEE .UMBER !LL UPDATES COMMITTED
"ASED ON THE USERS RESPONSE TO THE INITIAL QUESTIONS THE PROGRAM GENERATES THIS DYNAMIC 50$!4% STATEMENT AND PREPARES IT UPDATE SALESREPS SET NAME OFFICE QUOTA WHERE EMPL?NUM
#HAPTERçç
$YNAMICç31, ç
4HE STATEMENT SPECIFIES FOUR PARAMETERS AND THE PROGRAM ALLOCATES A 31,$! BIG ENOUGH TO HANDLE FOUR 31,6!2 STRUCTURES 7HEN THE USER SUPPLIES THE FIRST SET OF PARAMETER VALUES THE DYNAMIC 50$!4% STATEMENT BECOMES UPDATE SALESREPS SET NAME g3UE *ACKSONg OFFICE QUOTA WHERE EMPL?NUM
AND WITH THE SECOND SET OF PARAMETER VALUES IT BECOMES UPDATE SALESREPS SET NAME g*OE 3MITHg OFFICE .5,, QUOTA WHERE EMPL?NUM
4HIS PROGRAM IS SOMEWHAT COMPLEX BUT ITS SIMPLE COMPARED WITH A REAL GENERAL PURPOSE DATABASE UPDATE UTILITY )T ALSO ILLUSTRATES ALL OF THE DYNAMIC 31, FEATURES REQUIRED TO DYNAMICALLY EXECUTE STATEMENTS WITH A VARIABLE NUMBER OF PARAMETERS
$YNAMICõ1UERIES 4HE %8%#54% )--%$)!4% 02%0!2% AND %8%#54% STATEMENTS AS DESCRIBED THUS FAR SUPPORT DYNAMIC EXECUTION OF MOST 31, STATEMENTS (OWEVER THEY CANT SUPPORT DYNAMIC QUERIES BECAUSE THEY LACK A MECHANISM FOR RETRIEVING THE QUERY RESULTS 4O SUPPORT DYNAMIC QUERIES 31, COMBINES THE DYNAMIC 31, FEATURES OF THE 02%0!2% AND %8%#54% STATEMENTS WITH EXTENSIONS TO THE STATIC 31, QUERY PROCESSING STATEMENTS AND ADDS A NEW STATEMENT (ERE IS AN OVERVIEW OF HOW A PROGRAM PERFORMS A DYNAMIC QUERY ! DYNAMIC VERSION OF THE $%#,!2% #523/2 STATEMENT DECLARES A CURSOR FOR THE QUERY 5NLIKE THE STATIC $%#,!2% #523/2 STATEMENT WHICH INCLUDES A HARD CODED 3%,%#4 STATEMENT THE DYNAMIC FORM OF THE $%#,!2% #523/2 STATEMENT SPECIFIES THE STATEMENT NAME THAT WILL BE ASSOCIATED WITH THE DYNAMIC 3%,%#4 STATEMENT
4HE PROGRAM CONSTRUCTS A VALID 3%,%#4 STATEMENT AND STORES IT IN A VARIABLE JUST AS IT WOULD CONSTRUCT A DYNAMIC 50$!4% OR $%,%4% STATEMENT 4HE 3%,%#4 STATEMENT MAY CONTAIN PARAMETER MARKERS LIKE THOSE USED IN OTHER DYNAMIC 31, STATEMENTS
4HE PROGRAM USES THE 02%0!2% STATEMENT TO PASS THE STATEMENT STRING TO THE $"-3 WHICH PARSES VALIDATES AND OPTIMIZES THE STATEMENT AND GENERATES AN APPLICATION PLAN 4HIS IS IDENTICAL TO THE 02%0!2% PROCESSING USED FOR OTHER DYNAMIC 31, STATEMENTS
4HE PROGRAM USES THE $%3#2)"% STATEMENT TO REQUEST A DESCRIPTION OF THE QUERY RESULTS THAT WILL BE PRODUCED BY THE QUERY 4HE $"-3 RETURNS A COLUMN BY COLUMN DESCRIPTION OF THE QUERY RESULTS IN A 31, $ATA !REA 31,$! SUPPLIED BY THE PROGRAM TELLING THE PROGRAM HOW MANY COLUMNS OF QUERY RESULTS THERE ARE AND THE NAME DATA TYPE AND LENGTH OF EACH COLUMN 4HE $%3#2)"% STATEMENT IS USED EXCLUSIVELY FOR DYNAMIC QUERIES
4HE PROGRAM USES THE COLUMN DESCRIPTIONS IN THE 31,$! TO ALLOCATE A BLOCK OF MEMORY TO RECEIVE EACH COLUMN OF QUERY RESULTS 4HE PROGRAM MAY ALSO ALLOCATE SPACE FOR AN INDICATOR VARIABLE FOR THE COLUMN 4HE PROGRAM PLACES THE ADDRESS OF THE DATA AREA AND THE ADDRESS OF THE INDICATOR VARIABLE INTO THE 31,$! TO TELL THE $"-3 WHERE TO RETURN THE QUERY RESULTS
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0ROGRAMMINGçWITHç31,
! DYNAMIC VERSION OF THE /0%. STATEMENT ASKS THE $"-3 TO START EXECUTING THE QUERY AND PASSES VALUES FOR THE PARAMETERS SPECIFIED IN THE DYNAMIC 3%,%#4 STATEMENT 4HE /0%. STATEMENT POSITIONS THE CURSOR BEFORE THE FIRST ROW OF QUERY RESULTS
! DYNAMIC VERSION OF THE &%4#( STATEMENT ADVANCES THE CURSOR TO THE FIRST ROW OF QUERY RESULTS AND RETRIEVES THE DATA INTO THE PROGRAMS DATA AREAS AND INDICATOR VARIABLES 5NLIKE THE STATIC &%4#( STATEMENT WHICH SPECIFIES A LIST OF HOST VARIABLES TO RECEIVE THE DATA THE DYNAMIC &%4#( STATEMENT USES THE 31,$! TO TELL THE $"-3 WHERE TO RETURN THE DATA 3UBSEQUENT EXECUTIONS OF THIS DYNAMIC &%4#( STATEMENT MOVE THROUGH THE QUERY RESULTS ROW BY ROW ADVANCING THE CURSOR TO THE NEXT ROW OF QUERY RESULTS AND RETRIEVING ITS DATA INTO THE PROGRAMS DATA AREAS
4HE #,/3% STATEMENT ENDS ACCESS TO THE QUERY RESULTS AND BREAKS THE ASSOCIATION BETWEEN THE CURSOR AND THE QUERY RESULTS 4HIS #,/3% STATEMENT IS IDENTICAL TO THE STATIC 31, #,/3% STATEMENT NO EXTENSIONS ARE REQUIRED FOR DYNAMIC QUERIES
4HE PROGRAMMING REQUIRED TO PERFORM A DYNAMIC QUERY IS MORE EXTENSIVE THAN THE PROGRAMMING FOR ANY OTHER EMBEDDED 31, STATEMENT (OWEVER THE PROGRAMMING IS TYPICALLY MORE TEDIOUS THAN COMPLEX &IGURE SHOWS A SMALL QUERY PROGRAM THAT USES DYNAMIC 31, TO RETRIEVE AND DISPLAY SELECTED COLUMNS FROM A USER SPECIFIED TABLE 4HE CALLOUT NUMBERS IN THE FIGURE IDENTIFY THE EIGHT STEPS IN THE PRECEDING LIST 4HE PROGRAM IN THE FIGURE BEGINS BY PROMPTING THE USER FOR THE TABLE NAME AND THEN QUERIES THE SYSTEM CATALOG TO DISCOVER THE NAMES OF THE COLUMNS IN THAT TABLE )T ASKS THE USER TO SELECT THE COLUMNS TO BE RETRIEVED AND CONSTRUCTS A DYNAMIC 3%,%#4 STATEMENT BASED ON THE USERS RESPONSES 4HE STEP BY STEP MECHANICAL CONSTRUCTION OF A SELECT LIST IN THIS EXAMPLE IS VERY TYPICAL OF DATABASE FRONT END PROGRAMS THAT GENERATE DYNAMIC 31, )N REAL APPLICATIONS THE GENERATED SELECT LIST MIGHT INCLUDE EXPRESSIONS OR AGGREGATE FUNCTIONS AND THERE MIGHT BE ADDITIONAL PROGRAM LOGIC TO GENERATE '2/50 "9 (!6).' AND /2$%2 "9 CLAUSES ! GRAPHICAL USER INTERFACE WOULD ALSO BE USED INSTEAD OF THE PRIMITIVE USER PROMPTING IN THE SAMPLE PROGRAM (OWEVER THE PROGRAMMING STEPS AND CONCEPTS REMAIN THE SAME .OTICE THAT THE GENERATED 3%,%#4 STATEMENT IS IDENTICAL TO THE INTERACTIVE 3%,%#4 STATEMENT THAT YOU WOULD USE TO PERFORM THE REQUESTED QUERY 4HE HANDLING OF THE 02%0!2% AND $%3#2)"% STATEMENTS AND THE METHOD OF ALLOCATING STORAGE FOR THE RETRIEVED DATA IN THIS PROGRAM ARE ALSO TYPICAL OF DYNAMIC QUERY PROGRAMS .OTE HOW THE PROGRAM USES THE COLUMN DESCRIPTIONS PLACED IN THE 31,6!2 ARRAY TO ALLOCATE A DATA STORAGE BLOCK OF THE PROPER SIZE FOR EACH COLUMN 4HIS PROGRAM ALSO ALLOCATES SPACE FOR AN INDICATOR VARIABLE FOR EACH COLUMN 4HE PROGRAM PLACES THE ADDRESS OF THE DATA BLOCK AND INDICATOR VARIABLE BACK INTO THE 31,6!2 STRUCTURE 4HE /0%. &%4#( AND #,/3% STATEMENTS PLAY THE SAME ROLE FOR DYNAMIC QUERIES AS THEY DO FOR STATIC QUERIES AS ILLUSTRATED BY THIS PROGRAM .OTE THAT THE &%4#( STATEMENT SPECIFIES THE 31,$! INSTEAD OF A LIST OF HOST VARIABLES "ECAUSE THE PROGRAM HAS PREVIOUSLY FILLED IN THE 31,$!4! AND 31,).$ FIELDS OF THE 31,6!2 ARRAY THE $"-3 KNOWS WHERE TO PLACE EACH RETRIEVED COLUMN OF DATA !S THIS EXAMPLE SHOWS MUCH OF THE PROGRAMMING REQUIRED FOR A DYNAMIC QUERY IS CONCERNED WITH SETTING UP THE 31,$! AND ALLOCATING STORAGE FOR THE 31,$! AND THE RETRIEVED DATA 4HE PROGRAM MUST ALSO SORT OUT THE VARIOUS TYPES OF DATA THAT CAN BE RETURNED BY THE QUERY AND HANDLE EACH ONE CORRECTLY TAKING INTO ACCOUNT THE POSSIBILITY THAT THE RETURNED DATA WILL BE .5,, 4HESE CHARACTERISTICS OF THE SAMPLE PROGRAM ARE TYPICAL OF PRODUCTION
#HAPTERçç
$YNAMICç31, ç
APPLICATIONS THAT USE DYNAMIC QUERIES $ESPITE THE COMPLEXITY THE PROGRAMMING IS NOT TOO DIFFICULT IN LANGUAGES LIKE # # 0ASCAL 0,) OR *AVA ,ANGUAGES SUCH AS #/"/, AND &/242!. WHICH LACK THE CAPABILITY TO DYNAMICALLY ALLOCATE STORAGE AND WORK WITH VARIABLE LENGTH DATA STRUCTURES ARE NOT PRACTICAL FOR DYNAMIC QUERY PROCESSING 4HE FOLLOWING SECTIONS DISCUSS THE $%3#2)"% STATEMENT AND THE DYNAMIC VERSIONS OF THE $%#,!2% #523/2 /0%. AND &%4#( STATEMENTS
4HEõ$%3#2)"%õ3TATEMENT 4HE $%3#2)"% STATEMENT SHOWN IN &IGURE IS UNIQUE TO DYNAMIC QUERIES )T IS USED TO REQUEST A DESCRIPTION OF A DYNAMIC QUERY FROM THE $"-3 4HE $%3#2)"% STATEMENT IS USED AFTER THE DYNAMIC QUERY HAS BEEN COMPILED WITH THE 02%0!2% STATEMENT BUT BEFORE IT IS EXECUTED WITH THE /0%. STATEMENT 4HE QUERY TO BE DESCRIBED IS IDENTIFIED BY ITS STATEMENT NAME 4HE $"-3 RETURNS THE QUERY DESCRIPTION IN A 31,$! SUPPLIED BY THE PROGRAM -"*. : )*3*3"3*-0,&(&.&2",0520/3&15&2902/(2"-402/-043 4)&53&2'/2"4"#,&."-&".%4)&."3+34)&53&27)*$) $/,5-.3/'4)&4"#,&"2&4/#&*.$,5%&%*.4)&15&29 '4&24)&53&2;33&,&$4*/.3"2&$/-0,&4&4)&02/(2"-25.3 4)&2&15&34&%15&29".%%*30,"934)&2&35,43 &8&$31,*.$,5%&31,$" &8&$31,*.$,5%&31,%" &8&$31,#&(*.%&$,"2&3&$4*/. $)"234-4#5'
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#HAPTERçç
$YNAMICç31, ç
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4HE 31,$! IS A VARIABLE LENGTH STRUCTURE WITH AN ARRAY OF ONE OR MORE 31,6!2 STRUCTURES AS DESCRIBED EARLIER IN THE SECTION h%8%#54% WITH 31,$! v AND SHOWN IN &IGURE "EFORE PASSING THE 31,$! TO THE $%3#2)"% STATEMENT YOUR PROGRAM MUST FILL IN THE 31,. FIELD IN THE 31,$! HEADER TELLING THE $"-3 HOW LARGE THE 31,6!2 ARRAY IS IN THIS PARTICULAR 31,$! !S THE FIRST STEP OF ITS $%3#2)"% PROCESSING THE $"-3 FILLS IN THE 31,$ FIELD IN THE 31,$! HEADER WITH THE NUMBER OF COLUMNS OF QUERY RESULTS )F THE SIZE OF THE 31,6!2 ARRAY AS SPECIFIED BY THE 31,. FIELD IS TOO SMALL TO HOLD ALL OF THE COLUMN DESCRIPTIONS THE $"-3 DOES NOT FILL IN THE REMAINDER OF THE 31,$! /THERWISE THE $"-3 FILLS IN ONE 31,6!2 STRUCTURE FOR EACH COLUMN OF QUERY RESULTS IN LEFT TO RIGHT ORDER 4HE FIELDS OF EACH 31,6!2 DESCRIBE THE CORRESPONDING COLUMN s 4HE 31,.!-% STRUCTURE SPECIFIES THE NAME OF THE COLUMN WITH THE NAME IN THE $!4! FIELD AND THE LENGTH OF THE NAME IN THE ,%.'4( FIELD )F THE COLUMN IS DERIVED FROM AN EXPRESSION THE 31,.!-% FIELD IS NOT USED s 4HE 31,490% FIELD SPECIFIES AN INTEGER DATA TYPE CODE FOR THE COLUMN 4HE DATA TYPE CODES USED BY DIFFERENT BRANDS OF $"-3 VARY &OR THE )"- 31, PRODUCTS THE DATA TYPE CODE INDICATES BOTH THE DATA TYPE AND WHETHER .5,, VALUES ARE ALLOWED AS SHOWN IN 4ABLE s 4HE 31,,%. FIELD SPECIFIES THE LENGTH OF THE COLUMN &OR VARIABLE LENGTH DATA TYPES SUCH AS 6!2#(!2 THE REPORTED LENGTH IS THE MAXIMUM LENGTH OF THE DATA THE LENGTH OF THE COLUMNS IN INDIVIDUAL ROWS OF QUERY RESULTS WILL NOT EXCEED THIS LENGTH &OR $" AND MANY OTHER 31, PRODUCTS THE LENGTH RETURNED FOR A $%#)-!, DATA TYPE SPECIFIES BOTH THE SIZE OF THE DECIMAL NUMBER IN THE UPPER BYTE AND THE SCALE OF THE NUMBER IN THE LOWER BYTE s 4HE 31,$!4! AND 31,).$ FIELDS ARE NOT FILLED IN BY THE $"-3 9OUR APPLICATION PROGRAM FILLS IN THESE FIELDS WITH THE ADDRESSES OF THE DATA BUFFER AND INDICATOR VARIABLE FOR THE COLUMN BEFORE USING THE 31,$! LATER IN A &%4#( STATEMENT
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! COMPLICATION OF USING THE $%3#2)"% STATEMENT IS THAT YOUR PROGRAM MAY NOT KNOW IN ADVANCE HOW MANY COLUMNS OF QUERY RESULTS THERE WILL BE THEREFORE IT MAY NOT KNOW HOW LARGE A 31,$! MUST BE ALLOCATED TO RECEIVE THE DESCRIPTION /NE OF THREE STRATEGIES IS TYPICALLY USED TO ENSURE THAT THE 31,$! HAS ENOUGH SPACE FOR THE RETURNED DESCRIPTIONS s )F THE PROGRAM HAS GENERATED THE SELECT LIST OF THE QUERY IT CAN KEEP A RUNNING COUNT OF THE SELECT ITEMS AS IT GENERATES THEM )N THIS CASE THE PROGRAM CAN ALLOCATE A 31,$! WITH EXACTLY THE RIGHT NUMBER OF 31,6!2 STRUCTURES TO RECEIVE THE COLUMN DESCRIPTIONS 4HIS APPROACH WAS USED IN THE PROGRAM SHOWN IN &IGURE
s !LTERNATIVELY THE PROGRAM CAN ALLOCATE A 31,$! WITH A 31,6!2 ARRAY LARGE ENOUGH TO ACCOMMODATE A TYPICAL QUERY ! $%3#2)"% STATEMENT USING THIS 31,$! WILL SUCCEED MOST OF THE TIME )F THE 31,$! TURNS OUT TO BE TOO SMALL FOR THE QUERY THE 31,$ VALUE TELLS THE PROGRAM HOW LARGE THE 31,$! MUST BE AND IT CAN ALLOCATE A LARGER ONE AND $%3#2)"% THE STATEMENT AGAIN INTO THAT 31,$! 4HE $%3#2)"% STATEMENT IS NORMALLY USED FOR DYNAMIC QUERIES BUT YOU CAN ASK THE $"-3 TO $%3#2)"% ANY PREVIOUSLY PREPARED STATEMENT 4HIS FEATURE IS USEFUL FOR EXAMPLE IF A PROGRAM NEEDS TO PROCESS AN UNKNOWN 31, STATEMENT TYPED BY A USER 4HE PROGRAM CAN 02%0!2% AND $%3#2)"% THE STATEMENT AND EXAMINE THE 31,$ FIELD IN THE 31,$!
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s )F IT IS INCONVENIENT FOR THE PROGRAM TO COUNT THE NUMBER OF SELECT LIST ITEMS IT CAN INITIALLY $%3#2)"% THE DYNAMIC QUERY INTO A MINIMAL 31,$! WITH A ONE ELEMENT 31,6!2 ARRAY 7HEN THE $%3#2)"% STATEMENT RETURNS THE 31,$ VALUE TELLS THE PROGRAM HOW LARGE THE 31,$! MUST BE 4HE PROGRAM CAN THEN ALLOCATE A 31,$! OF THE CORRECT SIZE AND REEXECUTE THE $%3#2)"% STATEMENT SPECIFYING THE NEW 31,$! 4HERE IS NO LIMIT TO THE NUMBER OF TIMES THAT A PREPARED STATEMENT CAN BE DESCRIBED
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)F THE 31,$ FIELD IS ZERO THE STATEMENT TEXT WAS NOT A QUERY AND THE %8%#54% STATEMENT CAN BE USED TO EXECUTE IT )F THE 31,$ FIELD IS POSITIVE THE STATEMENT TEXT WAS A QUERY AND THE /0%.&%4#(#,/3% STATEMENT SEQUENCE MUST BE USED TO EXECUTE IT
4HEõ$%#,!2%õ#523/2õ3TATEMENT 4HE DYNAMIC $%#,!2% #523/2 STATEMENT SHOWN IN &IGURE IS A VARIATION OF THE STATIC $%#,!2% #523/2 STATEMENT 2ECALL FROM #HAPTER THAT THE STATIC $%#,!2% #523/2 STATEMENT LITERALLY SPECIFIES A QUERY BY INCLUDING THE 3%,%#4 STATEMENT AS ONE OF ITS CLAUSES "Y CONTRAST THE DYNAMIC $%#,!2% #523/2 STATEMENT SPECIFIES THE QUERY INDIRECTLY BY SPECIFYING THE STATEMENT NAME ASSOCIATED WITH THE QUERY BY THE 02%0!2% STATEMENT ,IKE THE STATIC $%#,!2% #523/2 STATEMENT THE DYNAMIC $%#,!2% #523/2 STATEMENT IS A DIRECTIVE TO THE 31, PRECOMPILER RATHER THAN AN EXECUTABLE STATEMENT )T MUST APPEAR BEFORE ANY OTHER REFERENCES TO THE CURSOR THAT IT DECLARES 4HE CURSOR NAME DECLARED BY THIS STATEMENT IS USED IN SUBSEQUENT /0%. &%4#( AND #,/3% STATEMENTS TO PROCESS THE RESULTS OF THE DYNAMIC QUERY
4HEõ$YNAMICõ/0%.õ3TATEMENT 4HE DYNAMIC /0%. STATEMENT SHOWN IN &IGURE IS A VARIATION OF THE STATIC /0%. STATEMENT )T CAUSES THE $"-3 TO BEGIN EXECUTING A QUERY AND POSITIONS THE ASSOCIATED CURSOR JUST BEFORE THE FIRST ROW OF QUERY RESULTS 7HEN THE /0%. STATEMENT COMPLETES SUCCESSFULLY THE CURSOR IS IN AN OPEN STATE AND IS READY TO BE USED IN A &%4#( STATEMENT 4HE ROLE OF THE /0%. STATEMENT FOR DYNAMIC QUERIES PARALLELS THE ROLE OF THE %8%#54% STATEMENT FOR OTHER DYNAMIC 31, STATEMENTS "OTH THE %8%#54% AND THE /0%. STATEMENTS CAUSE THE $"-3 TO EXECUTE A STATEMENT PREVIOUSLY COMPILED BY THE 02%0!2% STATEMENT )F THE DYNAMIC QUERY TEXT INCLUDES ONE OR MORE PARAMETER MARKERS THEN THE /0%. STATEMENT LIKE THE %8%#54% STATEMENT MUST SUPPLY VALUES FOR THESE PARAMETERS 4HE 53).' CLAUSE SPECIFIES PARAMETER VALUES AND IT HAS AN IDENTICAL FORMAT IN BOTH THE %8%#54% AND /0%. STATEMENTS
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$YNAMICç31, ç
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)F THE NUMBER OF PARAMETERS THAT WILL APPEAR IN A DYNAMIC QUERY IS KNOWN IN ADVANCE THE PROGRAM CAN PASS THE PARAMETER VALUES TO THE $"-3 THROUGH A LIST OF HOST VARIABLES IN THE 53).' CLAUSE OF THE /0%. STATEMENT !S IN THE %8%#54% STATEMENT THE NUMBER OF HOST VARIABLES MUST MATCH THE NUMBER OF PARAMETERS THE DATA TYPE OF EACH HOST VARIABLE MUST BE COMPATIBLE WITH THE TYPE REQUIRED BY THE CORRESPONDING PARAMETER AND AN INDICATOR VARIABLE CAN BE SPECIFIED FOR EACH HOST VARIABLE IF NECESSARY &IGURE SHOWS A PROGRAM EXCERPT WHERE THE DYNAMIC QUERY HAS THREE PARAMETERS WHOSE VALUES ARE SPECIFIED BY HOST VARIABLES )F THE NUMBER OF PARAMETERS IS NOT KNOWN UNTIL RUNTIME THE PROGRAM MUST PASS THE PARAMETER VALUES USING A 31,$! STRUCTURE 4HIS TECHNIQUE FOR PASSING PARAMETER VALUES WAS DESCRIBED FOR THE %8%#54% STATEMENT EARLIER IN THE SECTION h%8%#54% WITH 31,$!v 4HE SAME TECHNIQUE IS USED FOR THE /0%. STATEMENT &IGURE SHOWS A PROGRAM EXCERPT LIKE THE ONE IN &IGURE EXCEPT THAT IT USES A 31,$! TO PASS PARAMETERS
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.OTE CAREFULLY THAT THE 31,$! USED IN THE /0%. STATEMENT HAS ABSOLUTELY NOTHING TO DO WITH THE 31,$! USED IN THE $%3#2)"% AND &%4#( STATEMENTS s 4HE 31,$! IN THE /0%. STATEMENT IS USED TO PASS PARAMETER VALUES TO THE $"-3 FOR DYNAMIC QUERY EXECUTION 4HE ELEMENTS OF ITS 31,6!2 ARRAY CORRESPOND TO THE PARAMETER MARKERS IN THE DYNAMIC STATEMENT TEXT s 4HE 31,$! IN THE $%3#2)"% AND &%4#( STATEMENTS RECEIVES DESCRIPTIONS OF THE QUERY RESULTS COLUMNS FROM THE $"-3 AND TELLS THE $"-3 WHERE TO PLACE THE RETRIEVED QUERY RESULTS 4HE ELEMENTS OF ITS 31,6!2 ARRAY CORRESPOND TO THE COLUMNS OF QUERY RESULTS PRODUCED BY THE DYNAMIC QUERY
#HAPTERçç
$YNAMICç31, ç
4HEõ$YNAMICõ&%4#(õ3TATEMENT 4HE DYNAMIC &%4#( STATEMENT SHOWN IN &IGURE IS A VARIATION OF THE STATIC &%4#( STATEMENT )T ADVANCES THE CURSOR TO THE NEXT AVAILABLE ROW OF QUERY RESULTS OR THE REQUESTED ROW IF THE CURSOR IS SCROLLABLE AND ONE OF THE SCROLL KEYWORDS IS USED AND RETRIEVES THE VALUES OF ITS COLUMNS INTO THE PROGRAMS DATA AREAS 2ECALL FROM #HAPTER THAT THE STATIC &%4#( STATEMENT INCLUDES AN ).4/ CLAUSE WITH A LIST OF HOST VARIABLES THAT RECEIVE THE RETRIEVED COLUMN VALUES )N THE DYNAMIC &%4#( STATEMENT THE LIST OF HOST VARIABLES IS REPLACED BY A 31,$! "EFORE USING THE DYNAMIC &%4#( STATEMENT IT IS THE APPLICATION PROGRAMS RESPONSIBILITY TO PROVIDE DATA AREAS TO RECEIVE THE RETRIEVED DATA AND INDICATOR VARIABLE FOR EACH COLUMN 4HE APPLICATION PROGRAM MUST ALSO FILL IN THE 31,$!4! 31,).$ AND 31,,%. FIELDS IN THE 31,6!2 STRUCTURE FOR EACH COLUMN AS FOLLOWS s 4HE 31,$!4! FIELD MUST POINT TO THE DATA AREA FOR THE RETRIEVED DATA s 4HE 31,,%. FIELD MUST SPECIFY THE LENGTH OF THE DATA AREA POINTED TO BY THE 31,$!4! FIELD 4HIS VALUE MUST BE CORRECTLY SPECIFIED TO MAKE SURE THE $"-3 DOES NOT COPY RETRIEVED DATA BEYOND THE END OF THE DATA AREA s 4HE 31,).$ FIELD MUST POINT TO AN INDICATOR VARIABLE FOR THE COLUMN A BYTE INTEGER )F NO INDICATOR VARIABLE IS USED FOR A PARTICULAR COLUMN THE 31,).$ FIELD FOR THE CORRESPONDING 31,6!2 STRUCTURE SHOULD BE SET TO ZERO .ORMALLY THE APPLICATION PROGRAM ALLOCATES A 31,$! USES THE $%3#2)"% STATEMENT TO GET A DESCRIPTION OF THE QUERY RESULTS ALLOCATES STORAGE FOR EACH COLUMN OF QUERY RESULTS AND SETS THE 31,$!4! AND 31,).$ VALUES ALL BEFORE OPENING THE CURSOR 4HIS SAME 31,$! IS THEN PASSED TO THE &%4#( STATEMENT (OWEVER THERE IS NO REQUIREMENT THAT THE SAME 31,$! BE USED OR THAT THE 31,$! SPECIFY THE SAME DATA AREAS FOR EACH &%4#( STATEMENT )T IS PERFECTLY ACCEPTABLE FOR THE APPLICATION PROGRAM TO CHANGE THE 31,$!4! AND 31,).$ POINTERS BETWEEN &%4#( STATEMENTS RETRIEVING TWO SUCCESSIVE ROWS INTO DIFFERENT LOCATIONS
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4HEõ$YNAMICõ#,/3%õ3TATEMENT 4HE DYNAMIC FORM OF THE #,/3% STATEMENT IS IDENTICAL IN SYNTAX AND FUNCTION TO THE STATIC #,/3% STATEMENT SHOWN IN &IGURE )N BOTH CASES THE #,/3% STATEMENT ENDS ACCESS TO THE QUERY RESULTS 7HEN A PROGRAM CLOSES A CURSOR FOR A DYNAMIC QUERY THE PROGRAM NORMALLY SHOULD ALSO DEALLOCATE THE RESOURCES ASSOCIATED WITH THE DYNAMIC QUERY INCLUDING s 4HE 31,$! ALLOCATED FOR THE DYNAMIC QUERY AND USED IN THE $%3#2)"% AND &%4#( STATEMENTS s ! POSSIBLE SECOND 31,$! USED TO PASS PARAMETER VALUES TO THE /0%. STATEMENT s 4HE DATA AREAS ALLOCATED TO RECEIVE EACH COLUMN OF QUERY RESULTS RETRIEVED BY A &%4#( STATEMENT s 4HE DATA AREAS ALLOCATED AS INDICATOR VARIABLES FOR THE COLUMNS OF QUERY RESULTS )T MAY NOT BE NECESSARY TO DEALLOCATE THESE DATA AREAS IF THE PROGRAM WILL TERMINATE IMMEDIATELY AFTER THE #,/3% STATEMENT
$YNAMICõ31,õ$IALECTS ,IKE THE OTHER PARTS OF THE 31, LANGUAGE DYNAMIC 31, VARIES FROM ONE BRAND OF $"-3 TO ANOTHER )N FACT THE DIFFERENCES IN DYNAMIC 31, SUPPORT ARE MORE SERIOUS THAN FOR STATIC 31, BECAUSE DYNAMIC 31, EXPOSES MORE OF THE NUTS AND BOLTS OF THE UNDERLYING $"-3 DATA TYPES DATA FORMATS AND SO ON !S A PRACTICAL MATTER THESE DIFFERENCES MAKE IT IMPOSSIBLE TO WRITE A SINGLE GENERAL PURPOSE DATABASE FRONT END THAT IS PORTABLE ACROSS DIFFERENT $"-3 BRANDS USING DYNAMIC 31, )NSTEAD DATABASE FRONT END PROGRAMS MUST INCLUDE A TRANSLATION LAYER OFTEN CALLED A DRIVER FOR EACH BRAND OF $"-3 THAT THEY SUPPORT TO ACCOMMODATE THE DIFFERENCES 4HE EARLY FRONT END PRODUCTS USUALLY SHIPPED WITH A SEPARATE DRIVER FOR EACH OF THE POPULAR $"-3 BRANDS 4HE INTRODUCTION OF /$"# AS A UNIFORM 31, !0) LAYER MADE THIS JOB SIMPLER SINCE AN /$"# DRIVER COULD BE WRITTEN ONCE FOR EACH $"-3 BRAND AND THE FRONT END PROGRAM COULD BE WRITTEN TO SOLELY USE THE /$"# INTERFACE )N PRACTICE HOWEVER /$"#S LEAST COMMON DENOMINATOR APPROACH MEANT THAT THE FRONT END PROGRAMS COULDNT TAKE ADVANTAGE OF THE UNIQUE CAPABILITIES OF THE VARIOUS SUPPORTED $"-3 SYSTEMS AND IT LIMITED THE PERFORMANCE OF THE APPLICATION !S A RESULT MOST MODERN FRONT END PROGRAMS AND TOOLS STILL INCLUDE A SEPARATE EXPLICIT DRIVER FOR EACH OF THE POPULAR $"-3 BRANDS !N /$"# DRIVER IS USUALLY INCLUDED TO PROVIDE ACCESS TO THE OTHERS ! DETAILED DESCRIPTION OF THE DYNAMIC 31, FEATURES SUPPORTED BY ALL OF THE MAJOR $"-3 BRANDS IS BEYOND THE SCOPE OF THIS BOOK (OWEVER IT IS INSTRUCTIVE TO EXAMINE THE DYNAMIC 31, SUPPORT PROVIDED BY 31,$3 AND BY /RACLE AS EXAMPLES OF THE KINDS OF DIFFERENCES AND EXTENSIONS TO DYNAMIC 31, THAT YOU MAY FIND IN YOUR PARTICULAR $"-3
$YNAMICõ31,õINõ/RACLE
4HE /RACLE $"-3 PRECEDED $" INTO THE MARKET AND BASED ITS DYNAMIC 31, SUPPORT ON )"-S 3YSTEM2 PROTOTYPE !CTUALLY THE ENTIRE ORIGINAL /RACLE $"-3 WAS INDEPENDENTLY DEVELOPED FROM THE PUBLICLY AVAILABLE SPECIFICATIONS FOR 3YSTEM2 &OR THIS REASON THE /RACLE SUPPORT FOR DYNAMIC 31, DIFFERS SOMEWHAT FROM THE )"- 31, STANDARD !LTHOUGH /RACLE AND $" ARE BROADLY COMPATIBLE THEY DIFFER SUBSTANTIALLY AT THE DETAIL LEVEL
#HAPTERçç
$YNAMICç31, ç
4HESE DIFFERENCES INCLUDE /RACLES USE OF PARAMETER MARKERS ITS USE OF THE 31,$! THE FORMAT OF ITS 31,$! AND ITS SUPPORT FOR DATA TYPE CONVERSION 4HE /RACLE DIFFERENCES FROM $" ARE SIMILAR TO THOSE YOU MAY ENCOUNTER IN OTHER $"-3 BRANDS &OR THAT REASON IT IS INSTRUCTIVE TO BRIEFLY EXAMINE /RACLES DYNAMIC 31, SUPPORT AND ITS POINTS OF DIFFERENCE FROM $"
.AMEDõ0ARAMETERS 2ECALL THAT $" DOES NOT ALLOW HOST VARIABLE REFERENCES IN A DYNAMICALLY PREPARED STATEMENT )NSTEAD PARAMETERS IN THE STATEMENT ARE IDENTIFIED BY QUESTION MARKS PARAMETER MARKERS AND VALUES FOR THE PARAMETERS ARE SPECIFIED IN THE %8%#54% OR /0%. STATEMENT /RACLE ALLOWS YOU TO SPECIFY PARAMETERS IN A DYNAMICALLY PREPARED STATEMENT USING THE SYNTAX FOR HOST VARIABLES &OR EXAMPLE THIS SEQUENCE OF EMBEDDED 31, STATEMENTS IS LEGAL FOR /RACLE EXEC SQL BEGIN DECLARE SECTION CHAR STMTBUF;= INT EMPLOYEE?NUMBER EXEC SQL END DECLARE SECTION STRCPYSTMTBUF DELETE FROM SALESREPS WHERE EMPL?NUM REP?NUMBER EXEC SQL PREPARE DELSTMT FROM STMTBUF EXEC SQL EXECUTE DELSTMT USING EMPLOYEE?NUMBER
!LTHOUGH REP?NUMBER APPEARS TO BE A HOST VARIABLE IN THE DYNAMIC $%,%4% STATEMENT IT IS IN FACT A NAMED PARAMETER !S SHOWN IN THE EXAMPLE THE NAMED PARAMETER BEHAVES EXACTLY LIKE THE PARAMETER MARKERS IN $" ! VALUE FOR THE PARAMETER IS SUPPLIED FROM A REAL HOST VARIABLE IN THE %8%#54% STATEMENT .AMED PARAMETERS ARE A REAL CONVENIENCE WHEN YOU USE DYNAMIC STATEMENTS WITH A VARIABLE NUMBER OF PARAMETERS
4HEõ$%3#2)"%õ3TATEMENT
EXEC SQL DESCRIBE SELECT LIST FOR QRYSTMT INTO QRY?SQLDA
)T CORRESPONDS TO THE $" STATEMENT EXEC SQL DESCRIBE QRYSTMT INTO QRY?SQLDA
4HIS /RACLE $%3#2)"% STATEMENT REQUESTS A DESCRIPTION OF THE NAMED PARAMETERS IN A PREVIOUSLY PREPARED DYNAMIC STATEMENT 4HE STATEMENT MIGHT BE A QUERY OR SOME OTHER 31, STATEMENT EXEC SQL DESCRIBE BIND VARIABLES FOR THESTMT INTO THE?SQLDA
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4HE /RACLE $%3#2)"% STATEMENT IS USED LIKE THE $" $%3#2)"% STATEMENT TO DESCRIBE THE QUERY RESULTS OF A DYNAMIC QUERY ,IKE $" /RACLE RETURNS THE DESCRIPTIONS IN A 31,$! 4HE /RACLE $%3#2)"% STATEMENT CAN ALSO BE USED TO REQUEST A DESCRIPTION OF THE NAMED PARAMETERS IN A DYNAMICALLY PREPARED STATEMENT /RACLE ALSO RETURNS THESE PARAMETER DESCRIPTIONS IN A 31,$! 4HIS /RACLE $%3#2)"% STATEMENT REQUESTS A DESCRIPTION OF THE COLUMNS OF QUERY RESULTS FROM A PREVIOUSLY PREPARED DYNAMIC QUERY
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0ROGRAMMINGçWITHç31,
4HIS /RACLE STATEMENT HAS NO $" EQUIVALENT &OLLOWING THIS $%3#2)"% STATEMENT YOUR PROGRAM WOULD TYPICALLY EXAMINE THE INFORMATION IN THE 31,$! FILL IN THE POINTERS IN THE 31,$! TO POINT TO THE PARAMETER VALUES THE PROGRAM WANTS TO SUPPLY AND THEN EXECUTE THE STATEMENT USING THE 31,$! FORM OF THE /0%. OR %8%#54% STATEMENT EXEC SQL EXECUTE THESTMT USING DESCRIPTOR THE?SQLDA EXEC SQL OPEN QRYCURSOR USING DESCRIPTOR THE?SQLDA
4HE INFORMATION RETURNED BY BOTH FORMS OF THE /RACLE $%3#2)"% STATEMENT IS THE SAME AND IS DESCRIBED IN THE NEXT SECTION
4HEõ/RACLEõ31,$! 4HE /RACLE 31,$! PERFORMS THE SAME FUNCTIONS AS THE $" 31,$! BUT ITS FORMAT SHOWN IN &IGURE DIFFERS SUBSTANTIALLY FROM THAT OF $" 4HE TWO IMPORTANT FIELDS IN THE $" 31,$! HEADER BOTH HAVE COUNTERPARTS IN THE /RACLE 31,$! s 4HE . FIELD IN THE /RACLE 31,$! SPECIFIES THE SIZE OF THE ARRAYS USED TO HOLD COLUMN DEFINITIONS )T CORRESPONDS TO THE 31,. FIELD IN THE $" 31,$! s 4HE & FIELD IN THE /RACLE 31,$! INDICATES HOW MANY COLUMNS ARE CURRENTLY DESCRIBED IN THE ARRAYS OF THE 31,$! )T CORRESPONDS TO THE 31,$ FIELD IN THE $" 31,$! )NSTEAD OF $"S SINGLE ARRAY OF 31,6!2 STRUCTURES THAT CONTAIN COLUMN DESCRIPTIONS THE /RACLE 31,$! CONTAINS POINTERS TO A SERIES OF ARRAYS EACH OF WHICH DESCRIBES ONE ASPECT OF A COLUMN s 4HE 4 FIELD POINTS TO AN ARRAY OF INTEGERS THAT SPECIFY THE DATA TYPE FOR EACH QUERY RESULTS COLUMN OR NAMED PARAMETER 4HE INTEGERS IN THIS ARRAY CORRESPOND TO THE 31,490% FIELD IN EACH $" 31,6!2 STRUCTURE s 4HE 6 FIELD POINTS TO AN ARRAY OF POINTERS THAT SPECIFY THE BUFFER FOR EACH COLUMN OF QUERY RESULTS OR EACH PASSED PARAMETER VALUE 4HE POINTERS IN THIS ARRAY CORRESPOND TO THE 31,$!4! FIELD IN EACH $" 31,6!2 STRUCTURE
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#HAPTERçç
$YNAMICç31, ç
s 4HE , FIELD POINTS TO AN ARRAY OF INTEGERS THAT SPECIFY THE LENGTH OF EACH BUFFER POINTED TO BY THE 6 ARRAY 4HE INTEGERS IN THIS ARRAY CORRESPOND TO THE 31,,%. FIELD IN EACH $" 31,6!2 STRUCTURE s 4HE ) FIELD POINTS TO AN ARRAY OF DATA POINTERS THAT SPECIFY THE INDICATOR VARIABLE FOR EACH QUERY RESULTS COLUMN OR NAMED PARAMETER 4HE POINTERS IN THIS ARRAY CORRESPOND TO THE 31,).$ FIELD IN EACH $" 31,6!2 STRUCTURE s 4HE 3 FIELD POINTS TO AN ARRAY OF STRING POINTERS THAT SPECIFY THE BUFFERS WHERE /RACLE IS TO RETURN THE NAME OF EACH QUERY RESULTS COLUMN OR NAMED PARAMETER 4HE BUFFERS POINTED TO BY THIS ARRAY CORRESPOND TO THE 31,.!-% STRUCTURE IN EACH $" 31,6!2 STRUCTURE s 4HE - FIELD POINTS TO AN ARRAY OF INTEGERS THAT SPECIFY THE MAXIMUM LENGTH OF THE VARIABLE NAMES &OR $" THE 31,.!-% STRUCTURE HAS A FIXED LENGTH BUFFER SO THERE IS NO EQUIVALENT TO THE - FIELD s 4HE # FIELD POINTS TO AN ARRAY OF INTEGERS THAT SPECIFY THE ACTUAL LENGTHS OF THE NAMES POINTED TO BY THE 3 ARRAY 7HEN /RACLE RETURNS THE COLUMN OR PARAMETER NAMES IT SETS THE INTEGERS IN THIS ARRAY TO INDICATE THEIR ACTUAL LENGTHS &OR $" THE 31,.!-% STRUCTURE HAS A FIXED LENGTH BUFFER SO THERE IS NO EQUIVALENT TO THE # FIELD s 4HE 8 FIELD POINTS TO AN ARRAY OF STRING POINTERS THAT SPECIFY THE BUFFERS WHERE /RACLE IS TO RETURN THE NAME OF EACH NAMED INDICATOR PARAMETER 4HESE BUFFERS ARE USED ONLY BY THE /RACLE $%3#2)"% ",).$ ,)34 STATEMENT THEY HAVE NO $" EQUIVALENT s 4HE 9 FIELD POINTS TO AN ARRAY OF INTEGERS SPECIFYING THE SIZE OF EACH BUFFER POINTED TO BY THE 8 ARRAY 4HERE IS NO $" EQUIVALENT s 4HE : FIELD POINTS TO AN ARRAY OF INTEGERS SPECIFYING ACTUAL LENGTHS OF THE INDICATOR PARAMETER NAMES POINTED TO BY THE 8 ARRAY 7HEN /RACLE RETURNS THE INDICATOR PARAMETER NAMES IT SETS THE INTEGERS IN THIS ARRAY TO INDICATE THEIR ACTUAL LENGTHS 4HERE IS NO $" EQUIVALENT
$ATAõ4YPEõ#ONVERSIONS
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4HE DATA TYPE FORMATS THAT $" USES TO RECEIVE PARAMETER VALUES AND RETURN QUERY RESULTS ARE THOSE SUPPORTED BY THE )"- 3 ARCHITECTURE MAINFRAMES THAT RUN $" "ECAUSE IT WAS DESIGNED AS A PORTABLE $"-3 /RACLE USES ITS OWN INTERNAL DATA TYPE FORMATS /RACLE AUTOMATICALLY CONVERTS BETWEEN ITS INTERNAL DATA FORMATS AND THOSE OF THE COMPUTER SYSTEM ON WHICH IT IS RUNNING WHEN IT RECEIVES PARAMETER VALUES FROM YOUR PROGRAM AND WHEN IT RETURNS QUERY RESULTS TO YOUR PROGRAM 9OUR PROGRAM CAN USE THE /RACLE 31,$! TO CONTROL THE DATA TYPE CONVERSION PERFORMED BY /RACLE &OR EXAMPLE SUPPOSE YOUR PROGRAM USES THE $%3#2)"% STATEMENT TO DESCRIBE THE RESULTS OF A DYNAMIC QUERY AND DISCOVERS FROM THE DATA TYPE CODE IN THE 31,$! THAT THE FIRST COLUMN CONTAINS NUMERIC DATA 9OUR PROGRAM CAN REQUEST CONVERSION OF THE NUMERIC DATA BY CHANGING THE DATA TYPE CODE IN THE 31,$! BEFORE IT FETCHES THE DATA )F THE PROGRAM PLACES THE DATA TYPE CODE FOR A CHARACTER STRING INTO THE 31,$! FOR EXAMPLE /RACLE WILL CONVERT THE FIRST COLUMN OF QUERY RESULTS AND RETURN IT TO YOUR PROGRAM AS A STRING OF DIGITS 4HE DATA TYPE CONVERSION FEATURE OF THE /RACLE 31,$! PROVIDES EXCELLENT PORTABILITY BOTH ACROSS DIFFERENT COMPUTER SYSTEMS AND ACROSS DIFFERENT PROGRAMMING LANGUAGES ! SIMILAR FEATURE IS SUPPORTED BY SEVERAL OTHER $"-3 BRANDS BUT NOT BY THE )"- 31, PRODUCTS
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$YNAMICõ31,õANDõTHEõ31,õ3TANDARD 4HE 31, STANDARD DID NOT ADDRESS DYNAMIC 31, SO THE DE FACTO STANDARD FOR DYNAMIC 31, AS DESCRIBED IN THE PRECEDING SECTIONS WAS SET BY )"-S IMPLEMENTATION IN $" 4HE 31, STANDARD EXPLICITLY INCLUDED A STANDARD FOR DYNAMIC 31, SPECIFIED IN A SEPARATE CHAPTER 0ART OF THE STANDARD THAT WAS NEARLY PAGES LONG 0ART GREW TO OVER PAGES WHEN LAST UPDATED IN )N THE SIMPLEST AREAS OF DYNAMIC 31, THE 31, STANDARD CLOSELY FOLLOWS THE DYNAMIC 31, CURRENTLY USED BY COMMERCIAL $"-3 PRODUCTS "UT IN OTHER AREAS INCLUDING EVEN THE MOST BASIC DYNAMIC 31, QUERIES THE STANDARD INTRODUCES INCOMPATIBILITIES WITH EXISTING $"-3 PRODUCTS WHICH WILL REQUIRE THE REWRITING OF APPLICATIONS 4HE NEXT SEVERAL SECTIONS DESCRIBE THE 31, STANDARD FOR DYNAMIC 31, IN DETAIL WITH AN EMPHASIS ON THE DIFFERENCES FROM THE $" STYLE DYNAMIC 31, DESCRIBED IN THE PRECEDING SECTIONS )N PRACTICE SUPPORT FOR 31, STANDARD DYNAMIC 31, HAS BEEN SLOW TO APPEAR IN COMMERCIAL $"-3 PRODUCTS AND MOST DYNAMIC 31, PROGRAMMING STILL REQUIRES THE USE OF THE OLD $" STYLE DYNAMIC 31, %VEN WHEN A NEW VERSION OF A $"-3 PRODUCT SUPPORTS THE NEW 31, STATEMENTS THE $"-3 VENDOR ALWAYS PROVIDES A PRECOMPILER OPTION THAT ACCEPTS THE OLD DYNAMIC 31, STRUCTURE USED BY THE PARTICULAR $"-3 /FTEN THIS IS THE DEFAULT OPTION FOR THE PRECOMPILER BECAUSE WITH THOUSANDS AND THOUSANDS OF 31, PROGRAMS ALREADY IN EXISTENCE THE $"-3 VENDOR HAS AN ABSOLUTE REQUIREMENT THAT NEW $"-3 VERSIONS DO NOT BREAK OLD PROGRAMS 4HUS THE MIGRATION TO PORTIONS OF THE 31, STANDARD THAT REPRESENT INCOMPATIBILITIES WITH CURRENT PRACTICE WILL BE A SLOW AND EVOLUTIONARY ONE
"ASICõ$YNAMICõ31,õ3TATEMENTS 4HE 31, STATEMENTS IN THE !.3))3/ 31, STANDARD THAT IMPLEMENT BASIC DYNAMIC 31, STATEMENT EXECUTION THAT IS DYNAMIC 31, THAT DOES NOT INVOLVE DATABASE QUERIES ARE SHOWN IN &IGURE 4HESE STATEMENTS CLOSELY FOLLOW THE $" STRUCTURE AND LANGUAGE 4HIS INCLUDES THE SINGLE STEP AND TWO STEP METHODS OF EXECUTING DYNAMIC 31, STATEMENTS 4HE STANDARD %8%#54% )--%$)!4% STATEMENT HAS AN IDENTICAL SYNTAX AND OPERATION TO THAT OF ITS $" COUNTERPART )T IMMEDIATELY EXECUTES THE 31, STATEMENT PASSED TO THE $"-3 AS A CHARACTER STRING 4HUS THE %8%#54% )--%$)!4% STATEMENT IN &IGURE CONFORMS TO THE 31, STANDARD 4HE STANDARD 02%0!2% AND %8%#54% STATEMENTS ALSO OPERATE IDENTICALLY TO THEIR $" STYLE COUNTERPARTS 4HE 02%0!2% STATEMENT PASSES A TEXT STRING CONTAINING A 31, STATEMENT TO THE $"-3 AND CAUSES THE $"-3 TO ANALYZE THE STATEMENT OPTIMIZE IT AND BUILD AN APPLICATION PLAN FOR IT 4HE %8%#54% STATEMENT CAUSES THE $"-3 TO ACTUALLY EXECUTE A PREVIOUSLY PREPARED STATEMENT ,IKE THE $" VERSION THE 31, STANDARD %8%#54% STATEMENT OPTIONALLY ACCEPTS HOST VARIABLES THAT PASS THE SPECIFIC VALUES TO BE USED WHEN EXECUTING THE 31, STATEMENT 4HE 02%0!2% AND %8%#54% STATEMENTS IN &IGURE LABELED AS ITEMS AND RESPECTIVELY THUS CONFORM TO THE 31, STANDARD 4WO USEFUL EXTENSIONS TO THE 02%0!2%%8%#54% STRUCTURE ARE A PART OF THE &ULL COMPLIANCE LEVEL 31, STANDARD SPECIFICATION NEITHER IS PART OF THE %NTRY OR )NTERMEDIATE COMPLIANCE LEVELS 4HE FIRST IS A USEFUL COMPANION TO THE 02%0!2% STATEMENT THAT UNPREPARES A PREVIOUSLY COMPILED DYNAMIC 31, STATEMENT 4HE $%!,,/#!4% 02%0!2% STATEMENT PROVIDES THIS CAPABILITY 7HEN THE $"-3 PROCESSES THIS STATEMENT IT CAN FREE THE RESOURCES ASSOCIATED WITH THE COMPILED STATEMENT WHICH WILL USUALLY INCLUDE SOME INTERNAL REPRESENTATION OF THE APPLICATION PLAN FOR THE STATEMENT 4HE STATEMENT NAMED IN THE $%!,,/#!4% 02%0!2% STATEMENT MUST MATCH THE NAME SPECIFIED IN A PREVIOUSLY EXECUTED 02%0!2% STATEMENT
#HAPTERçç
$YNAMICç31, ç
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)N THE ABSENCE OF A CAPABILITY LIKE THAT PROVIDED BY $%!,,/#!4% 02%0!2% THE $"-3 HAS NO WAY OF KNOWING WHETHER A PREVIOUSLY PREPARED STATEMENT WILL BE EXECUTED AGAIN OR NOT AND SO MUST RETAIN ALL OF THE INFORMATION ASSOCIATED WITH THE STATEMENT )N PRACTICE SOME $"-3 BRANDS MAINTAIN THE COMPILED VERSION OF THE STATEMENT ONLY UNTIL THE END OF A TRANSACTION IN THESE SYSTEMS A STATEMENT MUST BE REPREPARED FOR EACH SUBSEQUENT TRANSACTION WHERE IT IS USED "ECAUSE OF THE OVERHEAD INVOLVED IN THIS PROCESS OTHER $"-3 BRANDS MAINTAIN THE COMPILED STATEMENT INFORMATION INDEFINITELY 4HE $%!,,/#!4% 02%0!2% CAN PLAY A MORE IMPORTANT ROLE IN THESE SYSTEMS WHERE A DATABASE SESSION MIGHT LAST FOR HOURS .OTE HOWEVER THAT THE 31, STANDARD EXPLICITLY SAYS THAT WHETHER A PREPARED STATEMENT IS VALID OUTSIDE OF THE TRANSACTION IN WHICH IT IS PREPARED IS IMPLEMENTATION DEPENDENT 4HE 31, STANDARD EXTENSION TO THE $" STYLE %8%#54% STATEMENT MAY BE EVEN MORE USEFUL IN PRACTICE )T ALLOWS THE %8%#54% STATEMENT TO BE USED TO PROCESS SIMPLE SINGLETON 3%,%#4 STATEMENTS THAT RETURN A SINGLE ROW OF QUERY RESULTS ,IKE THE $" %8%#54% STATEMENT THE 31, STANDARD STATEMENT INCLUDES A 53).' CLAUSE THAT NAMES THE HOST VARIABLES THAT SUPPLY THE VALUES FOR PARAMETERS IN THE STATEMENT BEING EXECUTED "UT THE 31, STANDARD STATEMENT ALSO PERMITS AN OPTIONAL ).4/ CLAUSE THAT NAMES THE HOST VARIABLES THAT RECEIVE THE VALUES RETURNED BY A SINGLE ROW QUERY 3UPPOSE YOU HAVE WRITTEN A PROGRAM THAT DYNAMICALLY GENERATES A QUERY STATEMENT THAT RETRIEVES THE NAME AND QUOTA OF A SALESPERSON WITH THE SALESPERSONS EMPLOYEE NUMBER AS AN INPUT PARAMETER 5SING $" STYLE DYNAMIC 31, EVEN THIS SIMPLE QUERY INVOLVES THE USE
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OF A 31,$! CURSORS A &%4#( STATEMENT LOOP AND SO ON 5SING STANDARD DYNAMIC 31, THE STATEMENT CAN BE EXECUTED USING THE SIMPLE TWO STATEMENT SEQUENCE 02%0!2% QRYSTMT &2/- STATEMENT?BUFFER %8%#54% QRYSTMT 53).' EMPLNUM ).4/ NAME QUOTA
!S WITH ANY PREPARED STATEMENT THIS SINGLE ROW QUERY COULD BE EXECUTED REPEATEDLY AFTER BEING PREPARED ONCE )T STILL SUFFERS FROM THE RESTRICTION THAT THE NUMBER OF RETURNED COLUMNS AND THEIR DATA TYPES MUST KNOW WHEN THE PROGRAM IS WRITTEN SINCE THEY MUST MATCH EXACTLY THE NUMBER AND DATA TYPES OF THE HOST VARIABLES IN THE ).4/ CLAUSE 4HIS RESTRICTION IS REMOVED BY ALLOWING THE USE OF A 31,$! STYLE DESCRIPTOR AREA INSTEAD OF A LIST OF HOST VARIABLES AS DESCRIBED IN THE NEXT SECTION
4HEõ3TANDARDõ31,$! !LTHOUGH ITS SUPPORT FOR 02%0!2%%8%#54% PROCESSING CLOSELY PARALLELS THAT OF $" DYNAMIC 31, THE 31, STANDARD DIVERGES SUBSTANTIALLY FROM $" STYLE IN THE AREA OF DYNAMIC QUERY PROCESSING )N PARTICULAR THE 31, STANDARD INCLUDES MAJOR CHANGES TO THE $" 31, $ATA !REA 31,$! WHICH IS AT THE HEART OF DYNAMIC MULTIROW QUERIES 2ECALL THAT A 31, $ATA !REA 31,$! PROVIDES TWO IMPORTANT FUNCTIONS s ! FLEXIBLE WAY TO PASS PARAMETERS TO BE USED IN THE EXECUTION OF A DYNAMIC 31, STATEMENT PASSING DATA FROM THE HOST PROGRAM TO THE $"-3 AS DESCRIBED EARLIER IN THE SECTION h%8%#54% WITH 31,$!v s 4HE WAY THAT THE QUERY RESULTS ARE RETURNED TO THE PROGRAM IN THE EXECUTION OF A DYNAMIC 31, QUERY PASSING DATA FROM THE $"-3 BACK TO THE HOST PROGRAM AS DESCRIBED EARLIER IN THE SECTION h4HE $YNAMIC &%4#( 3TATEMENTv 4HE $" STYLE 31,$! HANDLES THESE FUNCTIONS WITH FLEXIBILITY BUT IT HAS SOME SERIOUS DISADVANTAGES )T IS A VERY LOW LEVEL DATA STRUCTURE WHICH TENDS TO BE SPECIFIC TO A PARTICULAR PROGRAMMING LANGUAGE &OR EXAMPLE THE VARIABLE LENGTH STRUCTURE OF A $" STYLE 31,$! MAKES IT VERY DIFFICULT TO REPRESENT IN THE &/242!. LANGUAGE 4HE 31,$! STRUCTURE ALSO IMPLICITLY MAKES ASSUMPTIONS ABOUT THE MEMORY OF THE COMPUTER SYSTEM ON WHICH THE DYNAMIC 31, PROGRAM IS RUNNING HOW DATA ITEMS IN A STRUCTURE ARE ALIGNED ON SUCH A SYSTEM AND SO ON &OR THE WRITERS OF THE 31, STANDARD THESE LOW LEVEL DEPENDENCIES WERE UNACCEPTABLE BARRIERS TO PORTABILITY 4HEREFORE THEY REPLACED THE $" 31,$! STRUCTURE WITH A SET OF STATEMENTS FOR MANIPULATING A MORE ABSTRACT STRUCTURE CALLED A DYNAMIC 31, DESCRIPTOR 4HE STRUCTURE OF A 31, DESCRIPTOR IS SHOWN IN &IGURE #ONCEPTUALLY THE 31, DESCRIPTOR IS PARALLEL TO AND PLAYS EXACTLY THE SAME ROLE AS THE $" STYLE 31,$! SHOWN IN &IGURE 4HE FIXED PART OF THE 31, DESCRIPTOR SPECIFIES A COUNT OF THE NUMBER OF ITEMS IN THE VARIABLE PART OF THE DESCRIPTOR %ACH ITEM IN THE VARIABLE PART CONTAINS INFORMATION ABOUT A SINGLE PARAMETER BEING PASSED SUCH AS ITS DATA TYPE ITS LENGTH AN INDICATOR TELLING WHETHER A .5,, VALUE IS BEING PASSED AND SO ON "UT UNLIKE THE $" 31,$! THE 31, DESCRIPTOR IS NOT AN ACTUAL DATA STRUCTURE WITHIN THE HOST PROGRAM )NSTEAD IT IS A COLLECTION OF DATA ITEMS OWNED BY THE $"-3 SOFTWARE 4HE HOST PROGRAM MANIPULATES 31, DESCRIPTORSCREATING THEM DESTROYING THEM PLACING DATA ITEMS INTO THEM EXTRACTING DATA FROM THEMVIA A NEW SET OF DYNAMIC 31, STATEMENTS SPECIALLY DESIGNED FOR THAT PURPOSE &IGURE SUMMARIZES THESE 31, DESCRIPTOR MANAGEMENT STATEMENTS
#HAPTERçç
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$YNAMICç31, ç
4O UNDERSTAND HOW THE 31, DESCRIPTOR MANAGEMENT STATEMENTS WORK ITS INSTRUCTIVE TO REEXAMINE THE DYNAMIC 31, UPDATE PROGRAM IN &IGURE 4HIS PROGRAM ILLUSTRATES THE USE OF A $" STYLE 31,$! IN AN %8%#54% STATEMENT 4HE FLOW OF THE PROGRAM REMAINS IDENTICAL IF A 31, DESCRIPTOR IS USED INSTEAD BUT THE SPECIFICS CHANGE QUITE A LOT
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"EFORE USING THE DESCRIPTOR THE PROGRAM MUST CREATE IT USING THE STATEMENT !,,/#!4% $%3#2)04/2 PARMDESC 7)4( -!8 PARMCNT
4HIS STATEMENT REPLACES THE ALLOCATION OF STORAGE FOR THE PARMDA DATA STRUCTURE AT CALLOUT IN &IGURE 4HE DESCRIPTOR NAMED PARMDESC WILL PERFORM THE SAME FUNCTIONS AS THE PARMDA .OTE THAT THE PROGRAM IN &IGURE HAD TO CALCULATE HOW MUCH STORAGE WOULD BE REQUIRED FOR THE PARMDA STRUCTURE BEFORE ALLOCATING IT 7ITH THE 31, DESCRIPTOR THAT CALCULATION IS ELIMINATED AND THE HOST PROGRAM SIMPLY TELLS THE $"-3 HOW MANY ITEMS THE VARIABLE PART OF THE DESCRIPTOR MUST BE ABLE TO HOLD 4HE NEXT STEP IN THE PROGRAM IS TO SET UP THE DESCRIPTOR SO THAT IT DESCRIBES THE PARAMETERS TO BE PASSEDTHEIR DATA TYPES LENGTHS AND SO ON 4HE LOOP AT CALLOUT OF THE PROGRAM REMAINS INTACT BUT AGAIN THE DETAILS OF HOW THE DESCRIPTOR IS INITIALIZED DIFFER FROM THOSE FOR THE 31,$! !T CALLOUT AND CALLOUT THE DATA TYPE AND LENGTH FOR THE PARAMETER ARE SPECIFIED WITH A FORM OF THE 3%4 $%3#2)04/2 STATEMENT WITH THIS CODE EXCERPT TYPECODE COLUMNS;I=TYPECODE LENGTH COLUMNS;I=BUFLEN 3%4 $%3#2)04/2 PARMDESC 6!,5% I L 490% TYPECODE 3%4 $%3#2)04/2 PARMDESC 6!,5% I L ,%.'4( LENGTH
4HE DIFFERENCES FROM &IGURE ARE INSTRUCTIVE "ECAUSE THE DESCRIPTOR IS MAINTAINED BY THE $"-3 THE DATA TYPE AND LENGTH MUST BE PASSED TO THE $"-3 THROUGH THE 3%4 $%3#2)04/2 STATEMENT USING HOST VARIABLES )N THIS PARTICULAR EXAMPLE THE SIMPLE VARIABLES TYPECODE AND LENGTH ARE USED !DDITIONALLY THE DATA TYPE CODES IN &IGURE WERE SPECIFIC TO $" 4HE FACT THAT EACH $"-3 VENDOR USED DIFFERENT CODES TO REPRESENT DIFFERENT 31, DATA TYPES WAS A MAJOR SOURCE OF PORTABILITY PROBLEMS IN DYNAMIC 31, 4HE 31, STANDARD SPECIFIES INTEGER DATA TYPE CODES FOR ALL OF THE DATA TYPES SPECIFIED IN THE STANDARD ELIMINATING THIS ISSUE 4HE 31, STANDARD DATA TYPE CODES ARE SUMMARIZED IN 4ABLE 3O IN ADDITION TO THE OTHER CHANGES THE DATA TYPE CODES IN THE COLUMNS STRUCTURE OF &IGURE WOULD NEED TO BE MODIFIED TO USE THESE 31, STANDARD DATA TYPE CODES 4HE STATEMENTS AT CALLOUTS AND IN &IGURE WERE USED TO BIND THE 31,$! STRUCTURE TO THE PROGRAM BUFFERS USED TO CONTAIN THE PARAMETER DATA AND THE CORRESPONDING INDICATOR VARIABLE %FFECTIVELY THEY PUT POINTERS TO THESE PROGRAM BUFFERS INTO THE 31,$! FOR THE USE OF THE $"-3 7ITH 31, DESCRIPTORS THIS TYPE OF BINDING IS NOT POSSIBLE )NSTEAD THE DATA VALUE AND INDICATOR VALUE ARE SPECIFICALLY PASSED AS HOST VARIABLES LATER IN THE PROGRAM 4HUS THE STATEMENTS AT CALLOUTS AND WOULD BE ELIMINATED IN THE CONVERSION TO STANDARD 31, 4HE STATEMENT AT CALLOUT IN &IGURE SETS THE 31,$! TO INDICATE HOW MANY PARAMETER VALUES ARE ACTUALLY BEING PASSED TO THE $"-3 4HE 31, DESCRIPTOR MUST SIMILARLY BE SET TO INDICATE THE NUMBER OF PASSED PARAMETERS 4HIS IS DONE WITH A FORM OF THE 3%4 $%3#2)04/2 STATEMENT 3%4 $%3#2)04/2 PARMDESC #/5.4 PARMCNT
3TRICTLY SPEAKING THIS 3%4 $%3#2)04/2 STATEMENT SHOULD PROBABLY BE PLACED EARLIER IN THE PROGRAM AND SHOULD BE EXECUTED BEFORE THOSE FOR THE INDIVIDUAL ITEMS 4HE 31, STANDARD SPECIFIES A COMPLETE SET OF RULES THAT DESCRIBE HOW SETTING VALUES IN SOME PARTS OF THE DESCRIPTOR CAUSES VALUES IN OTHER PARTS OF THE DESCRIPTOR TO BE RESET &OR THE MOST PART THESE RULES SIMPLY SPECIFY THE NATURAL HIERARCHY OF INFORMATION
#HAPTERçç
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&OR EXAMPLE IF YOU SET THE DATA TYPE FOR A PARTICULAR ITEM TO INDICATE AN INTEGER THE STANDARD SAYS THAT THE CORRESPONDING INFORMATION IN THE DESCRIPTOR THAT TELLS THE LENGTH OF THE SAME ITEM WILL BE RESET TO SOME IMPLEMENTATION DEPENDENT VALUE .ORMALLY THIS DOESNT IMPACT YOUR PROGRAMMING HOWEVER YOU CANT ASSUME THAT JUST BECAUSE YOU SET SOME VALUE WITHIN THE DESCRIPTOR PREVIOUSLY IT STILL RETAINS THE SAME VALUE )TS BEST TO FILL THE DESCRIPTOR HIERARCHICALLY STARTING WITH HIGHER LEVEL INFORMATION FOR EXAMPLE THE NUMBER OF ITEMS AND THEIR DATA TYPES AND THEN PROCEEDING TO LOWER LEVEL INFORMATION DATA TYPE LENGTHS SUBTYPES WHETHER .5,, VALUES ARE ALLOWED AND SO ON 4HE FLOW OF THE PROGRAM IN &IGURE CAN NOW CONTINUE UNMODIFIED 4HE 02%0!2% STATEMENT COMPILES THE DYNAMIC 50$!4% STATEMENT AND ITS FORM DOES NOT CHANGE FOR STANDARD 31, 4HE PROGRAM THEN ENTERS THE FOR LOOP PROMPTING THE USER FOR PARAMETERS (ERE AGAIN THE CONCEPTS ARE THE SAME BUT THE DETAILS OF MANIPULATING THE 31,$! STRUCTURE AND THE 31, DESCRIPTOR DIFFER )F THE USER INDICATES THAT A .5,, VALUE IS TO BE ASSIGNED BY TYPING AN ASTERISK IN RESPONSE TO THE PROMPT THE PROGRAM IN &IGURE SETS THE PARAMETER INDICATOR BUFFER APPROPRIATELY WITH THE STATEMENT
PARMVAR SQLIND
AND IF THE VALUE IS NOT .5,, THE PROGRAM AGAIN SETS THE INDICATOR BUFFER WITH THE STATEMENT
PARMVAR SQLIND
&OR THE 31, DESCRIPTOR THESE STATEMENTS WOULD AGAIN BE CONVERTED TO A PAIR OF 3%4 $%3#2)04/2 STATEMENTS 3%4 $%3#2)04/2 PARMDESC 6!,5%J L ).$)#!4/2 3%4 $%3#2)04/2 PARMDESC 6!,5%J ).$)#!4/2
.OTE AGAIN THE USE OF THE LOOP CONTROL VARIABLE TO SPECIFY WHICH ITEM IN THE DESCRIPTOR IS BEING SET AND THE DIRECT PASSING OF DATA IN THIS CASE CONSTANTS RATHER THAN THE USE OF POINTERS TO BUFFERS IN THE 31,$! STRUCTURE &INALLY THE PROGRAM IN &IGURE PASSES THE ACTUAL PARAMETER VALUE TYPED BY THE USER TO THE $"-3 VIA THE 31,$! 4HE STATEMENTS AT CALLOUT ACCOMPLISH THIS FOR DATA OF DIFFERENT TYPES BY FIRST CONVERTING THE TYPED CHARACTERS INTO BINARY REPRESENTATIONS OF THE DATA AND PLACING THE BINARY DATA INTO THE DATA BUFFERS POINTED TO BY THE 31,$! !GAIN THE CONVERSION TO STANDARD 31, INVOLVES REPLACING THESE POINTERS AND DIRECT 31,$! MANIPULATION WITH A 3%4 $%3#2)04/2 STATEMENT &OR EXAMPLE THESE STATEMENTS PASS THE DATA AND ITS LENGTH FOR A VARIABLE LENGTH CHARACTER STRING LENGTH STRLENINBUF 3%4 $%3#2)04/2 PARMDESC 6!,5%J $!4! INBUF 3%4 $%3#2)04/2 PARMDESC 6!,5%J ,%.'4( LENGTH
&OR DATA ITEMS THAT DO NOT REQUIRE A LENGTH SPECIFICATION PASSING THE DATA IS EVEN EASIER SINCE ONLY THE $!4! FORM OF THE 3%4 $%3#2)04/2 STATEMENT IS REQUIRED )TS ALSO USEFUL TO NOTE THAT THE 31, STANDARD SPECIFIES IMPLICIT DATA TYPE CONVERSIONS BETWEEN HOST VARIABLES SUCH AS INBUF AND 31, DATA TYPES &OLLOWING THE 31, STANDARD IT WOULD BE NECESSARY FOR THE PROGRAM IN &IGURE TO PERFORM ALL OF THE DATA TYPE CONVERSION IN THE SSCANF FUNCTIONS
#HAPTERçç
$YNAMICç31, ç
)NSTEAD THE DATA COULD BE PASSED TO THE $"-3 AS CHARACTER DATA FOR AUTOMATIC CONVERSION AND ERROR DETECTION 7ITH THE 31,$! FINALLY SET UP AS REQUIRED THE PROGRAM IN &IGURE EXECUTES THE DYNAMIC 50$!4% STATEMENT WITH THE PASSED PARAMETERS AT CALLOUT USING AN %8%#54% STATEMENT THAT SPECIFIES A 31,$! 4HE CONVERSION OF THIS STATEMENT TO A 31, DESCRIPTOR IS STRAIGHTFORWARD IT BECOMES %8%#54% UPDATESTMT 53).' 31, $%3#2)04/2 PARMDESC
4HE KEYWORDS IN THE %8%#54% STATEMENT CHANGE SLIGHTLY AND THE NAME OF THE DESCRIPTOR IS SPECIFIED INSTEAD OF THE NAME OF THE 31,$! &INALLY THE PROGRAM IN &IGURE SHOULD BE MODIFIED LIKE THIS TO TELL THE $"-3 TO DEALLOCATE THE 31, DESCRIPTOR 4HE STATEMENT THAT DOES THIS IS $%!,,/#!4% $%3#2)04/2 PARMDESC
)N A SIMPLE PROGRAM LIKE THIS ONE THE $%!,,/#!4% IS NOT NECESSARY BUT IN A MORE COMPLEX REAL WORLD PROGRAM WITH MULTIPLE DESCRIPTORS ITS A VERY GOOD IDEA TO DEALLOCATE THE DESCRIPTORS WHEN THE PROGRAM NO LONGER REQUIRES THEM
4HEõ31,õ3TANDARDõANDõ$YNAMICõ31,õ1UERIES
!,,/#!4% $%3#2)04/2 QRYDESC 7)4( -!8 COLCOUNT $%3#2)"% QUERYSTMT 53).' 31, $%3#2)04/2 QRYDESC
4HE STANDARD 31, FORM OF THE $%3#2)"% STATEMENT HAS A PARALLEL EFFECT ON THE ONE IT REPLACES $ESCRIPTIONS OF THE QUERY RESULT COLUMNS ARE RETURNED COLUMN BY COLUMN INTO THE 31, DESCRIPTOR INSTEAD OF INTO THE 31,$! "ECAUSE THE DESCRIPTOR IS A $"-3 STRUCTURE RATHER THAN AN ACTUAL DATA STRUCTURE IN THE PROGRAM THE HOST PROGRAM MUST RETRIEVE THE INFORMATION FROM THE DESCRIPTOR PIECE BY PIECE AS REQUIRED 4HE '%4 $%3#2)04/2 STATEMENT PERFORMS THIS FUNCTION JUST AS THE 3%4 $%3#2)04/2 FUNCTION PERFORMS THE OPPOSITE FUNCTION OF PUTTING
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)N THE DYNAMIC 31, STATEMENTS OF THE PRECEDING SECTIONS THE 31, DESCRIPTOR LIKE THE 31,$! IT REPLACES IS USED TO PASS PARAMETER INFORMATION FROM THE HOST PROGRAM TO THE $"-3 FOR USE IN DYNAMIC STATEMENT EXECUTION 4HE 31, STANDARD ALSO USES THE 31, DESCRIPTOR IN DYNAMIC QUERY STATEMENTS WHERE LIKE THE 31,$! IT REPLACES IT CONTROLS THE PASSING OF QUERY RESULT FROM THE $"-3 BACK TO THE HOST PROGRAM &IGURE LISTS A $" STYLE DYNAMIC 31, QUERY PROGRAM )TS USEFUL TO EXAMINE HOW THE PROGRAM IN &IGURE WOULD CHANGE TO CONFORM TO THE 31, STANDARD !GAIN THE FLOW OF THE PROGRAM REMAINS IDENTICAL UNDER STANDARD 31, BUT THE SPECIFICS CHANGE QUITE A LOT 4HE STANDARD 31, FORMS OF THE DYNAMIC 31, QUERY PROCESSING STATEMENTS ARE SHOWN IN &IGURE 4HE DECLARATION OF THE CURSOR FOR THE DYNAMIC QUERY IN CALLOUT OF &IGURE REMAINS UNCHANGED UNDER THE 31, STANDARD 4HE CONSTRUCTION OF THE DYNAMIC 3%,%#4 STATEMENT IN CALLOUT IS ALSO UNCHANGED AS IS THE 02%0!2% STATEMENT OF CALLOUT 4HE CHANGES TO THE PROGRAM BEGIN AT CALLOUT WHERE THE PROGRAM USES THE $%3#2)"% STATEMENT TO OBTAIN A DESCRIPTION OF THE QUERY RESULTS WHICH IS RETURNED IN A 31,$! NAMED QRY?DA &OR STANDARD 31, THIS $%3#2)"% STATEMENT MUST BE MODIFIED TO REFER TO A 31, DESCRIPTOR WHICH MUST HAVE BEEN PREVIOUSLY ALLOCATED !SSUMING THE DESCRIPTOR IS NAMED QRYDESC THE STATEMENTS WOULD BE
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INFORMATION INTO THE 31, DESCRIPTOR )N THE PROGRAM OF &IGURE THE STATEMENTS AT CALLOUT WHICH OBTAINS THE LENGTH OF A PARTICULAR COLUMN OF QUERY RESULTS FROM A 31,$! WOULD BE REPLACED WITH THIS STATEMENT '%4 $%3#2)04/2 QRYDESC 6!,5% I LENGTH ,%.'4( QRY?VAR SQLDAT MALLOCLENGTH
4HE STATEMENT AT CALLOUT THAT ALLOCATES BUFFERS FOR EACH ITEM OF QUERY RESULTS IS STILL NEEDED BUT THE METHOD FOR TELLING THE $"-3 WHERE TO PUT THE RESULTS CHANGES FOR STANDARD 31, )NSTEAD OF PLACING THE ADDRESS OF THE PROGRAM DESTINATION FOR EACH ITEM INTO THE 31,$! THE PROGRAM MUST PLACE THESE ADDRESSES INTO THE 31, DESCRIPTOR USING THE 3%4 $%3#2)04/2 STATEMENT 4HE BUFFERS FOR THE INDICATOR VARIABLES ARE NOT NEEDED WITH THE 31, DESCRIPTOR )NSTEAD THE INFORMATION ABOUT WHETHER A COLUMN CONTAINS A .5,, VALUE CAN BE OBTAINED FROM THE DESCRIPTOR FOR EACH ROW AS IT IS FETCHED AS SEEN LATER IN THE PROGRAM EXAMPLE )N THIS PARTICULAR EXAMPLE THE NUMBER OF COLUMNS IN THE QUERY RESULTS ARE CALCULATED BY THE PROGRAM AS IT BUILDS THE QUERY 4HE PROGRAM COULD ALSO OBTAIN THE NUMBER OF COLUMNS FROM THE 31, DESCRIPTOR WITH THIS FORM OF THE '%4 $%3#2)04/2 STATEMENT '%4 $%3#2)04/2 QRYDESC COLCOUNT #/5.4
#HAPTERçç
$YNAMICç31, ç
(AVING OBTAINED THE DESCRIPTION OF THE QUERY RESULTS THE PROGRAM PERFORMS THE QUERY BY OPENING THE CURSOR AT CALLOUT 4HE SIMPLE FORM OF THE /0%. STATEMENT WITHOUT ANY INPUT PARAMETERS CONFORMS TO THE 31, STANDARD )F THE DYNAMIC QUERY SPECIFIED PARAMETERS THEY COULD BE PASSED TO THE $"-3 EITHER AS A SERIES OF HOST VARIABLES OR VIA A 31, DESCRIPTOR 4HE STANDARD 31, /0%. STATEMENT USING HOST VARIABLES IS IDENTICAL TO THE $" STYLE SHOWN IN THE PROGRAM IN &IGURE 4HE STANDARD 31, /0%. STATEMENT USING A DESCRIPTOR IS PARALLEL TO THE STANDARD 31, %8%#54% STATEMENT USING A DESCRIPTOR AND DIFFERS FROM THE $" STYLE &OR EXAMPLE THE /0%. STATEMENT OF &IGURE /0%. QRYCURSOR 53).' $%3#2)04/2 PARMDA
IS CHANGED FOR STANDARD 31, INTO THIS /0%. STATEMENT /0%. QRYCURSOR 53).' 31, $%3#2)04/2 PARMDESC
4HE TECHNIQUE FOR PASSING INPUT PARAMETERS TO THE /0%. STATEMENT VIA THE 31, DESCRIPTOR IS EXACTLY THE SAME AS THAT DESCRIBED EARLIER FOR THE %8%#54% STATEMENT ,IKE THE /RACLE IMPLEMENTATION OF DYNAMIC 31, THE 31, STANDARD PROVIDES A WAY FOR THE HOST PROGRAM TO OBTAIN A DESCRIPTION OF THE PARAMETERS IN A DYNAMIC QUERY AS WELL AS A DESCRIPTION OF THE QUERY RESULTS &OR THE PROGRAM FRAGMENT IN &IGURE THIS $%3#2)"% STATEMENT $%3#2)"% ).054 QUERYSTMT 53).' 31, $%3#2)04/2 PARMDESC
WILL RETURN IN THE 31, DESCRIPTOR NAMED PARMDESC A DESCRIPTION OF EACH OF THE PARAMETERS THAT APPEAR IN THE DYNAMIC QUERY 4HE NUMBER OF PARAMETERS CAN BE OBTAINED WITH THE '%4 $%3#2)04/2 STATEMENT RETRIEVING THE #/5.4 ITEM FROM THE DESCRIPTOR !S WITH THE /RACLE IMPLEMENTATION THE 31, STANDARD CAN HAVE TWO DESCRIPTORS ASSOCIATED WITH A DYNAMIC QUERY 4HE INPUT DESCRIPTOR OBTAINED WITH THE $%3#2)"% ).054 STATEMENT CONTAINS DESCRIPTIONS OF THE PARAMETERS 4HE OUTPUT DESCRIPTOR CONTAINS DESCRIPTIONS OF THE QUERY RESULTS COLUMNS 4HE STANDARD ALLOWS YOU TO EXPLICITLY ASK FOR THE OUTPUT DESCRIPTION $%3#2)"% /54054 QUERYSTMT 53).' 31, $%3#2)04/2 QRYDESC
&%4#( SQLCURS 53).' 31, $%3#2)04/2 QRYDESC
4HE &%4#( STATEMENT ADVANCES THE CURSOR TO THE NEXT ROW OF QUERY RESULTS AND BRINGS THE VALUES FOR THAT ROW INTO THE PROGRAM BUFFERS AS SPECIFIED WITHIN THE DESCRIPTOR STRUCTURE 4HE PROGRAM MUST STILL USE THE DESCRIPTOR TO DETERMINE INFORMATION ABOUT EACH COLUMN OF RETURNED RESULTS SUCH AS ITS LENGTH OR WHETHER IT CONTAINS A .5,, VALUE &OR EXAMPLE TO DETERMINE THE RETURNED LENGTH OF A COLUMN OF CHARACTER DATA THE PROGRAM MIGHT USE THE STATEMENT '%4 $%3#2)04/2 QRYDESC 6!,5%I LENGTH 2%452.%$?,%.'4(
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BUT THE $%3#2)"% /54054 FORM OF THE STATEMENT IS THE DEFAULT AND THE MOST COMMON PRACTICE IS TO OMIT THE KEYWORD /54054 2ETURNING TO THE DYNAMIC QUERY EXAMPLE OF &IGURE THE CURSOR HAS BEEN OPENED AT CALLOUT AND ITS TIME TO FETCH ROWS OF QUERY RESULTS AT CALLOUT !GAIN THE STANDARD 31, FORM OF THE &%4#( STATEMENT IS SLIGHTLY MODIFIED TO USE THE STANDARD 31, DESCRIPTOR
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0ARTç6ç
0ROGRAMMINGçWITHç31,
4O DETERMINE WHETHER THE VALUE IN THE COLUMN WAS .5,, THE PROGRAM CAN USE THE STATEMENT '%4 $%3#2)04/2 QRYDESC 6!,5%I INDBUF ).$)#!4/2
!ND SIMILARLY TO DETERMINE THE DATA TYPE OF THE COLUMN THE PROGRAM CAN USE THE STATEMENT '%4 $%3#2)04/2 QRYDESC 6!,5%I TYPE 490%
!S YOU CAN SEE THE DETAILS OF ROW BY ROW QUERY PROCESSING WITHIN THE FOR LOOP OF THE PROGRAM WILL DIFFER DRAMATICALLY FROM THOSE IN &IGURE (AVING PROCESSED ALL ROWS OF QUERY RESULTS THE PROGRAM CLOSES THE CURSOR AT CALLOUT 4HE #,/3% STATEMENT REMAINS UNCHANGED UNDER STANDARD 31, &OLLOWING THE CLOSING OF THE CURSOR IT WOULD BE GOOD PRACTICE TO DEALLOCATE THE 31, DESCRIPTORS WHICH WOULD HAVE BEEN ALLOCATED AT THE VERY BEGINNING OF THE PROGRAM 4HE CHANGES REQUIRED TO THE DYNAMIC 31, PROGRAMS IN &IGURES AND TO MAKE THEM CONFORM TO THE 31, STANDARD ILLUSTRATE IN DETAIL THE NEW FEATURES SPECIFIED BY THE STANDARD AND THE DEGREE TO WHICH THEY DIFFER FROM COMMON DYNAMIC 31, USAGE TODAY )N SUMMARY THE CHANGES FROM $" STYLE DYNAMIC 31, ARE s 4HE 31,$! STRUCTURE IS REPLACED WITH A NAMED 31, DESCRIPTOR s 4HE !,,/#!4% $%3#2)04/2 AND $%!,,/#!4% $%3#2)04/2 STATEMENTS ARE USED TO CREATE AND DESTROY DESCRIPTORS REPLACING ALLOCATION AND DEALLOCATION OF HOST PROGRAM 31,$! DATA STRUCTURES s )NSTEAD OF DIRECTLY MANIPULATING ELEMENTS OF THE 31,$! THE PROGRAM SPECIFIES PARAMETER VALUES AND INFORMATION THROUGH THE 3%4 $%3#2)04/2 STATEMENT s )NSTEAD OF DIRECTLY MANIPULATING ELEMENTS OF THE 31,$! THE PROGRAM OBTAINS INFORMATION ABOUT QUERY RESULTS AND OBTAINS THE QUERY RESULT DATA ITSELF THROUGH THE '%4 $%3#2)04/2 STATEMENT s 4HE $%3#2)"% STATEMENT IS USED BOTH TO OBTAIN DESCRIPTIONS OF QUERY RESULTS $%3#2)"% /54054 AND TO OBTAIN DESCRIPTIONS OF PARAMETERS $%3#2)"% ).054 s 4HE %8%#54% /0%. AND &%4#( STATEMENTS ARE SLIGHTLY MODIFIED TO SPECIFY THE 31, DESCRIPTOR BY NAME INSTEAD OF THE 31,$!
3UMMARY 4HIS CHAPTER DESCRIBED DYNAMIC 31, AN ADVANCED FORM OF EMBEDDED 31, $YNAMIC 31, IS RARELY NEEDED TO WRITE SIMPLE DATA PROCESSING APPLICATIONS BUT IT IS CRUCIAL FOR BUILDING GENERAL PURPOSE DATABASE FRONT ENDS 3TATIC 31, AND DYNAMIC 31, PRESENT A CLASSIC TRADE OFF BETWEEN EFFICIENCY AND FLEXIBILITY WHICH CAN BE SUMMARIZED AS FOLLOWS s 3IMPLICITY 3TATIC 31, IS RELATIVELY SIMPLE EVEN ITS MOST COMPLEX FEATURE CURSORS CAN BE EASILY UNDERSTOOD IN TERMS OF FAMILIAR FILE INPUTOUTPUT CONCEPTS $YNAMIC 31, IS COMPLEX REQUIRING DYNAMIC STATEMENT GENERATION VARIABLE LENGTH DATA STRUCTURES AND MEMORY MANAGEMENT WITH MEMORY ALLOCATIONDEALLOCATION DATA TYPE ALIGNMENT POINTER MANAGEMENT AND ASSOCIATED ISSUES
#HAPTERçç
$YNAMICç31, ç
s 0ERFORMANCE 3TATIC 31, IS COMPILED INTO AN APPLICATION PLAN AT COMPILE TIME DYNAMIC 31, MUST BE COMPILED AT RUNTIME !S A RESULT STATIC 31, PERFORMANCE IS GENERALLY MUCH BETTER THAN THAT OF DYNAMIC 31, 4HE PERFORMANCE OF DYNAMIC 31, IS DRAMATICALLY IMPACTED BY THE QUALITY OF THE APPLICATION DESIGN A DESIGN THAT MINIMIZES THE AMOUNT OF COMPILATION OVERHEAD CAN APPROACH STATIC 31, PERFORMANCE s &LEXIBILITY $YNAMIC 31, ALLOWS A PROGRAM TO DECIDE AT RUNTIME WHICH SPECIFIC 31, STATEMENTS IT WILL EXECUTE 3TATIC 31, REQUIRES THAT ALL 31, STATEMENTS BE CODED IN ADVANCE WHEN THE PROGRAM IS WRITTEN LIMITING THE FLEXIBILITY OF THE PROGRAM $YNAMIC 31, USES A SET OF EXTENDED EMBEDDED 31, STATEMENTS TO SUPPORT ITS DYNAMIC FEATURES s 4HE %8%#54% )--%$)!4% STATEMENT PASSES THE TEXT OF A DYNAMIC 31, STATEMENT TO THE $"-3 WHICH EXECUTES IT IMMEDIATELY s 4HE 02%0!2% STATEMENT PASSES THE TEXT OF A DYNAMIC 31, STATEMENT TO THE $"-3 WHICH COMPILES IT INTO AN APPLICATION PLAN BUT DOES NOT EXECUTE IT 4HE DYNAMIC STATEMENT MAY INCLUDE PARAMETER MARKERS WHOSE VALUES ARE SPECIFIED WHEN THE STATEMENT IS EXECUTED s 4HE %8%#54% STATEMENT ASKS THE $"-3 TO EXECUTE A DYNAMIC STATEMENT PREVIOUSLY COMPILED BY A 02%0!2% STATEMENT )T ALSO SUPPLIES PARAMETER VALUES FOR THE STATEMENT THAT IS TO BE EXECUTED s 4HE $%3#2)"% STATEMENT RETURNS A DESCRIPTION OF A PREVIOUSLY PREPARED DYNAMIC STATEMENT INTO A 31,$! )F THE DYNAMIC STATEMENT IS A QUERY THE DESCRIPTION INCLUDES A DESCRIPTION OF EACH COLUMN OF QUERY RESULTS s 4HE $%#,!2% #523/2 STATEMENT FOR A DYNAMIC QUERY SPECIFIES THE QUERY BY THE STATEMENT NAME ASSIGNED TO IT WHEN IT WAS COMPILED BY THE 02%0!2% STATEMENT s 4HE /0%. STATEMENT FOR A DYNAMIC QUERY PASSES PARAMETER VALUES FOR THE DYNAMIC 3%,%#4 STATEMENT AND REQUESTS QUERY EXECUTION s 4HE &%4#( STATEMENT FOR A DYNAMIC QUERY FETCHES A ROW OF QUERY RESULTS INTO PROGRAM DATA AREAS SPECIFIED BY A 31,$! STRUCTURE s 4HE #,/3% STATEMENT FOR A DYNAMIC QUERY ENDS ACCESS TO THE QUERY RESULTS
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#(!04%2
31,ç!0)S
4
HE EARLY )"- RELATIONAL DATABASE PROTOTYPES PIONEERED THE EMBEDDED 31, TECHNIQUE FOR PROGRAMMATIC ACCESS TO 31, BASED DATABASES WHICH WAS WIDELY ADOPTED BY MAINSTREAM 31, PRODUCTS (OWEVER SEVERAL MAJOR $"-3 PRODUCTS LED BY 3YBASES FIRST 31, 3ERVER IMPLEMENTATION TOOK A VERY DIFFERENT APPROACH )NSTEAD OF TRYING TO BLEND 31, WITH ANOTHER PROGRAMMING LANGUAGE THESE PRODUCTS PROVIDE A LIBRARY OF FUNCTION CALLS AS AN APPLICATION PROGRAMMING INTERFACE !0) FOR THE $"-3 4O PASS 31, STATEMENTS TO THE $"-3 AN APPLICATION PROGRAM CALLS FUNCTIONS IN THE !0) AND IT CALLS OTHER FUNCTIONS TO RETRIEVE QUERY RESULTS AND STATUS INFORMATION FROM THE $"-3 &OR MANY PROGRAMMERS A 31, !0) IS A VERY STRAIGHTFORWARD WAY TO USE 31, -OST PROGRAMMERS HAVE SOME EXPERIENCE IN USING FUNCTION LIBRARIES FOR OTHER PURPOSES SUCH AS STRING MANIPULATION MATHEMATICAL FUNCTIONS FILE INPUTOUTPUT AND SCREEN FORMS MANAGEMENT -ODERN OPERATING SYSTEMS SUCH AS 5.)8 AND 7INDOWS EXTENSIVELY USE !0) SUITES TO EXTEND THE CORE CAPABILITIES PROVIDED BY THE /3 ITSELF 4HE 31, !0) THUS BECOMES JUST ANOTHER LIBRARY FOR THE PROGRAMMER TO LEARN /VER THE LAST DECADE OR SO 31, !0)S HAVE BECOME VERY POPULAR EQUALING IF NOT SURPASSING THE POPULARITY OF THE EMBEDDED 31, APPROACH FOR NEW APPLICATIONS DEVELOPMENT 4HIS CHAPTER DESCRIBES THE GENERAL CONCEPTS USED BY ALL 31, !0) INTERFACES )T ALSO DESCRIBES SPECIFIC FEATURES OF SOME OF THE PROPRIETARY !0)S USED BY POPULAR 31, BASED $"-3 SYSTEMS AND BOTH THE !.3))3/ 31, #ALL ,EVEL )NTERFACE #,) STANDARD AND -ICROSOFTS /PEN $ATABASE #ONNECTIVITY /$"# STANDARD ON WHICH THE !.3))3/ #,) IS BASED &INALLY THIS CHAPTER DESCRIBES *$"# WHICH IS THE !0) STANDARD FOR 31, ACCESS FROM PROGRAMS WRITTEN IN *AVA AND IS USED BY MOST OF THE POPULAR )NTERNET APPLICATION SERVERS
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!0)õ#ONCEPTS 7HEN A $"-3 SUPPORTS A FUNCTION CALL INTERFACE AN APPLICATION PROGRAM COMMUNICATES WITH THE $"-3 EXCLUSIVELY THROUGH A SET OF CALLS THAT ARE COLLECTIVELY KNOWN AS AN APPLICATION PROGRAMMING INTERFACE OR !0) 4HE BASIC OPERATION OF A TYPICAL $"-3 !0) IS ILLUSTRATED IN &IGURE s 4HE PROGRAM BEGINS ITS DATABASE ACCESS WITH ONE OR MORE !0) CALLS THAT CONNECT THE PROGRAM TO THE $"-3 AND OFTEN TO A SPECIFIC DATABASE OR SCHEMA s 4O SEND A 31, STATEMENT TO THE $"-3 THE PROGRAM BUILDS THE STATEMENT AS A TEXT STRING IN A BUFFER OFTEN STORED AS A HOST LANGUAGE VARIABLE AND THEN MAKES AN !0) CALL TO PASS THE BUFFER CONTENTS TO THE $"-3 s 4HE PROGRAM MAKES !0) CALLS TO CHECK THE STATUS OF ITS $"-3 REQUEST AND TO HANDLE ERRORS s )F THE REQUEST IS A QUERY THE PROGRAM USES !0) CALLS TO RETRIEVE THE QUERY RESULTS INTO THE PROGRAMS BUFFERS 4YPICALLY THE CALLS RETURN DATA A ROW AT A TIME OR A COLUMN AT A TIME s 4HE PROGRAM ENDS ITS DATABASE ACCESS WITH AN !0) CALL THAT DISCONNECTS IT FROM THE $"-3
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31,ç!0)Sç
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! 31, !0) IS OFTEN USED WHEN THE APPLICATION PROGRAM AND THE DATABASE ARE ON TWO DIFFERENT SYSTEMS IN A CLIENTSERVER ARCHITECTURE AS SHOWN IN &IGURE )N THIS CONFIGURATION THE CODE FOR THE !0) FUNCTIONS IS LOCATED ON THE CLIENT SYSTEM WHERE THE APPLICATION PROGRAM EXECUTES 4HE $"-3 SOFTWARE IS LOCATED ON THE SERVER SYSTEM WHERE THE DATABASE RESIDES #ALLS FROM THE APPLICATION PROGRAM TO THE !0) TAKE PLACE LOCALLY WITHIN THE CLIENT SYSTEM AND THE !0) CODE TRANSLATES THE CALLS INTO MESSAGES THAT IT SENDS TO AND RECEIVES FROM THE $"-3 OVER A NETWORK ! 31, !0) OFFERS PARTICULAR ADVANTAGES FOR A CLIENTSERVER ARCHITECTURE BECAUSE IT CAN MINIMIZE THE AMOUNT OF NETWORK TRAFFIC BETWEEN THE !0) AND THE $"-3 4HE EARLY !0)S OFFERED BY VARIOUS $"-3 PRODUCTS DIFFERED SUBSTANTIALLY FROM ONE ANOTHER ,IKE MANY PARTS OF 31, PROPRIETARY 31, !0)S PROLIFERATED LONG BEFORE THERE WAS AN ATTEMPT TO STANDARDIZE THEM )N ADDITION 31, !0)S TEND TO EXPOSE THE UNDERLYING CAPABILITIES OF THE $"-3 MORE THAN THE EMBEDDED 31, APPROACH LEADING TO EVEN MORE DIFFERENCES .ONETHELESS ALL OF THE 31, !0)S AVAILABLE IN COMMERCIAL 31, PRODUCTS ARE BASED ON THE SAME FUNDAMENTAL CONCEPTS ILLUSTRATED IN &IGURES AND 4HESE CONCEPTS ALSO APPLY TO THE /$"# !0) AND TO MORE RECENT !.3))3/ STANDARDS BASED ON IT
4HEõDBLIBõ!0)õ31,õ3ERVER
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4HE FIRST MAJOR $"-3 PRODUCT TO EMPHASIZE ITS CALLABLE !0) WAS 31, 3ERVER IN VERSIONS FROM BOTH 3YBASE AND -ICROSOFT &OR MANY YEARS THE 31, 3ERVER CALLABLE !0) WAS THE ONLY INTERFACE OFFERED BY THESE PRODUCTS "OTH -ICROSOFT AND 3YBASE NOW OFFER EMBEDDED 31, CAPABILITIES AND HAVE ADDED NEWER OR HIGHER LEVEL CALLABLE !0)S BUT THE ORIGINAL 31, 3ERVER !0) REMAINS A VERY POPULAR WAY TO ACCESS THESE $"-3 BRANDS 4HE 31, 3ERVER !0) ALSO PROVIDED THE MODEL FOR MUCH OF -ICROSOFTS /$"# !0) 31, 3ERVER AND ITS !0) ARE ALSO AN EXCELLENT EXAMPLE OF A $"-3 DESIGNED FROM THE GROUND UP AROUND A CLIENTSERVER ARCHITECTURE &OR ALL OF THESE REASONS ITS USEFUL TO BEGIN OUR EXPLORATION OF 31, !0)S BY EXAMINING THE BASIC 31, 3ERVER !0) 4HE ORIGINAL 31, 3ERVER !0) WHICH IS CALLED THE DATABASE LIBRARY OR DBLIB CONSISTS OF ABOUT FUNCTIONS AVAILABLE TO AN APPLICATION PROGRAM 4HE !0) IS VERY COMPREHENSIVE BUT A TYPICAL PROGRAM USES ONLY ABOUT A DOZEN OF THE FUNCTION CALLS WHICH ARE SUMMARIZED IN 4ABLE 4HE OTHER CALLS PROVIDE ADVANCED FEATURES ALTERNATIVE METHODS OF INTERACTING WITH THE $"-3 OR SINGLE CALL VERSIONS OF FEATURES THAT OTHERWISE WOULD REQUIRE MULTIPLE CALLS
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"ASICõ31,õ3ERVERõ4ECHNIQUES ! SIMPLE 31, 3ERVER PROGRAM THAT UPDATES A DATABASE CAN USE A VERY SMALL SET OF DBLIB CALLS TO DO ITS WORK 4HE PROGRAM IN &IGURE IMPLEMENTS A SIMPLE QUOTA UPDATE APPLICATION FOR THE 3!,%32%03 TABLE IN THE SAMPLE DATABASE )T IS IDENTICAL TO THE PROGRAM IN &IGURE REPRODUCED HERE AS &IGURE BUT USES THE 31, 3ERVER !0) INSTEAD OF EMBEDDED 31, 4HE FIGURE ILLUSTRATES THE BASIC INTERACTION BETWEEN A PROGRAM AND 31, 3ERVER
4HE PROGRAM PREPARES A LOGIN RECORD FILLING IN THE USER NAME PASSWORD AND ANY OTHER INFORMATION REQUIRED TO CONNECT TO THE $"-3
4HE PROGRAM CALLS DBOPEN TO ESTABLISH A CONNECTION TO THE $"-3 ! CONNECTION MUST EXIST BEFORE THE PROGRAM CAN SEND 31, STATEMENTS TO 31, 3ERVER
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4HE PROGRAM BUILDS A 31, STATEMENT IN A BUFFER AND CALLS DBCMD TO PASS THE 31, TEXT TO DBLIB 3UCCESSIVE CALLS TO DBCMD ADD TO THE PREVIOUSLY PASSED TEXT THERE IS NO REQUIREMENT THAT A COMPLETE 31, STATEMENT BE SENT IN A SINGLE DBCMD CALL
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4HE PROGRAM CALLS DBEXIT TO CLOSE DOWN THE CONNECTION TO 31, 3ERVER
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31,ç!0)Sç
)TS INSTRUCTIVE TO COMPARE THE PROGRAMS IN &IGURE AND &IGURE TO SEE THE DIFFERENCES BETWEEN THE DBLIB APPROACH AND THE EMBEDDED 31, s 4HE EMBEDDED 31, PROGRAM EITHER IMPLICITLY CONNECTS TO THE ONLY AVAILABLE DATABASE AS IN $" OR IT INCLUDES AN EMBEDDED 31, STATEMENT FOR CONNECTION SUCH AS THE #/..%#4 STATEMENT SPECIFIED BY THE 31, STANDARD 4HE DBLIB PROGRAM CONNECTS TO A PARTICULAR 31, 3ERVER WITH THE DBOPEN CALL s 4HE ACTUAL 31, 50$!4% STATEMENT PROCESSED BY THE $"-3 IS IDENTICAL IN BOTH PROGRAMS 7ITH EMBEDDED 31, THE STATEMENT IS PART OF THE PROGRAMS SOURCE CODE 7ITH DBLIB THE STATEMENT IS PASSED TO THE !0) AS A SEQUENCE OF ONE OR MORE CHARACTER STRINGS )N FACT THE DBLIB APPROACH MORE CLOSELY RESEMBLES THE DYNAMIC 31, %8%#54% )--%$)!4% STATEMENT THAN IT DOES STATIC 31, s )N THE EMBEDDED 31, PROGRAM HOST VARIABLES PROVIDE THE LINK BETWEEN THE 31, STATEMENTS AND THE VALUES OF PROGRAM VARIABLES 7ITH DBLIB THE PROGRAM PASSES VARIABLE VALUES TO THE $"-3 IN THE SAME WAY THAT IT PASSES PROGRAM TEXTAS PART OF A 31, STATEMENT STRING s 7ITH EMBEDDED 31, ERRORS ARE RETURNED IN THE 31,#/$% OR 31,34!4% FIELD OF THE 31,#! STRUCTURE 7ITH DBLIB THE DBRESULTS CALL RETRIEVES THE STATUS OF EACH 31, STATEMENT /VERALL THE EMBEDDED 31, PROGRAM IN &IGURE IS SHORTER AND PROBABLY EASIER TO READ (OWEVER THE PROGRAM IS NEITHER PURELY # NOR PURELY 31, AND A PROGRAMMER MUST BE TRAINED IN THE USE OF EMBEDDED 31, TO UNDERSTAND IT 4HE USE OF HOST VARIABLES MEANS THAT THE INTERACTIVE AND EMBEDDED FORMS OF THE 31, STATEMENT ARE DIFFERENT )N ADDITION THE EMBEDDED 31, PROGRAM MUST BE PROCESSED BOTH BY THE 31, PRECOMPILER AND BY THE # COMPILER LENGTHENING THE COMPILATION CYCLE )N CONTRAST THE 31, 3ERVER PROGRAM IS A PLAIN VANILLA # PROGRAM DIRECTLY ACCEPTABLE TO THE # COMPILER AND DOES NOT REQUIRE SPECIAL CODING TECHNIQUES
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4HE PROGRAM IN &IGURE SENDS A SINGLE 31, STATEMENT TO 31, 3ERVER AND CHECKS ITS STATUS )F AN APPLICATION PROGRAM MUST EXECUTE SEVERAL 31, STATEMENTS IT CAN REPEAT THE DBCMD DBSQLEXEC DBRESULTS CYCLE FOR EACH STATEMENT !LTERNATIVELY THE PROGRAM CAN SEND SEVERAL STATEMENTS AS A SINGLE STATEMENT BATCH TO BE EXECUTED BY 31, 3ERVER &IGURE SHOWS A PROGRAM THAT USES A BATCH OF THREE 31, STATEMENTS !S IN &IGURE THE PROGRAM CALLS DBCMD TO PASS 31, TEXT TO DBLIB 4HE !0) SIMPLY CONCATENATES THE TEXT FROM EACH CALL .OTE THAT ITS THE PROGRAMS RESPONSIBILITY TO INCLUDE ANY REQUIRED SPACES OR PUNCTUATION IN THE PASSED TEXT 31, 3ERVER DOES NOT BEGIN EXECUTING THE STATEMENTS UNTIL THE PROGRAM CALLS DBSQLEXEC )N THIS EXAMPLE THREE STATEMENTS HAVE BEEN SENT TO 31, 3ERVER SO THE PROGRAM CALLS DBRESULTS THREE TIMES IN SUCCESSION %ACH CALL TO DBRESULTS ADVANCES THE !0) TO THE RESULTS OF THE NEXT STATEMENT IN THE BATCH AND TELLS THE PROGRAM WHETHER THE STATEMENT SUCCEEDED OR FAILED )N THE PROGRAM SHOWN IN &IGURE THE PROGRAMMER KNOWS IN ADVANCE THAT THREE STATEMENTS ARE IN THE BATCH AND THE PROGRAMMER CAN CODE THREE CORRESPONDING CALLS TO DBRESULTS )F THE NUMBER OF STATEMENTS IN THE BATCH IS NOT KNOWN IN ADVANCE THE PROGRAM CAN CALL DBRESULTS REPEATEDLY UNTIL IT RECEIVES THE ERROR CODE ./?-/2%? 2%35,43 4HE PROGRAM EXCERPT IN &IGURE ILLUSTRATES THIS TECHNIQUE
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%RRORõ(ANDLING 4HE VALUE RETURNED BY THE DBRESULTS FUNCTION TELLS THE PROGRAM WHETHER THE CORRESPONDING STATEMENT IN THE STATEMENT BATCH SUCCEEDED OR FAILED 4O GET MORE DETAILED INFORMATION ABOUT A FAILURE YOUR PROGRAM MUST PROVIDE ITS OWN MESSAGE HANDLING FUNCTION 4HE DBLIB SOFTWARE AUTOMATICALLY CALLS THE MESSAGE HANDLING FUNCTION WHEN 31, 3ERVER ENCOUNTERS AN ERROR WHILE EXECUTING 31, STATEMENTS .OTE THAT DBLIB CALLS THE MESSAGE HANDLING FUNCTION DURING ITS PROCESSING OF THE DBSQLEXEC OR DBRESULTS FUNCTION CALLS BEFORE IT RETURNS TO YOUR PROGRAM IE IT IS A CALLBACK FUNCTION CALLED BACK BY THE 31, 3ERVER SOFTWARE 4HIS ALLOWS THE MESSAGE HANDLING FUNCTION TO DO ITS OWN ERROR PROCESSING
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&IGURE SHOWS AN EXCERPT FROM A 31, 3ERVER PROGRAM THAT INCLUDES A MESSAGE HANDLING FUNCTION CALLED MSG?RTN 7HEN THE PROGRAM BEGINS IT ACTIVATES THE MESSAGE HANDLING FUNCTION BY CALLING DBERRHANDLE 3UPPOSE AN ERROR OCCURS LATER WHILE 31, 3ERVER IS PROCESSING THE $%,%4% STATEMENT 7HEN THE PROGRAM CALLS DBSQLEXEC OR DBRESULTS AND DBLIB RECEIVES THE ERROR MESSAGE FROM 31, 3ERVER IT CALLS THE MSG? RTN ROUTINE IN THE PROGRAM PASSING IT FIVE PARAMETERS s DBPROC 4HE CONNECTION ON WHICH THE ERROR OCCURRED s MSGSTATE ! PARAMETER PROVIDING INFORMATION ABOUT THE ERROR CONTEXT s SEVERITY ! NUMBER INDICATING THE SERIOUSNESS OF THE ERROR s MSGTEXT !N ERROR MESSAGE CORRESPONDING TO MSGNO 4HE MSG?RTN FUNCTION IN THIS PROGRAM HANDLES THE MESSAGE BY PRINTING IT AND SAVING THE ERROR NUMBER IN A PROGRAM VARIABLE FOR USE LATER IN THE PROGRAM 7HEN THE MESSAGE HANDLING FUNCTION RETURNS TO DBLIB WHICH CALLED IT DBLIB COMPLETES ITS OWN PROCESSING AND THEN RETURNS TO THE PROGRAM WITH A &!), STATUS 4HE PROGRAM CAN DETECT THIS RETURN VALUE AND PERFORM FURTHER ERROR PROCESSING IF APPROPRIATE
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s MSGNO 4HE 31, 3ERVER ERROR NUMBER IDENTIFYING THE ERROR
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31,ç!0)Sç
4HE PROGRAM EXCERPT IN THE FIGURE ACTUALLY PRESENTS A SIMPLIFIED VIEW OF 31, 3ERVER ERROR HANDLING )N ADDITION TO 31, STATEMENT ERRORS DETECTED BY 31, 3ERVER ERRORS CAN ALSO OCCUR WITHIN THE DBLIB !0) ITSELF &OR EXAMPLE IF THE NETWORK CONNECTION TO THE 31, 3ERVER IS LOST A DBLIB CALL MAY TIME OUT WAITING FOR A RESPONSE FROM 31, 3ERVER RESULTING IN AN ERROR 4HE !0) HANDLES THESE ERRORS BY CALLING A SEPARATE ERROR HANDLING FUNCTION WHICH OPERATES MUCH LIKE THE MESSAGE HANDLING FUNCTION DESCRIBED HERE ! COMPARISON OF &IGURE WITH &IGURES AND REPRODUCED HERE AS &IGURES AND RESPECTIVELY ILLUSTRATES THE DIFFERENCES IN ERROR HANDLING TECHNIQUES BETWEEN DBLIB AND EMBEDDED 31, s )N EMBEDDED 31, THE 31,#! STRUCTURE IS USED TO SIGNAL ERRORS AND WARNINGS TO THE PROGRAM 31, 3ERVER COMMUNICATES ERRORS AND WARNINGS BY CALLING SPECIAL FUNCTIONS WITHIN THE APPLICATION PROGRAM AND RETURNING A FAILURE STATUS FOR THE !0) FUNCTION THAT ENCOUNTERED THE ERROR s )N EMBEDDED 31, ERROR PROCESSING IS SYNCHRONOUS 4HE EMBEDDED 31, STATEMENT FAILS CONTROL RETURNS TO THE PROGRAM AND THE 31,#/$% OR 31,34!4% VALUE IS TESTED 31, 3ERVER ERROR PROCESSING IS ASYNCHRONOUS 7HEN AN !0) CALL FAILS 31, 3ERVER CALLS THE APPLICATION PROGRAMS ERROR HANDLING OR MESSAGE HANDLING FUNCTION DURING THE !0) CALL )T RETURNS TO THE APPLICATION PROGRAM WITH AN ERROR STATUS LATER s %MBEDDED 31, HAS ONLY A SINGLE TYPE OF ERROR AND A SINGLE MECHANISM FOR REPORTING IT 4HE 31, 3ERVER SCHEME HAS TWO TYPES OF ERRORS AND TWO PARALLEL MECHANISMS )N SUMMARY ERROR HANDLING IN EMBEDDED 31, IS SIMPLE AND STRAIGHTFORWARD BUT THE APPLICATION PROGRAM CAN MAKE ONLY A LIMITED NUMBER OF RESPONSES WHEN AN ERROR OCCURS ! 31, 3ERVER PROGRAM HAS MORE FLEXIBILITY IN HANDLING ERRORS (OWEVER THE CALL SCHEME USED BY DBLIB IS MORE SOPHISTICATED AND WHILE IT IS FAMILIAR TO SYSTEMS PROGRAMMERS IT MAY BE UNFAMILIAR TO APPLICATION PROGRAMMERS 1, Ê£nÊ Ê Ê ÊiLi``i`Ê-+ Ê «À}À>ÊiÝViÀ«ÌÊ ÜÌ
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4HE PROGRAM USES THE DBCMD AND DBSQLEXEC CALLS TO PASS A 3%,%#4 STATEMENT TO 31, 3ERVER AND REQUEST ITS EXECUTION
7HEN THE PROGRAM CALLS DBRESULTS FOR THE 3%,%#4 STATEMENT DBLIB RETURNS THE COMPLETION STATUS FOR THE QUERY AND ALSO MAKES THE QUERY RESULTS AVAILABLE FOR PROCESSING
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31,ç!0)Sç
4HE PROGRAM CALLS DBBIND ONCE FOR EACH COLUMN OF QUERY RESULTS TELLING DBLIB WHERE IT SHOULD RETURN THE DATA FOR THAT PARTICULAR COLUMN 4HE ARGUMENTS TO DBBIND INDICATE THE COLUMN NUMBER THE EXPECTED DATA TYPE THE SIZE OF THE BUFFER AND THE BUFFER TO RECEIVE ITS DATA
4HE PROGRAM LOOPS CALLING DBNEXTROW REPEATEDLY TO OBTAIN THE ROWS OF QUERY RESULTS 4HE !0) PLACES THE RETURNED DATA INTO THE DATA AREAS INDICATED IN THE PREVIOUS DBBIND CALLS
7HEN NO MORE ROWS OF QUERY RESULTS ARE AVAILABLE THE DBNEXTROW CALL RETURNS THE VALUE ./?-/2%?2/73 )F MORE STATEMENTS WERE IN THE STATEMENT BATCH FOLLOWING THE 3%,%#4 STATEMENT THE PROGRAM COULD CALL DBRESULTS TO ADVANCE TO THE NEXT STATEMENT
4WO OF THE DBLIB CALLS IN &IGURE DBBIND AND DBNEXTROW SUPPORT PROCESSING OF THE 31, 3ERVER QUERY RESULTS 4HE DBBIND CALL SETS UP A ONE TO ONE CORRESPONDENCE BETWEEN EACH COLUMN OF QUERY RESULTS AND THE PROGRAM VARIABLE THAT IS TO RECEIVE THE RETRIEVED DATA 4HIS PROCESS IS CALLED BINDING THE COLUMN )N THE FIGURE THE FIRST COLUMN .!-% IS BOUND TO A BYTE CHARACTER ARRAY AND WILL BE RETURNED AS A .5,, TERMINATED STRING 4HE SECOND AND THIRD COLUMNS 15/4! AND 3!,%3 ARE BOTH BOUND TO FLOATING POINT NUMBERS )T IS THE PROGRAMMERS RESPONSIBILITY TO MAKE SURE THAT THE DATA TYPE OF EACH COLUMN OF QUERY RESULTS IS COMPATIBLE WITH THE DATA TYPE OF THE PROGRAM VARIABLE TO WHICH IT IS BOUND /NCE AGAIN IT IS USEFUL TO COMPARE THE 31, 3ERVER QUERY PROCESSING IN &IGURE WITH THE EMBEDDED 31, QUERIES IN &IGURE AND &IGURE REPRODUCED HERE AS &IGURES AND RESPECTIVELY s %MBEDDED 31, HAS TWO DIFFERENT QUERY PROCESSING TECHNIQUESONE FOR SINGLE ROW QUERIES SINGLETON 3%,%#4 AND ONE FOR MULTIROW QUERIES CURSORS 4HE DBLIB !0) USES A SINGLE TECHNIQUE REGARDLESS OF THE NUMBER OF ROWS OF QUERY RESULTS s 4O SPECIFY THE QUERY EMBEDDED 31, REPLACES THE INTERACTIVE 3%,%#4 STATEMENT WITH THE SINGLETON 3%,%#4 STATEMENT OR THE $%#,!2% #523/2 STATEMENT 7ITH 31, 3ERVER THE 3%,%#4 STATEMENT SENT BY THE PROGRAM IS IDENTICAL TO THE INTERACTIVE 3%,%#4 STATEMENT FOR THE QUERY
s 7ITH EMBEDDED 31, ROW BY ROW ACCESS TO QUERY RESULTS IS PROVIDED BY SPECIAL PURPOSE EMBEDDED 31, STATEMENTS /0%. &%4#( AND #,/3% 7ITH 31, 3ERVER ACCESS TO QUERY RESULTS IS THROUGH DBLIB FUNCTION CALLS DBRESULTS AND DBNEXTROW WHICH KEEP THE 31, LANGUAGE ITSELF MORE STREAMLINED "ECAUSE OF ITS RELATIVE SIMPLICITY AND ITS SIMILARITY TO THE INTERACTIVE 31, INTERFACE MANY PROGRAMMERS FIND THE 31, 3ERVER INTERFACE EASIER TO USE FOR QUERY PROCESSING THAN THE EMBEDDED 31, INTERFACE
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2ETRIEVINGõ.5,,õ6ALUES 4HE DBNEXTROW AND DBBIND CALLS SHOWN IN &IGURE PROVIDE A SIMPLE WAY TO RETRIEVE QUERY RESULTS BUT THEY DO NOT SUPPORT .5,, VALUES 7HEN A ROW RETRIEVED BY DBNEXTROW INCLUDES A COLUMN WITH A .5,, VALUE 31, 3ERVER REPLACES THE .5,, WITH A .5,, SUBSTITUTION VALUE "Y DEFAULT 31, 3ERVER USES ZERO AS A SUBSTITUTION VALUE FOR NUMERIC DATA TYPES A STRING OF BLANKS FOR FIXED LENGTH STRINGS AND AN EMPTY STRING FOR VARIABLE LENGTH STRINGS 4HE APPLICATION PROGRAM CAN CHANGE THE DEFAULT VALUE FOR ANY DATA TYPE BY CALLING THE !0) FUNCTION DBSETNULL
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)N THE PROGRAM SHOWN IN &IGURE IF ONE OF THE SALESREPS HAD A .5,, VALUE IN HIS OR HER 15/4! COLUMN THE DBNEXTROW CALL FOR THAT SALESREP WOULD RETRIEVE A ZERO INTO THE REPQUOTA VARIABLE .OTE THAT THE PROGRAM CANNOT TELL FROM THE RETRIEVED DATA WHETHER THE 15/4! COLUMN FOR THE ROW REALLY HAS A ZERO VALUE OR WHETHER IT IS .5,, )N SOME APPLICATIONS THE USE OF SUBSTITUTION VALUES IS ACCEPTABLE BUT IN OTHERS IT IS IMPORTANT TO BE ABLE TO DETECT .5,, VALUES 4HESE LATTER APPLICATIONS MUST USE AN ALTERNATIVE SCHEME FOR RETRIEVING QUERY RESULTS DESCRIBED IN THE NEXT SECTION
2ETRIEVALõ5SINGõ0OINTERS 7ITH THE BASIC 31, 3ERVER DATA RETRIEVAL TECHNIQUE THE DBNEXTROW CALL COPIES THE DATA VALUE FOR EACH COLUMN INTO ONE OF YOUR PROGRAMS VARIABLES )F THERE ARE MANY ROWS OF QUERY RESULTS OR MANY LONG COLUMNS OF TEXT DATA COPYING THE DATA INTO YOUR PROGRAMS DATA AREAS CAN CREATE SIGNIFICANT OVERHEAD )N ADDITION THE DBNEXTROW CALL LACKS A MECHANISM FOR RETURNING .5,, VALUES TO YOUR PROGRAM 4O SOLVE THESE TWO PROBLEMS DBLIB OFFERS AN ALTERNATE METHOD OF RETRIEVING QUERY RESULTS &IGURE SHOWS THE PROGRAM EXCERPT FROM &IGURE REWRITTEN TO USE THIS ALTERNATE METHOD
4HE PROGRAM SENDS THE QUERY TO 31, 3ERVER AND USES DBRESULTS TO ACCESS THE RESULTS AS IT DOES FOR ANY 31, STATEMENT (OWEVER THE PROGRAM DOES NOT CALL DBBIND TO BIND THE COLUMNS OF QUERY RESULTS TO PROGRAM VARIABLES
4HE PROGRAM CALLS DBNEXTROW TO ADVANCE ROW BY ROW THROUGH THE QUERY RESULTS
&OR EACH COLUMN OF EACH ROW THE PROGRAM CALLS DBDATA TO OBTAIN A POINTER TO THE DATA VALUE FOR THE COLUMN 4HE POINTER POINTS TO A LOCATION WITHIN DBLIBS INTERNAL BUFFERS
)F A COLUMN CONTAINS VARIABLE LENGTH DATA SUCH AS A 6!2#(!2 DATA ITEM THE PROGRAM CALLS DBDATLEN TO FIND THE LENGTH OF THE DATA ITEM
)F A COLUMN HAS A .5,, VALUE THE DBDATA FUNCTION RETURNS A NULL POINTER AND DBDATLEN RETURNS AS THE LENGTH OF THE ITEM 4HESE RETURN VALUES GIVE THE PROGRAM A WAY TO DETECT AND RESPOND TO .5,, VALUES IN THE QUERY RESULTS
2ANDOMõ2OWõ2ETRIEVAL ! PROGRAM NORMALLY PROCESSES 31, 3ERVER QUERY RESULTS BY MOVING THROUGH THEM SEQUENTIALLY USING THE DBNEXTROW CALL &OR BROWSING APPLICATIONS DBLIB ALSO PROVIDES LIMITED RANDOM ACCESS TO THE ROWS OF QUERY RESULTS 9OUR PROGRAM MUST EXPLICITLY ENABLE RANDOM ROW ACCESS BY TURNING ON A DBLIB OPTION 4HE DBGETROW CALL CAN THEN BE USED TO RETRIEVE A ROW BY ITS ROW NUMBER 4O SUPPORT RANDOM ROW RETRIEVAL DBLIB STORES THE ROWS OF QUERY RESULTS IN AN INTERNAL BUFFER )F THE QUERY RESULTS FIT ENTIRELY WITHIN THE DBLIB BUFFER DBGETROW SUPPORTS RANDOM RETRIEVAL OF ANY ROW )F THE QUERY RESULTS EXCEED THE SIZE OF THE BUFFER ONLY THE INITIAL ROWS OF QUERY RESULTS ARE STORED 4HE PROGRAM CAN RANDOMLY RETRIEVE THESE ROWS BUT A
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4HE PROGRAM IN &IGURE IS MORE CUMBERSOME THAN THE ONE IN &IGURE )N GENERAL ITS EASIER TO USE THE DBBIND FUNCTION THAN THE DBDATA APPROACH UNLESS YOUR PROGRAM NEEDS TO HANDLE .5,, VALUES OR WILL BE HANDLING A LARGE VOLUME OF QUERY RESULTS
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DBNEXTROW CALL THAT ATTEMPTS TO RETRIEVE A ROW PAST THE END OF THE BUFFER RETURNS THE SPECIAL "5&?&5,, ERROR CONDITION 4HE PROGRAM MUST THEN DISCARD SOME OF THE SAVED ROWS FROM THE BUFFER USING THE DBCLRBUF CALL TO MAKE ROOM FOR THE NEW ROW /NCE THE ROWS ARE DISCARDED THEY CANNOT BE RE RETRIEVED WITH THE DBGETROW FUNCTION 4HUS DBLIB SUPPORTS RANDOM RETRIEVAL OF QUERY RESULTS WITHIN A LIMITED WINDOW DICTATED BY THE SIZE OF THE ROW BUFFER AS SHOWN IN &IGURE 9OUR PROGRAM CAN SPECIFY THE SIZE OF THE DBLIB ROW BUFFER BY CALLING THE DBLIB ROUTINE DBSETOPT 4HE RANDOM ACCESS PROVIDED BY DBGETROW IS SIMILAR TO THE SCROLL CURSORS SUPPORTED BY SEVERAL $"-3 PRODUCTS AND SPECIFIED BY THE 31, STANDARD )N BOTH CASES RANDOM RETRIEVAL BY ROW NUMBER IS SUPPORTED (OWEVER A SCROLL CURSOR IS A TRUE POINTER INTO THE ENTIRE SET OF QUERY RESULTS IT CAN RANGE FROM THE FIRST TO THE LAST ROW EVEN IF THE QUERY RESULTS CONTAIN THOUSANDS OF ROWS "Y CONTRAST THE DBGETROW FUNCTION PROVIDES RANDOM ACCESS ONLY WITHIN A LIMITED WINDOW 4HIS IS ADEQUATE FOR LIMITED BROWSING APPLICATIONS BUT CANNOT EASILY BE EXTENDED TO LARGE QUERIES
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)N AN EMBEDDED 31, PROGRAM A CURSOR PROVIDES A DIRECT INTIMATE LINK BETWEEN THE PROGRAM AND THE $"-3 QUERY PROCESSING 4HE PROGRAM COMMUNICATES WITH THE $"-3 ROW BY ROW AS IT USES THE &%4#( STATEMENT TO RETRIEVE QUERY RESULTS )F THE QUERY IS A SIMPLE SINGLE TABLE QUERY THE $"-3 CAN MAINTAIN A DIRECT CORRESPONDENCE BETWEEN THE CURRENT ROW OF QUERY RESULTS AND THE CORRESPONDING ROW WITHIN THE DATABASE 5SING THIS CORRESPONDENCE THE PROGRAM CAN USE THE POSITIONED UPDATE STATEMENTS 50$!4%x7(%2% #522%.4 /& AND $%,%4%x7(%2% #522%.4 /& TO MODIFY OR DELETE THE CURRENT ROW OF QUERY RESULTS 31, 3ERVER QUERY PROCESSING USES A MUCH MORE DETACHED ASYNCHRONOUS CONNECTION BETWEEN THE PROGRAM AND THE $"-3 )N RESPONSE TO A STATEMENT BATCH CONTAINING ONE OR MORE 3%,%#4 STATEMENTS 31, 3ERVER SENDS THE QUERY RESULTS BACK TO THE DBLIB SOFTWARE WHICH MANAGES THEM 2OW BY ROW RETRIEVAL IS HANDLED BY THE DBLIB !0) CALLS NOT BY 31, STATEMENTS !S A RESULT EARLY VERSIONS OF 31, 3ERVER COULD NOT SUPPORT POSITIONED UPDATES BECAUSE ITS NOTION OF A CURRENT ROW APPLIED TO QUERY RESULTS WITHIN THE DBLIB !0) NOT TO ROWS OF THE ACTUAL DATABASE TABLES
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,ATER VERSIONS OF 31, 3ERVER AND 3YBASE ADDED COMPLETE SUPPORT FOR STANDARD 31, CURSORS WITH THEIR ASSOCIATED $%#,!2%/0%.&%4#(#,/3% 31, STATEMENTS 31, 3ERVER AND 3YBASE CURSORS ACTUALLY OPERATE WITHIN 4RANSACT 31, STORED PROCEDURES AND THE ACTION OF THE &%4#( STATEMENT IS TO FETCH DATA FROM THE DATABASE INTO THE STORED PROCEDURE FOR PROCESSINGNOT TO ACTUALLY RETRIEVE IT INTO THE APPLICATION PROGRAM THAT CALLED THE STORED PROCEDURE 3TORED PROCEDURES AND THEIR OPERATION WITHIN VARIOUS POPULAR 31, $"-3 PRODUCTS ARE DISCUSSED IN #HAPTER
$YNAMICõ1UERIES )N THE PROGRAM EXAMPLES THUS FAR IN THIS CHAPTER THE QUERIES TO BE PERFORMED WERE KNOWN IN ADVANCE 4HE COLUMNS OF QUERY RESULTS COULD BE BOUND TO PROGRAM VARIABLES BY EXPLICIT DBBIND CALLS HARD CODED IN THE PROGRAM -OST PROGRAMS THAT USE 31, 3ERVER CAN BE WRITTEN USING THIS TECHNIQUE 4HIS STATIC COLUMN BINDING CORRESPONDS TO THE FIXED LIST OF HOST VARIABLES USED IN THE STATIC 31, &%4#( STATEMENT IN STANDARD EMBEDDED 31, DESCRIBED IN #HAPTER )F THE QUERY TO BE CARRIED OUT BY A PROGRAM IS NOT KNOWN AT THE TIME THE PROGRAM IS WRITTEN THE PROGRAM CANNOT INCLUDE HARD CODED DBBIND CALLS )NSTEAD THE PROGRAM MUST ASK DBLIB FOR A DESCRIPTION OF EACH COLUMN OF QUERY RESULTS USING SPECIAL !0) FUNCTIONS 4HE PROGRAM CAN THEN BIND THE COLUMNS ON THE FLY TO DATA AREAS THAT IT ALLOCATES AT RUNTIME 4HIS DYNAMIC COLUMN BINDING CORRESPONDS TO THE USE OF THE DYNAMIC 31, $".5-#/,3 STATEMENT AND 31,$! IN DYNAMIC EMBEDDED 31, AS DESCRIBED IN #HAPTER &IGURE SHOWS AN INTERACTIVE QUERY PROGRAM THAT ILLUSTRATES THE DBLIB TECHNIQUE FOR HANDLING DYNAMIC QUERIES 4HE PROGRAM ACCEPTS A TABLE NAME ENTERED BY THE USER AND THEN PROMPTS THE USER TO CHOOSE WHICH COLUMNS ARE TO BE RETRIEVED FROM THE TABLE !S THE USER SELECTS THE COLUMNS THE PROGRAM CONSTRUCTS A 3%,%#4 STATEMENT AND THEN USES THESE STEPS TO EXECUTE THE 3%,%#4 STATEMENT AND DISPLAY THE DATA FROM THE SELECTED COLUMNS
4HE PROGRAM PASSES THE GENERATED 3%,%#4 STATEMENT TO 31, 3ERVER USING THE DBCMD CALL REQUESTS ITS EXECUTION WITH THE DBSQLEXEC CALL AND CALLS DBRESULTS TO ADVANCE THE !0) TO THE QUERY RESULTS AS IT DOES FOR ALL QUERIES
4HE PROGRAM CALLS DBNUMCOLS TO FIND OUT HOW MANY COLUMNS OF QUERY RESULTS WERE PRODUCED BY THE 3%,%#4 STATEMENT
&OR EACH COLUMN THE PROGRAM CALLS DBCOLNAME TO FIND OUT THE NAME OF THE COLUMN AND CALLS DBCOLTYPE TO FIND OUT ITS DATA TYPE
4HE PROGRAM ALLOCATES A BUFFER TO RECEIVE EACH COLUMN OF QUERY RESULTS AND CALLS DBBIND TO BIND EACH COLUMN TO ITS BUFFER
7HEN ALL COLUMNS HAVE BEEN BOUND THE PROGRAM CALLS DBNEXTROW REPEATEDLY TO RETRIEVE EACH ROW OF QUERY RESULTS
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4HE DBLIB BASED PROGRAM IN &IGURE PERFORMS EXACTLY THE SAME FUNCTION AS THE DYNAMIC EMBEDDED 31, PROGRAM IN &IGURE REPRODUCED HERE AS &IGURE )TS INSTRUCTIVE TO COMPARE THE TWO PROGRAMS AND THE TECHNIQUES THEY USE s &OR BOTH EMBEDDED 31, AND DBLIB THE PROGRAM BUILDS A 3%,%#4 STATEMENT IN ITS BUFFERS AND SUBMITS IT TO THE $"-3 FOR PROCESSING 7ITH DYNAMIC 31, THE SPECIAL 02%0!2% STATEMENT HANDLES THIS TASK WITH THE 31, 3ERVER !0) THE STANDARD DBCMD AND DBSQLEXEC FUNCTIONS ARE USED s &OR BOTH INTERFACES THE PROGRAM MUST REQUEST A DESCRIPTION OF THE COLUMNS OF QUERY RESULTS FROM THE $"-3 7ITH DYNAMIC 31, THE SPECIAL $".5-#/,3 STATEMENT HANDLES THIS TASK AND THE DESCRIPTION IS RETURNED IN A 31,$! DATA STRUCTURE 7ITH DBLIB THE DESCRIPTION IS OBTAINED BY CALLING !0) FUNCTIONS .OTE THAT THE PROGRAM IN &IGURE MAINTAINS ITS OWN ARRAYS TO KEEP TRACK OF THE COLUMN INFORMATION
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4HE #,) USES A TECHNIQUE COMMONLY USED BY MODERN OPERATING SYSTEMS AND LIBRARY PACKAGES TO MANAGE THESE CONCEPTUAL ENTITIES ! SYMBOLIC POINTER CALLED A HANDLE IS ASSOCIATED WITH THE OVERALL 31, ENVIRONMENT WITH A 31, CONNECTION TO A SPECIFIC DATABASE SERVER AND WITH THE EXECUTION OF A 31, STATEMENT 4HE HANDLE IDENTIFIES AN AREA OF MEMORY MANAGED BY THE #,) ITSELF 3OME TYPE OF HANDLE IS PASSED AS ONE OF THE PARAMETERS IN EVERY #,) CALL 4HE #,) ROUTINES THAT MANAGE HANDLES ARE SHOWN IN &IGURE ! HANDLE IS CREATED ALLOCATED USING THE #,) 31,!LLOC(ANDLE ROUTINE /NE OF THE PARAMETERS OF THE ROUTINE TELLS THE #,) WHICH TYPE OF HANDLE IS TO BE ALLOCATED !NOTHER PARAMETER RETURNS THE HANDLE VALUE TO THE APPLICATION PROGRAM /NCE ALLOCATED A HANDLE IS PASSED TO SUBSEQUENT #,) ROUTINES TO MAINTAIN A CONTEXT FOR THE #,) CALLS )N THIS WAY DIFFERENT THREADS OF EXECUTION WITHIN A PROGRAM OR DIFFERENT CONCURRENTLY RUNNING PROGRAMS PROCESSES CAN EACH ESTABLISH THEIR OWN CONNECTION TO THE #,) AND CAN MAINTAIN THEIR OWN CONTEXTS INDEPENDENT OF ONE ANOTHER (ANDLES ALSO ALLOW A SINGLE PROGRAM TO HAVE MULTIPLE #,) CONNECTIONS TO DIFFERENT DATABASE SERVERS AND TO PROCESS MORE THAN ONE 31, STATEMENT IN PARALLEL 7HEN A HANDLE IS NO LONGER NEEDED THE APPLICATION CALLS 31,&REE(ANDLE TO TELL THE #,) TO RELEASE THE RESOURCES IT IS USING )N ADDITION TO THE GENERAL PURPOSE HANDLE MANAGEMENT ROUTINES 31,!LLOC(ANDLE AND 31,&REE(ANDLE THE #,) SPECIFICATION INCLUDES SEPARATE ROUTINES TO CREATE AND FREE AN ENVIRONMENT CONNECTION OR STATEMENT HANDLE 4HESE ROUTINES 31,!LLOC%NV 31,!LLOC3TMT AND SO ON WERE A PART OF THE ORIGINAL /$"# !0) AND ARE STILL SUPPORTED IN CURRENT /$"# IMPLEMENTATIONS FOR BACKWARD COMPATIBILITY (OWEVER -ICROSOFT HAS INDICATED THAT THE GENERAL HANDLE MANAGEMENT ROUTINES ARE NOW THE PREFERRED /$"# FUNCTIONS AND THE SPECIFIC ROUTINES MAY BE DROPPED IN FUTURE /$"# RELEASES &OR MAXIMUM CROSS PLATFORM PORTABILITY ITS BEST TO USE THE GENERAL PURPOSE ROUTINES
31, %NVIRONMENT 4HE 31, ENVIRONMENT IS THE HIGHEST LEVEL CONTEXT USED BY AN APPLICATION PROGRAM IN ITS CALLS TO THE #,) ! SINGLE THREADED APPLICATION TYPICALLY HAS ONE 31, ENVIRONMENT FOR THE ENTIRE PROGRAM ! MULTITHREADED APPLICATION MAY HAVE ONE 31, ENVIRONMENT PER THREAD OR ONE OVERALL 31, ENVIRONMENT DEPENDING ON THE ARCHITECTURE OF THE PROGRAM 4HE #,) CONCEPTUALLY PERMITS MULTIPLE CONNECTIONS POSSIBLY TO SEVERAL DIFFERENT DATABASE SERVERS FROM WITHIN ONE 31, ENVIRONMENT ! SPECIFIC #,) IMPLEMENTATION FOR A SPECIFIC $"-3 MAY OR MAY NOT ACTUALLY SUPPORT MULTIPLE CONNECTIONS
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.ORMALLY AN APPLICATION PROGRAM KNOWS THE NAME OF THE SPECIFIC DATABASE SERVER IN TERMS OF THE STANDARD THE h31, SERVERv THAT IT NEEDS TO ACCESS )N CERTAIN APPLICATIONS SUCH AS GENERAL PURPOSE QUERY OR DATA ENTRY TOOLS IT MAY BE DESIRABLE TO LET THE USER CHOOSE WHICH DATABASE SERVER IS TO BE USED 4HE #,) 31,$ATA3OURCES CALL RETURNS THE NAMES OF THE 31, SERVERS THAT ARE KNOWN TO THE #,)THAT IS THE DATA SOURCES THAT CAN BE LEGALLY SPECIFIED AS SERVER NAMES IN 31,#ONNECT CALLS 4O OBTAIN THE LIST OF SERVER NAMES THE APPLICATION REPEATEDLY CALLS 31,$ATA3OURCES %ACH CALL RETURNS A SINGLE SERVER DESCRIPTION UNTIL THE CALL RETURNS AN ERROR INDICATING NO MORE DATA ! PARAMETER TO THE CALL CAN BE OPTIONALLY USED TO ALTER THIS SEQUENTIAL RETRIEVAL OF SERVER NAMES
#,)õ3TATEMENTõ0ROCESSING 4HE #,) PROCESSES 31, STATEMENTS USING A TECHNIQUE VERY SIMILAR TO THAT DESCRIBED FOR DYNAMIC EMBEDDED 31, IN #HAPTER 4HE 31, STATEMENT IS PASSED TO THE #,) IN TEXT FORM AS A CHARACTER STRING )T CAN BE EXECUTED IN A ONE OR TWO STEP PROCESS &IGURE SHOWS THE BASIC 31, STATEMENT PROCESSING CALLS 4HE APPLICATION PROGRAM MUST FIRST CALL 31,!LLOC(ANDLE TO OBTAIN A STATEMENT HANDLE WHICH IDENTIFIES THE STATEMENT TO THE PROGRAM AND THE #,) !LL SUBSEQUENT 31,%XEC$IRECT 31,0REPARE AND 31,%XECUTE CALLS REFERENCE THIS STATEMENT HANDLE 7HEN THE HANDLE IS NO LONGER NEEDED IT IS FREED WITH A 31,&REE(ANDLE CALL &OR ONE STEP EXECUTION THE APPLICATION PROGRAM CALLS 31, 31,%XEC$IRECT PASSING THE 31, STATEMENT TEXT AS ONE OF THE PARAMETERS TO THE CALL 4HE $"-3 PROCESSES THE STATEMENT AS A RESULT OF THE CALL AND RETURNS THE COMPLETION STATUS OF THE STATEMENT 4HIS ONE STEP PROCESS WAS USED IN THE SIMPLE EXAMPLE PROGRAM IN &IGURE )T CORRESPONDS TO THE ONE STEP %8%#54% )--%$)!4% STATEMENT IN EMBEDDED DYNAMIC 31, DESCRIBED IN #HAPTER &OR TWO STEP EXECUTION THE APPLICATION PROGRAM CALLS 31,0REPARE PASSING THE 31, STATEMENT TEXT AS ONE OF THE PARAMETERS TO THE CALL 4HE $"-3 ANALYZES THE STATEMENT DETERMINES HOW TO CARRY IT OUT AND RETAINS THIS INFORMATION )T DOES NOT IMMEDIATELY CARRY OUT THE STATEMENT )NSTEAD SUBSEQUENT CALLS TO THE 31,%XECUTE ROUTINE ACTUALLY CAUSE THE STATEMENT TO BE EXECUTED 4HIS TWO STEP PROCESS CORRESPONDS EXACTLY TO THE 02%0!2% AND %8%#54% EMBEDDED DYNAMIC 31, STATEMENTS DESCRIBED IN #HAPTER 9OU SHOULD ALWAYS USE IT FOR ANY 31, OPERATIONS THAT WILL BE CARRIED OUT REPEATEDLY BECAUSE IT CAUSES THE $"-3 TO GO THROUGH THE OVERHEAD OF STATEMENT ANALYSIS AND OPTIMIZATION ONLY ONCE IN RESPONSE TO THE 31,0REPARE CALL 0ARAMETERS CAN BE PASSED THROUGH THE #,) TO TAILOR THE OPERATION OF THE MULTIPLE 31,%XECUTE CALLS THAT FOLLOW )N MANY CASES A 31, STATEMENT MUST BE REPEATEDLY EXECUTED WITH CHANGES ONLY IN SOME OF THE VALUES THAT IT SPECIFIES &OR EXAMPLE AN ).3%24 STATEMENT TO ADD AN ORDER TO THE SAMPLE DATABASE IS IDENTICAL FOR EVERY ORDER EXCEPT FOR THE SPECIFIC INFORMATION ABOUT THE CUSTOMER NUMBER PRODUCT AND MANUFACTURER AND QUANTITY ORDERED !S DESCRIBED IN #HAPTER FOR DYNAMIC EMBEDDED 31, SUCH STATEMENTS CAN BE PROCESSED EFFICIENTLY BY SPECIFYING THE VARIABLE PARTS OF THE STATEMENT AS INPUT PARAMETERS 4HE STATEMENT TEXT PASSED TO THE 31,0REPARE CALL HAS A PARAMETER MARKERA QUESTION MARK IN ITS TEXT AT EACH POSITION WHERE A PARAMETER VALUE IS TO BE INSERTED 7HEN THE STATEMENT IS LATER EXECUTED VALUES MUST BE SUPPLIED FOR EACH OF ITS INPUT PARAMETERS
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4HE MOST STRAIGHTFORWARD WAY TO SUPPLY INPUT PARAMETER VALUES IS WITH THE 31,"IND0ARAM CALL %ACH CALL TO 31,"IND0ARAM ESTABLISHES A LINKAGE BETWEEN ONE OF THE PARAMETER MARKERS IN THE 31, STATEMENT IDENTIFIED BY NUMBER AND A VARIABLE IN THE APPLICATION PROGRAM IDENTIFIED BY ITS MEMORY ADDRESS )N ADDITION AN ASSOCIATION IS OPTIONALLY ESTABLISHED WITH A SECOND APPLICATION PROGRAM VARIABLE AN INTEGER THAT PROVIDES THE LENGTH OF VARIABLE LENGTH INPUT PARAMETERS )F THE PARAMETER IS A .5,, TERMINATED STRING LIKE THOSE USED IN # PROGRAMS A SPECIAL NEGATIVE CODE VALUE DEFINED IN THE HEADER FILE AS THE SYMBOLIC CONSTANT 31,?.43 CAN BE PASSED INDICATING THAT THE STRING LENGTH CAN BE OBTAINED FROM THE DATA ITSELF BY THE #,) ROUTINES 3IMILARLY A NEGATIVE CODE IS USED TO INDICATE A .5,, VALUE FOR AN INPUT PARAMETER )F THREE INPUT PARAMETER MARKERS ARE IN THE STATEMENT THREE CALLS WILL BE MADE TO 31,"IND0ARAM ONE FOR EACH INPUT PARAMETER /NCE THE ASSOCIATION BETWEEN APPLICATION PROGRAM VARIABLES MORE ACCURATELY PROGRAM STORAGE LOCATIONS AND THE STATEMENT PARAMETERS IS ESTABLISHED THE STATEMENT CAN BE EXECUTED WITH A CALL TO 31,%XECUTE 4O CHANGE THE PARAMETER VALUES FOR SUBSEQUENT STATEMENTS IT IS ONLY NECESSARY TO PLACE NEW VALUES IN THE APPLICATION PROGRAM BUFFER AREAS BEFORE THE NEXT CALL TO 31,%XECUTE !LTERNATIVELY THE PARAMETERS CAN BE REBOUND TO DIFFERENT DATA AREAS WITHIN THE APPLICATION PROGRAM BY SUBSEQUENT CALLS TO 31,"IND0ARAM &IGURE SHOWS A PROGRAM THAT INCLUDES A 31, STATEMENT WITH TWO INPUT PARAMETERS 4HE PROGRAM REPEATEDLY PROMPTS THE USER FOR A CUSTOMER NUMBER AND A NEW CREDIT LIMIT FOR THE CUSTOMER 4HE VALUES PROVIDED BY THE USER BECOME THE INPUT PARAMETERS TO AN 50$!4% STATEMENT FOR THE #534/-%23 TABLE 4HE 31,0ARAM$ATA AND 31,0UT$ATA FUNCTIONS PROVIDE AN ALTERNATIVE METHOD OF PASSING PARAMETER DATA AT RUNTIME CALLED DEFERRED PARAMETER PASSING 4HE SELECTION OF THIS TECHNIQUE FOR A PARTICULAR STATEMENT PARAMETER IS INDICATED IN THE CORRESPONDING CALL TO 31,"IND0ARAM )NSTEAD OF ACTUALLY SUPPLYING A PROGRAM DATA LOCATION TO WHICH THE PARAMETER IS BOUND THE 31,"IND0ARAM CALL INDICATES THAT DEFERRED PARAMETER PASSING WILL BE USED AND PROVIDES A VALUE THAT WILL LATER BE USED TO IDENTIFY THE PARTICULAR PARAMETER BEING PROCESSED IN THIS WAY !FTER STATEMENT EXECUTION IS REQUESTED BY A 31,%XECUTE OR 31,%XEC$IRECT CALL THE PROGRAM CALLS 31,0ARAM$ATA TO DETERMINE WHETHER DEFERRED PARAMETER DATA IS REQUIRED BY THE STATEMENT )F SO THE #,) RETURNS A STATUS CODE 31,?.%%$?$!4! ALONG WITH AN INDICATOR OF WHICH PARAMETER NEEDS A VALUE 4HE PROGRAM THEN CALLS 31,0UT$ATA TO ACTUALLY PROVIDE THE VALUE FOR THE PARAMETER 4YPICALLY THE PROGRAM THEN CALLS 31,0ARAM$ATA AGAIN TO DETERMINE IF ANOTHER PARAMETER REQUIRES DYNAMIC DATA 4HE CYCLE REPEATS UNTIL ALL REQUIRED DYNAMIC DATA HAS BEEN SUPPLIED AND 31, STATEMENT EXECUTION THEN CONTINUES NORMALLY 4HIS ALTERNATIVE PARAMETER PASSING METHOD IS CONSIDERABLY MORE COMPLEX THAN THE STRAIGHTFORWARD PROCESS OF BINDING PARAMETERS TO APPLICATION PROGRAM LOCATIONS )T HAS TWO ADVANTAGES 4HE FIRST IS THAT THE ACTUAL PASSING OF DATA VALUES AND THE ALLOCATION OF STORAGE TO CONTAIN THOSE VALUES CAN BE DELAYED UNTIL THE LAST POSSIBLE MOMENT WHEN THE DATA IS ACTUALLY NEEDED 4HE SECOND ADVANTAGE IS THAT THE TECHNIQUE CAN BE USED TO PASS VERY LONG PARAMETER VALUES PIECE BY PIECE &OR SELECTED LONG DATA TYPES THE #,) ALLOWS REPEATED CALLS TO 31,0UT$ATA FOR THE SAME PARAMETER WITH EACH CALL PASSING THE NEXT PART OF THE DATA &OR EXAMPLE THE TEXT OF A DOCUMENT THAT IS SUPPLIED AS A PARAMETER FOR THE 6!,5%3 CLAUSE OF AN ).3%24 STATEMENT MIGHT BE PASSED IN CHARACTER PIECES THROUGH REPEATED 31,0UT$ATA CALLS UNTIL ALL OF THE DOCUMENT HAS BEEN PASSED 4HIS AVOIDS THE NEED TO ALLOCATE A SINGLE VERY LARGE MEMORY BUFFER WITHIN THE APPLICATION PROGRAM TO HOLD THE ENTIRE PARAMETER VALUE
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4HE PROGRAM CALLS 31,%XEC$IRECT TO PASS THE TEXT OF THE 31, 3%,%#4 STATEMENT AND TO CARRY OUT THE QUERY
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4HE PROGRAM EXCERPT IN &IGURE SHOWS A SIMPLE QUERY CARRIED OUT USING THIS TECHNIQUE 4HE PROGRAM IS IDENTICAL IN FUNCTION TO THE DBLIB BASED PROGRAM EXAMPLE IN &IGURE )TS INSTRUCTIVE TO COMPARE THE TWO PROGRAMS 4HE SPECIFICS OF THE CALLS AND THEIR PARAMETERS ARE QUITE DIFFERENT BUT THE FLOW OF THE PROGRAMS AND THE LOGICAL SEQUENCE OF CALLS THAT THEY MAKE ARE THE SAME
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%ACH CALL TO 31,"IND#OL ESTABLISHES AN ASSOCIATION BETWEEN ONE COLUMN OF QUERY RESULTS IDENTIFIED BY COLUMN NUMBER AND AN APPLICATION PROGRAM BUFFER IDENTIFIED BY ITS ADDRESS 7ITH EACH CALL TO 31,&ETCH THE #,) USES THIS BINDING TO COPY THE APPROPRIATE DATA VALUE FOR THE COLUMN INTO THE PROGRAMS BUFFER AREA 7HEN APPROPRIATE A SECOND PROGRAM DATA AREA IS SPECIFIED AS THE INDICATOR VARIABLE BUFFER FOR THE COLUMN %ACH CALL TO 31,&ETCH SETS THIS PROGRAM VARIABLE TO INDICATE THE ACTUAL LENGTH OF THE RETURNED DATA VALUE FOR VARIABLE LENGTH DATA AND TO INDICATE WHEN A .5,, VALUE IS RETURNED 4HE #,) ROUTINES IN &IGURE CAN ALSO BE USED TO IMPLEMENT AN ALTERNATIVE METHOD OF PROCESSING QUERY RESULTS )N THIS TECHNIQUE THE COLUMNS OF QUERY RESULTS ARE NOT BOUND TO LOCATIONS IN THE APPLICATION PROGRAM IN ADVANCE )NSTEAD EACH CALL TO 31,&ETCH ONLY ADVANCES THE CURSOR TO THE NEXT ROW OF QUERY RESULTS )T DOES NOT ACTUALLY CAUSE RETRIEVAL OF DATA INTO HOST PROGRAM DATA AREAS )NSTEAD A CALL TO 31,'ET$ATA IS MADE TO ACTUALLY RETRIEVE THE DATA /NE OF THE PARAMETERS OF 31,'ET$ATA SPECIFIES WHICH COLUMN OF QUERY RESULTS IS TO BE RETRIEVED 4HE OTHER PARAMETERS SPECIFY THE DATA TYPE TO BE RETURNED AND THE LOCATION OF THE BUFFER TO RECEIVE THE DATA AND AN ASSOCIATED INDICATOR VARIABLE VALUE !T THE BASIC LEVEL THE 31,'ET$ATA CALL IS SIMPLY AN ALTERNATIVE TO THE HOST VARIABLE BINDING APPROACH PROVIDED BY 31,"IND#OL BUT 31,'ET$ATA PROVIDES AN IMPORTANT ADVANTAGE WHEN PROCESSING VERY LARGE DATA ITEMS 3OME DATABASES SUPPORT LONG BINARY OR CHARACTER VALUED COLUMNS THAT CAN CONTAIN THOUSANDS OR MILLIONS OF BYTES OF DATA )TS USUALLY IMPRACTICAL TO ALLOCATE A PROGRAM BUFFER TO HOLD ALL OF THE DATA IN SUCH A COLUMN 5SING 31,'ET$ATA THE PROGRAM CAN ALLOCATE A BUFFER OF REASONABLE SIZE AND WORK ITS WAY THROUGH THE DATA A FEW THOUSAND BYTES AT A TIME
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)TS POSSIBLE TO INTERMIX THE 31,"IND#OL AND 31,'ET$ATA STYLES TO PROCESS THE QUERY RESULTS OF A SINGLE STATEMENT )N THIS CASE THE 31,&ETCH CALL ACTUALLY RETRIEVES THE DATA VALUES FOR THE BOUND COLUMNS THOSE FOR WHICH A 31,"IND#OL CALL HAS BEEN MADE BUT THE PROGRAM MUST EXPLICITLY CALL 31,'ET$ATA TO PROCESS THE OTHER COLUMNS 4HIS TECHNIQUE MAY BE ESPECIALLY APPROPRIATE IF A QUERY RETRIEVES SEVERAL COLUMNS OF TYPICAL 31, DATA NAMES DATES MONEY AMOUNTS AND A COLUMN OR TWO OF LONG DATA SUCH AS THE TEXT OF A CONTRACT .OTE THAT SOME #,) IMPLEMENTATIONS SEVERELY RESTRICT THE ABILITY TO INTERMIX THE TWO STYLES OF PROCESSING )N PARTICULAR SOME IMPLEMENTATIONS REQUIRE THAT ALL OF THE BOUND COLUMNS APPEAR FIRST IN THE LEFT TO RIGHT ORDER OF QUERY RESULTS BEFORE ANY COLUMNS RETRIEVED USING 31,'ET$ATA
3CROLLINGõ#URSORS 4HE 31,#,) STANDARD SPECIFIES #,) SUPPORT FOR SCROLLING CURSORS THAT PARALLELS THE SCROLLING CURSOR SUPPORT ORIGINALLY INCLUDED IN THE 31, STANDARD FOR EMBEDDED 31, 4HE 31,&ETCH3CROLL CALL SHOWN IN &IGURE PROVIDES THE EXTENDED &%4#( FUNCTIONS NEEDED FOR FORWARDBACKWARD AND RANDOM RETRIEVAL OF QUERY RESULTS /NE OF ITS PARAMETERS SPECIFIES THE STATEMENT HANDLE FOR THE QUERY JUST AS FOR THE SIMPLE 31,&ETCH CALL 4HE OTHER TWO PARAMETERS SPECIFY THE DIRECTION OF &%4#( MOTION 02%6)/53 .%84 AND SO ON AND THE OFFSET FOR &%4#( MOTIONS THAT REQUIRE IT ABSOLUTE AND RELATIVE RANDOM ROW RETRIEVAL 4HE OPERATION OF 31,"IND#OL AND 31,'ET$ATA FOR PROCESSING RETURNED VALUES IS IDENTICAL TO THAT DESCRIBED FOR THE 31,&ETCH CALL
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(ERE ARE THE STEPS FOR DYNAMIC QUERY PROCESSING USING #,)
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4HE PROGRAM CALLS 31,.UM2ESULT#OLS TO DETERMINE THE NUMBER OF COLUMNS OF QUERY RESULTS
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4HE ALTERNATIVE #,) METHOD FOR DYNAMIC QUERY PROCESSING INVOLVES #,) DESCRIPTORS ! #,) DESCRIPTOR CONTAINS LOW LEVEL INFORMATION ABOUT A STATEMENT PARAMETER A PARAMETER DESCRIPTOR OR THE COLUMNS OF A ROW OF QUERY RESULTS A ROW DESCRIPTOR 4HE INFORMATION IN THE DESCRIPTOR IS LIKE THAT CONTAINED IN THE VARIABLE AREA OF THE 31,$!THE COLUMN OR PARAMETERS NAME DATA TYPE AND SUBTYPE LENGTH DATA BUFFER LOCATION .5,, INDICATOR LOCATION AND SO ON 4HE PARAMETER DESCRIPTORS AND ROW DESCRIPTORS THUS CORRESPOND TO THE INPUT AND OUTPUT 31,$!S PROVIDED BY SOME $"-3 BRANDS IN THEIR EMBEDDED DYNAMIC 31, IMPLEMENTATIONS #,) DESCRIPTORS ARE IDENTIFIED BY DESCRIPTOR HANDLES 4HE #,) PROVIDES A DEFAULT SET OF DESCRIPTORS FOR PARAMETERS AND QUERY RESULTS COLUMNS WHEN A STATEMENT IS PREPARED !LTERNATIVELY THE PROGRAM CAN ALLOCATE ITS OWN DESCRIPTORS AND USE THEM 4HE HANDLES OF THE DESCRIPTORS FOR A STATEMENT ARE CONSIDERED STATEMENT ATTRIBUTES AND THEY ARE ASSOCIATED WITH A PARTICULAR STATEMENT HANDLE 4HE DESCRIPTOR HANDLE VALUES CAN BE RETRIEVED AND SET BY THE APPLICATION PROGRAM USING THE ATTRIBUTE MANAGEMENT ROUTINES DESCRIBED LATER IN THE SECTION h#,) !TTRIBUTESv 4WO CALLS ARE USED TO RETRIEVE INFORMATION FROM A DESCRIPTOR GIVEN ITS HANDLE 4HE 31,'ET$ESC&IELD CALL RETRIEVES A PARTICULAR FIELD OF A DESCRIPTOR WHICH IS IDENTIFIED BY A CODE VALUE )T IS TYPICALLY USED TO OBTAIN THE DATA TYPE OR LENGTH OF A QUERY RESULTS COLUMN FOR EXAMPLE 4HE 31,'ET$ESC2EC CALL RETRIEVES MANY PIECES OF INFORMATION IN ONE CALL INCLUDING THE COLUMN OR PARAMETER NAME DATA TYPE AND SUBTYPE LENGTH PRECISION AND SCALE AND WHETHER IT MAY CONTAIN .5,, VALUES ! CORRESPONDING SET OF CALLS IS USED TO PLACE INFORMATION INTO A DESCRIPTOR 4HE 31,3ET$ESC&IELD CALL SETS THE VALUE OF A SINGLE PIECE OF INFORMATION WITHIN A DESCRIPTOR 4HE 31,3ET$ESC2EC SETS MULTIPLE VALUES IN A SINGLE CALL INCLUDING THE DATA TYPE AND SUBTYPE LENGTH PRECISION AND SCALE AND NULLABILITY &OR CONVENIENCE THE #,) PROVIDES A 31,#OPY$ESC CALL THAT COPIES ALL OF THE VALUES FROM ONE DESCRIPTOR TO ANOTHER
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%ACH #,) FUNCTION RETURNS A SHORT INTEGER VALUE THAT INDICATES ITS COMPLETION STATUS )F THE COMPLETION STATUS INDICATES AN ERROR THE ERROR HANDLING #,) CALLS SHOWN IN &IGURE CAN BE USED TO OBTAIN MORE INFORMATION ABOUT THE ERROR AND DIAGNOSE IT 4HE MOST BASIC ERROR HANDLING CALL IS 31,%RROR 4HE APPLICATION PROGRAM PASSES THE ENVIRONMENT CONNECTION AND STATEMENT HANDLES AND IS RETURNED THE 31,34!4% RESULT CODE THE NATIVE ERROR CODE OF THE SUBSYSTEM PRODUCING THE ERROR AND AN ERROR MESSAGE IN TEXT FORM 4HE 31,%RROR ROUTINE ACTUALLY RETRIEVES SPECIFIC FREQUENTLY USED INFORMATION FROM THE #,) DIAGNOSTICS AREA 4HE OTHER ERROR HANDLING ROUTINES PROVIDE MORE COMPLETE INFORMATION THROUGH DIRECT ACCESS TO THE DIAGNOSTIC RECORDS CREATED AND MAINTAINED BY THE #,) )N GENERAL A #,) CALL CAN PRODUCE MULTIPLE ERRORS WHICH RESULT IN MULTIPLE DIAGNOSTIC RECORDS 4HE 31,'ET$IAG2EC CALL RETRIEVES AN INDIVIDUAL DIAGNOSTIC RECORD BY RECORD NUMBER 4HROUGH REPEATED CALLS THE APPLICATION PROGRAM CAN RETRIEVE COMPLETE INFORMATION ABOUT ALL ERROR RECORDS PRODUCED BY A #,) CALL %VEN MORE COMPLETE INFORMATION CAN BE OBTAINED BY INTERROGATING INDIVIDUAL DIAGNOSTIC FIELDS WITHIN THE RECORD 4HIS CAPABILITY IS PROVIDED BY THE 31,'ET$IAG&IELD CALL !LTHOUGH NOT STRICTLY AN ERROR PROCESSING FUNCTION THE 31,2OW#OUNT FUNCTION LIKE THE ERROR HANDLING FUNCTIONS IS CALLED AFTER A PREVIOUS #,) 31,%XECUTE CALL )T IS USED TO DETERMINE THE IMPACT OF THE PREVIOUS STATEMENT WHEN IT WAS SUCCESSFUL ! RETURNED VALUE INDICATES THE NUMBER OF ROWS OF DATA AFFECTED BY THE PREVIOUSLY EXECUTED STATEMENT &OR EXAMPLE THE VALUE WOULD BE RETURNED FOR A SEARCHED 50$!4% STATEMENT THAT UPDATES FOUR ROWS
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#,)õ!TTRIBUTES 4HE #,) PROVIDES A NUMBER OF OPTIONS THAT CONTROL SOME OF THE DETAILS OF ITS PROCESSING 3OME OF THESE CONTROL RELATIVELY MINOR BUT CRITICAL DETAILS SUCH AS WHETHER THE #,) SHOULD AUTOMATICALLY ASSUME THAT PARAMETERS PASSED AS STRING VALUES ARE .5,, TERMINATED /THERS CONTROL BROADER ASPECTS OF #,) OPERATION SUCH AS THE SCROLLABILITY OF CURSORS 4HE #,) GIVES APPLICATION PROGRAMS THE CAPABILITY TO CONTROL THESE PROCESSING OPTIONS THROUGH A SET OF #,) ATTRIBUTES 4HE ATTRIBUTES ARE STRUCTURED IN A HIERARCHY PARALLELING THE ENVIRONMENTCONNECTIONSTATEMENT HIERARCHY OF THE #,) HANDLE STRUCTURE %NVIRONMENT ATTRIBUTES CONTROL OVERALL OPERATIONAL OPTIONS #ONNECTION OPTIONS APPLY TO A PARTICULAR CONNECTION CREATED BY THE 31,#ONNECT CALL BUT MAY VARY FROM ONE CONNECTION TO ANOTHER 3TATEMENT ATTRIBUTES APPLY TO THE PROCESSING OF AN INDIVIDUAL STATEMENT IDENTIFIED BY A #,) STATEMENT HANDLE ! SET OF #,) CALLS SHOWN IN &IGURE IS USED BY AN APPLICATION PROGRAM TO CONTROL ATTRIBUTES 4HE GET CALLS 31,'ET%NV!TTR 31,'ET#ONNECT!TTR AND 31,'ET3TMT!TTR OBTAIN CURRENT ATTRIBUTE VALUES 4HE SET CALLS 31,3ET%NV!TTR 31,3ET#ONNECT!TTR AND 31,3ET3TMT!TTR MODIFY THE CURRENT ATTRIBUTE VALUES )N ALL OF THE CALLS THE PARTICULAR ATTRIBUTE BEING PROCESSED IS INDICATED BY A CODE VALUE !LTHOUGH THE #,) STANDARD PROVIDES THIS ELABORATE ATTRIBUTE STRUCTURE IT ACTUALLY SPECIFIES RELATIVELY FEW ATTRIBUTES 4HE SINGLE ENVIRONMENT ATTRIBUTE SPECIFIED IS .5,, 4%2-).!4)/. IT CONTROLS NULL TERMINATED STRINGS 4HE SINGLE CONNECTION ATTRIBUTE SPECIFIED CONTROLS WHETHER THE #,) AUTOMATICALLY POPULATES A PARAMETER DESCRIPTOR WHEN A STATEMENT IS PREPARED OR EXECUTED 3TATEMENT LEVEL ATTRIBUTES CONTROL THE SCROLLABILITY AND SENSITIVITY OF CURSORS 0ERHAPS THE MOST IMPORTANT OF THE #,) SPECIFIED ATTRIBUTES ARE THE HANDLES OF THE FOUR #,) DESCRIPTORS THAT MAY BE ASSOCIATED WITH A STATEMENT TWO PARAMETER DESCRIPTORS AND TWO ROW DESCRIPTORS 4HE CALLS IN &IGURE ARE USED TO OBTAIN AND SET THESE DESCRIPTOR HANDLES WHEN USING DESCRIPTOR BASED STATEMENT PROCESSING 4HE /$"# !0) ON WHICH THE 31,#,) STANDARD WAS ORIGINALLY BASED INCLUDES MANY MORE ATTRIBUTES &OR EXAMPLE /$"# CONNECTION ATTRIBUTES CAN BE USED TO SPECIFY A READ ONLY CONNECTION TO ENABLE ASYNCHRONOUS STATEMENT PROCESSING TO SPECIFY THE TIMEOUT FOR A CONNECTION REQUEST AND SO ON /$"# ENVIRONMENT ATTRIBUTES CONTROL AUTOMATIC TRANSLATION OF /$"# CALLS FROM EARLIER VERSIONS OF THE /$"# STANDARD /$"# STATEMENT ATTRIBUTES CONTROL TRANSACTION ISOLATION LEVELS SPECIFY WHETHER A CURSOR IS SCROLLABLE AND LIMIT THE NUMBER OF ROWS OF QUERY RESULTS THAT MIGHT BE GENERATED BY A RUNAWAY QUERY
4HE #,) INCLUDES THREE SPECIFIC CALLS THAT CAN BE USED TO OBTAIN INFORMATION ABOUT THE PARTICULAR #,) IMPLEMENTATION )N GENERAL THESE CALLS WILL NOT BE USED BY AN APPLICATION PROGRAM WRITTEN FOR A SPECIFIC PURPOSE 4HEY ARE NEEDED BY GENERAL PURPOSE PROGRAMS SUCH AS A QUERY OR REPORT WRITING PROGRAM THAT NEED TO DETERMINE THE SPECIFIC CHARACTERISTICS OF THE #,) THEY ARE USING 4HE CALLS ARE SHOWN IN &IGURE 4HE 31,'ET)NFO CALL IS USED TO OBTAIN DETAILED INFORMATION ABOUT A #,) IMPLEMENTATION SUCH AS THE MAXIMUM LENGTHS OF TABLE AND USER NAMES WHETHER THE $"-3 SUPPORTS OUTER JOINS OR TRANSACTIONS AND WHETHER 31, IDENTIFIERS ARE CASE SENSITIVE 4HE 31,'ET&UNCTIONS CALL IS USED TO DETERMINE WHETHER A SPECIFIC IMPLEMENTATION SUPPORTS A PARTICULAR #,) FUNCTION CALL )T IS CALLED WITH A FUNCTION CODE VALUE CORRESPONDING TO ONE OF THE #,) FUNCTIONS AND RETURNS A PARAMETER INDICATING WHETHER THE FUNCTION IS SUPPORTED
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-ICROSOFT ORIGINALLY DEVELOPED THE /PEN $ATABASE #ONNECTIVITY /$"# !0) TO PROVIDE A DATABASE BRANDnINDEPENDENT !0) FOR DATABASE ACCESS ON ITS 7INDOWS OPERATING SYSTEMS 4HE EARLY /$"# !0) BECAME THE FOUNDATION FOR THE 31,#,) STANDARD WHICH IS NOW THE OFFICIAL !.3))3/ STANDARD FOR A 31, #ALL ,EVEL )NTERFACE 4HE ORIGINAL /$"# !0) WAS EXTENDED AND MODIFIED DURING THE STANDARDIZATION PROCESS TO CREATE THE 31,#,) SPECIFICATION 7ITH THE INTRODUCTION OF /$"# RELEASE -ICROSOFT BROUGHT /$"# INTO CONFORMANCE WITH THE 31, #,) STANDARD 7ITH THIS REVISION /$"# BECOMES A SUPERSET OF THE 31,#,) SPECIFICATION /$"# GOES BEYOND THE 31,#,) CAPABILITIES IN SEVERAL AREAS IN PART BECAUSE -ICROSOFTS GOALS FOR /$"# WERE BROADER THAN SIMPLY CREATING A STANDARDIZED DATABASE ACCESS !0) -ICROSOFT ALSO WANTED TO ALLOW A SINGLE 7INDOWS APPLICATION PROGRAM TO BE ABLE TO CONCURRENTLY ACCESS SEVERAL DIFFERENT DATABASES USING THE /$"# !0) )T ALSO WANTED TO PROVIDE A STRUCTURE WHERE DATABASE VENDORS COULD SUPPORT /$"# WITHOUT GIVING UP THEIR PROPRIETARY !0)S AND WHERE THE SOFTWARE THAT PROVIDED /$"# SUPPORT FOR A PARTICULAR BRAND OF $"-3 COULD BE DISTRIBUTED BY THE DATABASE VENDOR AND INSTALLED ON 7INDOWS BASED CLIENT SYSTEMS AS NEEDED 4HE LAYERED STRUCTURE OF /$"# AND OF SPECIAL /$"# MANAGEMENT CALLS PROVIDES THESE CAPABILITIES
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4HEõ3TRUCTUREõOFõ/$"# 4HE STRUCTURE OF /$"# AS IT IS PROVIDED ON 7INDOWS BASED OR OTHER OPERATING SYSTEMS IS SHOWN IN &IGURE 4HERE ARE THREE BASIC LAYERS TO THE /$"# SOFTWARE s #ALLABLE !0) !T THE TOP LAYER /$"# PROVIDES A SINGLE CALLABLE DATABASE ACCESS !0) THAT CAN BE USED BY ALL APPLICATION PROGRAMS 4HE !0) IS PACKAGED AS A DYNAMIC LINKED LIBRARY $,, WHICH IS AN INTEGRAL PART OF THE VARIOUS 7INDOWS OPERATING SYSTEMS s /$"# DRIVERS !T THE BOTTOM LAYER OF THE /$"# STRUCTURE IS A COLLECTION OF /$"# DRIVERS %ACH OF THE $"-3 BRANDS HAS A SEPARATE DRIVER 4HE PURPOSE OF THE DRIVER IS TO TRANSLATE THE STANDARDIZED /$"# CALLS INTO THE APPROPRIATE CALLS FOR THE SPECIFIC $"-3 THAT IT SUPPORTS %ACH DRIVER CAN BE INDEPENDENTLY INSTALLED ON A PARTICULAR COMPUTER SYSTEM 4HIS ALLOWS THE $"-3 VENDORS TO PROVIDE AN /$"# DRIVER FOR THEIR PARTICULAR BRAND OF $"-3 AND TO DISTRIBUTE THE DRIVER INDEPENDENTLY OF THE 7INDOWS OPERATING SYSTEM SOFTWARE )F THE DATABASE RESIDES ON THE SAME SYSTEM AS THE /$"# DRIVER THE DRIVER IS USUALLY LINKED DIRECTLY TO THE DATABASES NATIVE !0) CODE )F THE DATABASE IS TO BE ACCESSED OVER A NETWORK THE DRIVER MAY CALL A NATIVE $"-3 CLIENT TO HANDLE THE CLIENTSERVER CONNECTION OR THE DRIVER MIGHT HANDLE THE NETWORK CONNECTION ITSELF s $RIVER MANAGER )N THE MIDDLE LAYER OF THE /$"# STRUCTURE IS THE /$"# DRIVER MANAGER )TS ROLE IS TO LOAD AND UNLOAD THE VARIOUS /$"# DRIVERS ON REQUEST FROM APPLICATION PROGRAMS 4HE DRIVER MANAGER IS ALSO RESPONSIBLE FOR ROUTING THE !0) CALLS MADE BY APPLICATION PROGRAMS TO THE APPROPRIATE DRIVER FOR EXECUTION
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7HEN AN APPLICATION PROGRAM WANTS TO ACCESS A DATABASE VIA /$"# IT GOES THROUGH THE SAME INITIATION SEQUENCE SPECIFIED BY THE 31,#,) STANDARD 4HE PROGRAM ALLOCATES AN ENVIRONMENT HANDLE THEN A CONNECTION HANDLE AND THEN CALLS 31,#ONNECT SPECIFYING THE PARTICULAR DATA SOURCE TO BE ACCESSED 7HEN IT RECEIVES THE 31,#ONNECT CALL THE /$"# DRIVER MANAGER EXAMINES THE CONNECTION INFORMATION PROVIDED AND DETERMINES THE APPROPRIATE /$"# DRIVER THAT IS NEEDED 4HE DRIVER MANAGER LOADS THE DRIVER INTO MEMORY IF ITS NOT ALREADY BEING USED BY ANOTHER APPLICATION PROGRAM 3UBSEQUENT CALLS BY THE APPLICATION PROGRAM ON THIS PARTICULAR #,)/$"# CONNECTION ARE ROUTED TO THIS DRIVER 4HE APPLICATION PROGRAM CAN IF APPROPRIATE MAKE OTHER 31,#ONNECT CALLS FOR OTHER DATA SOURCES THAT WILL CAUSE THE DRIVER MANAGER TO CONCURRENTLY LOAD OTHER DRIVERS FOR OTHER $"-3 BRANDS 4HE APPLICATION PROGRAM CAN THEN USE /$"# TO COMMUNICATE WITH TWO OR MORE DIFFERENT DATABASES OF DIFFERENT BRANDS BY USING A UNIFORM !0)
/$"#õANDõ$"-3õ)NDEPENDENCE "Y PROVIDING A UNIFORM !0) AND ITS DRIVER MANAGER ARCHITECTURE /$"# GOES A LONG WAY TOWARD PROVIDING A CROSS VENDOR !0) FOR DATABASE ACCESS BUT ITS IMPOSSIBLE TO PROVIDE FULLY TRANSPARENT ACCESS 4HE /$"# DRIVERS FOR THE VARIOUS DATABASE SYSTEMS CAN EASILY MASK COSMETIC DIFFERENCES IN THEIR 31, DIALECTS AND !0) SUITES BUT MORE FUNDAMENTAL DIFFERENCES ARE DIFFICULT OR IMPOSSIBLE TO MASK /$"# PROVIDES A PARTIAL SOLUTION TO THIS PROBLEM BY PROVIDING SEVERAL DIFFERENT LEVELS OF /$"# CAPABILITY AND BY MAKING EACH /$"# DRIVER SELF DESCRIBING THROUGH THE /$"##,) CALLS THAT RETURN INFORMATION ABOUT GENERAL FUNCTIONALITY SUPPORTED FUNCTIONS AND SUPPORTED DATA TYPES (OWEVER THE EXISTENCE OF DIFFERENT CAPABILITY LEVELS AND PROFILES EFFECTIVELY PUSHES THE $"-3 DIFFERENCES RIGHT BACK INTO THE APPLICATION PROGRAM WHICH MUST DEAL WITH THIS NONUNIFORMITY OF /$"# DRIVERS )N PRACTICE THE VAST MAJORITY OF APPLICATION PROGRAMS RELY ON ONLY THE BASIC CORE SET OF /$"# FUNCTIONALITY AND DONT BOTHER WITH MORE ADVANCED FEATURES OR PROFILES
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/NE OF THE AREAS WHERE /$"# OFFERS CAPABILITY BEYOND THE 31,#,) STANDARD IS THE RETRIEVAL OF INFORMATION ABOUT THE STRUCTURE OF A DATABASE FROM ITS SYSTEM CATALOG !S A PART OF THE !.3))3/ 31, STANDARD THE #,) ASSUMES THAT THIS INFORMATION ABOUT TABLES COLUMNS PRIVILEGES AND SO FORTH IS AVAILABLE THROUGH THE 31, )NFORMATION 3CHEMA AS DESCRIBED IN #HAPTER /$"# DOESNT ASSUME THE PRESENCE OF AN )NFORMATION 3CHEMA )NSTEAD IT PROVIDES A SET OF SPECIALIZED FUNCTIONS SHOWN IN 4ABLE THAT PROVIDE INFORMATION ABOUT THE STRUCTURE OF A DATA SOURCE "Y CALLING THESE FUNCTIONS AND PROCESSING THEIR RESULTS AN APPLICATION PROGRAM CAN DETERMINE AT RUNTIME INFORMATION ABOUT THE TABLES COLUMNS PRIVILEGES PRIMARY KEYS FOREIGN KEYS AND STORED PROCEDURES THAT FORM THE STRUCTURE OF A DATA SOURCE (OWEVER TO PRESERVE SECURITY THESE FUNCTIONS RETURN INFORMATION ONLY ABOUT OBJECTS TO WHICH THE USER HAS SPECIFIC ACCESS 4HE /$"# CATALOG FUNCTIONS TYPICALLY ARENT NEEDED BY AN APPLICATION PROGRAM THAT IS WRITTEN FOR A SPECIFIC PURPOSE (OWEVER THEY ARE ESSENTIAL FOR A GENERAL PURPOSE PROGRAM SUCH AS A QUERY PROGRAM REPORT GENERATOR OR DATA ANALYSIS TOOL 4HE CATALOG FUNCTIONS CAN BE CALLED ANY TIME AFTER A CONNECTION TO A DATA SOURCE HAS BEEN MADE &OR EXAMPLE A REPORT WRITING PROGRAM MIGHT CALL 31,#ONNECT AND THEN IMMEDIATELY CALL 31,4ABLES TO DETERMINE WHICH TABLES ARE AVAILABLE IN THE TARGET DATA SOURCE 4HE TABLES COULD THEN BE PRESENTED IN A LIST ON THE SCREEN ALLOWING THE USER TO SELECT WHICH TABLE SHOULD BE USED TO GENERATE A REPORT
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DATETIME LITERALS QUOTE CONVENTIONS KEYWORDS AND SO ON 4HE 31,.ATIVE31, CALL ALLOWS THE APPLICATION PROGRAM TO SEE THE EFFECT OF THIS TRANSLATION /$"# ALSO SUPPORTS ESCAPE SEQUENCES THAT ALLOW AN APPLICATION PROGRAM TO MORE EXPLICITLY DIRECT THE TRANSLATION OF 31, FEATURES THAT TEND TO BE LESS CONSISTENT ACROSS 31, DIALECTS SUCH AS OUTER JOINS AND PATTERN MATCHING SEARCH CONDITIONS
!SYNCHRONOUSõ%XECUTION !N /$"# DRIVER MAY SUPPORT ASYNCHRONOUS EXECUTION OF /$"# FUNCTIONS 7HEN AN APPLICATION PROGRAM MAKES AN ASYNCHRONOUS MODE /$"# CALL /$"# INITIATES THE REQUIRED PROCESSING USUALLY STATEMENT PREPARATION OR EXECUTION AND THEN IMMEDIATELY RETURNS CONTROL TO THE APPLICATION PROGRAM 4HE APPLICATION PROGRAM CAN PROCEED WITH OTHER WORK AND LATER RESYNCHRONIZE WITH THE /$"# FUNCTION TO DETERMINE ITS COMPLETION STATUS !SYNCHRONOUS EXECUTION CAN BE REQUESTED ON A PER CONNECTION OR A PER STATEMENT BASIS )N SOME CASES ASYNCHRONOUSLY EXECUTING FUNCTIONS CAN BE TERMINATED WITH A 31,#ANCEL CALL GIVING THE APPLICATION PROGRAM A METHOD FOR ABORTING LONG RUNNING /$"# OPERATIONS
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4YPE DRIVERS ONCE AGAIN PRESENT A DIFFERENT SET OF TRADE OFFS /NE MAJOR ADVANTAGE CLAIMED FOR THE 4YPE ARCHITECTURE IS THAT THE CLIENT SIDE CODE CAN BE WRITTEN IN *AVA USING THE NETWORK INTERFACES PROVIDED BY OTHER *AVA !0)S .OTICE ALSO THAT THE CLIENT SIDE CODE IS $"-3 NEUTRAL IT DOES THE SAME WORK NO MATTER WHAT THE TARGET $"-3 ON THE SERVER 4HIS MEANS THAT THE CLIENT SIDE CODE IS VERY PORTABLE ABLE TO RUN ON ANY SYSTEM THAT SUPPORTS A *AVA 6IRTUAL -ACHINE *6- AND *AVA NETWORK !0)S 4YPE DRIVERS SHARE ONE DISADVANTAGE WITH 4YPE DRIVERS THE USE OF A VENDOR NEUTRAL NETWORK LAYER JUST LIKE THE USE OF A VENDOR NEUTRAL /$"# LAYER MEANS THAT SOME CAPABILITIES OF THE UNDERLYING $"-3 MAY BE INACCESSIBLE THROUGH THE INTERMEDIATE LAYER ! 4YPE ARCHITECTURE ALSO INVOLVES A DOUBLE TRANSLATION OF EACH *$"# REQUEST JUST AS IN 4YPE HOWEVER ONE OF THE TRANSLATIONS TAKES PLACE ON THE SERVER SYSTEM MINIMIZING THE CLIENT SIDE IMPACT ! 4YPE DRIVER IS A .ETWORK 0ROPRIETARY DRIVER 4HE DRIVER TRANSLATES *$"# REQUESTS INTO NETWORK MESSAGES BUT THIS TIME IN A $"-3 PROPRIETARY FORMAT AS SHOWN IN &IGURE 4HE DRIVER IS WRITTEN IN *AVA AND IMPLEMENTS A NETWORK CLIENT FOR THE $"-3 NETWORKING SOFTWARE SUCH AS /RACLES 31, .ET /N THE SERVER THERE IS NO NEED FOR A MIDDLEWARE LAYER SINCE THE $"-3 SERVER ALREADY PROVIDES SUPPORT FOR THE $"-3 VENDORS OWN CLIENTSERVER NETWORKING 1UERY RESULTS FLOW BACK ACROSS THE NETWORK AGAIN IN VENDOR PROPRIETARY FORMAT AND SUPPLIED BACK TO THE REQUESTING PROGRAM
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4YPE DRIVERS PRESERVE ONE OF THE IMPORTANT ADVANTAGES OF 4YPE DRIVERS 4HEY CAN BE IMPLEMENTED IN PURE *AVA SO LIKE 4YPE THEY ARE PORTABLE ACROSS COMPUTER HARDWARE AND OPERATING SYSTEMS (OWEVER UNLIKE 4YPE DRIVERS THEY ARE $"-3 SPECIFIC SO DIFFERENT CLIENT SIDE CODE IS REQUIRED FOR EACH $"-3 BRAND YOU WANT TO ACCESS ! 4YPE ARCHITECTURE INVOLVES LESS OVERHEAD ON THE SERVER SYSTEM AND MAY THEREFORE DELIVER SLIGHTLY BETTER PERFORMANCE )N PRACTICE THE OVERHEAD OF THE NETWORK MESSAGING WILL ALMOST ALWAYS SWAMP THIS ADVANTAGE EXCEPT IN VERY HIGH TRANSACTION RATE APPLICATIONS &IGURE SUMMARIZES THE FOUR *$"# DRIVER TYPES AND SHOWS HOW THEY RELATE TO ONE ANOTHER 4HE TWO COLUMNS DIVIDE THE DRIVER TYPES BASED ON WHETHER THEY USE A VENDOR NEUTRAL INTERMEDIATE LAYER LEFT COLUMN OR TRANSLATE DIRECTLY FROM THE *$"# !0) TO A $"-3 PROPRIETARY INTERFACE 4HE TWO ROWS DIVIDE THE DRIVER TYPES BASED ON WHETHER THE TRANSLATION TO A SPECIFIC $"-3 !0) OCCURS ON THE CLIENT SIDE UPPER ROW OR ON THE SERVER SIDE LOWER ROW !S THE FIGURE SHOWS THESE TWO DECISIONS RESULT IN FOUR ¾ DRIVER TYPES
4HEõ*$"#õ!0) *AVA IS AN OBJECT ORIENTED LANGUAGE SO ITS PROBABLY NO SURPRISE THAT *$"# ORGANIZES ITS !0) FUNCTIONS AROUND A COLLECTION OF DATABASE RELATED OBJECTS AND THE METHODS THAT THEY PROVIDE s $RIVER -ANAGER OBJECT 4HE ENTRY POINT TO *$"# s #ONNECTION OBJECTS 2EPRESENT INDIVIDUAL ACTIVE CONNECTIONS TO TARGET DATABASES s 3TATEMENT OBJECTS 2EPRESENT 31, STATEMENTS TO BE EXECUTED
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4HE CONNECTION OBJECT STRINGS AND VARIABLES #ONNECTION DBCONN THE DATABASE CONNECTION )NT NUM RETURNED OFFICE NUMBER 3TRING CITY RETURNED CITY 3TRING REG RETURNED REGION 3TRING STR 3%,%#4 /&&)#% #)49 2%')/. &2/- /&&)#%3 CODE IN HERE CREATES THE CONNECTION #REATE A STATEMENT OBJECT FOR EXECUTING THE QUERY 3TATEMENT STMT DBCONNCREATE3TATEMENT #ARRY OUT QUERY n METHOD RETURNS A 2ESULT3ET OBJECT 2ESULT3ET ANSWER STMTEXECUTE1UERYSTR ,OOP THROUGH 2ESULT3ET A ROW AT A TIME WHILE ANSWERNEXT [ 2ETRIEVE EACH COLUMN OF DATA NUM ANSWERGET)NT/&&)#% CITY ANSWERGET3TRING#)49 REG ANSWERGET3TRING 0RINT THE ROW OF RESULTS 3YSTEMOUTPRINTLNCITY NUM REG ] %XPLICITLY CLOSE THE CURSOR AND CONNECTION ANSWERCLOSE DBCONNCLOSE
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4HE METHOD RETURNS A #ALLABLE3TATEMENT OBJECT
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2ETRIEVINGõ-ETADATAõWITHõ*$"# 4HE *$"# INTERFACE PROVIDES OBJECTS AND METHODS FOR RETRIEVING METADATA ABOUT DATABASES QUERY RESULTS AND PARAMETERIZED STATEMENTS ! *$"# #ONNECTION OBJECT PROVIDES ACCESS TO METADATA ABOUT THE DATABASE THAT IT REPRESENTS )NVOKING ITS GET-ETA$ATA METHOD RETURNS A $ATABASE-ETA$ATA OBJECT DESCRIBED IN 4ABLE %ACH METHOD LISTED IN THE TABLE RETURNS A RESULT SET CONTAINING INFORMATION ABOUT A TYPE OF DATABASE ENTITY TABLES COLUMNS PRIMARY KEYS AND SO ON 4HE RESULT SET CAN BE PROCESSED USING THE NORMAL *$"# QUERY RESULTS PROCESSING ROUTINES /THER METADATA ACCESS METHODS PROVIDE INFORMATION ABOUT THE DATABASE PRODUCT NAME SUPPORTED ON THIS CONNECTION ITS VERSION NUMBER AND SIMILAR INFORMATION -ETADATA INFORMATION ABOUT QUERY RESULTS CAN ALSO BE VERY USEFUL ! 2ESULT3ET OBJECT PROVIDES A GET-ETA$ATA METHOD THAT CAN BE INVOKED TO OBTAIN A DESCRIPTION OF ITS QUERY RESULTS 4HE METHOD RETURNS A 2ESULT3ET-ETA$ATA OBJECT DESCRIBED IN 4ABLE 4HE METHODS LET YOU DETERMINE HOW MANY COLUMNS ARE IN THE QUERY RESULTS AND THE NAME AND DATA TYPE OF EACH COLUMN IDENTIFIED BY THEIR ORDINAL POSITION WITHIN THE QUERY RESULTS
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&INALLY METADATA INFORMATION ABOUT THE PARAMETERS USED IN A PREPARED 31, STATEMENT OR A PREPARED CALL TO A STORED PROCEDURE CAN ALSO BE USEFUL 4HE GET0ARAMETER-ETA$ATA METHOD THAT RETRIEVES THIS INFORMATION IS INHERITED FROM THE #ALLABLE3TATEMENT OBJECT SINCE IT EXTENDS THE 0REPARED3TATEMENT OBJECT 4HE METHOD RETURNS A 0ARAMETER-ETA$ATA OBJECT DESCRIBED IN 4ABLE )NVOKING THE METHODS OF THIS OBJECT PROVIDES INFORMATION ABOUT HOW MANY PARAMETERS ARE USED IN THE STATEMENT THEIR DATA TYPES WHETHER EACH PARAMETER IS AN INPUT OUTPUT OR INPUTOUTPUT PARAMETER AND SIMILAR INFORMATION
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*$"# AND *$"# INTRODUCED SEVERAL CAPABILITIES THAT EXTEND THE BASIC DATABASE ACCESS FUNCTIONALITY OF *$"# *$"# DATA SOURCES FIRST INTRODUCED IN *$"# PROVIDE A HIGHER LEVEL METHOD FOR FINDING AVAILABLE DRIVERS AND DATABASES AND CONNECTING TO THEM 4HEY MASK THE DETAILS OF MAKING A CONNECTION FROM THE *AVA APPLICATION PROGRAMMER "ASICALLY A DATA SOURCE IS IDENTIFIED WITH SOME EXTERNAL DIRECTORY OR CATALOG THAT IS ABLE TO TRANSLATE LOGICAL ENTITY NAMES INTO SPECIFIC DETAILS 5SING A DATA SOURCE THE APPLICATION PROGRAMMER CAN SPECIFY A TARGET DATABASE BY AN ABSTRACT NAME AND HAVE THE DIRECTORY IN CONJUNCTION WITH THE *$"# SOFTWARE HANDLE THE DETAILS OF CONNECTIONS *$"# ROWSETS ARE ANOTHER ADVANCED CONCEPT ENHANCED AND EXTENDED IN THE *$"# REVISIONS ! ROWSET EXTENDS THE CONCEPT OF A *$"# RESULT SET WHICH YOU WILL RECALL REPRESENTS A SET OF QUERY RESULTS "EYOND THE QUERY RESULTS THEMSELVES A ROWSET ENCAPSULATES INFORMATION ABOUT THE UNDERLYING SOURCE DATABASE THE CONNECTION TO THE DATABASE ITS USER NAME AND PASSWORD AND SO ON 4HE ROWSET RETAINS ITS IDENTITY INDEPENDENT OF AN ACTIVE CONNECTION TO THE DATABASE 4HUS A ROWSET MAY EXIST IN A DISCONNECTED STATE AND IT CAN BE USED TO REESTABLISH A CONNECTION TO THE DATABASE 7HEN CONNECTED TO THE DATABASE THE ROWSET CAN CONTAIN QUERY RESULTS LIKE A RESULT SET 2OWSETS HAVE SEVERAL OTHER CHARACTERISTICS AND CAPABILITIES ! ROWSET MEETS THE REQUIREMENT FOR A *AVA"EANS COMPONENT AND WHEN CONNECTED TO A DATABASE PROVIDES A WAY TO MAKE A RESULT SET LOOK LIKE AN %NTERPRISE *AVA "EAN %*" 2OWSETS HOLD TABULAR ROWCOLUMN QUERY RESULTS
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AND THOSE RESULTS CAN BE RETRIEVED NAVIGATED AND EVEN UPDATED WHETHER THE ROWSET IS CURRENTLY CONNECTED TO THE SOURCE DATABASE OR NOT )F DISCONNECTED UPDATES ARE MADE RESYNCHRONIZATION IS IMPLIED WHEN THE ROWSET ONCE AGAIN IS CONNECTED TO THE SOURCE DATABASE &INALLY THE CONCEPT OF A ROWSET IS NOT NECESSARILY TIED TO 31, AND RELATIONAL DATABASES 4HE DATA IN A ROWSET CAN CONCEPTUALLY COME FROM ANY TABULAR DATA SOURCE SUCH AS A PERSONAL COMPUTER SPREADSHEET OR EVEN A TABLE WITHIN A WORD PROCESSING DOCUMENT ! COMPLETE DISCUSSION OF *$"# ROWSETS IS BEYOND THE SCOPE OF THIS BOOK SEE THE *$"# DOCUMENTATION AT HTTPJAVASUNCOMJAVASE TECHNOLOGIESDATABASEINDEXJSP FOR MORE INFORMATION ABOUT THIS AND OTHER *$"# CAPABILITIES #LICK THE *$"# $OCUMENTATION LINK FOR THE VERSION YOU WANT
3UMMARY -ANY 31, BASED $"-3 PRODUCTS PROVIDE A CALLABLE !0) FOR PROGRAMMATIC DATABASE ACCESS s $EPENDING ON THE PARTICULAR $"-3 BRAND AND ITS HISTORY THE CALLABLE !0) MAY BE AN ALTERNATIVE TO AN EMBEDDED 31, APPROACH OR IT MAY BE THE PRIMARY METHOD BY WHICH AN APPLICATION PROGRAM ACCESSES THE DATABASE s ! CALLABLE INTERFACE PUTS QUERY PROCESSING PARAMETER PASSING STATEMENT COMPILATION STATEMENT EXECUTION AND SIMILAR TASKS INTO THE CALL INTERFACE KEEPING THE PROGRAMMATIC 31, LANGUAGE IDENTICAL TO INTERACTIVE 31, 7ITH EMBEDDED 31, THESE TASKS ARE HANDLED BY SPECIAL 31, STATEMENTS /0%. &%4#( #,/3% 02%0!2% %8%#54% AND SO ON THAT ARE UNIQUE TO PROGRAMMATIC 31, s -ICROSOFTS /$"# IS A WIDELY SUPPORTED CALLABLE !0) THAT PROVIDES AN EFFECTIVE WAY FOR AN APPLICATION PROGRAM TO ACHIEVE INDEPENDENCE FROM A PARTICULAR $"-3 (OWEVER DIFFERENCES BETWEEN $"-3 BRANDS ARE REFLECTED IN VARYING SUPPORT FOR /$"# FUNCTIONS AND CAPABILITIES s 4HE 31,#ALL ,EVEL )NTERFACE 31,#,) STANDARD IS BASED ON /$"# AND IS COMPATIBLE WITH IT AT THE CORE LEVEL 31,#,) PROVIDES A CALLABLE !0) TO COMPLEMENT THE EMBEDDED 31, INTERFACE SPECIFIED IN THE 31, STANDARD -ANY $"-3 VENDORS SUPPORT THE 31,#,) BECAUSE OF THEIR HISTORICAL SUPPORT FOR /$"# s &OR *AVA PROGRAMS THE *$"# INTERFACE IS THE DE FACTO INDUSTRY STANDARD CALLABLE !0) SUPPORTED BY ALL OF THE MAJOR $"-3 PRODUCTS AND DEFINED AS THE DATABASE MANAGEMENT !0) WITHIN THE *AVA %NTERPRISE %DITION *%% STANDARD IMPLEMENTED BY ALL OF THE MAJOR APPLICATION SERVER PRODUCTS s 4HE PROPRIETARY CALLABLE !0)S OF THE DIFFERENT $"-3 BRANDS REMAIN IMPORTANT IN THE MARKET ESPECIALLY /RACLES /#) !LL OF THEM OFFER THE SAME BASIC FEATURES BUT THEY VARY DRAMATICALLY IN THE EXTENDED FEATURES THAT THEY OFFER AND IN THE DETAILS OF THE CALLS AND DATA STRUCTURES THAT THEY USE s )N GENERAL $"-3 VENDORS PUT CONSIDERABLE PERFORMANCE TUNING WORK INTO THEIR PROPRIETARY !0)S AND TEND TO OFFER /$"# ANDOR 31,#,) SUPPORT AS A CHECK OFF FEATURE 4HUS APPLICATIONS WITH HIGHER PERFORMANCE REQUIREMENTS TEND TO USE THE PROPRIETARY !0)S AND ARE LOCKED INTO A PARTICULAR $"-3 BRAND WHEN THEY DO
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HE INFLUENCE OF 31, CONTINUES TO EXPAND AS NEW 31, CAPABILITIES AND EXTENSIONS TO 31, ADDRESS NEW TYPES OF DATA MANAGEMENT REQUIREMENTS #HAPTERS THROUGH DESCRIBE SEVERAL OF THESE EXPANDING AREAS #HAPTER DESCRIBES STORED PROCEDURAL 31, WHICH PROVIDES PROCESSING CAPABILITIES WITHIN THE $"-3 ITSELF FOR IMPLEMENTING BUSINESS RULES AND CREATING WELL DEFINED DATABASE INTERACTIONS #HAPTER DESCRIBES 31,S ROLE IN ANALYZING DATA AND THE TREND TO CREATE 31, BASED DATA WAREHOUSES #HAPTER DESCRIBES THE ROLE OF 31, IN CREATING INTERACTIVE WEB SITES AND ESPECIALLY ITS RELATIONSHIP TO APPLICATION SERVER TECHNOLOGY #HAPTER DISCUSSES HOW 31, IS USED TO CREATE DISTRIBUTED DATABASES THAT TAP THE POWER OF COMPUTER NETWORKS #HAPTER DISCUSSES ONE OF THE MOST IMPORTANT AREAS OF 31, EVOLUTIONTHE INTERPLAY BETWEEN 31, AND OBJECT ORIENTED TECHNOLOGIES AND THE NEW GENERATION OF OBJECT RELATIONAL DATABASES #HAPTER FOCUSES ON THE RELATIONSHIP BETWEEN 31, AND ONE OF THE MOST IMPORTANT OF THESE TECHNOLOGIES 8-, ALONG WITH THE EMERGING )NTERNET WEB SERVICES ARCHITECTURE BASED ON 8-, #HAPTER EXPLORES DATABASES INTENDED FOR SPECIAL PURPOSES INCLUDING MOBILE AND EMBEDDED DATABASES &INALLY #HAPTER HIGHLIGHTS THE KEY TRENDS THAT WILL DRIVE THE EVOLUTION OF 31, FOR THE COMING DECADE
#(!04%2ç $ATABASE 0ROCESSING AND 3TORED 0ROCEDURAL 31, #(!04%2ç 31, AND $ATA 7AREHOUSING #(!04%2ç 31, AND !PPLICATION 3ERVERS #(!04%2ç 31, .ETWORKING AND $ISTRIBUTED $ATABASES #(!04%2ç 31, AND /BJECTS #(!04%2ç 31, AND 8-, #(!04%2ç 3PECIALTY $ATABASES
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HE LONG TERM TREND IN THE DATABASE MARKET IS FOR DATABASES TO TAKE ON A PROGRESSIVELY LARGER ROLE IN THE OVERALL DATA PROCESSING ARCHITECTURE 4HE PRE RELATIONAL DATABASE SYSTEMS BASICALLY HANDLED ONLY DATA STORAGE AND RETRIEVAL APPLICATION PROGRAMS WERE RESPONSIBLE FOR NAVIGATING THEIR WAY THROUGH THE DATABASE SORTING AND SELECTING DATA AND HANDLING ALL PROCESSING OF THE DATA 7ITH THE ADVENT OF RELATIONAL DATABASES AND 31, THE $"-3 TOOK ON EXPANDED RESPONSIBILITIES $ATABASE SEARCHING AND SORTING WERE EMBODIED IN 31, LANGUAGE CLAUSES AND PROVIDED BY THE $"-3 ALONG WITH THE CAPABILITY TO SUMMARIZE DATA %XPLICIT NAVIGATION THROUGH THE DATABASE BECAME UNNECESSARY 3UBSEQUENT 31, ENHANCEMENTS SUCH AS PRIMARY KEY FOREIGN KEY REFERENTIAL AND CHECK CONSTRAINTS CONTINUED THE TREND TAKING OVER DATA VALIDATION AND DATA INTEGRITY FUNCTIONS THAT HAD REMAINED THE SOLE RESPONSIBILITY OF APPLICATION PROGRAMS WITH EARLIER 31, IMPLEMENTATIONS !T EACH STEP HAVING THE $"-3 TAKE ON MORE RESPONSIBILITY PROVIDED MORE CENTRALIZED CONTROL AND REDUCED THE POSSIBILITY OF DATA CORRUPTION DUE TO APPLICATION PROGRAMMING ERRORS )N MANY INFORMATION TECHNOLOGY )4 DEPARTMENTS WITHIN LARGE COMPANIES AND ORGANIZATIONS THIS $"-3 TREND PARALLELED AN ORGANIZATIONAL TREND 4HE CORPORATE DATABASE AND THE DATA IT CONTAINS CAME TO BE VIEWED AS A MAJOR CORPORATE ASSET AND IN MANY )4 DEPARTMENTS A DEDICATED DATABASE ADMINISTRATION $"! GROUP EMERGED WITH RESPONSIBILITY FOR MAINTAINING THE DATABASE DEFINING AND IN SOME CASES UPDATING THE DATA IT CONTAINED AND PROVIDING STRUCTURED ACCESS TO IT /THER GROUPS WITHIN THE )4 DEPARTMENT OR ELSEWHERE WITHIN THE COMPANY COULD DEVELOP APPLICATION PROGRAMS REPORTS QUERIES OR OTHER LOGIC THAT ACCESSED THE DATABASE )N MOST ORGANIZATIONS APPLICATION PROGRAMS AND THE BUSINESSPEOPLE USING THEM HAVE HAD PRIMARY RESPONSIBILITY FOR UPDATING THE DATA WITHIN THE DATABASE (OWEVER THE $"! GROUP SOMETIMES HAS HAD RESPONSIBILITY FOR UPDATING REFERENCE LOOKUP TABLE DATA AND FOR ASSISTING WITH SCRIPTS AND UTILITIES TO PERFORM TASKS SUCH AS THE BULK LOADING OF NEWLY ACQUIRED DATA "UT THE SECURITY OF THE DATABASE THE PERMITTED FORMS OF ACCESS AND IN GENERAL EVERYTHING WITHIN THE REALM OF THE DATABASE BECAME THE PROVINCE OF THE $"!
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4HREE IMPORTANT FEATURES OF MODERN ENTERPRISE SCALE RELATIONAL DATABASESSTORED PROCEDURES FUNCTIONS AND TRIGGERSHAVE BEEN A PART OF THIS TREND 3TORED PROCEDURES CAN PERFORM DATABASE RELATED APPLICATION PROCESSING WITHIN THE DATABASE ITSELF &OR EXAMPLE A STORED PROCEDURE MIGHT IMPLEMENT THE APPLICATIONS LOGIC TO ACCEPT A CUSTOMER ORDER OR TO TRANSFER MONEY FROM ONE BANK ACCOUNT TO ANOTHER &UNCTIONS ARE STORED 31, PROGRAMS THAT RETURN ONLY A SINGLE VALUE FOR EACH ROW OF DATA 5NLIKE STORED PROCEDURES FUNCTIONS ARE INVOKED BY REFERENCING THEM IN 31, STATEMENTS IN ALMOST ANY CLAUSE WHERE A COLUMN NAME CAN BE USED 4HIS MAKES THEM IDEAL FOR PERFORMING CALCULATIONS AND DATA TRANSFORMATIONS ON DATA TO BE DISPLAYED IN QUERY RESULTS OR USED IN SEARCH CONDITIONS .EARLY ALL RELATIONAL $"-3 PRODUCTS COME WITH A SET OF VENDOR SUPPLIED FUNCTIONS FOR GENERAL USE AND THEREFORE FUNCTIONS ADDED BY LOCAL DATABASE USERS ARE OFTEN CALLED USER DEFINED FUNCTIONS 4RIGGERS ARE USED TO AUTOMATICALLY INVOKE THE PROCESSING CAPABILITY OF A STORED PROCEDURE BASED ON CONDITIONS THAT ARISE WITHIN THE DATABASE &OR EXAMPLE A TRIGGER MIGHT AUTOMATICALLY TRANSFER FUNDS FROM A SAVINGS ACCOUNT TO A CHECKING ACCOUNT IF THE CHECKING ACCOUNT BECOMES OVERDRAWN 4HIS CHAPTER DESCRIBES THE CORE CONCEPTS BEHIND STORED PROCEDURES FUNCTIONS AND TRIGGERS AND THEIR IMPLEMENTATION IN SEVERAL POPULAR $"-3 BRANDS 4HE STORED PROCEDURAL 31, CAPABILITIES OF THE POPULAR $"-3 PRODUCTS HAVE BEEN SIGNIFICANTLY EXPANDED IN THEIR MAJOR REVISIONS DURING THE LATE S AND S ! COMPLETE TREATMENT OF STORED PROCEDURE FUNCTION AND TRIGGER PROGRAMMING IS WELL BEYOND THE SCOPE OF THIS BOOK BUT THE CONCEPTS AND COMPARISONS HERE WILL GIVE YOU AN UNDERSTANDING OF THE CORE CAPABILITIES AND A FOUNDATION FOR BEGINNING TO USE THE SPECIFIC CAPABILITIES OF YOUR $"-3 SOFTWARE 3TORED PROCEDURES FUNCTIONS AND TRIGGERS BASICALLY EXTEND 31, INTO A MORE COMPLETE PROGRAMMING LANGUAGE AND THIS CHAPTER ASSUMES THAT YOU ARE FAMILIAR WITH BASIC PROGRAMMING CONCEPTS
0ROCEDURALõ31,õ#ONCEPTS )N ITS ORIGINAL FORM 31, WAS NOT ENVISIONED AS A COMPLETE PROGRAMMING LANGUAGE )T WAS DESIGNED AND IMPLEMENTED AS A LANGUAGE FOR EXPRESSING DATABASE OPERATIONSCREATING DATABASE STRUCTURES ENTERING DATA INTO THE DATABASE UPDATING DATABASE DATAAND ESPECIALLY FOR EXPRESSING DATABASE QUERIES AND RETRIEVING THE ANSWERS 31, COULD BE USED INTERACTIVELY BY TYPING 31, STATEMENTS AT A KEYBOARD ONE BY ONE )N THIS CASE THE SEQUENCE OF DATABASE OPERATIONS WAS DETERMINED BY THE HUMAN USER 31, COULD ALSO BE EMBEDDED WITHIN ANOTHER PROGRAMMING LANGUAGE SUCH AS #/"/, OR # )N THIS CASE THE SEQUENCE OF DATABASE OPERATIONS WAS DETERMINED BY THE FLOW OF CONTROL WITHIN THE #/"/, OR # PROGRAM 7ITH STORED PROCEDURAL 31, THE 31, LANGUAGE IS EXTENDED WITH SEVERAL CAPABILITIES NORMALLY ASSOCIATED WITH PROGRAMMING LANGUAGES 3EQUENCES OF EXTENDED 31, STATEMENTS ARE GROUPED TOGETHER TO FORM 31, PROGRAMS OR PROCEDURES &OR SIMPLICITY WE REFER TO STORED PROCEDURES FUNCTIONS AND TRIGGERS COLLECTIVELY AS 31, PROCEDURES 4HE SPECIFICS VARY FROM ONE IMPLEMENTATION TO ANOTHER BUT GENERALLY THESE CAPABILITIES ARE PROVIDED s #ONDITIONAL EXECUTION !N )&x4(%.x%,3% STRUCTURE ALLOWS A 31, PROCEDURE TO TEST A CONDITION AND TO CARRY OUT DIFFERENT OPERATIONS DEPENDING ON THE RESULT s ,OOPING ! 7(),% OR &/2 LOOP OR SIMILAR STRUCTURE ALLOWS A SEQUENCE OF 31, OPERATIONS TO BE PERFORMED REPEATEDLY UNTIL SOME TERMINATING CONDITION IS MET 3OME IMPLEMENTATIONS PROVIDE A SPECIAL CURSOR BASED LOOPING STRUCTURE TO PROCESS EACH ROW OF QUERY RESULTS
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s "LOCK STRUCTURE ! SEQUENCE OF 31, STATEMENTS CAN BE GROUPED INTO A SINGLE BLOCK AND USED IN OTHER FLOW OF CONTROL CONSTRUCTS AS IF THE STATEMENT BLOCK WERE A SINGLE STATEMENT s .AMED VARIABLES ! 31, PROCEDURE MAY STORE A VALUE THAT IT HAS CALCULATED RETRIEVED FROM THE DATABASE OR DERIVED IN SOME OTHER WAY INTO A PROGRAM VARIABLE AND LATER RETRIEVE THE STORED VALUE FOR USE IN SUBSEQUENT CALCULATIONS s .AMED PROCEDURES ! SEQUENCE OF 31, STATEMENTS MAY BE GROUPED TOGETHER GIVEN A NAME AND ASSIGNED FORMAL INPUT AND OUTPUT PARAMETERS LIKE A SUBROUTINE OR FUNCTION IN A CONVENTIONAL PROGRAMMING LANGUAGE /NCE DEFINED IN THIS WAY THE PROCEDURE MAY BE CALLED BY NAME PASSING IT APPROPRIATE VALUES FOR ITS INPUT PARAMETERS )F THE PROCEDURE IS A FUNCTION RETURNING A VALUE IT MAY BE USED IN 31, VALUE EXPRESSIONS #OLLECTIVELY THE STRUCTURES THAT IMPLEMENT THESE CAPABILITIES FORM A STORED PROCEDURAL LANGUAGE 30, 3TORED PROCEDURES WERE FIRST INTRODUCED BY 3YBASE IN THE ORIGINAL 3YBASE 31, 3ERVER PRODUCT &UNCTIONS AND TRIGGERS EVOLVED A BIT LATER AND THUS ARE DISCUSSED LATER IN THIS CHAPTER -UCH OF THE ORIGINAL ENTHUSIASM FOR STORED PROCEDURES WAS BECAUSE OF THEIR PERFORMANCE ADVANTAGES IN A CLIENTSERVER DATABASE ARCHITECTURE 7ITHOUT STORED PROCEDURES EVERY 31, OPERATION REQUESTED BY AN APPLICATION PROGRAM RUNNING ON THE CLIENT COMPUTER SYSTEM WOULD BE SENT ACROSS THE NETWORK TO THE DATABASE SERVER AND WOULD WAIT FOR A REPLY MESSAGE TO BE RETURNED ACROSS THE NETWORK )F A LOGICAL TRANSACTION REQUIRED SIX 31, OPERATIONS SIX NETWORK ROUND TRIPS WERE REQUIRED 7ITH STORED PROCEDURES THE SEQUENCE OF SIX 31, OPERATIONS COULD BE PROGRAMMED INTO A PROCEDURE AND STORED IN THE DATABASE 4HE APPLICATION PROGRAM WOULD SIMPLY REQUEST THE EXECUTION OF THE STORED PROCEDURE AND AWAIT THE RESULTS )N THIS WAY SIX NETWORK ROUND TRIPS COULD BE CUT TO ONE ROUND TRIPTHE REQUEST AND REPLY FOR EXECUTING THE STORED PROCEDURE 3TORED PROCEDURES PROVED TO BE A NATURAL FIT FOR THE CLIENTSERVER MODEL AND 3YBASE USED THEM TO ESTABLISH AN EARLY LEAD WITH THIS ARCHITECTURE ! COMPETITIVE RESPONSE QUICKLY FOLLOWED FROM MANY OF THE OTHER $"-3 VENDORS 4ODAY MOST ENTERPRISE $"-3 PRODUCTS PROVIDE A STORED PROCEDURE CAPABILITY AND THE BENEFITS OF STORED PROCEDURES IN CORPORATE DATABASES HAS EXPANDED CONSIDERABLY BEYOND THE EARLY FOCUS ON NETWORK PERFORMANCE 3TORED PROCEDURES ARE LESS RELEVANT FOR OTHER TYPES OF SPECIALIZED $"-3 SYSTEMS SUCH AS DATA WAREHOUSING SYSTEMS OR IN MEMORY DATABASES 3OME $"-3 PRODUCTS HAVE MODELED THEIR 30, STRUCTURES ON # OR 0ASCAL LANGUAGE CONSTRUCTS /THERS HAVE TRIED TO MATCH THE STYLE OF THE 31, $ATA -ANIPULATION ,ANGUAGE $-, AND $ATA $EFINITION ,ANGUAGE $$, STATEMENTS /RACLE ON THE OTHER HAND BASED ITS 30, 0,31, ON THE !DA PROGRAMMING LANGUAGE BECAUSE IT WAS THE STANDARD LANGUAGE OF ITS LARGE 53 GOVERNMENT CUSTOMERS 7HILE STORED PROCEDURE CONCEPTS ARE VERY SIMILAR FROM ONE 31, DIALECT TO ANOTHER THE SPECIFIC SYNTAX VARIES CONSIDERABLY
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/BTAIN THE CUSTOMER NUMBER NAME CREDIT LIMIT AND TARGET SALES AMOUNT FOR THE CUSTOMER AS WELL AS THE ASSIGNED SALESPERSON AND OFFICE
!DD A ROW TO THE CUSTOMER TABLE CONTAINING THE CUSTOMERS DATA
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#OMMIT THE CHANGES TO THE DATABASE IF ALL PREVIOUS STATEMENTS WERE SUCCESSFUL
7ITHOUT A STORED PROCEDURE CAPABILITY HERE IS A 31, STATEMENT SEQUENCE THAT DOES THIS WORK FOR 89: #ORPORATION NEW CUSTOMER NUMBER WITH A CREDIT LIMIT OF AND FIRST YEAR TARGET SALES OF TO BE ASSIGNED TO 0AUL #RUZ EMPLOYEE OF THE #HICAGO OFFICE ).3%24 ).4/ #534/-%23 #534?.5- #/-0!.9 #534?2%0 #2%$)4?,)-)4 6!,5%3 g89: #ORPORATIONg 50$!4% 3!,%32%03 3%4 15/4! 15/4! 7(%2% %-0,?.5- 50$!4% /&&)#%3 3%4 4!2'%4 4!2'%4 7(%2% #)49 g#HICAGOg #/--)4
7ITH A STORED PROCEDURE ALL OF THIS WORK CAN BE EMBEDDED INTO A SINGLE DEFINED 31, ROUTINE &IGURE SHOWS A STORED PROCEDURE FOR THIS TASK EXPRESSED IN /RACLES 0,31, STORED PROCEDURE DIALECT 4HE PROCEDURE IS NAMED !$$?#534 AND IT ACCEPTS SIX PARAMETERSTHE CUSTOMER NAME NUMBER CREDIT LIMIT AND TARGET SALES THE EMPLOYEE NUMBER OF THE ASSIGNED SALESPERSON AND THE CITY WHERE THE ASSIGNED SALES OFFICE IS LOCATED /NCE THIS PROCEDURE HAS BEEN CREATED IN THE DATABASE A STATEMENT LIKE THIS ONE !$$?#534g89: #ORPORATIONg g#HICAGOg
CALLS THE STORED PROCEDURE AND PASSES IT THE SIX SPECIFIED VALUES AS ITS PARAMETERS 4HE $"-3 EXECUTES THE STORED PROCEDURE CARRYING OUT EACH 31, STATEMENT IN THE PROCEDURE DEFINITION ONE BY ONE )F THE !$$?#534 PROCEDURE COMPLETES ITS EXECUTION SUCCESSFULLY A COMMITTED TRANSACTION HAS BEEN CARRIED OUT WITHIN THE $"-3 )F NOT THE RETURNED ERROR CODE AND MESSAGE INDICATES WHAT WENT WRONG
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4HE FOLLOWING SECTIONS DESCRIBE THESE ELEMENTS AND THE SPECIAL 31, STATEMENTS THAT ARE USED TO CONTROL THE FLOW OF EXECUTION WITHIN THE BODY OF A STORED PROCEDURE
#REATINGõAõ3TOREDõ0ROCEDURE )N MANY COMMON 30, DIALECTS THE #2%!4% 02/#%$52% STATEMENT IS USED TO CREATE A STORED PROCEDURE AND TO SPECIFY HOW IT OPERATES 4HE #2%!4% 02/#%$52% STATEMENT ASSIGNS THE NEWLY DEFINED PROCEDURE A NAME WHICH IS USED TO CALL IT 4HE NAME MUST TYPICALLY FOLLOW THE RULES FOR 31, IDENTIFIERS 4HE PROCEDURE IN &IGURE IS NAMED !$$?#534 ! STORED PROCEDURE ACCEPTS ZERO OR MORE PARAMETERS AS ITS ARGUMENTS 4HIS ONE HAS SIX PARAMETERS #?.!-% #?.5- #2%$?,)- 4'4?3,3 #?2%0 AND #?/&&# )N ALL OF THE COMMON 30, DIALECTS THE VALUES FOR THE PARAMETERS APPEAR IN A COMMA SEPARATED LIST ENCLOSED IN PARENTHESES FOLLOWING THE PROCEDURE NAME WHEN THE PROCEDURE IS CALLED 4HE HEADER OF THE STORED PROCEDURE DEFINITION SPECIFIES THE NAMES OF THE PARAMETERS AND THEIR DATA TYPES 4HE SAME 31, DATA TYPES SUPPORTED BY THE $"-3 FOR COLUMNS WITHIN THE DATABASE CAN BE USED AS PARAMETER DATA TYPES )N &IGURE ALL OF THE PARAMETERS ARE INPUT PARAMETERS SIGNIFIED BY THE ). KEYWORD IN THE PROCEDURE HEADER IN THE /RACLE 0,31, DIALECT 7HEN THE PROCEDURE IS CALLED THE PARAMETERS ARE ASSIGNED THE VALUES SPECIFIED IN THE PROCEDURE CALL AND THE STATEMENTS IN THE PROCEDURE BODY BEGIN TO EXECUTE 4HE PARAMETER NAMES MAY APPEAR WITHIN THE PROCEDURE BODY AND PARTICULARLY WITHIN STANDARD 31, STATEMENTS IN THE PROCEDURE BODY ANYWHERE THAT A CONSTANT MAY APPEAR 7HEN A PARAMETER NAME APPEARS THE $"-3 USES ITS CURRENT VALUE )N &IGURE THE PARAMETERS ARE USED IN THE ).3%24 STATEMENT AND THE 50$!4% STATEMENT BOTH AS DATA VALUES TO BE USED IN COLUMN CALCULATIONS AND AS SEARCH CONDITIONS )N ADDITION TO INPUT PARAMETERS SOME 30, DIALECTS ALSO SUPPORT OUTPUT PARAMETERS 4HESE ALLOW A STORED PROCEDURE TO PASS BACK VALUES THAT IT CALCULATES DURING ITS EXECUTION /UTPUT PARAMETERS PROVIDE AN IMPORTANT CAPABILITY FOR PASSING BACK INFORMATION FROM ONE STORED PROCEDURE TO ANOTHER STORED PROCEDURE THAT CALLS IT AND CAN ALSO BE USEFUL FOR DEBUGGING STORED PROCEDURES USING INTERACTIVE 31, 3OME 30, DIALECTS SUPPORT PARAMETERS THAT OPERATE AS BOTH INPUT AND OUTPUT PARAMETERS )N THIS CASE THE PARAMETER PASSES A VALUE TO THE STORED PROCEDURE AND ANY CHANGES TO THE VALUE DURING THE PROCEDURE EXECUTION ARE REFLECTED IN THE CALLING PROCEDURE &IGURE SHOWS THE SAME !$$?#534 PROCEDURE DEFINITION EXPRESSED IN THE 3YBASE 4RANSACT 31, DIALECT 4HE 4RANSACT 31, DIALECT IS ALSO USED BY -ICROSOFT 31, 3ERVER ITS BASICS ARE LARGELY UNCHANGED SINCE THE ORIGINAL 3YBASE 31, 3ERVER VERSION WHICH WAS THE FOUNDATION FOR BOTH THE -ICROSOFT AND 3YBASE PRODUCT LINES .OTE THE DIFFERENCES FROM THE /RACLE DIALECT s 4HE KEYWORD 02/#%$52% CAN BE ABBREVIATED TO 02/# s .O PARENTHESIZED LIST OF PARAMETERS FOLLOWS THE PROCEDURE NAME )NSTEAD THE PARAMETER DECLARATIONS IMMEDIATELY FOLLOW THE NAME OF THE STORED PROCEDURE s 4HE PARAMETER NAMES ALL BEGIN WITH AN hATv SIGN BOTH WHEN THEY ARE DECLARED AT THE BEGINNING OF THE PROCEDURE AND WHEN THEY APPEAR WITHIN 31, STATEMENTS IN THE PROCEDURE BODY s 4HERE IS NO FORMAL END OF PROCEDURE BODY MARKER )NSTEAD THE PROCEDURE BODY IS A SINGLE 4RANSACT 31, STATEMENT )F MORE THAN ONE STATEMENT IS NEEDED THE 4RANSACT 31, BLOCK STRUCTURE IS USED TO GROUP THE STATEMENTS
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4HE VALUES TO BE USED FOR THE PROCEDURES PARAMETERS ARE SPECIFIED IN ORDER IN A LIST THAT IS ENCLOSED BY PARENTHESES 7HEN CALLED FROM WITHIN ANOTHER PROCEDURE OR A TRIGGER THE %8%#54% STATEMENT MAY BE OMITTED AND THE CALL BECOMES SIMPLY !$$?#534g89: #ORPORATIONg g#HICAGOg
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4HE PROCEDURE MAY ALSO BE CALLED USING NAMED PARAMETERS IN WHICH CASE THE PARAMETER VALUES CAN BE SPECIFIED IN ANY SEQUENCE (ERE IS AN EXAMPLE %8%#54% !$$?#534 C?NAME g89: #ORPORATIONg C?NUM CRED?LIM C?OFFC g#HICAGOg C?REP TGT?SALES
)N THE 4RANSACT 31, DIALECT THE CALL TO THE STORED PROCEDURE BECOMES %8%#54% !$$?#534 g89: #ORPORATIONg g#HICAGOg
4HE PARENTHESES ARENT REQUIRED AND THE VALUES TO BE USED FOR PARAMETERS AGAIN FORM A COMMA SEPARATED LIST 4HE KEYWORD %8%#54% CAN BE ABBREVIATED TO %8%# AND THE PARAMETER NAMES CAN BE EXPLICITLY SPECIFIED IN THE CALL ALLOWING YOU TO SPECIFY THE PARAMETER VALUES IN ANY ORDER YOU WISH (ERE IS AN ALTERNATIVE EQUIVALENT 4RANSACT 31, CALL TO THE !$$?#534 STORED PROCEDURE %8%# !$$?#534 #?.!-% g89: #ORPORATIONg #?.5- #2%$?,)- #?/&&# g#HICAGOg #?2%0 4'4?3,3
4HE )NFORMIX 30, FORM OF THE SAME %8%#54% COMMAND IS %8%#54% 02/#%$52% !$$?#534g89: #ORPORATIONg g#HICAGOg
!GAIN THE PARAMETERS ARE ENCLOSED IN A COMMA SEPARATED PARENTHESIZED LIST 4HIS FORM OF THE %8%#54% STATEMENT MAY BE USED IN ANY CONTEXT &OR EXAMPLE IT MAY BE USED BY AN EMBEDDED 31, APPLICATION PROGRAM TO INVOKE A STORED PROCEDURE 7ITHIN A STORED PROCEDURE ITSELF ANOTHER STORED PROCEDURE CAN BE CALLED USING THIS EQUIVALENT STATEMENT #!,, !$$?#534g89: #ORPORATIONg g#HICAGOg
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)N ADDITION TO THE PARAMETERS PASSED INTO A STORED PROCEDURE ITS OFTEN CONVENIENT OR NECESSARY TO DEFINE OTHER VARIABLES TO HOLD INTERMEDIATE VALUES DURING THE PROCEDURES EXECUTION !LL STORED PROCEDURE DIALECTS PROVIDE THIS CAPABILITY 5SUALLY THE VARIABLES ARE DECLARED AT THE BEGINNING OF THE PROCEDURE BODY JUST AFTER THE PROCEDURE HEADER AND BEFORE THE LIST OF 31, STATEMENTS 4HE DATA TYPES OF THE VARIABLES CAN BE ANY OF THE 31, DATA TYPES SUPPORTED AS COLUMN DATA TYPES BY THE $"-3 &IGURE SHOWS A SIMPLE 4RANSACT 31, STORED PROCEDURE FRAGMENT THAT COMPUTES THE TOTAL OUTSTANDING ORDER AMOUNT FOR A SPECIFIC CUSTOMER NUMBER AND SETS UP ONE OF TWO MESSAGES DEPENDING ON WHETHER THE TOTAL ORDER AMOUNT IS UNDER .OTE THAT 4RANSACT 31, LOCAL VARIABLE NAMES LIKE PARAMETER NAMES BEGIN WITH AN h v SIGN
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4HE $%#,!2% STATEMENT DECLARES THE LOCAL VARIABLES FOR THIS PROCEDURE )N THIS CASE THERE ARE TWO VARIABLES ONE WITH THE -/.%9 DATA TYPE AND ONE 6!2#(!2 )N 4RANSACT 31, THE 3%,%#4 STATEMENT ASSUMES THE ADDITIONAL FUNCTION OF ASSIGNING VALUES TO VARIABLES ! SIMPLE FORM OF THIS USE OF 3%,%#4 IS THE ASSIGNMENT OF THE MESSAGE TEXT 3%,%#4 -3'?4%84 HIGH ORDER TOTAL
4HE ASSIGNMENT OF THE TOTAL ORDER AMOUNT AT THE BEGINNING OF THE PROCEDURE BODY IS A MORE COMPLEX EXAMPLE WHERE THE 3%,%#4 IS USED BOTH TO ASSIGN A VALUE AND AS THE INTRODUCER OF THE QUERY THAT GENERATES THE VALUE TO BE ASSIGNED &IGURE SHOWS THE )NFORMIX 30, VERSION OF THE SAME STORED PROCEDURE 4HERE ARE SEVERAL DIFFERENCES FROM THE 4RANSACT 31, VERSION s ,OCAL VARIABLES ARE DECLARED USING THE $%&).% STATEMENT 4HIS EXAMPLE SHOWS ONLY A VERY LIMITED SUBSET OF THE OPTIONS THAT ARE AVAILABLE s 6ARIABLE NAMES ARE ORDINARY 31, IDENTIFIERS THERE IS NO SPECIAL FIRST CHARACTER s ! SPECIALIZED 3%,%#4x).4/ STATEMENT IS USED WITHIN 30, TO ASSIGN THE RESULTS OF A SINGLETON 3%,%#4 STATEMENT INTO A LOCAL VARIABLE s 4HE ,%4 STATEMENT PROVIDES SIMPLE ASSIGNMENT OF VARIABLE VALUES
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&IGURE SHOWS THE /RACLE 0,31, VERSION OF THE SAME STORED PROCEDURE !GAIN THERE ARE SEVERAL DIFFERENCES TO NOTE FROM THE 4RANSACT 31, AND )NFORMIX 30, EXAMPLES s 4HE 3%,%#4).4/ STATEMENT HAS THE SAME FORM AS THE )NFORMIX PROCEDURE IT IS USED TO SELECT VALUES FROM A SINGLE ROW QUERY DIRECTLY INTO LOCAL VARIABLES s 4HE ASSIGNMENT STATEMENTS USE 0ASCAL STYLE NOTATION INSTEAD OF A SEPARATE ,%4 STATEMENT ,OCAL VARIABLES WITHIN A STORED PROCEDURE CAN BE USED AS A SOURCE OF DATA WITHIN 31, EXPRESSIONS ANYWHERE THAT A CONSTANT MAY APPEAR 4HE CURRENT VALUE OF THE VARIABLE IS USED IN THE EXECUTION OF THE STATEMENT )N ADDITION LOCAL VARIABLES MAY BE DESTINATIONS FOR DATA DERIVED FROM 31, EXPRESSIONS OR QUERIES AS SHOWN IN THE PRECEDING EXAMPLES
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)N ALL BUT THE VERY SIMPLEST STORED PROCEDURES IT IS OFTEN NECESSARY TO GROUP A SEQUENCE OF 31, STATEMENTS TOGETHER SO THAT THEY WILL BE TREATED AS IF THEY WERE A SINGLE STATEMENT &OR EXAMPLE IN THE )&x4(%.x%,3% STRUCTURE TYPICALLY USED TO CONTROL THE FLOW OF EXECUTION WITHIN A STORED PROCEDURE MOST STORED PROCEDURE DIALECTS EXPECT A SINGLE STATEMENT FOLLOWING THE 4(%. KEYWORD )F A PROCEDURE NEEDS TO PERFORM A SEQUENCE OF SEVERAL 31, STATEMENTS WHEN THE TESTED CONDITION IS TRUE IT MUST GROUP THE STATEMENTS TOGETHER AS A STATEMENT BLOCK AND THIS BLOCK WILL APPEAR AFTER 4(%.
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)N 4RANSACT 31, A STATEMENT BLOCK HAS THIS SIMPLE STRUCTURE 4RANSACT 31, BLOCK OF STATEMENTS BEGIN 3EQUENCE OF 31, STATEMENTS APPEARS HERE END
4HE SOLE FUNCTION OF THE "%').x%.$ PAIR IS TO CREATE A STATEMENT BLOCK THEY DO NOT IMPACT THE SCOPE OF LOCAL VARIABLES OR OTHER DATABASE OBJECTS 4HE 4RANSACT 31, PROCEDURE DEFINITION CONDITIONAL EXECUTION AND LOOPING CONSTRUCTS AND OTHERS ARE ALL DESIGNED TO OPERATE WITH SINGLE 31, STATEMENTS SO STATEMENT BLOCKS ARE FREQUENTLY USED IN EACH OF THESE CONTEXTS TO GROUP STATEMENTS TOGETHER AS A SINGLE UNIT
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)N )NFORMIX 30, A STATEMENT BLOCK INCLUDES NOT ONLY A STATEMENT SEQUENCE BUT ALSO MAY OPTIONALLY DECLARE LOCAL VARIABLES FOR USE WITHIN THE BLOCK AND EXCEPTION HANDLERS TO HANDLE ERRORS THAT MAY OCCUR WITHIN THE BLOCK (ERE IS THE STRUCTURE OF AN )NFORMIX 31, STATEMENT BLOCK )NFORMIX 30, BLOCK OF STATEMENTS $ECLARATION OF ANY LOCAL VARIABLES DEFINE $ECLARE HANDLING FOR EXCEPTIONS ON EXCEPTION $EFINE THE SEQUENCE OF 31, STATEMENTS BEGIN END
4HE VARIABLE DECLARATION SECTION IS OPTIONAL WE HAVE ALREADY SEEN AN EXAMPLE OF IT IN THE )NFORMIX STORED PROCEDURE BODY IN &IGURE 4HE EXCEPTION HANDLING SECTION IS ALSO OPTIONAL ITS ROLE IS DESCRIBED LATER IN THE h(ANDLING %RROR #ONDITIONSv SECTION 4HE "%').x %.$ SEQUENCE PERFORMS THE SAME FUNCTION AS IT DOES FOR 4RANSACT 31, )NFORMIX ALSO ALLOWS A SINGLE STATEMENT TO APPEAR IN THIS POSITION IF THE BLOCK CONSISTS OF JUST THE OTHER TWO COMPONENTS AND A SINGLE 31, OR 30, STATEMENT 4HE )NFORMIX 31, STRUCTURES DONT REQUIRE THE USE OF STATEMENT BLOCKS AS OFTEN AS THE 4RANSACT 31, STRUCTURES )N THE )NFORMIX DIALECT THE LOOPING CONDITIONAL EXECUTION STATEMENTS EACH INCLUDE AN EXPLICIT TERMINATION )&x%.$ )& 7(),%x%.$ 7(),% &/2x %.$ &/2 7ITHIN THE STRUCTURE A SINGLE 31, STATEMENT OR A SEQUENCE OF STATEMENTS EACH ENDING WITH A SEMICOLON MAY APPEAR !S A RESULT AN EXPLICIT BLOCK STRUCTURE IS NOT ALWAYS NEEDED SIMPLY TO GROUP TOGETHER A SEQUENCE OF 31, STATEMENTS 4HE /RACLE 0,31, BLOCK STRUCTURE HAS THE SAME CAPABILITIES AS THE )NFORMIX STRUCTURE )T OFFERS THE CAPABILITY TO DECLARE VARIABLES AND EXCEPTION CONDITIONS USING THIS FORMAT /RACLE 0,31, STATEMENT BLOCK $ECLARATION OF ANY LOCAL VARIABLES DECLARE 3PECIFY THE SEQUENCE OF STATEMENTS BEGIN $ECLARE HANDLING FOR EXCEPTIONS EXCEPTION END
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!LL THREE SECTIONS OF THE BLOCK STRUCTURE ARE OPTIONAL )TS COMMON TO SEE THE STRUCTURE USED WITH ONLY THE "%').x%.$ SEQUENCE TO DEFINE A STATEMENT SEQUENCE OR WITH A $%#,!2%x"%').x%.$ SEQUENCE TO DECLARE VARIABLES AND A SEQUENCE OF STATEMENTS !S WITH )NFORMIX THE /RACLE STRUCTURES THAT SPECIFY CONDITIONAL EXECUTION AND LOOPING HAVE A SELF DEFINING END OF STATEMENT MARKER SO SEQUENCES OF STATEMENTS WITHIN THESE STRUCTURES DO NOT NECESSARILY NEED AN EXPLICIT "%').x%.$ STATEMENT BLOCK STRUCTURE
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&UNCTIONS )N ADDITION TO STORED PROCEDURES MOST 30, DIALECTS SUPPORT A STORED FUNCTION CAPABILITY 4HE DISTINCTION IS THAT A FUNCTION RETURNS A SINGLE THING SUCH AS A DATA VALUE AN OBJECT OR AN 8-, DOCUMENT EACH TIME IT IS INVOKED WHILE A STORED PROCEDURE CAN RETURN MANY THINGS OR NOTHING AT ALL 3UPPORT FOR RETURNED VALUES VARIES BY 30, DIALECT &UNCTIONS ARE COMMONLY USED AS COLUMN EXPRESSIONS IN 3%,%#4 STATEMENTS AND THUS ARE INVOKED ONCE PER ROW IN THE RESULT SET ALLOWING THE FUNCTION TO PERFORM CALCULATIONS DATA CONVERSION AND OTHER PROCESSES TO PRODUCE THE RETURNED VALUE FOR THE COLUMN &OLLOWING IS A SIMPLE EXAMPLE OF A STORED FUNCTION !SSUME YOU WANT TO DEFINE A STORED PROCEDURE THAT GIVEN A CUSTOMER NUMBER CALCULATES THE TOTAL CURRENT ORDER AMOUNT FOR THAT CUSTOMER )F YOU DEFINE THE 31, PROCEDURE AS A FUNCTION THE TOTAL AMOUNT CAN BE RETURNED AS ITS VALUE &IGURE SHOWS AN /RACLE FUNCTION THAT CALCULATES THE TOTAL AMOUNT OF CURRENT ORDERS FOR A CUSTOMER GIVEN THE CUSTOMER NUMBER .OTE THE 2%452. CLAUSE IN THE PROCEDURE DEFINITION WHICH TELLS THE $"-3 THE DATA TYPE OF THE VALUE BEING RETURNED )N MOST $"-3 PRODUCTS IF YOU ENTER A FUNCTION CALL VIA THE INTERACTIVE 31, CAPABILITY THE FUNCTION VALUE IS DISPLAYED IN RESPONSE 7ITHIN A STORED PROCEDURE YOU CAN CALL A STORED FUNCTION AND USE ITS RETURN VALUE IN CALCULATIONS OR STORE IT IN A VARIABLE -ANY 30, DIALECTS ALSO ALLOW YOU TO USE A FUNCTION AS A USER DEFINED FUNCTION WITHIN 31, VALUE EXPRESSIONS 4HIS IS TRUE OF THE /RACLE 0,31, DIALECT SO THIS USE OF THE FUNCTION DEFINED IN &IGURE WITHIN A SEARCH CONDITION IS LEGAL 3%,%#4 #/-0!.9 .!-% &2/- #534/-%23 3!,%32%03 7(%2% #534?2%0 %-0,?.5- !.$ '%4?4/4?/2$3#534?.5-
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!S THE $"-3 EVALUATES THE SEARCH CONDITION FOR EACH ROW OF PROSPECTIVE QUERY RESULTS IT USES THE CUSTOMER NUMBER OF THE CURRENT CANDIDATE ROW AS AN ARGUMENT TO THE '%4?4/4? /2$3 FUNCTION AND CHECKS TO SEE IF IT EXCEEDS THE THRESHOLD 4HIS SAME QUERY COULD BE EXPRESSED AS A GROUPED QUERY WITH THE /2$%23 TABLE ALSO INCLUDED IN THE &2/- CLAUSE AND THE RESULTS GROUPED BY CUSTOMER AND SALESPERSON )N MANY IMPLEMENTATIONS THE $"-3 CARRIES OUT THE GROUPED QUERY MORE EFFICIENTLY THAN THE PRECEDING ONE WHICH PROBABLY FORCES THE $"-3 TO PROCESS THE ORDERS TABLE ONCE FOR EACH CUSTOMER &IGURE SHOWS THE )NFORMIX 30, DEFINITION FOR THE SAME STORED FUNCTION SHOWN IN &IGURE %XCEPT FOR STYLISTIC VARIATIONS IT DIFFERS VERY LITTLE FROM THE /RACLE VERSION 4HE 4RANSACT 31, DIALECT USED IN -ICROSOFT 31, 3ERVER AND 3YBASE !DAPTIVE 3ERVER %NTERPRISE !3% HAS A STORED USER DEFINED FUNCTION CAPABILITY SIMILAR TO THE ONE ILLUSTRATED IN &IGURES AND
2ETURNINGõ6ALUESõVIAõ0ARAMETERS &UNCTIONS PROVIDE ONLY THE ABILITY TO RETURN A SINGLE THING FROM A STORED ROUTINE 3EVERAL STORED PROCEDURE DIALECTS PROVIDE A METHOD FOR RETURNING MORE THAN ONE VALUE OR OTHER THING BY PASSING THE VALUES BACK TO THE CALLING ROUTINE THROUGH OUTPUT PARAMETERS 4HE OUTPUT PARAMETERS ARE LISTED IN THE STORED PROCEDURES PARAMETER LIST JUST LIKE THE INPUT PARAMETERS SEEN IN THE PREVIOUS EXAMPLES (OWEVER INSTEAD OF BEING USED TO PASS DATA VALUES INTO THE STORED PROCEDURE WHEN IT IS CALLED THE OUTPUT PARAMETERS ARE USED TO PASS DATA BACK OUT OF THE STORED PROCEDURE TO THE CALLING PROCEDURE &IGURE SHOWS A 0,31, STORED PROCEDURE TO RETRIEVE THE NAME OF A CUSTOMER HIS OR HER SALESPERSON AND THE SALES OFFICE TO WHICH THE CUSTOMER IS ASSIGNED GIVEN A SUPPLIED CUSTOMER NUMBER 4HE PROCEDURE HAS FOUR PARAMETERS 4HE FIRST ONE #.5- IS AN INPUT PARAMETER AND SUPPLIES THE REQUESTED CUSTOMER NUMBER 4HE OTHER THREE PARAMETERS ARE OUTPUT PARAMETERS USED TO PASS THE RETRIEVED DATA VALUES BACK TO THE CALLING PROCEDURE
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)N THIS SIMPLE EXAMPLE THE 3%,%#4).4/ FORM OF THE QUERY PLACES THE RETURNED VARIABLES DIRECTLY INTO THE OUTPUT PARAMETERS )N A MORE COMPLEX STORED PROCEDURE THE RETURNED VALUES MIGHT BE CALCULATED AND PLACED INTO THE OUTPUT PARAMETERS WITH A 0,31, ASSIGNMENT STATEMENT 7HEN A STORED PROCEDURE WITH OUTPUT PARAMETERS IS CALLED THE VALUE PASSED FOR EACH OUTPUT PARAMETER MUST BE AN ACCEPTABLE TARGET THAT CAN RECEIVE THE RETURNED DATA VALUE 4HE TARGET MAY BE A LOCAL VARIABLE FOR EXAMPLE OR A PARAMETER OF A HIGHER LEVEL PROCEDURE THAT IS CALLING A LOWER LEVEL PROCEDURE TO DO SOME WORK FOR IT (ERE IS AN /RACLE 0,31, ANONYMOUS UNNAMED BLOCK THAT MAKES AN APPROPRIATE CALL TO THE '%4?#534?).&/ PROCEDURE IN &IGURE 'ET THE CUSTOMER INFO FOR CUSTOMER DECLARE THE?NAME VARCHAR THE?REP VARCHAR THE?CITY VARCHAR EXECUTE GET?CUST?INFO THE?NAME THE?REP THE?CITY
/F COURSE IT WOULD BE UNUSUAL TO CALL THIS PROCEDURE WITH A LITERAL CUSTOMER NUMBER BUT ITS PERFECTLY LEGAL SINCE THAT IS AN INPUT PARAMETER 4HE REMAINING THREE PARAMETERS HAVE ACCEPTABLE DATA ASSIGNMENT TARGETS IN THIS CASE THEY ARE 0,31, VARIABLES PASSED TO THEM SO THAT THEY CAN RECEIVE THE RETURNED VALUES 4HE FOLLOWING CALL TO THE SAME PROCEDURE IS ILLEGAL BECAUSE THE SECOND PARAMETER IS AN OUTPUT PARAMETER AND THUS CANNOT RECEIVE A LITERAL VALUE 'ET THE CUSTOMER INFO FOR CUSTOMER EXECUTE GET?CUST?INFO g89: #Og THE?REP THE?CITY
)N ADDITION TO INPUT AND OUTPUT PARAMETERS /RACLE ALLOWS YOU TO SPECIFY PROCEDURE PARAMETERS THAT ARE BOTH INPUT AND OUTPUT )./54 PARAMETERS 4HEY MUST OBEY THE SAME PREVIOUSLY CITED RESTRICTIONS FOR OUTPUT PARAMETERS BUT IN ADDITION THEIR VALUES ARE USED AS INPUT BY THE PROCEDURE
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&IGURE SHOWS A VERSION OF THE '%4?#534?).&/ PROCEDURE DEFINED IN THE 4RANSACT 31, DIALECT 4HE WAY IN WHICH THE OUTPUT PARAMETERS ARE IDENTIFIED IN THE PROCEDURE HEADER DIFFERS SLIGHTLY FROM THE /RACLE VERSION VARIABLE NAMES BEGIN WITH THE h v SIGN AND THE SINGLE ROW 3%,%#4 STATEMENT HAS A DIFFERENT FORM /THERWISE THE STRUCTURE OF THE PROCEDURE AND ITS OPERATION ARE IDENTICAL TO THE /RACLE EXAMPLE 7HEN THIS PROCEDURE IS CALLED FROM ANOTHER 4RANSACT 31, PROCEDURE THE FACT THAT THE SECOND THIRD AND FOURTH PARAMETERS ARE OUTPUT PARAMETERS MUST BE INDICATED IN THE CALL TO THE PROCEDURE AS WELL AS IN ITS DEFINITION (ERE IS THE 4RANSACT 31, SYNTAX FOR CALLING THE PROCEDURE IN &IGURE 'ET THE CUSTOMER INFO FOR CUSTOMER DECLARE THE?NAME VARCHAR DECLARE THE?REP VARCHAR DECLARE THE?CITY VARCHAR EXEC GET?CUST?INFO C?NUM C?NAME THE?NAME OUTPUT R?NAME THE?REP OUTPUT C?OFFC THE?CITY OUTPUT
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&IGURE SHOWS THE )NFORMIX 30, VERSION OF THE SAME STORED PROCEDURE EXAMPLE )NFORMIX TAKES A DIFFERENT APPROACH TO HANDLING MULTIPLE RETURN VALUES )NSTEAD OF OUTPUT PARAMETERS )NFORMIX EXTENDS THE DEFINITION OF A STORED FUNCTION TO ALLOW MULTIPLE RETURN VALUES 4HUS THE '%4?#534?).&/ PROCEDURE BECOMES A FUNCTION FOR THE )NFORMIX DIALECT 4HE MULTIPLE RETURN VALUES ARE SPECIFIED IN THE 2%452.).' CLAUSE OF THE PROCEDURE HEADER AND THEY ARE ACTUALLY RETURNED BY THE 2%452. STATEMENT
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4HE )NFORMIX #!,, STATEMENT THAT INVOKES THE STORED FUNCTION USES A SPECIAL 2%452.).' CLAUSE TO RECEIVE THE RETURNED VALUES 'ET THE CUSTOMER INFO FOR CUSTOMER DEFINE THE?NAME VARCHAR DEFINE THE?REP VARCHAR DEFINE THE?CITY VARCHAR CALL GET?CUST?INFO RETURNING THE?NAME THE?REP THE?CITY
!S IN THE 4RANSACT 31, DIALECT )NFORMIX ALSO ALLOWS A VERSION OF THE #!,, STATEMENT THAT PASSES THE PARAMETERS BY NAME CALL GET?CUST?INFO C?NUM RETURNING THE?NAME THE?REP THE?CITY
#ONDITIONALõ%XECUTION /NE OF THE MOST BASIC FEATURES OF STORED PROCEDURES IS AN )&x4(%.x%,3% CONSTRUCT FOR DECISION MAKING WITHIN THE PROCEDURE ,OOK BACK AT THE ORIGINAL !$$?#534 PROCEDURE DEFINED IN &IGURE FOR ADDING A NEW CUSTOMER 3UPPOSE THAT THE RULES FOR ADDING NEW CUSTOMERS ARE MODIFIED SO THAT THERE IS A CAP ON THE AMOUNT BY WHICH A SALESPERSONS QUOTA SHOULD BE INCREASED FOR A NEW CUSTOMER )F THE CUSTOMERS ANTICIPATED FIRST YEAR ORDERS ARE OR LESS THAT AMOUNT SHOULD BE ADDED TO THE QUOTA BUT IF THEY ARE MORE THAN THE QUOTA SHOULD BE INCREASED BY ONLY &IGURE SHOWS A MODIFIED PROCEDURE THAT IMPLEMENTS THIS NEW POLICY 4HE )&x4(%.x%,3% LOGIC OPERATES EXACTLY AS IT DOES IN ANY CONVENTIONAL PROGRAMMING LANGUAGE
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!LL OF THE STORED PROCEDURE DIALECTS ALLOW NESTED )& STATEMENTS FOR MORE COMPLEX DECISION MAKING 3EVERAL PROVIDE EXTENDED CONDITIONAL LOGIC TO STREAMLINE MULTIWAY BRANCHING &OR EXAMPLE SUPPOSE YOU WANTED TO DO THREE DIFFERENT THINGS WITHIN THE !$$? #534 STORED PROCEDURE DEPENDING ON WHETHER THE CUSTOMERS ANTICIPATED FIRST YEAR ORDERS ARE UNDER BETWEEN AND OR OVER )N /RACLES 0,31, YOU COULD EXPRESS THE THREE WAY DECISION THIS WAY 0ROCESS SALES TARGET BY RANGE IF TGT?SLS THEN (ANDLE LOW TARGET CUSTOMERS HERE ELSIF TGT?SLS THEN (ANDLE MID TARGET CUSTOMERS HERE ELSE (ANDLE HIGH TARGET CUSTOMERS HERE END IF
)N THE )NFORMIX DIALECT THE SAME MULTIWAY BRANCH STRUCTURE IS SUPPORTED 4HE KEYWORD %,3)& BECOMES %,)& BUT ALL OTHER ASPECTS REMAIN THE SAME
2EPEATEDõ%XECUTION !NOTHER FEATURE COMMON TO ALMOST ALL STORED PROCEDURE DIALECTS IS A CONSTRUCT FOR REPEATED EXECUTION OF A GROUP OF STATEMENTS LOOPING $EPENDING ON THE DIALECT THERE MAY BE SUPPORT FOR "ASIC STYLE &/2 LOOPS WHERE AN INTEGER LOOP CONTROL VALUE IS COUNTED UP OR COUNTED DOWN OR FOR # STYLE 7(),% LOOPS WITH A TEST CONDITION EXECUTED AT THE BEGINNING OR END OF THE LOOP )N THE SAMPLE DATABASE ITS HARD TO COME UP WITH AN UNCONTRIVED EXAMPLE OF SIMPLE LOOP PROCESSING !SSUME YOU WANT TO PROCESS SOME GROUP OF STATEMENTS REPEATEDLY WHILE THE VALUE OF A LOOP CONTROL VARIABLE NAMED )4%-?.5- RANGES FROM TO (ERE IS AN /RACLE 0,31, LOOP THAT HANDLES THIS SITUATION 0ROCESS EACH OF TEN ITEMS FOR ITEM?NUM IN LOOP 0ROCESS THIS PARTICULAR ITEM 4EST WHETHER TO END THE LOOP EARLY EXIT WHEN ITEM?NUM SPECIAL?ITEM END LOOP
4HE STATEMENTS IN THE BODY OF THE LOOP ARE NORMALLY EXECUTED TEN TIMES EACH TIME WITH A LARGER INTEGER VALUE OF THE )4%-?.5- VARIABLE 4HE %8)4 STATEMENT PROVIDES THE CAPABILITY TO EXIT AN /RACLE 0,31, LOOP EARLY )T CAN BE UNCONDITIONAL OR IT CAN BE USED WITH A BUILT IN TEST CONDITION AS IN THIS EXAMPLE
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(ERE IS THE SAME LOOP STRUCTURE EXPRESSED IN )NFORMIX 30, SHOWING SOME OF ITS ADDITIONAL CAPABILITIES AND THE DIALECTIC DIFFERENCES FROM 0,31, 0ROCESS EACH OF TEN ITEMS FOR ITEM?NUM TO STEP 0ROCESS THIS PARTICULAR ITEM 4EST WHETHER TO END THE LOOP EARLY IF ITEM?NUM SPECIAL?ITEM THEN EXIT FOR END FOR
4HE OTHER COMMON FORM OF LOOPING IS WHEN A SEQUENCE OF STATEMENTS IS EXECUTED REPEATEDLY WHILE A CERTAIN CONDITION EXISTS OR UNTIL A SPECIFIED CONDITION EXISTS (ERE IS AN /RACLE 0,31, LOOP CONSTRUCT THAT REPEATS INDEFINITELY 3UCH A LOOP MUST OF COURSE PROVIDE A TEST WITHIN THE BODY OF THE LOOP THAT DETECTS A LOOP TERMINATING CONDITION IN THIS CASE A MATCH OF TWO VARIABLE VALUES AND THAT EXPLICITLY EXITS THE LOOP 2EPEATEDLY PROCESS SOME DATA LOOP $O SOME KIND OF PROCESSING EACH TIME 4EST WHETHER TO END THE LOOP EARLY EXIT WHEN TEST?VALUE EXIT?VALUE END LOOP
! MORE COMMON LOOPING CONSTRUCT IS ONE THAT BUILDS THE TEST INTO THE LOOP STRUCTURE ITSELF 4HE LOOP IS REPEATEDLY EXECUTED AS LONG AS THE TEST IS TRUE &OR EXAMPLE SUPPOSE YOU WANT TO REDUCE TARGETS FOR THE OFFICES IN THE SAMPLE DATABASE UNTIL THE TOTAL OF THE TARGETS IS LESS THAN MILLION %ACH OFFICES TARGET IS TO BE REDUCED BY THE SAME AMOUNT WHICH SHOULD BE A MULTIPLE OF (ERE IS A NOT VERY EFFICIENT 4RANSACT 31, STORED PROCEDURE LOOP THAT GRADUALLY LOWERS OFFICE TARGETS UNTIL THE TOTAL IS BELOW THE THRESHOLD ,OWER TARGETS UNTIL TOTAL BELOW WHILE SELECT SUMTARGET FROM OFFICES BEGIN UPDATE OFFICES SET TARGET TARGET n END
4HE "%').x%.$ BLOCK IN THIS 7(),% LOOP ISNT STRICTLY NECESSARY BUT MOST 4RANSACT 31, 7(),% LOOPS INCLUDE ONE 4RANSACT 31, REPEATS THE SINGLE 31, STATEMENT FOLLOWING THE TEST CONDITION AS THE BODY OF THE 7(),% LOOP )F THE BODY OF THE LOOP CONSISTS OF MORE THAN ONE STATEMENT YOU MUST USE A "%').x%.$ BLOCK TO GROUP THE STATEMENTS
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(ERE IS THE /RACLE 0,31, VERSION OF THE SAME LOOP ,OWER TARGETS UNTIL TOTAL BELOW SELECT SUMTARGET INTO TOTAL?TGT FROM OFFICES WHILE TOTAL?TGT LOOP UPDATE OFFICES SET TARGET TARGET n SELECT SUMTARGET INTO TOTAL?TGT FROM OFFICES END LOOP
4HE SUBQUERY STYLE VERSION OF THE 3%,%#4 STATEMENT FROM 4RANSACT 31, HAS BEEN REPLACED BY THE 0,31, 3%,%#4).4/ FORM OF THE STATEMENT WITH A LOCAL VARIABLE USED TO HOLD THE TOTAL OF THE OFFICE TARGETS %ACH TIME THE LOOP IS EXECUTED THE /&&)#%3 TABLE IS UPDATED AND THEN THE TOTAL OF THE TARGETS IS RECALCULATED (ERE IS THE SAME LOOP ONCE MORE EXPRESSED USING )NFORMIX 30,S 7(),% STATEMENT ,OWER TARGETS UNTIL TOTAL BELOW SELECT SUMTARGET INTO TOTAL?TGT FROM OFFICES WHILE TOTAL?TGT UPDATE OFFICES SET TARGET TARGET n SELECT SUMTARGET INTO TOTAL?TGT FROM OFFICES END WHILE
/THER VARIANTS OF THESE LOOP PROCESSING CONSTRUCTS ARE PROVIDED BY THE VARIOUS DIALECTS BUT THE CAPABILITIES AND SYNTAX ARE SIMILAR TO THESE EXAMPLES
/THERõ&LOW OF #ONTROLõ#ONSTRUCTS 3OME STORED PROCEDURE DIALECTS PROVIDE STATEMENTS TO CONTROL LOOPING AND ALTER THE FLOW OF CONTROL )N )NFORMIX FOR EXAMPLE THE %8)4 STATEMENT INTERRUPTS THE NORMAL FLOW WITHIN A LOOP AND CAUSES EXECUTION TO RESUME WITH THE NEXT STATEMENT FOLLOWING THE LOOP ITSELF 4HE #/.4).5% STATEMENT INTERRUPTS THE NORMAL FLOW WITHIN THE LOOP BUT CAUSES EXECUTION TO RESUME WITH THE NEXT LOOP ITERATION "OTH OF THESE STATEMENTS HAVE THREE FORMS DEPENDING ON THE TYPE OF LOOP BEING INTERRUPTED EXIT FOR EXIT WHILE EXIT FOREACH CONTINUE FOR CONTINUE WHILE CONTINUE FOREACH
)N 4RANSACT 31, A SINGLE STATEMENT "2%!+ PROVIDES THE EQUIVALENT OF THE )NFORMIX %8)4 STATEMENT VARIANTS AND THERE IS A SINGLE FORM OF THE #/.4).5% STATEMENT AS WELL )N /RACLE THE %8)4 STATEMENT PERFORMS THE SAME FUNCTION AS FOR )NFORMIX AND THERE IS NO #/.4).5% STATEMENT !DDITIONAL CONTROL OVER THE FLOW OF EXECUTION WITHIN A STORED PROCEDURE IS PROVIDED BY STATEMENT LABELS AND THE '/4/ STATEMENT )N MOST DIALECTS THE STATEMENT LABEL IS AN IDENTIFIER FOLLOWED BY A COLON 4HE '/4/ STATEMENT NAMES THE LABEL TO WHICH CONTROL SHOULD BE TRANSFERRED
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4HERE IS TYPICALLY A RESTRICTION THAT YOU CANNOT TRANSFER CONTROL OUT OF A LOOP OR A CONDITIONAL TESTING STATEMENT AND ALWAYS A PROHIBITION AGAINST TRANSFERRING CONTROL INTO THE MIDDLE OF SUCH A STATEMENT !S IN STRUCTURED PROGRAMMING LANGUAGES THE USE OF '/4/ STATEMENTS IS DISCOURAGED BECAUSE IT MAKES STORED PROCEDURE CODE HARDER TO UNDERSTAND AND DEBUG
#URSOR "ASEDõ2EPETITION /NE COMMON NEED FOR REPETITION OF STATEMENTS WITHIN A STORED PROCEDURE IS WHEN THE PROCEDURE EXECUTES A QUERY AND NEEDS TO PROCESS THE QUERY RESULTS ROW BY ROW !LL OF THE MAJOR DIALECTS PROVIDE A STRUCTURE FOR THIS TYPE OF PROCESSING #ONCEPTUALLY THE STRUCTURES PARALLEL THE $%#,!2% #523/2 /0%. #523/2 &%4#( AND #,/3% #523/2 STATEMENTS IN EMBEDDED 31, OR IN THE CORRESPONDING 31, !0) CALLS (OWEVER INSTEAD OF FETCHING THE QUERY RESULTS INTO THE APPLICATION PROGRAM IN THIS CASE THEY ARE BEING FETCHED INTO THE STORED PROCEDURE WHICH IS EXECUTING WITHIN THE $"-3 ITSELF )NSTEAD OF RETRIEVING THE QUERY RESULTS INTO APPLICATION PROGRAM VARIABLES HOST VARIABLES THE STORED PROCEDURE RETRIEVES THEM INTO LOCAL STORED PROCEDURE VARIABLES 4O ILLUSTRATE THIS CAPABILITY ASSUME THAT YOU WANT TO POPULATE TWO TABLES WITH DATA FROM THE /2$%23 TABLE /NE TABLE NAMED ")'/2$%23 SHOULD CONTAIN CUSTOMER NAME AND ORDER SIZE FOR ANY ORDERS OVER 4HE OTHER 3-!,,/2$%23 SHOULD CONTAIN THE SALESPERSONS NAME AND ORDER SIZE FOR ANY ORDERS UNDER 4HE BEST AND MOST EFFICIENT WAY TO DO THIS WOULD BE TO USE TWO SEPARATE 31, ).3%24 STATEMENTS WITH SUBQUERIES BUT FOR PURPOSES OF ILLUSTRATION CONSIDER THIS METHOD INSTEAD
%XECUTE A QUERY TO RETRIEVE THE ORDER AMOUNT CUSTOMER NAME AND SALESPERSON NAME FOR EACH ORDER
&OR EACH ROW OF QUERY RESULTS CHECK THE ORDER AMOUNT TO SEE WHETHER IT FALLS INTO THE PROPER RANGE FOR INCLUDING IN THE ")'/2$%23 OR 3-!,,/2$%23 TABLES
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#OMMIT THE UPDATES TO THE DATABASE
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&IGURE SHOWS AN /RACLE STORED PROCEDURE THAT CARRIES OUT THIS METHOD 4HE CURSOR THAT DEFINES THE QUERY IS DEFINED EARLY IN THE PROCEDURE AND ASSIGNED THE NAME /?#523/2 4HE VARIABLE #523?2/7 IS DEFINED AS AN /RACLE ROW TYPE )T IS A STRUCTURED /RACLE ROW VARIABLE WITH INDIVIDUAL COMPONENTS LIKE A # LANGUAGE STRUCTURE "Y DECLARING IT AS HAVING THE SAME ROW TYPE AS THE CURSOR THE INDIVIDUAL COMPONENTS OF #523?2/7 HAVE THE SAME DATA TYPES AND NAMES AS THE CURSORS QUERY RESULTS COLUMNS 4HE QUERY DESCRIBED BY THE CURSOR IS ACTUALLY CARRIED OUT BY THE CURSOR BASED &/2 LOOP )T BASICALLY TELLS THE $"-3 TO CARRY OUT THE QUERY DESCRIBED BY THE CURSOR EQUIVALENT TO THE /0%. STATEMENT IN EMBEDDED 31, BEFORE STARTING THE LOOP PROCESSING 4HE $"-3 THEN EXECUTES THE &/2 LOOP REPEATEDLY BY FETCHING A ROW OF QUERY RESULTS AT THE TOP OF THE LOOP PLACING THE COLUMN VALUES INTO THE #523?2/7 VARIABLE AND THEN EXECUTING THE STATEMENTS IN THE LOOP BODY 7HEN NO MORE ROWS OF QUERY RESULTS ARE TO BE FETCHED THE CURSOR IS CLOSED AND PROCESSING CONTINUES AFTER THE LOOP
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&IGURE SHOWS AN EQUIVALENT STORED PROCEDURE WITH THE SPECIALIZED &/2 LOOP STRUCTURE OF )NFORMIX 30, )N THIS CASE THE QUERY RESULTS ARE RETRIEVED INTO ORDINARY LOCAL VARIABLES THERE IS NO SPECIAL ROW DATA TYPE USED 4HE &/2%!#( STATEMENT INCORPORATES SEVERAL DIFFERENT FUNCTIONS )T DEFINES THE QUERY TO BE CARRIED OUT THROUGH THE 3%,%#4 EXPRESSION THAT IT CONTAINS )T MARKS THE BEGINNING OF THE LOOP THAT IS TO BE EXECUTED FOR EACH ROW OF QUERY RESULTS 4HE END OF THE LOOP IS MARKED BY THE %.$ &/2%!#( STATEMENT
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4HE 4RANSACT 31, DIALECT DOESNT HAVE A SPECIALIZED &/2 LOOP STRUCTURE FOR CURSOR BASED QUERY RESULTS PROCESSING )NSTEAD THE $%#,!2% #523/2 /0%. &%4#( AND #,/3% STATEMENTS OF EMBEDDED 31, HAVE DIRECT COUNTERPARTS WITHIN THE 4RANSACT 31, LANGUAGE &IGURE SHOWS A 4RANSACT 31, VERSION OF THE SORT?ORDERS PROCEDURE .OTE THE ') %'$ ($')$''( ( $! +' !( )$ $! &*'- '(*!)( !' $'") !' #" !' '#"
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SEPARATE $%#,!2% /0%. &%4#( AND #,/3% STATEMENTS FOR THE CURSOR ,OOP CONTROL IS PROVIDED BY TESTING THE SYSTEM VARIABLE 31,34!453 WHICH IS THE 4RANSACT 31, EQUIVALENT OF THE 31,34!4% CODE )T RECEIVES A VALUE OF ZERO WHEN A FETCH IS SUCCESSFUL AND A NONZERO VALUE WHEN THERE ARE NO MORE ROWS TO FETCH
(ANDLINGõ%RRORõ#ONDITIONS 7HEN AN APPLICATION PROGRAM USES EMBEDDED 31, OR A 31, !0) FOR DATABASE PROCESSING THE APPLICATION PROGRAM IS RESPONSIBLE FOR HANDLING ERRORS THAT ARISE %RROR STATUS CODES ARE RETURNED TO THE APPLICATION PROGRAM AND MORE ERROR INFORMATION IS TYPICALLY AVAILABLE THROUGH ADDITIONAL !0) CALLS OR ACCESS TO AN EXTENDED DIAGNOSTICS AREA 7HEN DATABASE PROCESSING TAKES PLACE WITHIN A STORED PROCEDURE THE PROCEDURE ITSELF MUST HANDLE ERRORS 4RANSACT 31, PROVIDES ERROR HANDLING THROUGH A SET OF GLOBAL SYSTEM VARIABLES 4HE SPECIFIC ERROR HANDLING VARIABLES ARE ONLY A FEW OF WELL OVER SYSTEM VARIABLES THAT PROVIDE INFORMATION ON THE STATE OF THE SERVER TRANSACTION STATE OPEN CONNECTIONS AND OTHER DATABASE CONFIGURATION AND STATUS INFORMATION 4HE TWO MOST USEFUL GLOBAL VARIABLES FOR ERROR HANDLING ARE s
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4HE NORMAL COMPLETION VALUES FOR BOTH VARIABLES ARE ZERO OTHER VALUES INDICATE VARIOUS ERRORS AND WARNINGS 4HE GLOBAL VARIABLES CAN BE USED IN THE SAME WAY AS LOCAL VARIABLES WITHIN A 4RANSACT 31, PROCEDURE 3PECIFICALLY THEIR VALUES CAN BE CHECKED FOR BRANCHING AND LOOP CONTROL /RACLES 0,31, PROVIDES A DIFFERENT STYLE OF ERROR HANDLING 4HE /RACLE $"-3 PROVIDES A SET OF SYSTEM DEFINED EXCEPTIONS WHICH ARE ERRORS OR WARNING CONDITIONS THAT CAN ARISE DURING 31, STATEMENT PROCESSING 7ITHIN AN /RACLE STORED PROCEDURE ACTUALLY ANY /RACLE STATEMENT BLOCK THE %8#%04)/. SECTION TELLS THE $"-3 HOW IT SHOULD HANDLE ANY EXCEPTION CONDITIONS THAT OCCUR DURING THE EXECUTION OF THE PROCEDURE 4HERE ARE OVER A DOZEN DIFFERENT PREDEFINED /RACLE DETECTED EXCEPTION CONDITIONS )N ADDITION YOU CAN DEFINE YOUR OWN EXCEPTION CONDITIONS -OST OF THE PREVIOUS EXAMPLES IN THIS CHAPTER DONT PROVIDE ANY REAL ERROR HANDLING CAPABILITY &IGURE SHOWS A REVISED VERSION OF THE /RACLE STORED FUNCTION IN &IGURE 4HIS IMPROVED VERSION DETECTS THE SPECIFIC SITUATION WHERE THE SUPPLIED CUSTOMER NUMBER DOES NOT HAVE ANY ASSOCIATED ORDERS THAT IS WHERE THE QUERY TO CALCULATE TOTAL ORDERS RETURNS A ./?$!4!?&/5.$ EXCEPTION )T RESPONDS TO THIS SITUATION BY SIGNALING BACK TO THE APPLICATION PROGRAM AN APPLICATION LEVEL ERROR AND ASSOCIATED MESSAGE !NY OTHER EXCEPTION CONDITIONS THAT ARISE ARE CAUGHT BY THE 7(%. /4(%23 EXCEPTION HANDLER 4HE )NFORMIX 30, TAKES A SIMILAR APPROACH TO EXCEPTION HANDLING &IGURE SHOWS THE )NFORMIX VERSION OF THE STORED FUNCTION WITH )NFORMIX STYLE EXCEPTION HANDLING 4HE /. %8#%04)/. STATEMENT IS A DECLARATIVE STATEMENT AND SPECIFIES THE SEQUENCE OF 31, STATEMENTS TO BE EXECUTED WHEN A SPECIFIC EXCEPTION ARISES ! COMMA SEPARATED LIST OF EXCEPTION NUMBERS MAY BE SPECIFIED
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#HAPTERçç
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!DVANTAGESõOFõ3TOREDõ0ROCEDURES 3TORED PROCEDURES OFFER SEVERAL ADVANTAGES BOTH FOR DATABASE USERS AND DATABASE ADMINISTRATORS INCLUDING s 2UNTIME PERFORMANCE -ANY $"-3 BRANDS COMPILE STORED PROCEDURES EITHER AUTOMATICALLY OR AT THE USERS REQUEST INTO AN INTERNAL REPRESENTATION THAT CAN BE EXECUTED VERY EFFICIENTLY BY THE $"-3 AT RUNTIME %XECUTING A PRECOMPILED STORED PROCEDURE CAN BE MUCH FASTER THAN RUNNING THE EQUIVALENT 31, STATEMENTS THROUGH THE 02%0!2%%8%#54% PROCESS s 2EUSABILITY /NCE A STORED PROCEDURE HAS BEEN DEFINED FOR A SPECIFIC FUNCTION THAT PROCEDURE MAY BE CALLED FROM MANY DIFFERENT APPLICATION PROGRAMS THAT NEED TO PERFORM THE FUNCTION PERMITTING VERY EASY REUSE OF APPLICATION LOGIC AND REDUCING THE RISK OF APPLICATION PROGRAMMER ERROR s 2EDUCED NETWORK TRAFFIC )N A CLIENTSERVER CONFIGURATION SENDING A STORED PROCEDURE CALL ACROSS THE NETWORK AND RECEIVING THE RESULTS IN A REPLY MESSAGE GENERATES MUCH LESS NETWORK TRAFFIC THAN USING A NETWORK ROUND TRIP FOR EACH INDIVIDUAL 31, STATEMENT 4HIS CAN IMPROVE OVERALL SYSTEM PERFORMANCE CONSIDERABLY IN A NETWORK WITH HEAVY TRAFFIC OR ONE THAT HAS LOWER SPEED CONNECTIONS s 3ECURITY )N MOST $"-3 BRANDS THE STORED PROCEDURE IS TREATED AS A TRUSTED ENTITY WITHIN THE DATABASE AND EXECUTES WITH ITS OWN PRIVILEGES 4HE USER EXECUTING THE STORED PROCEDURE NEEDS TO HAVE ONLY PERMISSION TO EXECUTE IT NOT PERMISSION ON THE UNDERLYING TABLES THAT THE STORED PROCEDURE MAY ACCESS OR MODIFY 4HUS THE STORED PROCEDURE ALLOWS THE DATABASE ADMINISTRATOR TO MAINTAIN TIGHTER SECURITY ON THE UNDERLYING DATA WHILE STILL GIVING INDIVIDUAL USERS THE SPECIFIC DATA UPDATE OR DATA ACCESS CAPABILITIES THEY REQUIRE s %NCAPSULATION 3TORED PROCEDURES ARE A WAY TO ACHIEVE ONE OF THE CORE OBJECTIVES OF OBJECT ORIENTED PROGRAMMINGTHE ENCAPSULATION OF DATA VALUES STRUCTURES AND ACCESS WITHIN A SET OF VERY LIMITED WELL DEFINED EXTERNAL INTERFACES )N OBJECT TERMINOLOGY STORED PROCEDURES CAN BE THE METHODS THROUGH WHICH THE OBJECTS IN THE UNDERLYING 2$"-3 ARE EXCLUSIVELY MANIPULATED 4O FULLY ATTAIN THE OBJECT ORIENTED APPROACH ALL DIRECT ACCESS TO THE UNDERLYING DATA VIA 31, MUST BE DISALLOWED THROUGH THE 2$"-3 SECURITY SYSTEM LEAVING ONLY THE STORED PROCEDURES FOR DATABASE ACCESS )N PRACTICE FEW IF ANY PRODUCTION RELATIONAL DATABASES OPERATE IN THIS RESTRICTED MANNER
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s 3IMPLICITY OF ACCESS )N A LARGE ENTERPRISE DATABASE A COLLECTION OF STORED PROCEDURES MAY BE THE MAIN WAY IN WHICH APPLICATION PROGRAMS ACCESS THE DATABASE 4HE STORED PROCEDURES FORM A WELL DEFINED SET OF TRANSACTIONS AND QUERIES THAT APPLICATIONS CAN PERFORM ON THE DATABASE &OR MOST APPLICATION PROGRAMMERS A CALL TO A SIMPLE PREDEFINED FUNCTION THAT CHECKS AN ACCOUNT BALANCE GIVEN A CUSTOMER NUMBER OR ONE THAT ADDS AN ORDER GIVEN A CUSTOMER NUMBER QUANTITY AND PRODUCT ID IS EASIER TO UNDERSTAND THAN THE CORRESPONDING 31, STATEMENTS
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31,ç4ODAYçANDç4OMORROW
s "USINESS RULES ENFORCEMENT 4HE CONDITIONAL PROCESSING CAPABILITIES OF STORED PROCEDURES ARE OFTEN USED TO PLACE BUSINESS RULES INTO THE DATABASE &OR EXAMPLE A STORED PROCEDURE USED TO ADD AN ORDER TO THE DATABASE MIGHT CONTAIN LOGIC TO CHECK THE CREDIT OF THE CUSTOMER PLACING THE ORDER AND CHECK WHETHER THERE IS ENOUGH INVENTORY ON HAND TO FILL THE ORDER AND REJECT THE ORDER IF THESE CONDITIONS CANNOT BE MET ! LARGE COMPANY COULD QUITE EASILY HAVE SEVERAL DIFFERENT WAYS IN WHICH ORDERS ARE TAKEN AND ENTERED INTO THE CORPORATE DATABASEONE PROGRAM FOR USE BY DIRECT SALESPEOPLE ONE FOR PEOPLE IN THE TELESALES DEPARTMENT ANOTHER THAT ACCEPTS ORDERS PLACED VIA THE 7EB AND SO ON %ACH OF THESE WOULD TYPICALLY HAVE ITS OWN ORDER ACCEPTANCE PROGRAM USUALLY WRITTEN BY DIFFERENT PROGRAMMERS AT DIFFERENT TIMES "UT IF ALL OF THE PROGRAMS ARE FORCED TO USE THE SAME STORED PROCEDURE TO ADD AN ORDER THE COMPANY CAN BE ASSURED THAT THE BUSINESS RULES IN THAT PROCEDURE ARE BEING UNIFORMLY ENFORCED NO MATTER WHERE THE ORDER ORIGINATED
3TOREDõ0ROCEDUREõ0ERFORMANCE $IFFERENT $"-3 BRANDS VARY IN THE WAY THEY ACTUALLY IMPLEMENT STORED PROCEDURES )N SEVERAL BRANDS THE STORED PROCEDURE TEXT IS STORED WITHIN THE DATABASE AND IS INTERPRETED WHEN THE PROCEDURE IS EXECUTED 4HIS HAS THE ADVANTAGE OF CREATING A VERY FLEXIBLE STORED PROCEDURE LANGUAGE BUT IT CREATES SIGNIFICANT RUNTIME OVERHEAD FOR COMPLEX STORED PROCEDURES 4HE $"-3 MUST READ THE STATEMENTS THAT MAKE UP THE STORED PROCEDURE AT RUNTIME PARSE AND ANALYZE THEM AND DETERMINE WHAT TO DO ON THE FLY "ECAUSE OF THE OVERHEAD IN THE INTERPRETED APPROACH SOME $"-3 BRANDS COMPILE STORED PROCEDURES INTO AN INTERMEDIATE FORM THAT IS MUCH MORE EFFICIENT TO EXECUTE #OMPILATION MAY BE AUTOMATIC WHEN THE STORED PROCEDURE IS CREATED OR THE $"-3 MAY PROVIDE THE ABILITY FOR THE USER TO REQUEST STORED PROCEDURE COMPILATION 4HE DISADVANTAGE OF COMPILED STORED PROCEDURES IS THAT THE EXACT TECHNIQUE USED TO CARRY OUT THE STORED PROCEDURE IS FIXED WHEN THE PROCEDURE IS COMPILED 3UPPOSE FOR EXAMPLE THAT A STORED PROCEDURE IS CREATED AND COMPILED SOON AFTER A DATABASE IS FIRST CREATED AND LATER SOME USEFUL INDEXES ARE DEFINED ON THE DATA 4HE COMPILED QUERIES IN THE STORED PROCEDURE WONT TAKE ADVANTAGE OF THESE INDEXES AND AS A RESULT THEY MAY RUN MUCH MORE SLOWLY THAN IF THEY WERE RECOMPILED 4O DEAL WITH STALE COMPILED PROCEDURES SOME $"-3 BRANDS AUTOMATICALLY MARK ANY COMPILED PROCEDURES THAT MAY BE AFFECTED BY SUBSEQUENT DATABASE CHANGES AS BEING IN NEED OF RECOMPILATION 4HE NEXT TIME THE PROCEDURE IS CALLED THE $"-3 NOTICES THE MARK AND RECOMPILES THE PROCEDURE BEFORE EXECUTING IT .ORMALLY THIS APPROACH PROVIDES THE BEST OF BOTH WORLDSTHE PERFORMANCE BENEFITS OF PRECOMPILATION WHILE KEEPING THE COMPILED PROCEDURE UP TO DATE )TS DISADVANTAGE IS THAT IT CAN YIELD UNPREDICTABLE STORED PROCEDURE EXECUTION TIMES 7HEN NO RECOMPILE IS NECESSARY THE STORED PROCEDURE MAY EXECUTE QUICKLY WHEN A RECOMPILE IS ACTIVATED IT MAY PRODUCE A SIGNIFICANT DELAY AND IN MOST CASES THE RECOMPILE DELAY IS MUCH LONGER THAN THE DISADVANTAGE OF USING THE OLD COMPILED VERSION 4O DETERMINE THE STORED PROCEDURE COMPILATION CAPABILITIES OF A PARTICULAR $"-3 YOU CAN EXAMINE ITS #2%!4% 02/#%$52% AND %8%#54% 02/#%$52% STATEMENT OPTIONS OR LOOK FOR OTHER PROCEDURE MANAGEMENT STATEMENTS SUCH AS !,4%2 02/#%$52%
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
3YSTEM $EFINEDõ3TOREDõ0ROCEDURES $"-3 BRANDS THAT SUPPORT STORED PROCEDURES SOMETIMES PROVIDE BUILT IN SYSTEM DEFINED STORED PROCEDURES TO AUTOMATE DATABASE PROCESSING OR MANAGEMENT FUNCTIONS 3YBASE 31, 3ERVER PIONEERED THIS USE OF SYSTEM STORED PROCEDURES 4ODAY HUNDREDS OF 4RANSACT 31, SYSTEM STORED PROCEDURES PROVIDE FUNCTIONS SUCH AS MANAGING USERS DATABASE ROLES JOB EXECUTION DISTRIBUTED SERVERS REPLICATION AND OTHERS -OST 4RANSACT 31, SYSTEM PROCEDURES FOLLOW THIS NAMING CONVENTION s SP?ADD?SOMETHING !DDS A NEW OBJECT USER SERVER REPLICA ETC s SP?DROP?SOMETHING $ROPS AN EXISTING OBJECT s SP?HELP?SOMETHING 'ETS INFORMATION ABOUT AN OBJECT OR OBJECTS &OR EXAMPLE THE SP?HELPUSER PROCEDURE RETURNS INFORMATION ABOUT THE VALID USERS OF THE CURRENT DATABASE 9OU WILL NOTICE THAT IN -ICROSOFT 31, 3ERVER THE NAMES OF 4RANSACT 31, SYSTEM STORED PROCEDURES OFTEN HAVE UNDERSCORES BETWEEN WORDS EXCEPT FOR THE ONE INCLUDED IN THE NAME PREFIX SP? !LSO SINCE THE VENDORS USE THE PREFIX SP? TO DISTINGUISH THEIR SUPPLIED SYSTEM STORED PROCEDURES ITS A GOOD IDEA TO AVOID USING THAT PREFIX IN PROCEDURES THAT USERS ADD TO THE DATABASE /RACLE USES THE PREFIX $"-3? FOR PROCEDURES PROVIDED WITH ITS NAMESAKE $"-3 -OST OF THESE PROCEDURES ARE BUNDLED INTO PACKAGES BY FUNCTIONAL CATEGORY &OR EXAMPLE THE PACKAGE $"-3?,/" CONTAINS GENERAL PURPOSE ROUTINES STORED PROCEDURES AND FUNCTIONS FOR OPERATIONS ON LARGE OBJECTS ,/"S
%XTERNALõ3TOREDõ0ROCEDURES
XP?SENDMAIL 2%#)0)%.43 g*OEg g3AMg -%33!'% g#USTOMER TABLE NEARLY FULLg
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!LTHOUGH STORED PROCEDURES WRITTEN IN THE EXTENDED 31, DIALECTS OF THE MAJOR ENTERPRISE $"-3 BRANDS CAN BE QUITE POWERFUL THEY HAVE LIMITATIONS /NE MAJOR LIMITATION IS THAT THEY DO NOT PROVIDE ACCESS TO FEATURES OUTSIDE THE $"-3 SUCH AS THE FEATURES OF THE OPERATING SYSTEM OR OTHER APPLICATIONS RUNNING ON THE SAME COMPUTER SYSTEM 4HE EXTENDED 31, DIALECTS ALSO TEND TO BE FAIRLY HIGH LEVEL LANGUAGES WITH LIMITED CAPABILITY FOR THE LOWER LEVEL PROGRAMMING USUALLY DONE IN # OR # 4O OVERCOME THESE LIMITATIONS SOME $"-3 BRANDS PROVIDE ACCESS TO EXTERNAL STORED PROCEDURES !N EXTERNAL STORED PROCEDURE IS A PROCEDURE WRITTEN IN A CONVENTIONAL PROGRAMMING LANGUAGE SUCH AS # OR 0ASCAL AND COMPILED OUTSIDE THE $"-3 ITSELF 4HE $"-3 IS GIVEN A DEFINITION OF THE PROCEDURES NAME AND ITS PARAMETERS ALONG WITH OTHER ESSENTIAL INFORMATION SUCH AS THE CALLING CONVENTIONS USED BY THE PROGRAMMING LANGUAGE IN WHICH THE STORED PROCEDURE WAS WRITTEN /NCE DEFINED TO THE $"-3 THE EXTERNAL STORED PROCEDURE CAN BE CALLED AS IF IT WERE A 31, STORED PROCEDURE 4HE $"-3 HANDLES THE CALL TURNS OVER CONTROL TO THE EXTERNAL PROCEDURE AND THEN RECEIVES ANY RETURN VALUES AND PARAMETERS -ICROSOFT 31, 3ERVER PROVIDES A SET OF SYSTEM DEFINED EXTERNAL STORED PROCEDURES THAT PROVIDE ACCESS TO SELECTED OPERATING SYSTEM CAPABILITIES 4HE XP?SENDMAIL PROCEDURE CAN BE USED TO SEND ELECTRONIC MAIL TO USERS BASED ON CONDITIONS WITHIN THE $"-3
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0ARTç6)ç
31,ç4ODAYçANDç4OMORROW
3IMILARLY THE XP?CMDSHELL EXTERNAL PROCEDURE CAN BE CALLED TO PASS COMMANDS TO THE UNDERLYING OPERATING SYSTEM ON WHICH 31, 3ERVER IS OPERATING "EYOND THESE PREDEFINED EXTERNAL PROCEDURES 31, 3ERVER ALLOWS A USER WRITTEN EXTERNAL PROCEDURE TO BE STORED IN A DYNAMIC LINKED LIBRARY $,, AND CALLED FROM WITHIN 31, 3ERVER STORED PROCEDURES )NFORMIX PROVIDES BASIC ACCESS TO UNDERLYING OPERATING SYSTEM CAPABILITIES WITH A SPECIAL 3934%- STATEMENT )N ADDITION IT SUPPORTS USER WRITTEN EXTERNAL PROCEDURES THROUGH ITS #2%!4% 02/#%$52% STATEMENT 7HERE THE STATEMENT BLOCK COMPRISING THE BODY OF AN )NFORMIX 30, PROCEDURE WOULD APPEAR AN %84%2.!, CLAUSE SPECIFIES THE NAME LOCATION AND LANGUAGE OF THE EXTERNALLY WRITTEN PROCEDURE 7ITH THE PROCEDURE DEFINED IN THIS WAY IT CAN BE CALLED IN THE SAME WAY AS NATIVE )NFORMIX 30, PROCEDURES .EWER VERSIONS OF /RACLE /RACLE AND LATER PROVIDE THE SAME CAPABILITY ALSO VIA THE #2%!4% 02/#%$52% STATEMENT )"-S $" DATABASE FAMILY PROVIDES THE SAME SET OF CAPABILITIES
4RIGGERS !S DESCRIBED AT THE BEGINNING OF THIS CHAPTER A TRIGGER IS A SPECIAL SET OF STORED PROCEDURAL CODE WHOSE ACTIVATION IS CAUSED BY MODIFICATIONS TO THE DATABASE CONTENTS 5NLIKE STORED PROCEDURES A TRIGGER IS NOT ACTIVATED BY A #!,, OR %8%#54% STATEMENT )NSTEAD THE TRIGGER IS ASSOCIATED WITH A DATABASE TABLE 7HEN THE DATA IN THE TABLE IS CHANGED BY AN ).3%24 $%,%4% OR 50$!4% STATEMENT THE TRIGGER IS FIRED WHICH MEANS THAT THE $"-3 EXECUTES THE 31, STATEMENTS THAT MAKE UP THE BODY OF THE TRIGGER 3OME $"-3 BRANDS ALLOW DEFINITION OF SPECIFIC UPDATES THAT CAUSE A TRIGGER TO FIRE !LSO SOME $"-3 BRANDS NOTABLY /RACLE ALLOW TRIGGERS TO BE BASED ON SYSTEM EVENTS SUCH AS USERS CONNECTING TO THE DATABASE OR EXECUTION OF A DATABASE SHUTDOWN COMMAND 4RIGGERS CAN BE USED TO CAUSE AUTOMATIC UPDATES OF INFORMATION WITHIN A DATABASE &OR EXAMPLE SUPPOSE YOU WANTED TO SET UP THE SAMPLE DATABASE SO THAT ANY TIME A NEW SALESPERSON IS INSERTED INTO THE 3!,%32%03 TABLE THE SALES TARGET FOR THE OFFICE WHERE THE SALESPERSON WORKS IS RAISED BY THE NEW SALESPERSONS QUOTA (ERE IS AN /RACLE 0,31, TRIGGER THAT ACCOMPLISHES THIS GOAL #REATE OR REPLACE TRIGGER UPD?TGT )NSERT TRIGGER FOR 3!,%32%03 BEFORE INSERT ON SALESREPS FOR EACH ROW BEGIN IF NEWQUOTA IS NOT NULL THEN UPDATE OFFICES SET TARGET TARGET NEWQUOTA END IF END
4HE #2%!4% 42)''%2 STATEMENT IS USED BY MOST $"-3 BRANDS THAT SUPPORT TRIGGERS TO DEFINE A NEW TRIGGER WITHIN THE DATABASE )T ASSIGNS A NAME TO THE TRIGGER 50$?4'4 FOR THIS ONE AND IDENTIFIES THE TABLE THE TRIGGER IS ASSOCIATED WITH 3!,%32%03 AND THE UPDATE ACTIONS ON THAT TABLE THAT WILL CAUSE THE TRIGGER TO BE EXECUTED ).3%24 IN THIS CASE 4HE BODY OF THIS TRIGGER TELLS THE $"-3 THAT FOR EACH NEW ROW INSERTED INTO THE TABLE IT SHOULD EXECUTE THE SPECIFIED 50$!4% STATEMENT FOR THE /&&)#%3 TABLE 4HE 15/4! VALUE FROM THE NEWLY INSERTED 3!,%32%03 ROW IS REFERRED TO AS .%715/4! WITHIN THE TRIGGER BODY
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
!DVANTAGESõANDõ$ISADVANTAGESõOFõ4RIGGERS 4RIGGERS CAN BE EXTREMELY USEFUL AS AN INTEGRAL PART OF A DATABASE DEFINITION AND THEY CAN BE USED FOR A VARIETY OF DIFFERENT FUNCTIONS INCLUDING THESE s !UDITING CHANGES ! TRIGGER CAN DETECT AND DISALLOW SPECIFIC UPDATES AND CHANGES THAT SHOULD NOT BE PERMITTED IN THE DATABASE s #ASCADED OPERATIONS ! TRIGGER CAN DETECT AN OPERATION WITHIN THE DATABASE SUCH AS DELETION OF A CUSTOMER OR SALESPERSON AND AUTOMATICALLY CASCADE THE IMPACT THROUGHOUT THE DATABASE SUCH AS ADJUSTING ACCOUNT BALANCES OR SALES TARGETS s %NFORCE INTERRELATIONSHIPS ! TRIGGER CAN ENFORCE MORE COMPLEX INTERRELATIONSHIPS AMONG THE DATA IN A DATABASE THAN THOSE THAT CAN BE EXPRESSED BY SIMPLE REFERENTIAL INTEGRITY CONSTRAINTS OR CHECK CONSTRAINTS SUCH AS THOSE THAT REQUIRE A SEQUENCE OF 31, STATEMENTS OR )&x4(%.x%,3% PROCESSING s 3TORED PROCEDURE INVOCATION ! TRIGGER CAN CALL ONE OR MORE STORED PROCEDURES OR EVEN INVOKE ACTIONS OUTSIDE THE $"-3 ITSELF THROUGH EXTERNAL PROCEDURE CALLS IN RESPONSE TO DATABASE UPDATES s $ETECTING SYSTEM EVENTS &OR $"-3S THAT SUPPORT TRIGGERS BASED ON SYSTEM EVENTS THE TRIGGER CAN AUDIT OR MONITOR SUCH EVENTS SUCH AS TRACING A PARTICULAR USER WHENEVER THEY CONNECT TO THE DATABASE )N EACH OF THESE CASES A TRIGGER EMBODIES A SET OF BUSINESS RULES THAT GOVERN THE DATA IN THE DATABASE AND MODIFICATIONS TO THAT DATA 4HE RULES ARE EMBEDDED IN A SINGLE PLACE IN THE DATABASE THE TRIGGER DEFINITION !S A RESULT THEY ARE UNIFORMLY ENFORCED ACROSS ALL APPLICATIONS THAT ACCESS THE DATABASE 7HEN THEY NEED TO BE CHANGED THEY CAN BE CHANGED ONCE WITH THE ASSURANCE THAT THE CHANGE WILL BE APPLIED UNIFORMLY 4HE MAJOR DISADVANTAGE OF TRIGGERS IS THEIR POTENTIAL PERFORMANCE IMPACT )F A TRIGGER IS SET ON A PARTICULAR TABLE THEN EVERY DATABASE OPERATION THAT ATTEMPTS TO CHANGE THAT TABLES DATA IN THE MANNER DEFINED IN THE TRIGGER AN INSERT DELETE OR UPDATE TO ONE OR MORE COLUMNS CAUSES THE $"-3 TO EXECUTE THE TRIGGER PROCEDURE &OR A DATABASE THAT REQUIRES VERY HIGH DATA INSERTION OR UPDATE RATES THE OVERHEAD OF THIS PROCESSING CAN BE CONSIDERABLE 4HIS IS ESPECIALLY TRUE FOR BULK LOAD OPERATIONS WHERE THE DATA MAY HAVE ALREADY BEEN PRECHECKED FOR INTEGRITY 4O DEAL WITH THIS DISADVANTAGE SOME $"-3 BRANDS ALLOW TRIGGERS TO BE SELECTIVELY ENABLED AND DISABLED AS APPROPRIATE
4RIGGERSõINõ4RANSACT 31, 4RANSACT 31, PROVIDES TRIGGERS THROUGH A #2%!4% 42)''%2 STATEMENT IN BOTH ITS -ICROSOFT 31, 3ERVER AND 3YBASE !DAPTIVE 3ERVER DIALECTS (ERE IS A 4RANSACT 31, TRIGGER DEFINITION FOR THE SAMPLE DATABASE WHICH IMPLEMENTS THE SAME TRIGGER AS THE PRECEDING /RACLE 0, 31, EXAMPLE
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CREATE TRIGGER UPD?TGT )NSERT TRIGGER FOR 3!,%32%03 ON SALESREPS FOR INSERT AS IF ROWCOUNT
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31,ç4ODAYçANDç4OMORROW
BEGIN UPDATE OFFICES SET TARGET TARGET INSERTEDQUOTA FROM OFFICES INSERTED WHERE OFFICESOFFICE INSERTEDREP?OFFICE END ELSE RAISERROR
4HE FIRST CLAUSE NAMES THE TRIGGER 50$?4'4 4HE SECOND CLAUSE IS REQUIRED AND IDENTIFIES THE TABLE TO WHICH THE TRIGGER APPLIES 4HE THIRD CLAUSE IS ALSO REQUIRED AND TELLS WHICH DATABASE UPDATE OPERATIONS CAUSE THE TRIGGER TO BE FIRED )N THIS CASE ONLY AN ).3%24 STATEMENT CAUSES THE TRIGGER TO FIRE 9OU CAN ALSO SPECIFY 50$!4% OR $%,%4% OPERATIONS OR A COMBINATION OF TWO OR THREE OF THESE OPERATIONS IN A COMMA SEPARATED LIST 4RANSACT 31, RESTRICTS TRIGGERS SO THAT ONLY ONE TRIGGER MAY BE DEFINED ON A PARTICULAR TABLE FOR EACH OF THE THREE DATA MODIFICATION OPERATIONS 4HE BODY OF THE TRIGGER FOLLOWS THE !3 KEYWORD 4O UNDERSTAND THE BODY OF A TRIGGER LIKE THIS ONE YOU NEED TO UNDERSTAND HOW 4RANSACT 31, TREATS THE ROWS IN THE TARGET TABLE DURING DATABASE MODIFICATION OPERATIONS &OR PURPOSES OF TRIGGER OPERATION 4RANSACT 31, DEFINES TWO LOGICAL TABLES WHOSE COLUMN STRUCTURE IS IDENTICAL TO THE TARGET TABLE ON WHICH THE TRIGGER IS DEFINED /NE OF THESE LOGICAL TABLES IS NAMED $%,%4%$ AND THE OTHER IS NAMED ).3%24%$ 4HESE LOGICAL TABLES ARE POPULATED WITH ROWS FROM THE TARGET TABLE DEPENDING ON THE DATA MODIFICATION STATEMENT THAT CAUSED THE TRIGGER TO FIRE AS FOLLOWS s $%,%4% %ACH TARGET TABLE ROW THAT IS DELETED BY THE $%,%4% STATEMENT IS PLACED INTO THE $%,%4%$ TABLE 4HE ).3%24%$ TABLE IS EMPTY s ).3%24 %ACH TARGET TABLE ROW THAT IS ADDED BY THE ).3%24 STATEMENT IS ALSO PLACED INTO THE ).3%24%$ TABLE 4HE $%,%4%$ TABLE IS EMPTY s 50$!4% &OR EACH TARGET TABLE ROW THAT IS CHANGED BY THE 50$!4% STATEMENT A COPY OF THE ROW BEFORE ANY MODIFICATIONS IS PLACED INTO THE $%,%4%$ TABLE ! COPY OF THE ROW AFTER ALL MODIFICATIONS IS PLACED INTO THE ).3%24%$ TABLE 4HESE TWO LOGICAL TABLES CAN BE REFERENCED WITHIN THE BODY OF THE TRIGGER AND THE DATA IN THEM CAN BE COMBINED WITH DATA FROM OTHER TABLES DURING THE TRIGGERS OPERATION )N THIS 4RANSACT 31, TRIGGER THE TRIGGER BODY FIRST TESTS TO MAKE SURE THAT ONLY A SINGLE ROW OF THE 3!,%32%03 TABLE HAS BEEN INSERTED BY CHECKING THE SYSTEM VARIABLE 2/7#/5.4 )F THIS IS TRUE THEN THE 15/4! COLUMN FROM THE ).3%24%$ LOGICAL TABLE IS ADDED TO THE APPROPRIATE ROW OF THE /&&)#%3 TABLE 4HE APPROPRIATE ROW IS DETERMINED BY JOINING THE LOGICAL TABLE TO THE /&&)#%3 TABLE BASED ON MATCHING OFFICE NUMBERS (ERE IS A DIFFERENT TRIGGER THAT DETECTS A DIFFERENT TYPE OF DATA INTEGRITY PROBLEM )N THIS CASE IT CHECKS FOR AN ATTEMPT TO DELETE A CUSTOMER WHEN THERE ARE STILL ORDERS OUTSTANDING IN THE DATABASE FOR THAT CUSTOMER )F IT DETECTS THIS SITUATION THE TRIGGER AUTOMATICALLY ROLLS BACK THE ENTIRE TRANSACTION INCLUDING THE $%,%4% STATEMENT THAT FIRED THE TRIGGER CREATE TRIGGER CHK?DEL?CUST $ELETE TRIGGER FOR #534/-%23 ON CUSTOMERS FOR DELETE
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
AS $ETECT ANY ORDERS FOR DELETED CUST gS IF SELECT COUNT FROM ORDERS DELETED WHERE ORDERSCUST DELETEDCUST?NUM BEGIN ROLLBACK TRANSACTION PRINT #ANNOT DELETE STILL HAVE ORDERS RAISERROR END
4RANSACT 31, TRIGGERS CAN BE SPECIFIED TO FIRE ON ANY 50$!4% FOR A TARGET TABLE OR JUST FOR UPDATES OF SELECTED COLUMNS 4HIS TRIGGER FIRES ON INSERTS OR UPDATES TO THE 3!,%32%03 TABLE AND DOES DIFFERENT PROCESSING DEPENDING ON WHETHER THE 15/4! OR 3!,%3 COLUMN HAS BEEN UPDATED CREATE TRIGGER UPD?REPS 5PDATE TRIGGER FOR 3!,%32%03 ON SALESREPS FOR INSERT UPDATE IF UPDATEQUOTA (ANDLE UPDATES TO QUOTA COLUMN IF UPDATE SALES (ANDLE UPDATES TO SALES COLUMN
4RIGGERSõINõ)NFORMIXõ30, )NFORMIX ALSO SUPPORTS TRIGGERS THROUGH A #2%!4% 42)''%2 STATEMENT !S IN THE 4RANSACT 31, DIALECT THE BEGINNING OF THE #2%!4% 42)''%2 STATEMENT DEFINES THE TRIGGER NAME THE TABLE ON WHICH THE TRIGGER IS BEING DEFINED AND THE TRIGGERING ACTIONS (ERE ARE STATEMENT FRAGMENTS THAT SHOW THE SYNTAX CREATE TRIGGER NEW?SLS INSERT ON SALESREPS CREATE TRIGGER DEL?CUS?CHK DELETE ON CUSTOMERS CREATE TRIGGER ORD?UPD UPDATE ON ORDERS CREATE TRIGGER SLS?UPD UPDATE OF QUOTA SALES ON SALESREPS
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4HE LAST EXAMPLE IS A TRIGGER THAT FIRES ONLY WHEN TWO SPECIFIC COLUMNS OF THE 3!,%32%03 TABLE ARE UPDATED
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31,ç4ODAYçANDç4OMORROW
)NFORMIX ALLOWS YOU TO SPECIFY THAT A TRIGGER SHOULD OPERATE AT THREE DISTINCT TIMES DURING THE PROCESSING OF A TRIGGERED CHANGE TO THE TARGET TABLE s "%&/2% 4HE TRIGGER FIRES BEFORE ANY CHANGES TAKE PLACE .O ROWS OF THE TARGET TABLE HAVE YET BEEN MODIFIED s !&4%2 4HE TRIGGER FIRES AFTER ALL CHANGES TAKE PLACE !LL AFFECTED ROWS OF THE TARGET TABLE HAVE BEEN MODIFIED s &/2 %!#( 2/7 4HE TRIGGER FIRES REPEATEDLY ONCE AS EACH ROW AFFECTED BY THE CHANGE IS BEING MODIFIED "OTH THE OLD AND NEW DATA VALUES FOR THE ROW ARE AVAILABLE TO THE TRIGGER !N INDIVIDUAL TRIGGER DEFINITION CAN SPECIFY ACTIONS TO BE TAKEN AT ONE OR MORE OF THESE STEPS &OR EXAMPLE A TRIGGER COULD EXECUTE A STORED PROCEDURE TO CALCULATE THE SUM OF ALL ORDERS "%&/2% AN UPDATE MONITOR UPDATES TO EACH /2$%23 ROW AS THEY OCCUR WITH A SECOND ACTION AND THEN CALCULATE THE REVISED ORDER TOTAL !&4%2 THE UPDATE WITH A CALL TO ANOTHER STORED PROCEDURE (ERE IS A TRIGGER DEFINITION THAT DOES ALL OF THIS CREATE TRIGGER UPD?ORD UPDATE OF AMOUNT ON ORDERS REFERENCING OLD AS PRE NEW AS POST #ALCULATE ORDER TOTAL BEFORE CHANGES BEFORE EXECUTE PROCEDURE ADD?ORDERS INTO OLD?TOTAL #APTURE ORDER INCREASES AND DECREASES FOR EACH ROW WHEN POSTAMOUNT PREAMOUNT 7RITE DECREASE DATA INTO TABLE INSERT INTO ORD?LESS VALUES PRECUST PREORDER?DATE PREAMOUNT POSTAMOUNT WHEN POSTAMOUNT PREAMOUNT 7RITE INCREASE DATA INTO TABLE INSERT INTO ORD?MORE VALUES PRECUST PREORDER?DATE PREAMOUNT POSTAMOUNT !FTER CHANGES RECALCULATE TOTAL AFTER EXECUTE PROCEDURE ADD?ORDERS INTO NEW?TOTAL
4HE "%&/2% CLAUSE IN THIS TRIGGER SPECIFIES THAT A STORED PROCEDURE NAMED !$$?/2$%23 IS TO BE CALLED BEFORE ANY 50$!4% STATEMENT PROCESSING OCCURS 0RESUMABLY THIS PROCEDURE CALCULATES THE TOTAL ORDERS AND RETURNS THE TOTAL VALUE INTO THE LOCAL VARIABLE /,$?4/4!, 3IMILARLY THE !&4%2 CLAUSE SPECIFIES THAT A STORED PROCEDURE IN THIS CASE THE SAME ONE IS TO BE CALLED AFTER ALL 50$!4% STATEMENT PROCESSING IS COMPLETE 4HIS TIME THE TOTAL ORDERS AMOUNT IS PLACED INTO A DIFFERENT LOCAL VARIABLE .%7?4/4!,
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
4HE &/2 %!#( 2/7 CLAUSE SPECIFIES THE ACTION TO BE TAKEN AS EACH AFFECTED ROW IS UPDATED )N THIS CASE THE REQUESTED ACTION IS AN ).3%24 INTO ONE OF TWO ORDER TRACKING TABLES DEPENDING ON WHETHER THE ORDER AMOUNT IS BEING INCREASED OR DECREASED 4HESE TRACKING TABLES CONTAIN THE CUSTOMER NUMBER DATE AND BOTH THE OLD AND NEW ORDER AMOUNTS 4O OBTAIN THE REQUIRED VALUES THE TRIGGER MUST BE ABLE TO REFER TO BOTH THE OLD PRECHANGE AND THE NEW POSTCHANGE VALUES OF EACH ROW 4HE 2%&%2%.#).' CLAUSE PROVIDES NAMES BY WHICH THESE TWO STATES OF THE ROW CURRENTLY BEING MODIFIED IN THE /2$%23 TABLE CAN BE USED )N THIS EXAMPLE THE PRECHANGE VALUES OF THE COLUMNS ARE AVAILABLE THROUGH THE COLUMN NAME QUALIFIER 02% AND THE POSTCHANGE VALUES ARE AVAILABLE THROUGH THE COLUMN NAME QUALIFIER 0/34 4HESE ARE NOT SPECIAL NAMES ANY NAMES CAN BE USED )NFORMIX IS MORE LIMITED THAN SOME OTHER $"-3 BRANDS IN THE ACTIONS THAT CAN BE SPECIFIED WITHIN THE TRIGGER DEFINITION ITSELF 4HESE STATEMENTS ARE AVAILABLE s ).3%24 s $%,%4% s 50$!4% s %8%#54% 02/#%$52% )N PRACTICE THE LAST OPTION PROVIDES QUITE A BIT OF FLEXIBILITY 4HE CALLED PROCEDURE CAN PERFORM ALMOST ANY PROCESSING THAT COULD BE DONE INLINE WITHIN THE TRIGGER BODY ITSELF
4RIGGERSõINõ/RACLEõ0,31, /RACLE PROVIDES A MORE COMPLEX TRIGGER FACILITY THAN EITHER THE )NFORMIX OR 4RANSACT 31, FACILITY DESCRIBED IN THE PRECEDING SECTIONS )T USES A #2%!4% 42)''%2 STATEMENT TO SPECIFY TRIGGERED ACTIONS !S IN THE )NFORMIX FACILITY A TRIGGER CAN BE SPECIFIED TO FIRE AT SPECIFIC TIMES DURING SPECIFIC UPDATE OPERATIONS s 3TATEMENT LEVEL TRIGGER ! STATEMENT LEVEL TRIGGER FIRES ONCE FOR EACH DATA MODIFICATION STATEMENT )T CAN BE SPECIFIED TO FIRE EITHER BEFORE THE STATEMENT IS EXECUTED OR AFTER THE STATEMENT HAS COMPLETED ITS ACTION s 2OW LEVEL TRIGGER ! ROW LEVEL TRIGGER FIRES ONCE FOR EACH ROW BEING MODIFIED BY A STATEMENT )N /RACLES STRUCTURE THIS TYPE OF TRIGGER MAY ALSO FIRE EITHER BEFORE THE ROW IS MODIFIED OR AFTER IT IS MODIFIED s )NSTEAD OF TRIGGER !N INSTEAD OF TRIGGER TAKES THE PLACE OF AN ATTEMPTED DATA MODIFICATION STATEMENT )T PROVIDES A WAY TO DETECT AN ATTEMPTED 50$!4% ).3%24 OR $%,%4% OPERATION BY A USER OR PROCEDURE AND TO SUBSTITUTE OTHER PROCESSING INSTEAD 9OU CAN SPECIFY THAT A TRIGGER SHOULD BE EXECUTED INSTEAD OF A STATEMENT OR THAT IT SHOULD BE EXECUTED INSTEAD OF EACH ATTEMPTED MODIFICATION OF A ROW
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s 3YSTEM EVENT TRIGGER ! TRIGGER THAT FIRES WHEN A PARTICULAR SYSTEM EVENT TAKES PLACE SUCH AS A USER CONNECTING TO THE DATABASE OR ENTRY OF A DATABASE SHUTDOWN COMMAND
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4HE FOLLOWING CODE IS A 0,31, TRIGGER DEFINITION THAT IMPLEMENTS THE SAME PROCESSING AS IN THE COMPLEX )NFORMIX EXAMPLE FROM THE PREVIOUS SECTION )T HAS BEEN SPLIT INTO THREE SEPARATE /RACLE #2%!4% 42)''%2 STATEMENTS ONE EACH FOR THE "%&/2% AND !&4%2 STATEMENT LEVEL TRIGGERS AND ONE TRIGGER THAT IS EXECUTED FOR EACH UPDATE ROW CREATE TRIGGER BEF?UPD?ORD BEFORE UPDATE ON ORDERS BEGIN #ALCULATE ORDER TOTAL BEFORE CHANGES OLD?TOTAL ADD?ORDERS END CREATE TRIGGER AFT?UPD?ORD AFTER UPDATE ON ORDERS BEGIN #ALCULATE ORDER TOTAL AFTER CHANGES NEW?TOTAL ADD?ORDERS END CREATE TRIGGER DUR?UPD?ORD BEFORE UPDATE OF AMOUNT ON ORDERS REFERENCING OLD AS PRE NEW AS POST #APTURE ORDER INCREASES AND DECREASES FOR EACH ROW WHEN POSTAMOUNT PREAMOUNT BEGIN IF POSTAMOUNT PREAMOUNT THEN IF POSTAMOUNT PREAMOUNT THEN 7RITE DECREASE DATA INTO TABLE INSERT INTO ORD?LESS VALUES PRECUST PREORDER?DATE PREAMOUNT POSTAMOUNT ELSIF POSTAMOUNT PREAMOUNT THEN 7RITE INCREASE DATA INTO TABLE INSERT INTO ORD?MORE VALUES PRECUST PREORDER?DATE PREAMOUNT POSTAMOUNT END IF END IF END
4HESE TRIGGER STRUCTURES AND THEIR OPTIONS PROVIDE DIFFERENT VALID /RACLE TRIGGER TYPES RESULTING FROM A CHOICE OF ).3%24$%,%4%50$!4% TRIGGERS FOR "%&/2% OR !&4%2 PROCESSING AT THE ROW OR STATEMENT LEVEL ¾¾ AND TWO MORE FROM INSTEAD OF TRIGGERS AT
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
THE STATEMENT OR ROW LEVEL )N PRACTICE RELATIONAL DATABASES BUILT USING /RACLE DONT TEND TO USE INSTEAD OF TRIGGERS THEY WERE INTRODUCED IN /RACLE TO SUPPORT SOME OF ITS NEWER OBJECT ORIENTED FEATURES
/THERõ4RIGGERõ#ONSIDERATIONS 4RIGGERS POSE SOME OF THE SAME ISSUES FOR $"-3 PROCESSING THAT 50$!4% AND $%,%4% RULES PRESENT &OR EXAMPLE TRIGGERS CAN CAUSE A CASCADED SERIES OF ACTIONS 3UPPOSE A USERS ATTEMPT TO UPDATE A TABLE CAUSES A TRIGGER TO FIRE AND WITHIN THE BODY OF THAT TRIGGER IS AN 50$!4% STATEMENT FOR ANOTHER TABLE ! TRIGGER ON THAT TABLE CAUSES THE 50$!4% OF STILL ANOTHER TABLE AND SO ON 4HE SITUATION IS EVEN WORSE IF ONE OF THE FIRED TRIGGERS ATTEMPTS TO UPDATE THE ORIGINAL TARGET TABLE THAT CAUSED THE FIRING OF THE TRIGGER SEQUENCE IN THE FIRST PLACE )N THIS CASE AN INFINITE LOOP OF FIRED TRIGGERS COULD RESULT 6ARIOUS $"-3 SYSTEMS DEAL WITH THIS ISSUE IN DIFFERENT WAYS 3OME IMPOSE RESTRICTIONS ON THE ACTIONS THAT CAN BE TAKEN DURING EXECUTION OF A TRIGGER /THERS PROVIDE BUILT IN FUNCTIONS THAT ALLOW A TRIGGERS BODY TO DETECT THE LEVEL OF NESTING AT WHICH THE TRIGGER IS OPERATING 3OME PROVIDE A SYSTEM SETTING THAT CONTROLS WHETHER CASCADED TRIGGER PROCESSING IS ALLOWED &INALLY SOME PROVIDE A LIMIT ON THE NUMBER OF LEVELS OF NESTED TRIGGERS THAT CAN FIRE /NE ADDITIONAL ISSUE ASSOCIATED WITH TRIGGERS IS THE OVERHEAD THAT CAN RESULT DURING VERY HEAVY DATABASE USAGE SUCH AS WHEN BULK DATA IS BEING LOADED INTO A DATABASE 3OME $"-3 BRANDS PROVIDE THE ABILITY TO SELECTIVELY ENABLE AND DISABLE TRIGGER PROCESSING TO HANDLE THIS SITUATION /RACLE FOR EXAMPLE PROVIDES THIS FORM OF THE !,4%2 42)''%2 STATEMENT !,4%2 42)''%2 "%&?50$?/2$ $)3!",%
! SIMILAR CAPABILITY IS PROVIDED WITHIN THE #2%!4% 42)''%2 STATEMENT OF )NFORMIX
3TOREDõ0ROCEDURES õ&UNCTIONS õ4RIGGERS õANDõTHEõ31,õ3TANDARD
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4HE DEVELOPMENT OF $"-3 STORED PROCEDURES FUNCTIONS AND TRIGGERS HAS BEEN LARGELY DRIVEN BY $"-3 VENDORS AND THE COMPETITIVE DYNAMICS OF THE DATABASE INDUSTRY 3YBASES INITIAL INTRODUCTION OF STORED PROCEDURES AND TRIGGERS IN 31, 3ERVER TRIGGERED A COMPETITIVE RESPONSE AND BY THE MID S MANY OF THE ENTERPRISE CLASS SYSTEMS HAD ADDED THEIR OWN PROPRIETARY PROCEDURAL EXTENSIONS TO 31, 3TORED PROCEDURES WERE NOT A FOCUS OF THE 31, STANDARD BUT BECAME A PART OF THE STANDARDIZATION AGENDA AFTER THE PUBLICATION OF THE 31, STANDARD 4HE WORK ON STORED PROCEDURE STANDARDS WAS SPLIT OFF FROM THE BROADER OBJECT ORIENTED EXTENSIONS THAT WERE PROPOSED FOR 31, AND WAS FOCUSED ON A SET OF PROCEDURAL EXTENSIONS TO THE 31, LANGUAGE 4HE RESULT WAS A NEW PART OF THE 31, STANDARD PUBLISHED IN AS 31,0ERSISTENT 3TORED -ODULES 31,03- )NTERNATIONAL 3TANDARD )3/)%# 4HE ACTUAL FORM OF THE STANDARD SPECIFICATION IS A COLLECTION OF ADDITIONS EDITS NEW PARAGRAPHS AND REPLACEMENT PARAGRAPHS TO THE 31, STANDARD )3/)%# )N ADDITION TO BEING A MODIFICATION OF THE 31, STANDARD 31,03- WAS ALSO DRAFTED AS A PART OF THE PLANNED FOLLOW ON STANDARD WHICH WAS CALLED 31, DURING ITS DRAFTING 4HE DEVELOPMENT OF THE FOLLOW ON STANDARD TOOK LONGER THAN EXPECTED BUT 31,03- EVENTUALLY TOOK ITS PLACE AS 0ART OF THE 31, STANDARD OFFICIALLY KNOWN AS 31, 4HE 31, #ALL ,EVEL )NTERFACE #,) STANDARD DESCRIBED IN #HAPTER WAS TREATED THE SAME WAY IT IS NOW 0ART OF THE 31, STANDARD
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7HEN THE 31, STANDARD WAS PUBLISHED SELECTED PARTS OF 31,03- THAT ARE USED BY OTHER PARTS OF THE STANDARD WERE MOVED TO THE CORE 31,&OUNDATION SPECIFICATION 0ART 4HE 31,03- STANDARD PUBLISHED IN ADDRESSED ONLY STORED PROCEDURES AND FUNCTIONS IT EXPLICITLY DID NOT PROVIDE A SPECIFICATION OF A TRIGGER FACILITY FOR THE )3/ 31, STANDARD 4HE STANDARDIZATION OF TRIGGER FUNCTIONS WAS CONSIDERED DURING THE DEVELOPMENT OF THE 31, AND 31,03- STANDARDS BUT THE STANDARDS GROUPS DETERMINED THAT TRIGGERS WERE TOO CLOSELY TIED TO OTHER OBJECT ORIENTED EXTENSIONS PROPOSED FOR 31, 4HE 31, STANDARD THAT RESULTED FROM THE 31, WORK FINALLY PROVIDED AN !.3))3/ STANDARD TRIGGER FACILITY 4HE PUBLICATION OF THE 31,03- AND 31, STANDARDS LAGGED THE FIRST COMMERCIAL IMPLEMENTATION OF STORED PROCEDURES AND TRIGGERS BY MANY YEARS "Y THE TIME THE STANDARD WAS ADOPTED MOST ENTERPRISE $"-3 VENDORS HAD RESPONDED TO USER ENTHUSIASM AND COMPETITIVE PRESSURE BY INTRODUCING STORED PROCEDURE AND TRIGGER CAPABILITIES IN THEIR PRODUCTS 5NLIKE SOME OTHER 31, EXTENSIONS WHERE )"-S CLOUT AND A $" IMPLEMENTATION HAD SET A DE FACTO STANDARD THE MAJOR $"-3 VENDORS IMPLEMENTED STORED PROCEDURES AND TRIGGERS IN DIFFERENT PROPRIETARY WAYS AND IN SOME CASES COMPETED WITH ONE ANOTHER BASED ON UNIQUE FEATURES OF THEIR IMPLEMENTATIONS !S A RESULT THE !.3))3/ STANDARDIZATION OF STORED PROCEDURES AND TRIGGERS HAS HAD LITTLE IMPACT ON THE $"-3 MARKET TO DATE )TS REASONABLE TO EXPECT THAT !.3) )3/ IMPLEMENTATIONS WILL FIND THEIR WAY INTO MAJOR $"-3 PRODUCTS OVER TIME BUT AS A COMPLEMENT TO RATHER THAN A REPLACEMENT FOR THE PROPRIETARY IMPLEMENTATIONS
4HEõ31,03-õ3TOREDõ0ROCEDURESõ3TANDARD 4HE CAPABILITIES SPECIFIED IN THE 31,03- STANDARD PARALLEL THE CORE FEATURES OF THE PROPRIETARY STORED PROCEDURE CAPABILITIES OF TODAYS $"-3 SYSTEMS 4HEY INCLUDE 31, LANGUAGE CONSTRUCTS TO s $EFINE AND NAME PROCEDURES AND FUNCTIONS WRITTEN IN THE EXTENDED 31, LANGUAGE s )NVOKE CALL A PREVIOUSLY DEFINED PROCEDURE OR FUNCTION s 0ASS PARAMETERS TO A CALLED PROCEDURE OR FUNCTION AND OBTAIN THE RESULTS OF ITS EXECUTION s $ECLARE AND USE LOCAL VARIABLES WITHIN THE PROCEDURE OR FUNCTION s 'ROUP A BLOCK OF 31, STATEMENTS TOGETHER FOR EXECUTION s #ONDITIONALLY EXECUTE 31, STATEMENTS )&x4(%.x%,3% s 2EPEATEDLY EXECUTE A GROUP OF 31, STATEMENTS LOOPING 4HE 31,03- STANDARD SPECIFIES TWO TYPES OF 31, INVOKED ROUTINES ! 31, PROCEDURE IS A ROUTINE THAT CAN RETURN ANY NUMBER OF VALUES OR NO VALUE AT ALL )T IS CALLED WITH A #!,, STATEMENT #!,, !$$?#534g89: #ORPORATIONg g#HICAGOg
!S WITH THE PROPRIETARY STORED PROCEDURE LANGUAGES ILLUSTRATED IN THE PREVIOUS EXAMPLES THROUGHOUT THIS CHAPTER 31,03- STORED PROCEDURES ACCEPT PARAMETERS PASSED VIA THE #!,, STATEMENT 31,03- STORED PROCEDURES CAN ALSO PASS DATA BACK TO THEIR CALLER VIA OUTPUT PARAMETERS AGAIN MIRRORING THE CAPABILITIES OF THE PROPRIETARY STORED PROCEDURE LANGUAGES 31,03- ALSO SUPPORTS COMBINED INPUTOUTPUT PARAMETERS LIKE SOME OF THE PROPRIETARY LANGUAGES
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
! 31, FUNCTION DOES RETURN A VALUE )T IS CALLED JUST LIKE A BUILT IN 31, FUNCTION WITHIN A VALUE EXPRESSION 3%,%#4 #/-0!.9 &2/- #534/-%23 7(%2% '%4?4/4?/2$3#534?.5-
31,03- RESTRICTS 31, FUNCTIONS TO ONLY RETURNING A SINGLE VALUE THROUGH THE FUNCTION CALL MECHANISM /UTPUT PARAMETERS AND INPUTOUTPUT PARAMETERS ARE NOT ALLOWED IN 31, FUNCTIONS 31, ROUTINES ARE OBJECTS WITHIN THE DATABASE STRUCTURE DESCRIBED IN THE 31, STANDARD 31,03- ALLOWS THE CREATION OF ROUTINES WITHIN A 31, SCHEMA A SCHEMA LEVEL ROUTINE WHERE IT EXISTS ALONG WITH THE TABLES VIEWS ASSERTIONS AND OTHER OBJECTS )T ALSO ALLOWS THE CREATION OF ROUTINES WITHIN A 31, MODULE WHICH IS THE 31, PROCEDURE MODEL CARRIED FORWARD FROM THE 31, STANDARD
#REATINGõAõ31,õ2OUTINE &OLLOWING THE PRACTICE OF MOST $"-3 BRANDS THE 31,03- STANDARD USES THE #2%!4% 02/#%$52% AND #2%!4% &5.#4)/. STATEMENTS TO SPECIFY THE DEFINITIONS OF STORED PROCEDURES AND FUNCTIONS &IGURE SHOWS SYNTAX FOR THE #2%!4% 02/#%$52% STATEMENT AND &IGURE SHOWS THE SYNTAX FOR THE #2%!4% &5.#4)/. STATEMENT )N ADDITION TO THE CAPABILITIES SHOWN IN THE FIGURE THE STANDARD PROVIDES A CAPABILITY TO DEFINE EXTERNAL STORED PROCEDURES SPECIFYING THE LANGUAGE THEY ARE WRITTEN IN WHETHER THEY CAN READ OR MODIFY DATA IN THE DATABASE THEIR CALLING CONVENTIONS AND OTHER CHARACTERISTICS
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&LOW OF #ONTROLõ3TATEMENTS 4HE 31,03- STANDARD SPECIFIES THE COMMON PROGRAMMING STRUCTURES THAT ARE FOUND IN MOST STORED PROCEDURE DIALECTS TO CONTROL THE FLOW OF EXECUTION &IGURE SHOWS THE CONDITIONAL BRANCHING AND LOOPING SYNTAX .OTE THAT THE 31, STATEMENT LISTS SPECIFIED FOR EACH STRUCTURE CONSIST OF A SEQUENCE OF 31, STATEMENTS EACH ENDING WITH A SEMICOLON 4HUS EXPLICIT BLOCK STRUCTURES ARE NOT REQUIRED FOR SIMPLE MULTISTATEMENT SEQUENCES THAT APPEAR IN AN )&x4(%.x%,3% STATEMENT OR IN A ,//0 STATEMENT 4HE LOOPING STRUCTURES PROVIDE A GREAT DEAL OF FLEXIBILITY FOR LOOP PROCESSING 4HERE ARE FORMS THAT PLACE THE TEST AT THE TOP OF THE LOOP OR AT THE BOTTOM OF THE LOOP AS WELL AS A FORM THAT PROVIDES INFINITE LOOPING AND REQUIRES THE EXPLICIT CODING OF A TEST TO BREAK LOOP EXECUTION %ACH OF THE PROGRAM CONTROL STRUCTURES IS EXPLICITLY TERMINATED BY AN %.$ FLAG THAT MATCHES THE TYPE OF STRUCTURE MAKING PROGRAMMING DEBUGGING EASIER
#URSORõ/PERATIONS 4HE 31,03- STANDARD EXTENDS THE CURSOR MANIPULATION CAPABILITIES SPECIFIED IN THE 31, STANDARD FOR EMBEDDED 31, INTO 31, ROUTINES 4HE $%#,!2% #523/2 /0%. &%4#( AND #,/3% STATEMENTS RETAIN THEIR ROLES AND FUNCTIONS )NSTEAD OF USING APPLICATION PROGRAM HOST VARIABLES TO SUPPLY PARAMETER VALUES AND TO RECEIVE RETRIEVED DATA 31, ROUTINE PARAMETERS AND VARIABLES CAN BE USED FOR THESE FUNCTIONS 4HE 31,03- STANDARD INTRODUCES ONE NEW CURSOR CONTROLLED LOOPING STRUCTURE SHOWN IN &IGURE ,IKE THE SIMILAR STRUCTURES IN THE /RACLE AND )NFORMIX DIALECTS DESCRIBED IN THE h#URSOR "ASED 2EPETITIONv SECTION EARLIER IN THIS CHAPTER IT COMBINES THE CURSOR DEFINITION AND THE /0%. &%4#( AND #,/3% STATEMENTS INTO A SINGLE LOOP DEFINITION THAT ALSO SPECIFIES THE PROCESSING TO BE PERFORMED FOR EACH ROW OF RETRIEVED QUERY RESULTS
#HAPTERçç
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"LOCKõ3TRUCTURE &IGURE SHOWS THE BLOCK STRUCTURE SPECIFIED BY THE 31,03- STANDARD )T IS QUITE A COMPREHENSIVE STRUCTURE PROVIDING THE FOLLOWING CAPABILITIES s ,ABELS THE BLOCK OF STATEMENTS WITH A STATEMENT LABEL s $ECLARES LOCAL VARIABLES FOR USE WITHIN THE BLOCK s $ECLARES LOCAL USER DEFINED ERROR CONDITIONS s $ECLARES CURSORS FOR QUERIES TO BE EXECUTED WITHIN THE BLOCK s $ECLARES HANDLERS TO PROCESS ERROR CONDITIONS THAT ARISE s $EFINES THE SEQUENCE OF 31, STATEMENTS TO BE EXECUTED
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4HESE CAPABILITIES RESEMBLE SOME OF THOSE DESCRIBED EARLIER IN THE h3TATEMENT "LOCKSv SECTION OF THIS CHAPTER FOR THE )NFORMIX AND /RACLE DIALECT STORED PROCEDURE DIALECTS ,OCAL VARIABLES WITHIN 31,03- PROCEDURES AND FUNCTIONS ACTUALLY WITHIN STATEMENT BLOCKS ARE DECLARED USING THE $%#,!2% STATEMENT 6ALUES ARE ASSIGNED USING THE 3%4 STATEMENT &UNCTIONS RETURN A VALUE USING THE 2%452. STATEMENT (ERE IS A STATEMENT BLOCK THAT MIGHT APPEAR WITHIN A STORED FUNCTION WITH EXAMPLES OF THESE STATEMENTS TRY?AGAIN BEGIN $ECLARE SOME LOCAL VARIABLES DECLARE MSG?TEXT VARCHAR DECLARE TOT?AMT DECIMAL 'ET THE ORDER TOTAL SET TOT?AMT GET?TOT?ORDS IF TOT?AMT THEN RETURN TOT?AMT ELSE RETURN END IF END TRY?AGAIN
%RRORõ(ANDLING 4HE BLOCK STRUCTURE SPECIFIED BY THE 31,03- STANDARD PROVIDES FAIRLY COMPREHENSIVE SUPPORT FOR ERROR HANDLING 4HE STANDARD SPECIFIES PREDEFINED CONDITIONS THAT CAN BE DETECTED AND HANDLED INCLUDING s 31,7!2.).' /NE OF THE WARNING CONDITIONS SPECIFIED IN THE 31, STANDARD s ./4 &/5.$ 4HE CONDITION THAT NORMALLY OCCURS WHEN THE END OF A SET OF QUERY RESULTS IS REACHED WITH A &%4#( STATEMENT s 31,34!4% VALUE ! TEST FOR SPECIFIC 31,34!4% ERROR CODES s 5SER DEFINED CONDITION ! CONDITION NAMED BY THE STORED PROCEDURE #ONDITIONS ARE TYPICALLY DEFINED IN TERMS OF 31,34!4% VALUES 2ATHER THAN USING NUMERICAL 31,34!4% CODES YOU CAN ASSIGN THE CONDITION A SYMBOLIC NAME 9OU CAN ALSO SPECIFY YOUR OWN USER DEFINED CONDITION DECLARE BAD?ERR CONDITION FOR SQLSTATE gg DECLARE MY?ERR CONDITION
/NCE THE CONDITION HAS BEEN DEFINED YOU CAN FORCE THE CONDITION TO OCCUR THROUGH THE EXECUTION OF A 31, ROUTINE WITH THE 3)'.!, STATEMENT
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SIGNAL BAD?ERR SIGNAL SQLSTATE gg
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4O HANDLE ERROR CONDITIONS THAT MAY ARISE 31,03- ALLOWS YOU TO DECLARE A CONDITION HANDLER 4HE DECLARATION SPECIFIES THE LIST OF CONDITIONS THAT ARE TO BE HANDLED AND THE ACTION TO BE TAKEN )T ALSO SPECIFIES THE TYPE OF CONDITION HANDLING 4HE TYPES DIFFER IN WHAT HAPPENS TO THE FLOW OF CONTROL AFTER THE HANDLER IS FINISHED WITH ITS WORK s #/.4).5% TYPE !FTER THE CONDITION HANDLER COMPLETES ITS WORK CONTROL RETURNS TO THE NEXT STATEMENT FOLLOWING THE ONE THAT CAUSED THE CONDITION 4HAT IS EXECUTION CONTINUES WITH THE NEXT STATEMENT s %8)4 TYPE !FTER THE CONDITION HANDLER COMPLETES ITS WORK CONTROL RETURNS TO THE END OF THE STATEMENT BLOCK CONTAINING THE STATEMENT THAT CAUSED THE CONDITION 4HAT IS EXECUTION EFFECTIVELY EXITS THE BLOCK s 5.$/ TYPE !FTER THE CONDITION HANDLER COMPLETES ITS WORK ALL MODIFICATIONS ARE UNDONE TO DATA IN THE DATABASE CAUSED BY STATEMENTS WITHIN THE SAME STATEMENT BLOCK AS THE STATEMENT CAUSING THE ERROR 4HE EFFECT IS THE SAME AS IF A TRANSACTION HAD BEEN INITIATED AT THE BEGINNING OF THE STATEMENT BLOCK AND WAS BEING ROLLED BACK (ERE ARE SOME EXAMPLES THAT SHOW THE STRUCTURE OF THE HANDLER DEFINITION (ANDLE 31, WARNINGS HERE THEN CONTINUE DECLARE CONTINUE HANDLER FOR SQLWARNING CALL MY?WARN?ROUTINE (ANDLE SEVERE ERRORS BY UNDOING EFFECTS DECLARE UNDO HANDLER FOR USER?DISASTER BEGIN $O DISASTER CLEANUP HERE END
%RROR HANDLING CAN GET QUITE COMPLEX AND ITS POSSIBLE FOR ERRORS TO ARISE DURING THE EXECUTION OF THE HANDLER ROUTINE ITSELF 4O AVOID INFINITE RECURSION ON ERRORS THE NORMAL CONDITION SIGNALING DOES NOT APPLY DURING THE EXECUTION OF A CONDITION HANDLER 4HE STANDARD ALLOWS YOU TO OVERRIDE THIS RESTRICTION WITH THE 2%3)'.!, STATEMENT )T OPERATES JUST LIKE THE 3)'.!, STATEMENT BUT IS USED EXCLUSIVELY WITHIN CONDITION HANDLER ROUTINES
2OUTINEõ.AMEõ/VERLOADING 4HE 31,03- STANDARD PERMITS OVERLOADING OF STORED PROCEDURE AND FUNCTION NAMES /VERLOADING IS A COMMON ATTRIBUTE IN OBJECT ORIENTED SYSTEMS AND IS A WAY TO MAKE STORED ROUTINES MORE FLEXIBLE IN HANDLING A WIDE VARIETY OF DATA TYPES AND SITUATIONS 5SING THE OVERLOADING CAPABILITY SEVERAL DIFFERENT ROUTINES CAN BE GIVEN THE SAME ROUTINE NAME 4HE MULTIPLE ROUTINES DEFINED WITH THE SAME NAME MUST DIFFER FROM ONE ANOTHER IN THE NUMBER OF PARAMETERS THAT THEY ACCEPT OR IN THE DATA TYPES OF THE INDIVIDUAL PARAMETERS &OR EXAMPLE YOU MIGHT DEFINE THESE THREE STORED FUNCTIONS CREATE FUNCTION COMBOA B A INTEGER B INTEGER RETURNS INTEGER AS RETURN A B
#HAPTERçç
$ATABASEç0ROCESSINGçANDç3TOREDç0ROCEDURALç31,ç
CREATE FUNCTION COMBOA B C A INTEGER B INTEGER C INTEGER RETURNS INTEGER AS RETURN A B C CREATE PROCEDURE COMBOA B A VARCHAR B VARCHAR RETURNS VARCHAR AS RETURN A \\ B
4HE FIRST #/-"/ FUNCTION COMBINES TWO INTEGERS BY ADDING THEM AND RETURNS THE SUM 4HE SECOND #/-"/ FUNCTION COMBINES THREE INTEGERS THE SAME WAY 4HE THIRD #/-"/ FUNCTION COMBINES TWO CHARACTER STRINGS BY CONCATENATING THEM 4HE STANDARD ALLOWS ALL OF THESE FUNCTIONS NAMED #/-"/ TO BE DEFINED AT THE SAME TIME WITHIN THE DATABASE 7HEN THE $"-3 ENCOUNTERS A REFERENCE TO THE #/-"/ FUNCTION IT EXAMINES THE NUMBER OF ARGUMENTS IN THE REFERENCE AND THEIR DATA TYPES AND DETERMINES WHICH VERSION OF THE #/-"/ FUNCTION TO CALL 4HUS THE OVERLOADING CAPABILITY ALLOWS A 31, PROGRAMMER TO CREATE A FAMILY OF ROUTINES THAT LOGICALLY PERFORM THE SAME FUNCTION AND HAVE THE SAME NAME EVEN THOUGH THE SPECIFICS OF THEIR USAGE FOR DIFFERENT DATA TYPES IS DIFFERENT )N OBJECT ORIENTED TERMS OVERLOADING IS SOMETIMES CALLED POLYMORPHISM MEANING LITERALLY THAT THE SAME FUNCTION CAN TAKE MANY DIFFERENT FORMS 4O SIMPLIFY THE MANAGEMENT OF A FAMILY OF ROUTINES THAT SHARE AN OVERLOADED NAME THE 31,03- STANDARD HAS THE CONCEPT OF A SPECIFIC NAME A SECOND NAME THAT IS ASSIGNED TO THE ROUTINE THAT IS UNIQUE WITHIN THE DATABASE SCHEMA OR MODULE )T UNIQUELY IDENTIFIES A SPECIFIC ROUTINE 4HE SPECIFIC NAME IS USED TO DROP THE ROUTINE AND IT IS REFLECTED IN THE INFORMATION SCHEMA VIEWS THAT DESCRIBE STORED ROUTINES 4HE SPECIFIC NAME IS NOT USED TO CALL THE ROUTINE THAT WOULD DEFEAT THE PRIMARY PURPOSE OF THE OVERLOADED ROUTINE NAME 3UPPORT FOR SPECIFIC NAMES OR SOME SIMILAR MECHANISM IS A PRACTICAL REQUIREMENT FOR ANY SYSTEM THAT PERMITS OVERLOADING OR POLYMORPHISM FOR OBJECTS AND PROVIDES A CAPABILITY TO MANAGE THEM BY DROPPING OR CHANGING THEIR DEFINITIONS SINCE THE SYSTEM MUST BE ABLE TO DETERMINE WHICH SPECIFIC OBJECT IS BEING MODIFIED
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4HE BULK OF THE 31,03- STANDARD IS CONCERNED WITH THE EXTENSIONS TO THE 31, LANGUAGE THAT ARE USED TO DEFINE 31, PROCEDURES AND FUNCTIONS .OTE HOWEVER THAT THE METHOD USED TO INVOKE A PROCEDURE THE #!,, STATEMENT OR A FUNCTION A REFERENCE TO THE FUNCTION BY NAME WITHIN A 31, STATEMENT IS NOT PARTICULAR TO PROCEDURES DEFINED IN THE 31, LANGUAGE )N FACT THE 31,03- STANDARD PROVIDES FOR EXTERNAL STORED PROCEDURES AND FUNCTIONS WRITTEN IN SOME OTHER PROGRAMMING LANGUAGE SUCH AS # OR 0ASCAL &OR EXTERNAL PROCEDURES THE #2%!4% 02/#%$52% AND #2%!4% &5.#4)/. STATEMENTS ARE STILL USED TO DEFINE THE PROCEDURE TO THE $"-3 SPECIFYING ITS NAME AND THE PARAMETERS THAT IT ACCEPTS OR RETURNS ! SPECIAL CLAUSE OF THE #2%!4% STATEMENT SPECIFIES THE LANGUAGE IN WHICH THE STORED PROCEDURE OR FUNCTION IS WRITTEN SO THAT THE $"-3 MAY PERFORM THE APPROPRIATE CONVERSION OF DATA TYPES AND CALL THE ROUTINE APPROPRIATELY
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/THERõ3TOREDõ0ROCEDUREõ#APABILITIES 4HE 31,03- STANDARD TREATS PROCEDURES AND FUNCTIONS AS MANAGED OBJECTS WITHIN THE DATABASE USING EXTENSIONS TO THE 31, STATEMENTS USED TO MANAGE OTHER OBJECTS 9OU USE A VARIATION OF THE $2/0 STATEMENT TO DELETE ROUTINES WHEN THEY ARE NO LONGER NEEDED AND A VARIATION OF THE !,4%2 STATEMENT TO CHANGE THE DEFINITION OF A FUNCTION OR PROCEDURE 4HE 31, STANDARD PERMISSIONS MECHANISM IS SIMILARLY EXTENDED WITH ADDITIONAL PRIVILEGES 4HE %8%#54% PRIVILEGE GIVES A USER THE ABILITY TO EXECUTE A STORED PROCEDURE OR FUNCTION )T IS MANAGED BY THE '2!.4 AND 2%6/+% STATEMENTS IN THE SAME MANNER AS OTHER DATABASE PRIVILEGES "ECAUSE THE STORED ROUTINES DEFINED BY 31,03- ARE DEFINED WITHIN 31, SCHEMAS MANY ROUTINES CAN BE DEFINED IN MANY DIFFERENT SCHEMAS THROUGHOUT THE DATABASE 7HEN CALLING A STORED ROUTINE THE ROUTINE NAME CAN BE FULLY QUALIFIED TO UNIQUELY IDENTIFY THE ROUTINE WITHIN THE DATABASE 4HE 31,03- STANDARD PROVIDES AN ALTERNATIVE METHOD OF SEARCHING FOR THE DEFINITION OF UNQUALIFIED ROUTINE NAMES THROUGH A NEW 0!4( CONCEPT 4HE 0!4( IS THE SEQUENCE OF SCHEMA NAMES THAT SHOULD BE SEARCHED TO RESOLVE A ROUTINE REFERENCE ! DEFAULT 0!4( CAN BE SPECIFIED AS PART OF THE SCHEMA HEADER IN THE #2%!4% 3#(%-! STATEMENT 4HE 0!4( CAN ALSO BE DYNAMICALLY MODIFIED DURING A 31, SESSION THROUGH THE 3%4 0!4( STATEMENT 4HE 31,03- STANDARD ALSO LETS THE AUTHOR OF A STORED PROCEDURE OR FUNCTION GIVE THE $"-3 SOME HINTS ABOUT ITS OPERATION TO IMPROVE THE EFFICIENCY OF EXECUTION /NE EXAMPLE IS THE ABILITY TO DEFINE A STORED ROUTINE AS $%4%2-).)34)# OR ./4 $%4%2-).)34)# ! $%4%2-).)34)# ROUTINE WILL ALWAYS RETURN THE SAME RESULTS WHEN IT IS CALLED WITH THE SAME PARAMETER VALUES )F THE $"-3 OBSERVES THAT A $%4%2-).)34)# ROUTINE IS CALLED REPEATEDLY IT MAY CHOOSE TO KEEP A COPY OF THE RESULTS THAT IT RETURNS ,ATER WHEN THE ROUTINE IS CALLED AGAIN THE $"-3 DOES NOT NEED TO ACTUALLY EXECUTE THE ROUTINE IT CAN SIMPLY RETURN THE SAME RESULTS THAT IT RETURNED THE LAST TIME !NOTHER FORM OF HINT TELLS THE $"-3 WHETHER AN EXTERNAL STORED PROCEDURE OR FUNCTION READS DATABASE CONTENTS AND WHETHER IT MODIFIES DATABASE CONTENTS 4HIS NOT ONLY ALLOWS THE $"-3 TO OPTIMIZE DATABASE ACCESS BUT CAN ALSO IMPOSE A SECURITY RESTRICTION ON EXTERNAL ROUTINES FROM OTHER SOURCES /THER HINTS DETERMINE WHETHER A FUNCTION SHOULD BE CALLED IF ONE OF ITS PARAMETERS HAS A .5,, VALUE AND CONTROL HOW THE $"-3 SELECTS THE SPECIFIC FUNCTION OR PROCEDURE TO BE EXECUTED WHEN OVERLOADING IS USED
4HEõ31,03-õ4RIGGERSõ3TANDARD 4RIGGERS WERE ADDRESSED FOR STANDARDIZATION AS PART OF THE 31, EFFORT WHICH LED TO THE EVENTUAL PUBLICATION OF THE 31, !.3))3/ STANDARD "Y THAT TIME MANY COMMERCIAL $"-3 PRODUCTS HAD ALREADY IMPLEMENTED TRIGGERS AND THE STANDARD SYNTHESIZED THE SPECIFIC CAPABILITIES THAT HAD PROVEN USEFUL IN PRACTICE ,IKE THE COMMERCIAL PRODUCTS !.3))3/ STANDARD TRIGGERS ARE DEFINED FOR A SINGLE SPECIFIC TABLE 4HE STANDARD PERMITS TRIGGER DEFINITIONS ONLY ON TABLES NOT ON VIEWS 4HE PROPRIETARY 31, 3ERVER /RACLE AND )NFORMIX TRIGGER MECHANISMS SHOWN IN THE EXAMPLES THROUGHOUT THIS CHAPTER PROVIDE A CONTEXT FOR EXAMINING THE !.3))3/
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STANDARD MECHANISM 4HE STANDARD DOES NOT PROVIDE ANY RADICAL DEPARTURE FROM THE CAPABILITIES ALREADY DESCRIBED FOR THE VARIOUS $"-3 PRODUCTS (ERE IS HOW THE STANDARD COMPARES WITH THEM s .AMING 4HE STANDARD TREATS TRIGGERS AS NAMED OBJECTS WITHIN THE DATABASE s 4YPES 4HE STANDARD PROVIDES ).3%24 $%,%4% AND 50$!4% TRIGGERS 50$!4% TRIGGERS CAN BE ASSOCIATED WITH THE UPDATE OF A SPECIFIC COLUMN OR GROUP OF COLUMNS s 4IMING 4HE STANDARD PROVIDES FOR TRIGGERS THAT OPERATE BEFORE A DATABASE UPDATE STATEMENT OR AFTER THE STATEMENT s 2OW LEVEL OR STATEMENT LEVEL OPERATION 4HE STANDARD PROVIDES FOR BOTH STATEMENT LEVEL TRIGGERS EXECUTED ONCE PER DATABASE UPDATING STATEMENT AND ROW LEVEL TRIGGERS EXECUTED REPEATEDLY FOR EACH ROW OF THE TABLE THAT IS MODIFIED s !LIASES !CCESS TO THE hBEFOREv AND hAFTERv VALUES IN A MODIFIED ROW OR TABLE IS PROVIDED VIA AN ALIAS MECHANISM LIKE THE TABLE ALIASES USED IN THE &2/- CLAUSE 9OU USE THE #2%!4% 42)''%2 STATEMENT SHOWN IN &IGURE TO DEFINE A TRIGGER 4HE STATEMENT CLAUSES ARE FAMILIAR FROM THE PROPRIETARY TRIGGER EXAMPLES THROUGHOUT THE EARLIER SECTIONS OF THIS CHAPTER
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/NE VERY USEFUL EXTENSION PROVIDED BY THE STANDARD IS THE 7(%. CLAUSE THAT CAN BE SPECIFIED AS PART OF A TRIGGERED ACTION 4HE 7(%. CLAUSE IS OPTIONAL AND IT OPERATES LIKE A 7(%2% CLAUSE FOR DETERMINING WHETHER A TRIGGERED ACTION WILL BE CARRIED OUT 7HEN THE $"-3 EXECUTES THE PARTICULAR TYPE OF STATEMENT SPECIFIED IN THE TRIGGER DEFINITION IT EVALUATES THE SEARCH CONDITION SPECIFIED IN THE 7(%. CLAUSE 4HE FORM OF THE SEARCH CONDITION IS EXACTLY LIKE THE SEARCH CONDITION IN A 7(%2% CLAUSE AND IT WILL PRODUCE EITHER A 425% OR &!,3% RESULT 4HE TRIGGERED ACTION IS CARRIED OUT ONLY IF THE RESULT IS 425% 4O PROVIDE SECURITY FOR TRIGGERS THE 31, STANDARD ESTABLISHES A NEW 42)''%2 PRIVILEGE THAT MAY BE GRANTED FOR SPECIFIC TABLES TO SPECIFIC USERS 7ITH THIS PRIVILEGE A USER MAY ESTABLISH A TRIGGER ON THE TABLE 4HE OWNER OF A TABLE IS ALWAYS ALLOWED TO ESTABLISH TRIGGERS ON THE TABLE
3UMMARY 3TORED PROCEDURES AND TRIGGERS ARE TWO VERY USEFUL CAPABILITIES FOR 31, DATABASES USED IN TRANSACTION PROCESSING APPLICATIONS s 3TORED PROCEDURES ALLOW YOU TO PREDEFINE COMMON DATABASE OPERATIONS AND INVOKE THEM SIMPLY BY CALLING THE STORED PROCEDURE FOR IMPROVED EFFICIENCY AND LESS CHANCE OF ERROR s %XTENSIONS TO THE BASIC 31, LANGUAGE GIVE STORED PROCEDURES THE FEATURES NORMALLY FOUND IN PROGRAMMING LANGUAGES 4HESE FEATURES INCLUDE LOCAL VARIABLES CONDITIONAL PROCESSING BRANCHING AND SPECIAL STATEMENTS FOR ROW BY ROW QUERY RESULTS PROCESSING s 3TORED FUNCTIONS ARE A SPECIAL FORM OF STORED PROCEDURE THAT RETURN A SINGLE VALUE OR IN SOME IMPLEMENTATIONS A SINGLE OBJECT OR 8-, DOCUMENT s 4RIGGERS ARE PROCEDURES WHOSE EXECUTION IS AUTOMATICALLY INITIATED BASED ON ATTEMPTED MODIFICATIONS TO A TABLE ! TRIGGER CAN BE FIRED BY AN ).3%24 $%,%4% OR 50$!4% STATEMENT FOR THE TABLE OR IN SOME IMPLEMENTATIONS A SYSTEM EVENT s 4HE SPECIFIC 31, DIALECTS USED BY THE MAJOR $"-3 BRANDS TO SUPPORT STORED PROCEDURES AND TRIGGERS VARY WIDELY s 4HERE IS NOW AN INTERNATIONAL STANDARD FOR STORED PROCEDURES FUNCTIONS AND TRIGGERS !S ONE OF THE NEWER STANDARDS IT HAS NOT YET HAD A MAJOR IMPACT ON IMPLEMENTATION BY LEADING $"-3 VENDORS
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NE OF THE MOST IMPORTANT APPLICATIONS OF 31, AND RELATIONAL DATABASE TECHNOLOGY TODAY IS THE RAPIDLY GROWING AREA OF DATA WAREHOUSING AND BUSINESS INTELLIGENCE 4HE FOCUS OF DATA WAREHOUSING IS TO USE ACCUMULATED DATA TO PROVIDE INFORMATION AND INSIGHTS FOR DECISION MAKING 7ITH THE RISING POPULARITY OF THE )NTERNET AND THE DIRECT INTERACTION WITH CUSTOMERS THAT IT PROVIDES THE AMOUNT OF DATA AVAILABLE ABOUT CUSTOMER BEHAVIOR REFLECTED IN THEIR CLICK BY CLICK JOURNEY THROUGH WEB PAGES HAS LITERALLY EXPLODED $ATA WAREHOUSING TREATS THIS DATA AS A VALUABLE ASSET TO BE TRANSLATED THROUGH ANALYSIS INTO COMPETITIVE ADVANTAGE 4HE COMPLEMENTARY PROCESS OF DATA MINING INVOLVES IN DEPTH ANALYSIS OF HISTORICAL AND TREND DATA TO FIND VALUABLE INSIGHTS ABOUT CUSTOMER BEHAVIOR AND CROSS DEPENDENCIES 31, BASED RELATIONAL DATABASES ARE A KEY TECHNOLOGY UNDERLYING DATA WAREHOUSING APPLICATIONS "USINESS INTELLIGENCE APPLICATIONS HAVE EXPLODED IN POPULARITY OVER THE LAST TWO DECADES AND CONTINUE TO GROW #ORPORATE )4 SURVEYS SHOW THAT THE MAJORITY OF LARGE CORPORATIONS HAVE SOME TYPE OF BUSINESS ANALYSIS OR DATA WAREHOUSING PROJECTS UNDER WAY )N MANY WAYS DATA WAREHOUSING REPRESENTS RELATIONAL DATABASES COMING FULL CIRCLE BACK TO THEIR ROOTS 7HEN RELATIONAL DATABASES FIRST APPEARED ON THE SCENE THE ESTABLISHED DATABASES SUCH AS )"-S HIERARCHICAL )-3 DATABASE WERE SQUARELY FOCUSED ON BUSINESS TRANSACTION PROCESSING APPLICATIONS 2ELATIONAL TECHNOLOGY GAINED POPULARITY BY FOCUSING ON DECISION SUPPORT APPLICATIONS AND THEIR AD HOC QUERIES !S THE POPULARITY OF THESE APPLICATIONS GREW MOST RELATIONAL DATABASE VENDORS SHIFTED THEIR FOCUS TO COMPETE FOR NEW TRANSACTION PROCESSING APPLICATIONS 7ITH DATA WAREHOUSING ATTENTION HAS TURNED BACK TO WHAT WAS FORMERLY CALLED DECISION SUPPORT ALBEIT WITH NEW TERMINOLOGY AND MUCH MORE POWERFUL TOOLS THAN IN THOSE OF EARLIER YEARS
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$ATAõ7AREHOUSINGõ#ONCEPTS /NE OF THE FOUNDATIONS OF DATA WAREHOUSING IS THE NOTION THAT DATABASES FOR TRANSACTION PROCESSING AND DATABASES FOR BUSINESS ANALYSIS SERVE VERY DIFFERENT NEEDS 4HE CORE FOCUS OF AN ONLINE TRANSACTION PROCESSING /,40 DATABASE IS TO SUPPORT THE BASIC DAY TO DAY FUNCTIONS OF AN ORGANIZATION )N A MANUFACTURING COMPANY /,40 DATABASES SUPPORT THE TAKING OF CUSTOMER ORDERS ORDERING OF RAW MATERIALS MANAGEMENT OF INVENTORY BILLING OF CUSTOMERS AND SIMILAR FUNCTIONS 4HEIR HEAVIEST USERS ARE THE APPLICATIONS USED BY ORDER PROCESSING CLERKS PRODUCTION WORKERS WAREHOUSE STAFF AND THE LIKE "Y CONTRAST THE CORE FOCUS OF A BUSINESS INTELLIGENCE ") DATABASE GIVEN THE NAME /NLINE !NALYTICAL 0ROCESSING /,!0 DATABASE BY % & #ODD IS TO SUPPORT BUSINESS DECISION MAKING THROUGH DATA ANALYSIS AND REPORTING )TS HEAVIEST USERS ARE TYPICALLY PRODUCT MANAGERS PRODUCTION PLANNERS AND MARKETING PROFESSIONALS 4ABLE HIGHLIGHTS THE SIGNIFICANT DIFFERENCES IN /,40 AND BUSINESS INTELLIGENCE APPLICATION PROFILES AND IN THE DATABASE WORKLOADS THEY PRODUCE ! TYPICAL ONLINE TRANSACTION PROCESSING OF A CUSTOMERS ORDER MIGHT INVOLVE THESE DATABASE ACCESSES s 2EAD A ROW OF THE CUSTOMER TABLE TO VERIFY THE PROPER CUSTOMER NUMBER s #HECK THE CREDIT LIMIT FOR THAT CUSTOMER s 2EAD A ROW OF THE INVENTORY TABLE TO VERIFY THAT A PRODUCT IS AVAILABLE s )NSERT A NEW ROW IN AN ORDER TABLE AND IN AN ORDER ITEMS TABLE TO RECORD THE CUSTOMERS ORDER s 5PDATE THE ROW OF THE INVENTORY TABLE TO REFLECT THE DECREASED QUANTITY AVAILABLE
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4HE WORKLOAD PRESENTS A LARGE VOLUME OF SHORT SIMPLE DATABASE REQUESTS THAT TYPICALLY READ WRITE OR UPDATE INDIVIDUAL ROWS AND THEN COMMIT A TRANSACTION 4HE SAME TYPE OF WORKLOAD IS PRESENTED BY ALL OF THE MOST FREQUENT TYPES OF TRANSACTIONS SUCH AS s 2ETRIEVING THE PRICE OF A PRODUCT s #HECKING THE QUANTITY OF PRODUCT AVAILABLE s $ELETING AN ORDER s 5PDATING A CUSTOMER ADDRESS s 2AISING A CUSTOMERS CREDIT LIMIT )N CONTRAST A TYPICAL BUSINESS ANALYSIS TRANSACTION GENERATING AN ORDER ANALYSIS REPORT MIGHT INVOLVE THESE DATABASE ACCESSES s *OIN INFORMATION FROM THE ORDERS ORDER ITEMS PRODUCTS AND CUSTOMERS TABLES s 3UMMARIZE THE DETAIL FROM THE ORDERS TABLE BY PRODUCT IN A SUMMARY QUERY s #OMPUTE THE TOTAL ORDER QUANTITIES FOR EACH PRODUCT s 3ORT THE RESULTING INFORMATION BY CUSTOMER 4HIS WORKLOAD PRESENTS A SINGLE LONG RUNNING QUERY THAT IS READ INTENSIVE )T PROCESSES MANY ROWS OF THE DATABASE IN THIS CASE EVERY ORDER ITEM AND INVOLVES COMPUTING TOTALS AND AVERAGES AND SUMMARIZING DATA 4HESE CHARACTERISTICS ARE TYPICAL OF ALMOST ALL BUSINESS ANALYSIS QUERIES SUCH AS s 7HICH REGIONS HAD THE BEST PERFORMANCE LAST QUARTER s (OW DID SALES BY PRODUCT LAST QUARTER COMPARE WITH LAST YEAR s 7HAT IS THE TREND LINE FOR A PARTICULAR PRODUCTS SALES s 7HICH CUSTOMERS ARE BUYING THE HIGHEST GROWTH PRODUCTS s 7HICH CHARACTERISTICS DO THOSE CUSTOMERS SHARE 4HE DIFFERENCE BETWEEN THE BUSINESS INTELLIGENCE AND THE /,40 WORKLOADS IS SUBSTANTIAL AND MAKES IT DIFFICULT OR IMPOSSIBLE FOR A SINGLE $"-3 TO SERVE BOTH TYPES OF APPLICATIONS
#OMPONENTSõOFõAõ$ATAõ7AREHOUSE &IGURE SHOWS THE ARCHITECTURE OF A DATA WAREHOUSING ENVIRONMENT )T HAS THREE TYPICAL KEY COMPONENTS
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s 7AREHOUSE LOADING TOOLS ! SUITE OF PROGRAMS THAT EXTRACT DATA FROM CORPORATE TRANSACTION PROCESSING SYSTEMS RELATIONAL DATABASES MAINFRAME AND MINICOMPUTER FILES LEGACY DATABASES PROCESS THE DATA AND LOAD IT INTO THE WAREHOUSE 4HIS PROCESS TYPICALLY INVOLVES SUBSTANTIAL CLEANUP OF THE TRANSACTION DATA FILTERING IT REFORMATTING IT AND LOADING IT ON A BULK BASIS INTO THE WAREHOUSE ! COMMON TERM USED FOR THESE TOOLS AND PROCESSES IS EXTRACT TRANSFORM AND LOAD %4,
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s ! WAREHOUSE DATABASE ! RELATIONAL DATABASE OPTIMIZED FOR STORING VAST QUANTITIES OF DATA BULK LOADING DATA AT HIGH SPEEDS AND SUPPORTING COMPLEX BUSINESS ANALYSIS QUERIES s $ATA ANALYSIS TOOLS ! SUITE OF PROGRAMS FOR PERFORMING STATISTICAL AND TIME SERIES ANALYSIS DOING hWHAT IFv ANALYSIS AND PRESENTING THE RESULTS IN TEXTUAL ANDOR GRAPHICAL FORM 6ENDORS IN THE DATA WAREHOUSING MARKET HAVE TENDED TO CONCENTRATE ON ONE OF THESE COMPONENT AREAS 3EVERAL VENDORS BUILD PRODUCT SUITES THAT FOCUS ON THE WAREHOUSE LOADING PROCESS AND CHALLENGES /THER VENDORS HAVE FOCUSED ON DATA ANALYSIS 3OME VENDORS HAVE CONSOLIDATED TO COVER BOTH THESE AREAS BUT BOTH AREAS REMAIN THE FOCUS FOR INDIVIDUAL INDEPENDENT SOFTWARE COMPANIES INCLUDING SEVERAL WHOSE REVENUES ARE IN THE MILLION RANGE 3PECIALIZED WAREHOUSE DATABASES WERE ALSO THE TARGET OF SEVERAL STARTUP COMPANIES EARLY IN THE DATA WAREHOUSING MARKET /VER TIME THE MAJOR ENTERPRISE $"-3 VENDORS ALSO MOVED TO ADDRESS THIS AREA 3OME DEVELOPED THEIR OWN SPECIALIZED WAREHOUSE DATABASES OTHERS ADDED WAREHOUSE DATABASES TO THEIR PRODUCT LINE BY ACQUIRING SMALLER COMPANIES THAT PRODUCED THEM 4ODAY THE DATABASE COMPONENT SHOWN IN &IGURE IS ALMOST ALWAYS A SPECIALIZED 31, BASED WAREHOUSE $"-3 SUPPLIED BY ONE OF THE MAJOR ENTERPRISE DATABASE VENDORS
4HEõ%VOLUTIONõOFõ$ATAõ7AREHOUSING 4HE INITIAL FOCUS OF DATA WAREHOUSING WAS THE CREATION OF HUGE ENTERPRISEWIDE COLLECTIONS OF ALL OF THE ENTERPRISES ACCUMULATED DATA "Y CREATING SUCH A WAREHOUSE OF DATA ALMOST ANY POSSIBLE QUESTION ABOUT HISTORICAL BUSINESS PRACTICES COULD BE POSED -ANY COMPANIES STARTED DOWN THE ROAD TO CREATING WAREHOUSES WITH THIS APPROACH BUT SUCCESS RATES WERE LOW ,ARGE ENTERPRISEWIDE WAREHOUSES GENERALLY PROVED TOO DIFFICULT TO CREATE TOO BIG TOO EXPENSIVE AND TOO UNWIELDY TO USE
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4HE FOCUS EVENTUALLY TURNED TO SMALLER DATA WAREHOUSES FOCUSED ON SPECIFIC AREAS OF A BUSINESS THAT COULD MOST BENEFIT FROM IN DEPTH DATA ANALYSIS 4HE TERM DATA MART WAS COINED TO DESCRIBE THESE SMALLER BUT STILL OFTEN MASSIVE DATA WAREHOUSES 7ITH THE ADVENT OF MULTIPLE DATA MARTS WITHIN ENTERPRISES A RECENT AREA OF FOCUS HAS BEEN ON MANAGEMENT OF DISTRIBUTED DATA MARTS )N PARTICULAR THERE IS A LARGE POTENTIAL FOR DUPLICATION OF EFFORT IN THE DATA CLEANSING AND REFORMATTING PROCESS WHEN MULTIPLE MARTS ARE DRAWING DATA FROM THE SAME PRODUCTION DATABASES /NE EMERGING ANSWER SEEMS TO BE A COORDINATED APPROACH TO DATA TRANSFORMATION FOR DISTRIBUTED MARTS RATHER THAN A RETURN TO HUGE CENTRALIZED WAREHOUSES !NOTHER APPROACH IS TO LEAVE THE DATA IN PLACE IN /,40 DATABASES AND FORM DATA MARTS ON DEMAND THROUGH USE OF A MIDDLEWARE TOOL THAT MAKES THE DATA IN MULTIPLE DATABASES APPEAR AS IF IT IS ALL IN ONE HUGE FEDERATED DATABASE WHICH CAN BE THOUGHT OF AS A VIRTUAL DATA WAREHOUSE )N THIS ARCHITECTURE KNOWN AS ENTERPRISE INFORMATION INTEGRATION %)) THE MIDDLEWARE TOOL REPLICATES EACH QUERY ACROSS ALL THE SUPPORTED PHYSICAL DATABASES AND CONSOLIDATES THE RESULTS BEFORE RETURNING THEM TO THE USER WHO SUBMITTED THE ORIGINAL QUERY $ATA WAREHOUSING AND MORE RECENTLY DATA MARTS HAVE GROWN TO PROMINENCE IN MANY DIFFERENT INDUSTRIES 4HEY ARE MOST WIDELY AND AGGRESSIVELY USED IN INDUSTRIES WHERE BETTER INFORMATION ABOUT BUSINESS TRENDS CAN BE USED TO MAKE DECISIONS THAT SAVE OR GENERATE LARGE AMOUNTS OF MONEY &OR EXAMPLE s (IGH VOLUME MANUFACTURING !NALYSIS OF CUSTOMER PURCHASE TRENDS SEASONALITY AND SO ON CAN HELP THE COMPANY PLAN ITS PRODUCTION AND LOWER ITS INVENTORY LEVELS SAVING MONEY FOR OTHER PURPOSES s 0ACKAGED GOODS !NALYSIS OF PROMOTIONS COUPONS ADVERTISING CAMPAIGNS DIRECT MAIL ETC AND THE RESPONSE OF CONSUMERS WITH DIFFERENT DEMOGRAPHICS CAN HELP TO DETERMINE THE MOST EFFECTIVE WAY TO REACH PROSPECTIVE CUSTOMERS SAVING MILLIONS OF DOLLARS IN ADVERTISING AND PROMOTION COSTS s 4ELECOMMUNICATIONS !NALYSIS OF CUSTOMER CALLING PATTERNS CAN HELP TO CREATE MORE ATTRACTIVE PRICING AND PROMOTIONAL PLANS PERHAPS ATTRACTING NEW CUSTOMERS FROM A COMPETITOR s !IRLINES !NALYSIS OF CUSTOMER TRAVEL PATTERNS IS CRITICAL TO YIELD MANAGEMENT THE PROCESS OF SETTING AIRFARES AND ASSOCIATED RESTRICTIONS ON AVAILABLE AIRLINE SEATS TO MAXIMIZE PROFITABILITY s &INANCIAL SERVICES !NALYSIS OF CUSTOMER CREDIT FACTORS AND COMPARING THEM WITH HISTORICAL CUSTOMER PROFILES CAN HELP TO MAKE BETTER DECISIONS ABOUT WHICH CUSTOMERS ARE CREDITWORTHY
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4HE STRUCTURE SCHEMA OF A WAREHOUSE DATABASE IS TYPICALLY DESIGNED TO MAKE THE INFORMATION EASY TO ANALYZE SINCE THAT IS THE MAJOR FOCUS OF ITS USE 4HE STRUCTURE MUST MAKE IT EASY TO SLICE AND DICE THE DATA ALONG VARIOUS DIMENSIONS &OR EXAMPLE ONE DAY A BUSINESS ANALYST MAY WANT TO LOOK AT SALES BY PRODUCT CATEGORY BY REGION TO COMPARE THE PERFORMANCE OF DIFFERENT PRODUCTS IN DIFFERENT AREAS OF THE COUNTRY 4HE NEXT DAY THE SAME ANALYST MAY WANT TO LOOK AT SALES TRENDS OVER TIME BY REGION TO SEE WHICH REGIONS ARE GROWING AND WHICH ARE NOT 4HE STRUCTURE OF THE DATABASE MUST LEND ITSELF TO THIS TYPE OF ANALYSIS ALONG SEVERAL DIFFERENT DIMENSIONS
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&ACTõ#UBES )N MOST CASES THE DATA STORED IN A WAREHOUSE CAN BE ACCURATELY MODELED AS AN . DIMENSIONAL CUBE . CUBE OF HISTORICAL BUSINESS FACTS ! SIMPLE THREE DIMENSIONAL $ CUBE OF SALES DATA IS SHOWN IN &IGURE TO ILLUSTRATE THE STRUCTURE 4HE FACT IN EACH CELL OF THE CUBE IS A DOLLAR SALES AMOUNT !LONG ONE EDGE OF THE CUBE ONE OF THE DIMENSIONS IS THE MONTH DURING WHICH THE SALES TOOK PLACE !NOTHER DIMENSION IS THE REGION WHERE THE SALES OCCURRED 4HE THIRD DIMENSION IS THE TYPE OF PRODUCT THAT WAS SOLD %ACH CELL IN THE CUBE REPRESENTS THE SALES FOR ONE COMBINATION OF THESE THREE DIMENSIONS 4HE AMOUNT IN THE UPPER LEFT FRONT CELL REPRESENTS THE SALES AMOUNT FOR *ANUARY FOR CLOTHING IN THE %AST REGION &IGURE SHOWS A SIMPLE $ CUBE BUT MANY WAREHOUSING APPLICATIONS WILL HAVE A DOZEN DIMENSIONS OR MORE !LTHOUGH A $ CUBE IS DIFFICULT TO VISUALIZE THE PRINCIPLES ARE THE SAME AS FOR THE $ EXAMPLE %ACH DIMENSION REPRESENTS SOME VARIABLE ON WHICH THE DATA MAY BE ANALYZED %ACH COMBINATION OF DIMENSION VALUES HAS ONE ASSOCIATED FACT VALUE WHICH IS USUALLY THE HISTORICAL BUSINESS RESULT OBTAINED FOR THAT COLLECTION OF DIMENSION VALUES 4O ILLUSTRATE THE DATABASE STRUCTURES TYPICALLY USED IN WAREHOUSING APPLICATIONS WE USE A WAREHOUSE THAT MIGHT BE FOUND IN A DISTRIBUTION COMPANY 4HROUGH THE EFFORTS OF ITS SALES FORCE THE COMPANY DISTRIBUTES DIFFERENT TYPES OF PRODUCTS MADE BY VARIOUS SUPPLIERS TO SEVERAL HUNDRED CUSTOMERS LOCATED IN VARIOUS REGIONS OF THE COUNTRY 4HE COMPANY WANTS TO ANALYZE HISTORICAL SALES DATA ALONG THESE DIMENSIONS TO DISCOVER TRENDS AND GAIN INSIGHTS THAT WILL HELP IT BETTER MANAGE ITS BUSINESS 4HE UNDERLYING MODEL FOR THIS ANALYSIS WILL BE A $ FACT CUBE WITH THESE DIMENSIONS s #ATEGORY 4HE CATEGORY OF PRODUCT THAT WAS SOLD WITH VALUES SUCH AS CLOTHING LINENS ACCESSORIES AND SHOES 4HE WAREHOUSE HAS ABOUT TWO DOZEN PRODUCT CATEGORIES s 3UPPLIER 4HE SUPPLIER WHO MANUFACTURES THE PARTICULAR PRODUCT SOLD 4HE COMPANY MIGHT DISTRIBUTE PRODUCTS FROM DIFFERENT SUPPLIERS s #USTOMER 4HE CUSTOMER WHO PURCHASED THE PRODUCTS 4HE COMPANY HAS SEVERAL HUNDRED CUSTOMERS 3OME OF THE LARGER CUSTOMERS PURCHASE PRODUCTS CENTRALLY AND ARE SERVICED BY A SINGLE SALESPERSON OTHERS PURCHASE ON A LOCAL BASIS AND ARE SERVED BY LOCAL SALESPEOPLE
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s 2EGION 4HE REGION OF THE COUNTRY WHERE THE PRODUCTS WERE SOLD 3OME OF THE COMPANYS CUSTOMERS OPERATE IN ONLY ONE REGION OF THE COUNTRY OTHERS OPERATE IN TWO OR MORE REGIONS s -ONTH 4HE MONTH WHEN THE PRODUCTS WERE SOLD &OR COMPARISON PURPOSES THE COMPANY HAS DECIDED TO MAINTAIN MONTHS THREE YEARS OF HISTORICAL SALES DATA IN THE WAREHOUSE 7ITH THESE CHARACTERISTICS EACH OF THE FIVE DIMENSIONS IS RELATIVELY INDEPENDENT OF THE OTHERS 3ALES TO A PARTICULAR CUSTOMER MAY BE CONCENTRATED IN A SINGLE REGION OR IN MULTIPLE REGIONS ! SPECIFIC CATEGORY OF PRODUCT MAY BE SUPPLIED BY ONE OR MANY DIFFERENT SUPPLIERS 4HE FACT IN EACH CELL OF THE $ CUBE IS THE SALES AMOUNT FOR THAT PARTICULAR COMBINATION OF DIMENSION VALUES 7ITH THE ATTRIBUTES JUST DESCRIBED THE FACT CUBE CONTAINS OVER MILLION CELLS CATEGORIES ¾ SUPPLIERS ¾ CUSTOMERS ¾ REGIONS ¾ MONTHS
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)N MOST DATA WAREHOUSES THE MOST EFFECTIVE WAY TO MODEL THE . DIMENSIONAL FACT CUBE IS WITH A STAR SCHEMA ! STAR SCHEMA FOR THE DISTRIBUTOR WAREHOUSE IN THE PREVIOUS EXAMPLE IS SHOWN IN &IGURE %ACH DIMENSION OF THE CUBE IS REPRESENTED BY A DIMENSION TABLE &IVE OF THEM ARE IN THE FIGURE #!4%'/2)%3 3500,)%23 #534/-%23 2%')/.3 AND -/.4(3 /NE ROW IN EACH DIMENSION TABLE IS FOR EACH POSSIBLE VALUE OF THAT DIMENSION 4HE -/.4(3 TABLE HAS ROWS ONE FOR EACH MONTH OF SALES HISTORY BEING STORED 4HREE REGIONS PRODUCE A THREE ROW 2%')/.3 TABLE $IMENSION TABLES IN A STAR SCHEMA OFTEN CONTAIN COLUMNS WITH DESCRIPTIVE TEXT INFORMATION OR OTHER ATTRIBUTES ASSOCIATED WITH THAT DIMENSION SUCH AS THE NAME OF THE BUYER FOR A CUSTOMER OR THE CUSTOMERS ADDRESS AND PHONE NUMBER OR THE PURCHASING TERMS FOR A SUPPLIER 4HESE COLUMNS MAY BE DISPLAYED IN REPORTS GENERATED FROM THE DATABASE ! DIMENSION TABLE ALWAYS HAS ONE OR MORE COLUMNS THAT CONTAIN NATURAL IDENTIFIERS FOR THE DIMENSION SUCH AS A REGION CODE A MONTH AND YEAR AN AIRPORT CODE OR A CLOTHING SIZE (OWEVER THOSE NATURAL IDENTIFIERS ARE SELDOM USED AS THE PRIMARY KEY OF THE DIMENSION TABLE BECAUSE THE NATURAL IDENTIFIERS MAY CHANGE OVER TIME A PHENOMENON KNOWN AS SLOWLY CHANGING DIMENSIONS 4O AVOID CHANGES IN PRIMARY KEY VALUES PLAYING HAVOC WITH HISTORICAL ROWS IN THE FACT TABLE IT IS COMMON TO USE ARBITRARY NUMBERS THAT HAVE NO BUSINESS MEANING KNOWN AS SURROGATE KEYS AS PRIMARY KEYS IN ALL FACT TABLES 3URROGATE KEYS ALSO SIMPLIFY THE FOREIGN KEYS BECAUSE EACH REQUIRES ONLY ONE COLUMN 7ITHOUT A SURROGATE KEY FOR THE -/.4(3 DIMENSION TABLE ITS FOREIGN KEY IN THE FACT TABLE WOULD REQUIRE TWO COLUMNS ONE FOR THE MONTH AND THE OTHER FOR THE YEAR )N THE SAMPLE WAREHOUSE OF &IGURE WE USE SURROGATE KEYS IN ALL THE TABLES BUT NOTE THAT THE NATURAL IDENTIFIERS ARE ALSO INCLUDED IN THE DIMENSION TABLES &OR EXAMPLE NOTE THE REGION NAMES IN 2%')/.3 %AST 7EST ETC AND THE CATEGORY NAMES IN #!4%'/2)%3 #LOTHING 3HOES ETC 4HE LARGEST TABLE IN THE DATABASE IS THE FACT TABLE IN THE CENTER OF THE SCHEMA 4HIS TABLE IS NAMED 3!,%3 IN &IGURE 4HE FACT TABLE CONTAINS A COLUMN WITH THE DATA VALUES THAT APPEAR IN THE CELLS OF THE . CUBE IN &IGURE )N ADDITION THE FACT TABLE CONTAINS A COLUMN THAT FORMS THE FOREIGN KEY FOR EACH OF THE DIMENSION TABLES 4HE FOREIGN KEYS LINK THE ROW TO THE CORRESPONDING DIMENSION TABLE ROWS FOR ITS POSITION IN THE CUBE 4HIS EXAMPLE HAS FIVE SUCH FOREIGN KEY COLUMNS 7ITH THIS STRUCTURE EACH ROW REPRESENTS THE DATA FOR ONE CELL OF THE . CUBE
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(OWEVER A SINGLE CUBE CAN ONLY SHOW THREE DIMENSIONS 4O HANDLE ADDITIONAL DIMENSIONS YOU HAVE TO VISUALIZE ADDITIONAL CUBES 4HE . CUBE IN &IGURE SHOWS THE 2%')/.3 #!4%'/2)%3 AND -/.4(3 DIMENSIONS 4O REPRESENT THE 3500,)%23 DIMENSION THE . CUBE NEEDS TO BE REPLICATED TIMES ONCE FOR EACH POSSIBLE SUPPLIER &URTHERMORE TO REPRESENT THE #534/-%23 DIMENSION WE NEED TO REPLICATE THOSE CUBES TIMES ONE FOR EACH POSSIBLE CUSTOMER CUBES IN ALL &ORTUNATELY SOME MULTIDIMENSIONAL $"-3S CAN PRESENT CUBES FOR ANALYSIS WITHOUT NEEDING TO PHYSICALLY STORE EACH CUBE THAT MIGHT BE REQUIRED FOR PRESENTATION 4HE FACT TABLE TYPICALLY CONTAINS ONLY A FEW COLUMNS BUT MANY ROWSTENS OR HUNDREDS OF MILLIONS OR EVEN BILLIONS OF ROWSARE NOT UNUSUAL IN A PRODUCTION DATA WAREHOUSE 4HE FACT COLUMN ALMOST ALWAYS CONTAINS NUMERIC VALUES THAT CAN BE ACCUMULATED SUCH AS CURRENCY AMOUNTS UNITS SHIPPED OR RECEIVED OR POUNDS PROCESSED 6IRTUALLY ALL REPORTS FROM THE WAREHOUSE INVOLVE SUMMARY DATATOTALS AVERAGES HIGH OR LOW VALUES PERCENTAGESBASED ON ARITHMETIC COMPUTATIONS ON THIS NUMERIC VALUE
#HAPTERçç
31,çANDç$ATAç7AREHOUSINGç
4HE SCHEMA STRUCTURE OF &IGURE IS CALLED A STAR SCHEMA FOR OBVIOUS REASONS 4HE FACT TABLE IS AT THE CENTER OF A STAR OF DATA RELATIONSHIPS 4HE DIMENSION TABLES FORM THE POINTS OF THE STAR 4HE RELATIONSHIPS CREATED BY THE FOREIGN KEYS IN THE FACT TABLE CONNECT THE CENTER TO THE POINTS 7ITH THE STAR SCHEMA STRUCTURE MOST BUSINESS ANALYSIS QUESTIONS TURN INTO QUERIES THAT JOIN THE CENTRAL FACT TABLE WITH ONE OR MORE DIMENSION TABLES (ERE ARE SOME EXAMPLES 3HOW THE TOTAL SALES FOR CLOTHING IN *ANUARY BY REGION 3%,%#4 3!,%3?!-/5.4 2%')/. &2/- 3!,%3 2%')/.3 7(%2% -/.4( g*ANUARYg !.$ 9%!2 !.$ 02/$?490% g#LOTHINGg !.$ 3!,%32%')/. 2%')/.32%')/. /2$%2 "9 2%')/.
3HOW THE AVERAGE SALES FOR EACH #534/-%2 BY 3500,)%2 FOR EACH MONTH 3%,%#4 !6'3!,%3?!-/5.4 #534?.!-% 3500?.!-% -/.4( 9%!2 &2/- 3!,%3 #534/-%23 3500,)%23 7(%2% 3!,%3#534?#/$% #534/-%23#534?#/$% !.$ 3!,%33500?#/$% 3500,)%233500?#/$% '2/50 "9 #534?.!-% 3500?.!-% -/.4( 9%!2 /2$%2 "9 #534?.!-% 3500?.!-% -/.4( 9%!2
-ULTILEVELõ$IMENSIONS )N THE STAR SCHEMA STRUCTURE OF &IGURE EACH OF THE DIMENSIONS HAS ONLY ONE LEVEL )N PRACTICE MULTILEVEL DIMENSIONS ARE QUITE COMMON &OR EXAMPLE s 3ALES DATA MAY IN FACT BE ACCUMULATED FOR EACH SALES OFFICE %ACH OFFICE IS A PART OF A SALES DISTRICT AND EACH DISTRICT IS A PART OF A SALES REGION s 3ALES DATA IS ACCUMULATED BY MONTH BUT IT MAY ALSO BE USEFUL TO LOOK AT QUARTERLY SALES RESULTS %ACH MONTH IS A PART OF A PARTICULAR QUARTER s 3ALES DATA MAY BE ACCUMULATED FOR INDIVIDUAL PRODUCTS ORDERED AND THE PRODUCTS ARE ASSOCIATED WITH A PARTICULAR SUPPLIER -ULTILEVEL DIMENSIONS SUCH AS THESE COMPLICATE THE BASIC STAR SCHEMA AND IN PRACTICE YOU CAN DEAL WITH THEM IN SEVERAL WAYS
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s !DDITIONAL DATA IN THE DIMENSION TABLES 4HE GEOGRAPHIC DIMENSION TABLE 2%')/.3 MIGHT CONTAIN INFORMATION ABOUT INDIVIDUAL OFFICES BUT ALSO INCLUDE COLUMNS INDICATING THE DISTRICT AND REGION TO WHICH THE OFFICE BELONGS !GGREGATE DATA FOR THESE HIGHER LEVELS OF THE GEOGRAPHIC DIMENSION CAN THEN BE OBTAINED BY SUMMARY QUERIES THAT JOIN THE FACT TABLE TO THE DIMENSION TABLE AND CAN BE FILTERED BASED ON THE DISTRICT OR REGION COLUMNS 4HIS APPROACH IS CONCEPTUALLY SIMPLE BUT IT MEANS THAT ALL AGGREGATE SUMMARY DATA MUST BE CALCULATED QUERY BY QUERY 4HIS LIKELY PRODUCES UNACCEPTABLY POOR PERFORMANCE
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s -ULTIPLE LEVELS WITHIN THE DIMENSION TABLES 4HE GEOGRAPHIC DIMENSION TABLE MIGHT BE EXTENDED TO INCLUDE ROWS FOR OFFICES DISTRICTS AND REGIONS 2OWS CONTAINING SUMMARY TOTAL DATA FOR THESE HIGHER LEVEL DIMENSIONS ARE ADDED TO THE FACT TABLE WHEN IT IS UPDATED 4HIS SOLVES THE RUNTIME QUERY PERFORMANCE PROBLEM BY PRECALCULATING AGGREGATE SUMMARY DATA (OWEVER IT COMPLICATES THE QUERIES CONSIDERABLY "ECAUSE EVERY SALE IS NOW INCLUDED IN THREE SEPARATE FACT TABLE ROWS ONE EACH FOR OFFICE DISTRICT AND REGION ANY TOTALS MUST BE COMPUTED VERY CAREFULLY 3PECIFICALLY THE FACT TABLE MUST USUALLY CONTAIN A LEVEL COLUMN TO INDICATE THE LEVEL OF DATA SUMMARIZATION PROVIDED BY THAT ROW AND EVERY QUERY THAT COMPUTES TOTALS OR OTHER STATISTICS MUST INCLUDE A SEARCH CONDITION THAT RESTRICTS IT TO ROWS AT ONLY A SPECIFIC LEVEL s 0RECOMPUTED SUMMARIES IN THE DIMENSION TABLES )NSTEAD OF COMPLICATING THE FACT TABLE SUMMARY DATA COULD BE PRECOMPUTED AND STORED IN THE DIMENSION TABLES FOR EXAMPLE SUMMARY SALES FOR A DISTRICT COULD BE STORED IN THE DISTRICTS ROW OF THE GEOGRAPHIC DIMENSION TABLE 4HIS SOLVES THE DUPLICATE FACTS PROBLEM OF THE PREVIOUS SOLUTION BUT IT WORKS ONLY FOR VERY SIMPLE PRECOMPUTED AMOUNTS 4HE PRECALCULATED TOTALS DONT HELP WITH QUERIES ABOUT PRODUCTS BY DISTRICT OR ABOUT DISTRICT RESULTS BY MONTH FOR EXAMPLE WITHOUT FURTHER COMPLICATING THE DIMENSION TABLES s -ULTIPLE FACT TABLES AT DIFFERENT LEVELS )NSTEAD OF COMPLICATING THE FACT TABLE THIS APPROACH CREATES MULTIPLE FACT TABLES FOR DIFFERENT LEVELS OF SUMMARY DATA 4O SUPPORT CROSS DIMENSION QUERIES FOR EXAMPLE DISTRICTnRESULTSnBY MONTH SPECIALIZED FACT TABLES THAT SUMMARIZE DATA ON THIS BASIS ARE NEEDED 4HE RESULTING PATTERN OF DIMENSION TABLES AND FACT TABLES TENDS TO HAVE MANY INTERRELATIONSHIPS CREATING A PATTERN RESEMBLING A SNOWFLAKE HENCE THIS TYPE OF SCHEMA IS OFTEN REFERRED TO AS A SNOWFLAKE SCHEMA 4HIS APPROACH SOLVES THE RUNTIME PERFORMANCE PROBLEM AND ELIMINATES THE POSSIBILITY OF ERRONEOUS DATA FROM A SINGLE FACT TABLE BUT IT CAN ADD SIGNIFICANT COMPLEXITY TO THE WAREHOUSE DATABASE DESIGN MAKING IT HARDER TO UNDERSTAND &URTHERMORE MANY OF THE POPULAR DATA ANALYSIS TOOLS CANNOT HANDLE SNOWFLAKE SCHEMAS )N PRACTICE FINDING THE RIGHT SCHEMA AND ARCHITECTURE FOR A PARTICULAR WAREHOUSE IS A COMPLICATED DECISION DRIVEN BY THE SPECIFICS OF THE FACTS AND DIMENSIONS THE TYPES OF QUERIES FREQUENTLY PERFORMED AND OTHER CONSIDERATIONS -ANY COMPANIES USE SPECIALIZED CONSULTANTS TO HELP THEM DESIGN DATA WAREHOUSES AND DEAL WITH EXACTLY THESE ISSUES
31,õ%XTENSIONSõFORõ$ATAõ7AREHOUSING 7ITH A STAR SCHEMA STRUCTURE A RELATIONAL DATABASE CONCEPTUALLY PROVIDES A GOOD FOUNDATION FOR MANAGING DATA FOR BUSINESS ANALYSIS 4HE CAPABILITY TO FREELY RELATE INFORMATION WITHIN THE DATABASE BASED SOLELY ON DATA VALUES IS A GOOD MATCH FOR THE AD HOC UNSTRUCTURED QUERIES THAT TYPIFY BUSINESS INTELLIGENCE APPLICATIONS "UT THERE ARE SOME SERIOUS MISMATCHES
#HAPTERçç
31,çANDç$ATAç7AREHOUSINGç
BETWEEN TYPICAL BUSINESS INTELLIGENCE QUERIES AND THE CAPABILITIES OF THE CORE 31, &OR EXAMPLE s $ATA ORDERING -ANY BUSINESS INTELLIGENCE QUERIES DEAL EXPLICITLY OR IMPLICITLY WITH DATA ORDERINGTHEY POSE QUESTIONS LIKE h7HAT IS THE TOP PERCENT v h7HAT ARE THE TOP v OR h7HICH ARE THE WORST PERFORMING v !S A SET ORIENTED LANGUAGE 31, MANIPULATES UNORDERED SETS OF ROWS 4HE ONLY SUPPORT FOR SORTING AND ORDERING DATA WITHIN STANDARD 31, IS THE /2$%2 "9 CLAUSE IN THE 3%,%#4 STATEMENT WHICH IS APPLIED ONLY AT THE END OF ALL OTHER SET ORIENTED PROCESSING s 4IME SERIES -ANY BUSINESS INTELLIGENCE QUERIES COMPARE VALUES BASED ON TIME CONTRASTING THIS YEARS RESULTS TO LAST YEARS OR THIS MONTHS RESULTS TO THE SAME MONTH LAST YEAR OR COMPUTING YEAR OVER YEAR GROWTH RATES FOR EXAMPLE )T IS VERY DIFFICULT AND SOMETIMES IMPOSSIBLE TO GET SIDE BY SIDE COMPARISONS OF DATA FROM DIFFERENT PERIODS WITHIN A SINGLE ROW OF STANDARD 31, QUERY RESULTS DEPENDING ON THE STRUCTURE OF THE UNDERLYING DATABASE s #OMPARISON TO AGGREGATE VALUES -ANY BUSINESS INTELLIGENCE QUERIES COMPARE VALUES FOR INDIVIDUAL ENTITIES FOR EXAMPLE OFFICE SALES RESULTS TO AN OVERALL TOTAL OR TO SUBTOTALS SUCH AS REGIONAL RESULTS 4HESE COMPARISONS ARE DIFFICULT TO EXPRESS IN STANDARD 31, ! REPORT FORMAT SHOWING LINE ITEM DETAIL SUBTOTALS AND TOTALS IS IMPOSSIBLE TO GENERATE DIRECTLY FROM 31, SINCE ALL ROWS OF QUERY RESULTS MUST HAVE THE SAME COLUMN STRUCTURE 4O DEAL WITH THESE ISSUES $"-3 PRODUCTS ON DATA WAREHOUSING HAVE TENDED TO EXTEND THE CORE 31, &OR EXAMPLE THE $"-3 FROM 2ED "RICK ONE OF THE DATA WAREHOUSING PIONEERS WHICH WAS SUBSEQUENTLY ACQUIRED BY )NFORMIX WHICH WAS IN TURN ACQUIRED BY )"- FEATURES THESE EXTENSIONS AS PART OF ITS 2ED "RICK )NTELLIGENT 31, 2)31, LANGUAGE s 2ANKING 3UPPORTS QUERIES THAT ASK FOR THE TOP AND SIMILAR REQUESTS s -OVING TOTALS AND AVERAGES 3UPPORTS QUERIES THAT SMOOTH RAW DATA FOR TIME SERIES ANALYSIS s 2UNNING TOTALS AND AVERAGES !LLOWS QUERY RESPONSES THAT SHOW RESULTS FOR INDIVIDUAL MONTHS PLUS YEAR TO DATE TOTALS AND SIMILAR REQUESTS s 2ATIOS !LLOWS QUERIES THAT SIMPLY EXPRESS THE RATIO OF INDIVIDUAL VALUES TO A TOTAL OR TO A SUBTOTAL WITHOUT THE USE OF COMPLEX SUBQUERIES s $ECODING 3IMPLIFIES THE TRANSLATION OF DIMENSION VALUE CODES LIKE THE SUPPLIER ID IN THE EXAMPLE WAREHOUSE INTO UNDERSTANDABLE NAMES s 3UBTOTALS !LLOW PRODUCTION OF QUERY RESULTS THAT COMBINE DETAILED AND SUMMARY DATA VALUES AT VARIOUS LEVELS OF SUMMARIZATION
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/THER WAREHOUSING VENDORS PROVIDE SIMILAR EXTENSIONS IN THEIR 31, IMPLEMENTATIONS OR PROVIDE THE SAME CAPABILITIES BUILT INTO THEIR DATA ANALYSIS PRODUCTS !S WITH EXTENSIONS IN OTHER AREAS OF THE 31, ALTHOUGH THE CONCEPTUAL CAPABILITIES PROVIDED BY SEVERAL DIFFERENT $"-3 BRANDS MAY BE SIMILAR THE SPECIFICS OF THE IMPLEMENTATION DIFFER SUBSTANTIALLY
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7AREHOUSEõ0ERFORMANCE 4HE PERFORMANCE OF A DATA WAREHOUSE IS ONE OF THE KEYS TO ITS USEFULNESS )F BUSINESS ANALYSIS QUERIES TAKE TOO LONG PEOPLE TEND NOT TO USE THE WAREHOUSE ON AN AD HOC BASIS FOR DECISION MAKING )F IT TAKES TOO LONG TO LOAD DATA INTO THE WAREHOUSE THE CORPORATE )NFORMATION 3YSTEMS )3 ORGANIZATION WILL PROBABLY RESIST FREQUENT UPDATES AND STALE DATA MAY MAKE THE WAREHOUSE LESS USEFUL !CHIEVING A GOOD BALANCE BETWEEN LOAD PERFORMANCE AND RUNTIME PERFORMANCE IS ONE OF THE KEYS TO SUCCESSFUL WAREHOUSE DEPLOYMENT
,OADõ0ERFORMANCE 4HE PROCESS OF LOADING A WAREHOUSE CAN BE VERY TIME CONSUMING )TS COMMON FOR WAREHOUSE DATA LOADS TO TAKE HOURS OR EVEN DAYS FOR VERY LARGE WAREHOUSES ,OAD PROCESSING TYPICALLY INVOLVES THESE OPERATIONS s $ATA EXTRACTION 4HE DATA TO BE LOADED INTO THE WAREHOUSE DATABASE TYPICALLY COMES FROM SEVERAL DIFFERENT OPERATIONAL DATA SOURCES 3OME MAY BE RELATIONAL DATABASES THAT SUPPORT /,40 APPLICATIONS s $ATA CLEANSING /PERATIONAL DATA TENDS TO BE hDIRTYv IN THE SENSE THAT IT CONTAINS SIGNIFICANT ERRORS &OR EXAMPLE OLDER TRANSACTION PROCESSING SYSTEMS MAY NOT HAVE STRONG INTEGRITY CHECKS PERMITTING THE ENTRY OF INCORRECT CUSTOMER NUMBERS OR PRODUCT NUMBERS 4HE WAREHOUSE LOADING PROCESS TYPICALLY INCLUDES DATA INTEGRITY AND DATA SANITY CHECKS s $ATA CROSS CHECKING )N MANY COMPANIES THE DATA PROCESSING SYSTEMS THAT SUPPORT VARIOUS BUSINESS OPERATIONS HAVE BEEN DEVELOPED AT DIFFERENT TIMES AND ARE NOT INTEGRATED #HANGES THAT ARE PROCESSED BY ONE SYSTEM FOR EXAMPLE ADDING NEW PRODUCT NUMBERS TO AN ORDER PROCESSING APPLICATION MAY NOT AUTOMATICALLY BE REFLECTED IN OTHER SYSTEMS FOR EXAMPLE THE INVENTORY CONTROL SYSTEM OR THERE MAY BE DELAYS IN PROPAGATING CHANGES 7HEN DATA FROM THESE NONINTEGRATED SYSTEMS ARRIVES AT THE WAREHOUSE IT MUST BE CHECKED FOR INTERNAL CONSISTENCY s $ATA REFORMATTING $ATA FORMATS IN THE OPERATIONAL DATA STORES MAY DIFFER CONSIDERABLY FROM THE WAREHOUSE DATABASE #HARACTER DATA MAY NEED TRANSFORMATION FROM A MAINFRAMES %"#$)# ENCODING TO !3#)) :ONED DECIMAL OR PACKED DECIMAL DATA MAY NEED REFORMATTING $ATE AND TIME FORMATS ARE ANOTHER SOURCE OF DIFFERENCES "EYOND THESE SIMPLE DATA FORMAT DIFFERENCES DATA FROM ONE /,40 DATA SOURCE ROW MAY HAVE TO BE BROKEN APART INTO MULTIPLE WAREHOUSE TABLES WHILE DATA FROM MULTIPLE /,40 TABLES OR FILES MAY HAVE TO BE COMBINED TO CREATE A WAREHOUSE TABLE s $ATA INSERTIONUPDATE !FTER THE PREPROCESSING ACTUAL BULK LOADING OF DATA INTO A WAREHOUSE DATABASE TENDS TO BE A SPECIALIZED OPERATION (IGH VOLUME DATA LOADERS TYPICALLY OPERATE IN A BATCH ORIENTED MODE WITHOUT TRANSACTION LOGIC AND WITH SPECIALIZED RECOVERY 2OW LOADING OR UPDATE RATES OF TENS OR HUNDREDS OF GIGABYTES PER HOUR MAY BE REQUIRED s )NDEX CREATIONUPDATE 4HE SPECIALIZED INDEXES USED BY THE WAREHOUSE MUST BE MODIFIED TO REFLECT THE REVISED WAREHOUSE CONTENTS !S WITH THE ACTUAL DATA INSERTION AND UPDATE SPECIALIZED HANDLING IS TYPICALLY APPLIED )N SOME CASES IT IS MORE EFFICIENT TO RAPIDLY RE CREATE AN ENTIRE INDEX THAN TO MODIFY IT INCREMENTALLY AS DATA ROWS ARE INSERTED OR UPDATED /THER INDEX STRUCTURES PERMIT MORE INCREMENTAL UPDATES
#HAPTERçç
31,çANDç$ATAç7AREHOUSINGç
4HESE TASKS ARE TYPICALLY PERFORMED BY SPECIALIZED WAREHOUSE BUILDING PROGRAMS ON A BATCH PROCESSING BASIS !D HOC QUERY ACCESS TO THE WAREHOUSE IS TURNED OFF DURING THE UPDATEREFRESH PROCESSING ALLOWING IT TO PROCEED AT MAXIMUM SPEED WITHOUT COMPETITION FOR $"-3 CYCLES $ESPITE THESE OPTIMIZATIONS WAREHOUSE LOAD TIMES TEND TO GROW AS THE AMOUNT OF ACCUMULATED DATA GROWS SO THE LOAD TIME VERSUS RUNTIME PERFORMANCE TRADE OFF MUST BE MADE ON AN ONGOING BASIS 7AREHOUSES WITH MANY INDEXES OR PRECOMPUTED SUMMARY VALUES MAY OFFER MUCH BETTER RUNTIME PERFORMANCE BUT AT THE EXPENSE OF UNACCEPTABLY LONG LOAD TIMES 3IMPLER STRUCTURES WITH LESS LOADING WORK MAY INCREASE THE TIME REQUIRED FOR AD HOC QUERIES BEYOND AN ACCEPTABLE LEVEL )N PRACTICE THE WAREHOUSE ADMINISTRATOR MUST FIND A GOOD BALANCE BETWEEN LOADING AND RUNTIME QUERY PERFORMANCE
1UERYõ0ERFORMANCE $ATABASE VENDORS FOCUSED ON WAREHOUSING HAVE INVESTED CONSIDERABLE ENERGY IN OPTIMIZING THEIR $"-3 PRODUCTS TO MAXIMIZE QUERY PERFORMANCE !S A RESULT WAREHOUSING PERFORMANCE HAS IMPROVED DRAMATICALLY 4HE GROWTH IN THE SIZE AND COMPLEXITY OF WAREHOUSES HAS PREVENTED SOME OF THIS PERFORMANCE GAIN FROM ACTUALLY BEING TRANSLATED INTO PERCEIVED END USER BENEFIT 3EVERAL DIFFERENT TECHNIQUES HAVE EVOLVED TO MAXIMIZE THE PERFORMANCE OF BUSINESS ANALYSIS QUERIES IN A WAREHOUSE INCLUDING s 3PECIALIZED INDEXING SCHEMES 4YPICAL BUSINESS ANALYSIS QUERIES INVOLVE A SUBSET OF THE DATA IN THE WAREHOUSE SELECTED ON THE BASIS OF DIMENSION VALUES &OR EXAMPLE A COMPARISON OF THIS MONTHS AND LAST MONTHS RESULTS INVOLVES ONLY OF THE MONTHS OF DATA IN THE EXAMPLE WAREHOUSE 3PECIALIZED INDEXING SCHEMES HAVE BEEN DEVELOPED TO ALLOW VERY RAPID SELECTION OF THE APPROPRIATE ROWS FROM THE FACT TABLE AND JOINING TO THE DIMENSION TABLES 3EVERAL OF THESE INVOLVE BITMAP TECHNIQUES WHERE THE INDIVIDUAL POSSIBLE VALUES FOR A DIMENSION OR A COMBINATION OF DIMENSIONS ARE EACH ASSIGNED A SINGLE BIT IN AN INDEX VALUE 2OWS MEETING A SELECTION CRITERION CAN BE VERY RAPIDLY IDENTIFIED BY BITWISE LOGICAL OPERATIONS WHICH A COMPUTER SYSTEM CAN PERFORM MORE RAPIDLY THAN IT CAN VALUE COMPARISONS
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s 0ARALLEL PROCESSING TECHNIQUES "USINESS ANALYSIS QUERIES CAN OFTEN BE BROKEN UP INTO PARTS THAT CAN BE CARRIED OUT IN PARALLEL TO REDUCE THE OVERALL TIME REQUIRED TO PRODUCE THE FINAL RESULTS )N A QUERY JOINING FOUR WAREHOUSE TABLES FOR EXAMPLE THE $"-3 MIGHT TAKE ADVANTAGE OF A TWO PROCESSOR SYSTEM BY JOINING TWO OF THE TABLES IN ONE PROCESS AND TWO OTHERS IN ANOTHER 4HE RESULTS OF THESE INTERMEDIATE JOINS ARE THEN COMBINED !LTERNATIVELY THE WORKLOAD OF PROCESSING A SINGLE TABLE IN THE QUERY MIGHT BE SPLIT AND CARRIED OUT IN PARALLELFOR EXAMPLE ASSIGNING ROWS FOR SPECIFIC MONTH RANGES TO SPECIFIC PROCESSES 4HE USE OF MULTIPROCESSOR SYSTEMS IN THESE CASES IS QUITE DIFFERENT THAN FOR /,40 DATABASES &OR /,40 THE FOCUS OF MULTIPROCESSOR OPERATIONS IS TO INCREASE OVERALL THROUGHPUT &OR WAREHOUSING THE FOCUS IS USUALLY THE IMPROVEMENT IN OVERALL EXECUTION TIME IN RESPONSE TO A SINGLE COMPLEX QUERY
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s 3PECIALIZED OPTIMIZATIONS 7HEN FACED WITH A COMPLEX DATABASE QUERY INVOLVING SELECTION CRITERIA AND JOINS THE $"-3 HAS MANY DIFFERENT SEQUENCES IN WHICH IT CAN CARRY OUT THE QUERY 4HE OPTIMIZER FOR AN /,40 DATABASE TENDS TO BENEFIT FROM THE ASSUMPTION THAT FOREIGN KEYPRIMARY KEY RELATIONSHIPS SHOULD BE EXERCISED EARLY IN ITS PROCESSING SINCE THEY TEND TO CUT DOWN DRAMATICALLY ON THE NUMBER OF ROWS OF INTERMEDIATE RESULTS 4HE OPTIMIZER FOR A WAREHOUSING DATABASE MAY MAKE A QUITE DIFFERENT DECISION BASED ON INFORMATION ACCUMULATED DURING THE LOAD PROCESS ABOUT THE DISTRIBUTION OF DATA VALUES WITHIN THE DATABASE s 4ABLE AND INDEX PARTITIONING ! PARTITION IS A SUBDIVISION OF A TABLE OR INDEX THAT IS STORED AND MANAGED SEPARATELY AND YET IS TRANSPARENT TO THE DATABASE USER /NE BENEFIT OF PARTITIONING IS THE ABILITY TO BACK UP RESTORE ADD AND REMOVE PARTITIONS WITHOUT DISRUPTING OPERATIONS ON THE REST OF THE PARTITIONS (OWEVER THERE CAN BE A HUGE PERFORMANCE BENEFIT AS WELL IF THE $"-3 CAN BREAK GLOBAL QUERIES INTO QUERIES FOR EACH PARTITION THAT CAN BE RUN IN PARALLEL AND CAN ELIMINATE PARTITIONS THAT DO NOT HAVE DATA RELEVANT TO THE QUERY BEING RUN s 4IGHTER HARDWARE AND SOFTWARE INTEGRATION 4HE PERFORMANCE CHALLENGES OF MODERN DATA WAREHOUSES HAVE DRIVEN A NEED FOR TIGHTER INTEGRATION OF THE HARDWARE AND SOFTWARE PLATFORMS ON WHICH DATA WAREHOUSES ARE RUN 4HESE INTEGRATION POINTS RANGE FROM DATA WAREHOUSE APPLIANCES COMPOSED OF HARDWARE THAT IS CAREFULLY MATCHED TO THE OPTIMAL CAPABILITIES OF THE SOFTWARE TO DATA FILTERING AND AGGREGATION CAPABILITY PLACED IN THE FIRMWARE OF THE STORAGE DEVICES SUCH AS IS BEING DONE WITH %XADATA FROM /RACLE !S WITH LOAD TIME PERFORMANCE MAXIMIZING THE RUNTIME PERFORMANCE OF A WAREHOUSE IS AN ONGOING TASK FOR THE DATABASE ADMINISTRATOR .EWER REVISIONS OF $"-3 SOFTWARE OFTEN PROVIDE PERFORMANCE BENEFITS AS DO HIGHER PERFORMANCE PROCESSORS OR MORE PROCESSORS
3UMMARY $ATA WAREHOUSING IS A RAPIDLY GROWING PART OF THE MARKET FOR 31, BASED RELATIONAL DATABASES AND IS ONE WITH A SET OF SPECIALIZED REQUIREMENTS s 7AREHOUSE DATABASES ARE OPTIMIZED FOR THE WORKLOAD OF TYPICAL BUSINESS ANALYSIS QUERIES WHICH IS QUITE DIFFERENT FROM /,40 WORKLOADS s 3PECIALIZED UTILITY PROGRAMS PROVIDE HIGH PERFORMANCE LOADING OF THE WAREHOUSE AND ANALYSIS TOOLS FOR TAKING ADVANTAGE OF WAREHOUSED DATA s 3PECIALIZED DATABASE SCHEMA STRUCTURES SUCH AS THE STAR SCHEMA ARE OFTEN USED IN WAREHOUSE APPLICATIONS TO SUPPORT TYPICAL BUSINESS ANALYSIS QUERIES AND OPTIMIZE PERFORMANCE s 31, EXTENSIONS ARE FREQUENTLY USED TO SUPPORT TYPICAL BUSINESS ANALYSIS QUERIES INVOLVING TIME SERIES AND TREND ANALYSIS RANK ORDERINGS AND TIME BASED COMPARISONS s #AREFUL DESIGN OF A LARGE WAREHOUSE IS REQUIRED TO PROVIDE THE CORRECT BALANCE BETWEEN LOAD TIME PERFORMANCE AND RUNTIME PERFORMANCE
#(!04%2
31,çANDç!PPLICATIONç3ERVERS
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PPLICATION SERVERS ARE ONE OF THE MAJOR NEW COMPUTER TECHNOLOGIES SPAWNED BY THE GROWTH OF THE )NTERNET !PPLICATION SERVERS FORM A KEY LAYER IN MOST COMMERCIAL WEB SITE ARCHITECTURES !S THE NAME IMPLIES APPLICATION SERVERS PROVIDE A PLATFORM FOR EXECUTING THE APPLICATION LOGIC THAT DRIVES USER INTERACTION ON A WEB SITE "UT APPLICATION SERVERS PERFORM ANOTHER IMPORTANT ROLETHEY ACT AS MEDIATORS BETWEEN THE )NTERNET SIDE COMPONENTS OF A WEB SITE THE WEB SERVERS AND CONTENT MANAGEMENT TOOLS AND THE )4 SIDE COMPONENTS SUCH AS LEGACY CORPORATE APPLICATIONS AND DATABASES )N THIS ROLE APPLICATION SERVERS MUST WORK CLOSELY WITH $"-3 SOFTWARE AND 31, IS THE LANGUAGE FOR THAT COMMUNICATION 4HIS CHAPTER EXPLORES THE ROLE OF 31, IN A MULTITIER WEB SITE ARCHITECTURE BUILT USING APPLICATION SERVERS
31,õANDõ7EBõ3ITESõ%ARLYõ)MPLEMENTATIONS !PPLICATION SERVERS DID NOT ALWAYS PLAY A PROMINENT ROLE IN WEB SITE ARCHITECTURES 4HE EARLIEST WEB SITES WERE FOCUSED ALMOST EXCLUSIVELY ON DELIVERING CONTENT TO THEIR USERS IN THE FORM OF STATIC WEB PAGES 4HE CONTENT OF THE WEB SITE WAS STRUCTURED AS A SERIES OF PREDEFINED WEB PAGES THAT WERE STORED IN FILES ! WEB SERVER ACCEPTED REQUESTS FROM USER BROWSERS IN THE FORM OF (440 ;(YPERTEXT 4RANSFER 0ROTOCOL= MESSAGES LOCATED THE PARTICULAR PAGES REQUESTED AND SENT THEM BACK TO THE BROWSER FOR DISPLAY AGAIN USING (440 4HE WEB PAGE CONTENTS WERE EXPRESSED IN (4-, THE (YPER4EXT -ARKUP ,ANGUAGE 4HE (4-, FOR A GIVEN PAGE CONTAINED THE TEXT AND GRAPHICS TO BE DISPLAYED ON THE PAGE AND THE LINKS THAT SUPPORTED NAVIGATION FROM THIS PAGE TO OTHERS )T DIDNT TAKE LONG BEFORE THE DEMANDS FOR INFORMATION TO BE DELIVERED VIA THE 7ORLD 7IDE 7EB OUTSTRIPPED THE STATIC CAPABILITIES OF PREDEFINED WEB PAGES #OMPANIES BEGAN TO USE WEB SITES TO COMMUNICATE WITH THEIR CUSTOMERS AND NEEDED TO SUPPORT BASIC CAPABILITIES LIKE SEARCHING FOR SPECIFIC PRODUCTS OR ACCEPTING A CUSTOMER ORDER 4HE FIRST STEP TOWARD PROVIDING ACTUAL PROCESSING CAPABILITY IN CONJUNCTION WITH DISPLAY OF A WEB PAGE WAS PROVIDED BY THE WEB SERVERS THEMSELVES AS SHOWN IN &IGURE )NSTEAD OF ACCEPTING ONLY REQUESTS FOR STATIC WEB PAGES WEB SERVERS ALSO ACCEPTED REQUESTS TO EXECUTE A SCRIPT A SERIES OF INSTRUCTIONS THAT DETERMINED WHICH INFORMATION TO DISPLAY
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7EB SERVER SCRIPTS WERE OFTEN WRITTEN IN SPECIALIZED SCRIPTING LANGUAGES SUCH AS 0ERL AND 0(0 )N ITS SIMPLEST FORM A SCRIPT MIGHT PERFORM A VERY SIMPLE COMPUTATION SUCH AS RETRIEVING THE CURRENT DATE AND TIME FROM THE OPERATING SYSTEM AND OUTPUT THE RESULT AS PART OF A WEB PAGE )N A SLIGHTLY MORE COMPLEX FORM THE SCRIPT MIGHT ACCEPT INPUT TYPED BY A USER INTO A FORMS ORIENTED WEB PAGE PERFORM A DATABASE QUERY BASED ON THE INPUT AND DISPLAY THE RESULTS "ECAUSE THE OUTPUT OF THE SCRIPT COULD VARY FROM ONE EXECUTION TO THE NEXT THE RESULTING WEB PAGE BECAME DYNAMIC ITS CONTENTS COULD CHANGE FROM ONE VIEWING TO THE NEXT DEPENDING ON THE RESULTS OF THE SCRIPT EXECUTION EACH TIME 3CRIPTING LANGUAGES PROVIDED THE EARLIEST LINKS BETWEEN WEB SITES AND 31, DATABASES ! SCRIPT MIGHT FOR EXAMPLE SUBMIT A 31, QUERY TO A $"-3 THROUGH A VARIATION ON THE INTERACTIVE 31, INTERFACE AND ACCEPT THE RESULTS OF THE QUERY FOR DISPLAY ON THE WEB PAGE "UT THERE WERE MANY PROBLEMS WITH SCRIPTING SOLUTIONS FOR WEB SITE PROCESSING -OST OF THE SCRIPT LANGUAGES ARE INTERPRETED AND EXECUTING A COMPLEX SCRIPT CAN CONSUME A LOT OF #05 CYCLES 3CRIPTING FACILITIES RAN AS SEPARATE PROCESSES ON 5.)8 BASED OR 7INDOWS BASED SERVERSA HIGH OVERHEAD STRUCTURE IF DOZENS OR HUNDREDS OF SCRIPTS MUST BE EXECUTED EVERY SECOND 4HESE AND OTHER LIMITATIONS OF SCRIPTING SOLUTIONS SET THE STAGE FOR AN ALTERNATIVE APPROACH AND THE EMERGENCE OF APPLICATION SERVERS AS A PART OF THE WEB SITE ARCHITECTURE
!PPLICATIONõ3ERVERSõANDõ4HREE 4IERõ7EBõ3ITEõ!RCHITECTURES 4HE LOGICAL EVOLUTION FROM WEB SERVER SCRIPTING WAS THE DEFINITION OF A SEPARATE ROLE FOR AN APPLICATION SERVER RESULTING IN THE THREE TIER ARCHITECTURE SHOWN IN &IGURE .OTE THAT MANY )4 PROFESSIONALS CONSIDER THE WEB SERVER AND APPLICATION SERVER TO BE SEPARATE TIERS NAMING THIS ARCHITECTURE FOUR TIER OR MORE COMMONLY . TIER 4HE WEB SERVER RETAINS ITS PRIMARY RESPONSIBILITY FOR LOCATING AND SERVING UP STATIC WEB PAGES AND STATIC PIECES OF WEB PAGES FROM ITS FILES 7HEN APPLICATION PROCESSING IS REQUIRED TO DETERMINE WHICH INFORMATION TO DISPLAY OR TO PROCESS INFORMATION SUPPLIED BY THE USER THE WEB SERVER INVOKES A SEPARATE APPLICATION SERVER TO PERFORM THE PROCESSING )N A SMALLER LOWER VOLUME WEB SITE THE APPLICATION SERVER MAY RUN AS A SEPARATE PROCESS ON THE SAME PHYSICAL SERVER
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SYSTEM AS THE WEB SERVER )N THE MORE GENERAL CASE USED BY LARGER WEB SITES THE WEB SERVER AND APPLICATION SERVER WILL RUN ON TWO DIFFERENT SERVER COMPUTERS TYPICALLY CONNECTED BY A HIGH SPEED LOCAL AREA NETWORK )N EITHER CONFIGURATION THE WEB SERVER PASSES REQUESTS IN THE FORM OF MESSAGES TO THE APPLICATION SERVER AND RECEIVES RESPONSES IN THE FORM OF (4-, CONTENTS TO BE DISPLAYED ON THE PAGE 4HE EARLY DAYS OF APPLICATION SERVERS OFFERED A WIDE RANGE OF APPLICATION SERVER PRODUCTS 3OME SERVERS REQUIRED THAT APPLICATIONS BE WRITTEN IN # OR # /THERS REQUIRED THE USE OF *AVA 4HE INTERFACE BETWEEN THE APPLICATION SERVER AND THE WEB SERVER WAS WELL DEFINED BY THE !0)S OF THE TWO LEADING WEB SERVER VENDORS .ETSCAPE AND -ICROSOFT "UT ALL OTHER ASPECTSFROM PROGRAMMING LANGUAGE TO THE SUPPORTING SERVICES PROVIDED BY THE APPLICATION SERVER TO THE !0) FOR DATABASE ACCESSWERE NOT STANDARDIZED 3UN -ICROSYSTEMS INTRODUCTION OF %NTERPRISE *AVA "EANS %*"S AND THE *AVA %NTERPRISE %DITION *%% SPECIFICATION BASED ON THEM BEGAN A ROUND OF STANDARDIZATION OF APPLICATION SERVERS ! JAVA BEAN IS A *AVA CLASS THAT FOLLOWS THE 3UN *AVA "EANS 3TANDARD WHICH PROVIDES A FRAMEWORK FOR CREATING OBJECTS TO BE USED BY '5) TOOLS %*"S BUILT ON THE MUSHROOMING POPULARITY OF *AVA AS A PROGRAMMING LANGUAGE 4HE SPECIFICATION CAME FROM 3UN A LEADING SERVER VENDOR AND A COMPANY WIDELY RECOGNIZED FOR ITS LEADERSHIP IN )NTERNET TECHNOLOGIES 4HE SPECIFICATIONS ALSO CONTAINED A STANDARDIZED !0) FOR DATABASE ACCESS ONE OF THE MOST IMPORTANT FUNCTIONS PROVIDED BY AN APPLICATION SERVER IN THE FORM OF *AVA $ATABASE #ONNECTIVITY *$"#
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7ITHIN A SHORT TIME APPLICATION SERVERS BASED ON THE *%% SPECIFICATION PULLED AHEAD IN THE MARKET 6ENDORS WHO HAD TAKEN AN ALTERNATIVE APPROACH AUGMENTED THEIR PRODUCTS WITH *AVA CAPABILITY AND EVENTUALLY ABANDONED THEIR PROPRIETARY PRODUCTS FOR A *%% BASED STRATEGY ! SHORT TIME LATER THE APPLICATION SERVER MARKET BEGAN A ROUND OF CONSOLIDATION 3UN ACQUIRED .ET$YNAMICS ONE OF THE PIONEERING *%% APPLICATION SERVER VENDORS "%! 3YSTEMS A LEADING VENDOR OF SOFTWARE MIDDLEWARE FOR TRANSACTION PROCESSING ACQUIRED 7EB,OGIC ANOTHER APPLICATION SERVER PIONEER "%! WAS ACQUIRED BY /RACLE IN .ETSCAPE WHICH PROVIDED ONE OF THE LEADING WEB SERVERS FILLED OUT ITS PRODUCT LINE BY ACQUIRING +IVA ANOTHER EARLY APPLICATION SERVER MARKET LEADER ,ATER WHEN !/, ACQUIRED .ETSCAPE AND THEN FORMED A JOINT VENTURE WITH 3UN BOTH OF THESE *%% APPLICATION SERVER PRODUCTS CAME UNDER COMMON MANAGEMENT AT 3UN EVENTUALLY MERGING INTO THE 3UN I0LANET APPLICATION SERVER LATER REBRANDED THE 3UN/.% APPLICATION SERVER (EWLETT 0ACKARD FOLLOWED WITH ITS OWN ACQUISITION OF "LUESTONE ANOTHER APPLICATION SERVER VENDOR )"- DEPARTED FROM THE ACQUISITION PATH BY BUILDING ITS OWN APPLICATION SERVER MARKETED UNDER THE 7EB3PHERE BRAND NAME /RACLE ALSO INTRODUCED ITS OWN INTERNALLY DEVELOPED PRODUCT THE /RACLE !PPLICATION 3ERVER ALTHOUGH MUCH OF ITS SOFTWARE WAS REPLACED BY PURCHASED THIRD PARTY COMPONENTS OVER TIME AS /RACLE STRUGGLED TO ESTABLISH ITS POSITION /VER THE COURSE OF SEVERAL YEARS OF AGGRESSIVE COMPETITION THE *%% SPECIFICATION CONTINUED TO EVOLVE INCLUDING EXPANDED FEATURES FOR APPLICATION SERVER DATABASE ACCESS "%!S 7EB,OGIC AND )"-S 7EB3PHERE EMERGED AS THE DOMINANT PLAYERS WITH ROUGHLY EQUAL MARKET SHARE 0RODUCTS FROM 3UN /RACLE AND A DOZEN SMALLER VENDORS DIVIDED UP THE REMAINDER OF THE MARKET %VERY SIGNIFICANT APPLICATION SERVER PRODUCT COMPLIED WITH THE *%% SPECIFICATION AND PROVIDED *$"# BASED FACILITIES FOR DATABASE ACCESS
$ATABASEõ!CCESSõFROMõ!PPLICATIONõ3ERVERS 4HE CONVERGENCE OF THE APPLICATION SERVER MARKET AROUND THE *%% SPECIFICATION EFFECTIVELY STANDARDIZED AT LEAST FOR A TIME THE EXTERNAL INTERFACE BETWEEN THE APPLICATION SERVER AND A $"-3 AROUND *$"# #ONCEPTUALLY AN APPLICATION SERVER CAN AUTOMATICALLY ACCESS ANY DATABASE PRODUCT THAT OFFERS A *$"# COMPLIANT !0) THUS ACHIEVING $"-3 INDEPENDENCE )N PRACTICE SUBTLE DIFFERENCES BETWEEN THE $"-3 SYSTEMS IN AREAS LIKE 31, DIALECTS AND DATABASE NAMING STILL REQUIRE SOME TWEAKING AND TESTING AND MANIFEST THEMSELVES IN SUBTLE DEPENDENCIES WITHIN THE CODE DEPLOYED ON THE APPLICATION SERVER (OWEVER THESE DIFFERENCES TEND TO BE MINOR AND ADJUSTING FOR THEM IS RELATIVELY STRAIGHTFORWARD 4HE APPROACH TO DATA MANAGEMENT FOR THE APPLICATION CODE RUNNING ON THE APPLICATION SERVER IS A SLIGHTLY MORE COMPLICATED STORY 7HILE THE APPLICATION SERVER DOES PROVIDE UNIFORM SERVICES FOR DATA MANAGEMENT IT PROVIDES THESE IN SEVERAL DIFFERENT ARCHITECTURES THAT USE THE VARIOUS TYPES OF %*"S IN THE *%% SPECIFICATION 4HE APPLICATION DESIGNER MUST CHOOSE AMONG THESE APPROACHES AND IN SOME CASES WILL MIX AND MATCH THEM TO ACHIEVE THE REQUIREMENTS OF THE APPLICATION (ERE ARE SOME OF THE DECISIONS THAT MUST BE MADE s 7ILL THE APPLICATION LOGIC DO DIRECT DATABASE ACCESS FROM WITHIN A SESSION BEAN OR WILL DATABASE CONTENTS BE REPRESENTED AS ENTITY BEANS WITH DATABASE ACCESS LOGIC ENCAPSULATED WITHIN THEM 3ESSION BEANS AND ENTITY BEANS ARE DEFINED IN THE NEXT TOPIC s )F DIRECT ACCESS FROM SESSION BEANS IS USED CAN THE SESSION BEAN REMAIN STATELESS WHICH SIMPLIFIES THE CODING OF THE BEAN AND ITS MANAGEMENT BY THE APPLICATION SERVER OR DOES THE LOGIC OF DATABASE ACCESS REQUIRE THE BEAN TO BE STATEFUL PRESERVING A CONTEXT FROM ONE INVOCATION TO ANOTHER
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s )F ENTITY BEANS ARE USED TO REPRESENT DATABASE CONTENTS CAN THE APPLICATION RELY ON THE CONTAINER MANAGED PERSISTENCE PROVIDED BY THE APPLICATION SERVER TO MANAGE DATABASE INTERACTION OR DOES THE APPLICATIONS LOGIC REQUIRE THAT THE ENTITY BEAN PROVIDE ITS OWN DATABASE ACCESS LOGIC THROUGH BEAN MANAGED PERSISTENCE s )F ENTITY BEANS ARE USED TO MODEL DATABASE CONTENTS DO THE BEANS CORRESPOND ON A ONE TO ONE BASIS TO THE TABLES IN THE UNDERLYING DATABASE FINE GRAINED MODELING OR IS IT MORE APPROPRIATE FOR THE BEANS TO PRESENT A HIGHER LEVEL MORE OBJECT ORIENTED VIEW OF THE DATA WITH THE DATA WITHIN EACH BEAN DRAWN FROM MULTIPLE DATABASE TABLES COARSE GRAINED MODELING 4HE TRADE OFFS REPRESENTED BY THESE DESIGN QUESTIONS PROVIDE AN EXCELLENT PERSPECTIVE ON THE CHALLENGE OF MATCHING 31, AND RELATIONAL DATABASE TECHNOLOGY TO THE DEMANDS OF THE 7EB AND ITS STATELESS ARCHITECTURE AND TO THE DEMANDS OF APPLICATION SERVERS AND OBJECT ORIENTED PROGRAMMING 4HE NEXT SEVERAL SECTIONS DESCRIBE THE BASICS OF %*"S AND THE TRADE OFFS AMONG THE DIFFERENT DATA ACCESS ARCHITECTURES THEY CAN SUPPORT
%*"õ4YPES 7ITHIN A *%% COMPLIANT APPLICATION SERVER THE USER DEVELOPED *AVA APPLICATIONS CODE THAT IMPLEMENTS THE SPECIFIC BUSINESS LOGIC IS PACKAGED AND EXECUTES AS A COLLECTION OF %*"S !N %*" HAS A WELL DEFINED SET OF EXTERNAL INTERFACES METHODS THAT IT MUST PROVIDE AND IS WRITTEN WITH AN EXPLICIT SET OF CLASS SPECIFIC PUBLIC METHODS THAT DEFINE THE EXTERNAL INTERFACE TO THE BEAN 4HE WORK DONE WITHIN THE BEAN AND ANY PRIVATE DATA VARIABLES THAT IT MAINTAINS FOR ITS OWN USE CAN BE ENCAPSULATED AND HIDDEN FROM OTHER BEANS AND FROM DEVELOPERS WHO DO NOT NEED TO KNOW THESE INTERNAL DETAILS AND WHO SHOULD NOT WRITE CODE THAT DEPENDS ON THEM 4HE %*"S EXECUTE ON THE APPLICATION SERVER WITHIN A CONTAINER WHICH PROVIDES BOTH A RUNTIME ENVIRONMENT FOR THE BEANS AND SERVICES FOR THEM 4HESE RANGE FROM GENERAL SERVICES SUCH AS MANAGING MEMORY FOR THE BEANS AND SCHEDULING THEIR EXECUTION TO SPECIFIC SERVICES LIKE NETWORK ACCESS AND DATABASE ACCESS VIA *$"# 4HE CONTAINER ALSO PROVIDES PERSISTENCE SERVICES PRESERVING THE STATE OF BEANS ACROSS ACTIVATIONS 0ERSISTENCE IS THE OBJECT ORIENTED PROGRAMMING PROPERTY THAT PRESERVES DATA FOR FUTURE USE $ATABASES ARE A COMMON MEANS OF PERSISTENCE %*"S COME IN TWO MAJOR TYPES THAT ARE OF INTEREST FROM A DATA MANAGEMENT PERSPECTIVE 4HE %*" TYPES ARE GRAPHICALLY ILLUSTRATED IN &IGURE 4HE TWO MAJOR TYPES OF BEANS ARE s 3ESSION BEANS 4HESE BEANS REPRESENT INDIVIDUAL USER SESSIONS WITH THE !PPLICATION SERVER #ONCEPTUALLY THERE IS A ONE TO ONE ASSOCIATION BETWEEN EACH SESSION BEAN AND A CURRENT USER )N THE FIGURE USERS -ARY *OE AND 3AM ARE EACH REPRESENTED BY THEIR OWN SESSION BEAN )F THERE ARE INTERNAL INSTANCE VARIABLES WITHIN THE BEAN THESE VARIABLE VALUES REPRESENT THE CURRENT STATE ASSOCIATED WITH THE USER DURING THIS PARTICULAR SESSION
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s %NTITY BEANS 4HESE BEANS REPRESENT BUSINESS OBJECTS AND LOGICALLY CORRESPOND TO INDIVIDUAL ROWS OF A DATABASE TABLE &OR EXAMPLE FOR ENTITY BEANS REPRESENTING SALES OFFICES THERE IS A ONE TO ONE ASSOCIATION BETWEEN EACH ENTITY BEAN AND A PARTICULAR OFFICE WHICH IS ALSO REPRESENTED IN OUR SAMPLE DATABASE BY A SINGLE ROW IN THE /&&)#%3 TABLE )F THERE ARE INTERNAL INSTANCE VARIABLES WITHIN THE BEAN THESE VARIABLE VALUES REPRESENT THE CURRENT STATE ASSOCIATED WITH THE OFFICE WHICH IS ALSO REPRESENTED BY THE COLUMN VALUES IN THIS ROW OF THE /&&)#%3 TABLE 4HIS STATE IS INDEPENDENT OF ANY PARTICULAR USER SESSION
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3ESSIONõ"EANõ$ATABASEõ!CCESS ! SESSION BEAN WILL TYPICALLY ACCESS A DATABASE IN A SERIES OF ONE OR MORE *$"# CALLS ON BEHALF OF THE USER REPRESENTED BY THE BEAN !N APPLICATION SERVER CLASSIFIES SESSION BEANS INTO TWO CATEGORIES DEPENDING ON HOW THE BEAN MANAGES STATE s 3TATELESS SESSION BEAN 4HIS TYPE OF BEAN DOES NOT MAINTAIN ANY STATUS INFORMATION ACROSS METHOD INVOCATIONS )T CARRIES OUT ITS ACTIONS ON BEHALF OF ONE USER AT A TIME AND ONE REQUEST AT A TIME %ACH REQUEST TO THE BEAN IS INDEPENDENT OF THE LAST 7ITH THIS RESTRICTION EVERY INVOCATION OF THE BEAN MUST CARRY WITH IT IN THE FORM OF THE PARAMETERS PASSED WITH THE INVOCATION ALL OF THE INFORMATION NEEDED TO CARRY OUT THE REQUEST s 3TATEFUL SESSION BEAN 4HIS TYPE OF BEAN MAINTAINS STATUS INFORMATION ACROSS METHOD INVOCATIONS 4HE BEAN NEEDS TO hREMEMBERv INFORMATION FROM ITS PREVIOUS INVOCATIONS ITS STATE TO CARRY OUT THE TASKS REQUESTED BY LATER INVOCATIONS )T USES PRIVATE INSTANCE VARIABLES TO HOLD THE INFORMATION 4HE NEXT TWO SECTIONS SHOW EXAMPLES OF APPLICATION TASKS THAT ARE MOST EASILY IMPLEMENTED AS EACH TYPE OF SESSION BEAN 9OU SPECIFY WHETHER A SESSION BEAN IS STATELESS OR STATEFUL IN THE DEPLOYMENT DESCRIPTOR FOR THE BEAN WHICH CONTAINS INFORMATION SUPPLIED TO THE APPLICATION SERVER ON WHICH THE BEAN IS DEPLOYED
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!N APPLICATION SERVER ON A BUSY WEB SITE CAN EASILY HAVE MORE SESSION BEANS AND OTHER %*"S IN USE THAN IT HAS MAIN MEMORY AVAILABLE TO STORE THEM )N THIS SITUATION THE APPLICATION SERVER WILL KEEP A LIMITED NUMBER OF SESSION BEAN INSTANCES ACTIVE IN ITS MAIN MEMORY )F A USER ASSOCIATED WITH A CURRENTLY INACTIVE SESSION BEAN BECOMES ACTIVE THAT IS ONE OF HIS OR HER WEB SITE CLICKS MUST BE PROCESSED THE APPLICATION SERVER CHOOSES ANOTHER INSTANCE OF THE SAME BEAN CLASS AND PASSIVATES ITTHAT IS IT SAVES THE VALUES OF ANY INSTANCE VARIABLES DEFINED FOR THE BEAN AND THEN REUSES THE BEAN TO SERVE THE USER SESSION NEEDING ACTIVATION 7HETHER A SESSION BEAN IS STATEFUL OR STATELESS HAS A SIGNIFICANT IMPACT ON THIS PASSIVATION AND ACTIVATION 3INCE A STATELESS SESSION BEAN DOES NOT NEED ITS STATUS PRESERVED ACROSS METHOD INVOCATIONS THE APPLICATION SERVER DOES NOT NEED TO SAVE ITS INSTANCE VARIABLE VALUES WHEN IT PASSIVATES THE BEAN AND DOES NOT NEED TO RESTORE INSTANCE VARIABLE VALUES WHEN IT REACTIVATES THE BEAN "UT FOR A STATEFUL SESSION BEAN THE APPLICATION SERVER NEEDS TO COPY ITS INSTANCE VALUE VARIABLES TO PERSISTENT STORAGE A DISK FILE OR A DATABASE WHEN IT PASSIVATES THE BEAN AND THEN RESTORE THOSE VALUES WHEN IT REACTIVATES THE BEAN 4HUS STATEFUL SESSION BEANS CAN SIGNIFICANTLY DIMINISH THE PERFORMANCE AND THROUGHPUT OF AN APPLICATION SERVER ON A BUSY SITE 3TATELESS BEANS ARE PREFERABLE FOR PERFORMANCE BUT MANY APPLICATIONS ARE DIFFICULT OR IMPOSSIBLE TO IMPLEMENT WITHOUT USING STATEFUL BEANS
5SINGõ*$"#õFROMõAõ3TATELESSõ3ESSIONõ"EAN &IGURE SHOWS A SIMPLE EXAMPLE OF AN APPLICATION THAT CAN EASILY BE HANDLED WITH STATELESS SESSION BEAN DATABASE ACCESS ! PAGE ON A WEB SITE DISPLAYS THE CURRENT PRICE OF A COMPANYS STOCK WHEN THE PAGE IS DISPLAYED 4HE PAGE CANT BE STATIC SINCE THE DISPLAYED PRICE WILL CHANGE MINUTE BY MINUTE 3O WHEN THE USERS BROWSER REQUESTS THE PAGE THE WEB SERVER HANDS OFF THE REQUEST TO AN APPLICATION SERVER WHICH EVENTUALLY INVOKES A METHOD OF A SESSION BEAN 4HE SESSION BEAN CAN USE *$"# TO SEND A 31, 3%,%#4 STATEMENT TO A DATABASE OF CURRENT STOCK PRICES AND RECEIVE BACK THE ANSWER AS ONE LINE OF QUERY RESULTS 4HE SESSION BEAN REFORMATS THE STOCK QUOTE AS A FRAGMENT OF A WEB PAGE AND PASSES IT BACK TO THE WEB SERVER FOR DISPLAY TO THE USER 3TATELESS SESSION BEANS CAN PERFORM MORE COMPLEX FUNCTIONS AS WELL 3UPPOSE THE SAME COMPANY HAS A PAGE ON ITS WEB SITE WHERE A USER CAN REQUEST A PRODUCT CATALOG BY FILLING IN THE CONTENTS OF A SMALL FORM 7HEN THE FORM IS FILLED IN AND THE USER CLICKS THE 3END BUTTON THE BROWSER SENDS THE DATA FROM THE FORM TO THE WEB SERVER WHICH AGAIN HANDS OFF THE REQUEST TO AN APPLICATION SERVER 4HIS TIME A DIFFERENT METHOD OF THE SESSION BEAN IS INVOKED AND RECEIVES THE DATA FROM THE FORM AS PARAMETERS 4HE SESSION BEAN CAN USE *$"# TO SEND A 31, ).3%24 STATEMENT TO A DATABASE TABLE HOLDING PENDING CATALOG REQUESTS )N EACH OF THESE EXAMPLES ALL OF THE INFORMATION THAT THE SESSION BEAN NEEDS TO CARRY OUT ITS TASK IS PASSED TO IT WITH THE METHOD INVOCATION 7HEN THE BEAN HAS COMPLETED ITS TASK THE INFORMATION IS NOT NEEDED ANYMORE 4HE NEXT INVOCATION AGAIN RECEIVES ALL OF THE INFORMATION IT NEEDS SO THERE IS NO NEED TO CARRY OVER STATUS INFORMATION %VEN MORE IMPORTANTLY THE DATABASE ACTIVITY ON EACH INVOCATION IS COMPLETELY INDEPENDENT FROM EVERY OTHER INVOCATION .O DATABASE TRANSACTION SPANS MULTIPLE METHOD INVOCATIONS -ANY WEB INTERACTIONS CANT LIVE WITH THE LIMITATIONS IMPOSED BY STATELESS SESSION BEANS #ONSIDER A MORE COMPLEX WEB BASED FORM THAT SPANS FOUR PAGES !S THE USER FILLS OUT EACH PAGE AND SENDS IT TO THE WEB SITE THE SESSION BEAN MUST ACCUMULATE THE INFORMATION AND RETAIN IT ACROSS THE FOUR PAGE CLICKS UNTIL ALL OF THE DATA IS READY TO BE CAPTURED INTO A DATABASE 4HE NEED TO RETAIN INFORMATION ACROSS METHOD INVOCATIONS CALLS FOR A STATEFUL SESSION BEAN
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4O MAINTAIN THIS OBJECT ORIENTED MODEL THERE MUST BE VERY CLOSE COOPERATION BETWEEN THE ENTITY BEAN REPRESENTATIONS OF ENTITIES AND THEIR DATABASE REPRESENTATIONS )F A SESSION BEAN INVOKES A CUSTOMER ENTITY BEAN METHOD THAT CHANGES A CUSTOMERS CREDIT LIMIT THAT CHANGE MUST BE REFLECTED IN THE DATABASE SO THAT AN ORDER PROCESSING APPLICATION USING THE DATABASE WILL USE THE NEW LIMIT 3IMILARLY IF AN INVENTORY MANAGEMENT APPLICATION ADDS TO THE QUANTITY ON HAND FOR A PARTICULAR PRODUCT IN THE DATABASE THAT PRODUCTS ENTITY BEAN IN THE APPLICATION SERVER MUST BE UPDATED *UST AS AN APPLICATION SERVER WILL PASSIVATE AND REACTIVATE SESSION BEANS AS NECESSARY IT WILL PASSIVATE AND REACTIVATE ENTITY BEANS REPEATEDLY IN RESPONSE TO A HEAVY WORKLOAD "EFORE THE APPLICATION SERVER PASSIVATES AN ENTITY BEAN THE BEANS STATE MUST BE SAVED IN A PERSISTENT WAY BY UPDATING THE DATABASE 3IMILARLY WHEN THE APPLICATION SERVER REACTIVATES AN ENTITY BEAN ITS INSTANCE VARIABLES MUST BE SET TO THEIR VALUES JUST BEFORE IT WAS PASSIVATED BY RELOADING THOSE VALUES FROM THE DATABASE 4HE ENTITY BEAN CLASS DEFINES CALLBACK METHODS THAT AN ENTITY BEAN MUST PROVIDE TO IMPLEMENT THIS SYNCHRONIZATION 4HERE IS CLOSE CORRESPONDENCE BETWEEN ACTIONS CARRIED OUT ON ENTITY BEANS AND DATABASE ACTIONS AS SHOWN IN 4ABLE 4HE *%% SPECIFICATION PROVIDES TWO ALTERNATIVE WAYS TO MANAGE THIS COORDINATION s "EAN MANAGED PERSISTENCE 4HE ENTITY BEAN ITSELF IS RESPONSIBLE FOR MAINTAINING SYNCHRONIZATION WITH THE DATABASE 4HE APPLICATION PROGRAMMER WHO DEVELOPS THE ENTITY BEAN AND CODES ITS IMPLEMENTATION METHODS MUST USE *$"# TO READ AND WRITE DATA IN THE DATABASE WHEN NECESSARY 4HE APPLICATION SERVER CONTAINER NOTIFIES THE BEAN WHEN IT TAKES ACTIONS THAT REQUIRE DATABASE INTERACTION s #ONTAINER MANAGED PERSISTENCE 4HE %*" CONTAINER PROVIDED BY THE APPLICATION SERVER IS RESPONSIBLE FOR MAINTAINING SYNCHRONIZATION WITH THE DATABASE 4HE CONTAINER MONITORS INTERACTION WITH THE ENTITY BEAN AND AUTOMATICALLY USES *$"# TO READ AND WRITE DATA IN THE DATABASE AND TO UPDATE THE INSTANCE VARIABLES WITHIN THE BEAN WHEN NEEDED 4HE APPLICATION PROGRAMMER WHO DEVELOPS THE ENTITY BEAN AND CODES ITS IMPLEMENTATION METHODS CAN FOCUS ON THE BUSINESS LOGIC IN THE BEAN AND ASSUME THAT ITS INSTANCE VARIABLES WILL ACCURATELY REPRESENT THE STATE OF THE DATA IN THE DATABASE
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#HAPTERçç
31,çANDç!PPLICATIONç3ERVERSç
.OTE THAT ENTITY BEANS ARE ALWAYS STATEFULTHE DISTINCTION BETWEEN THESE TWO BEAN TYPES IS NOT THE DIFFERENCE BETWEEN STATELESS AND STATEFUL BEANS BUT RATHER THE DIFFERENCE BETWEEN WHO IS RESPONSIBLE FOR MAINTAINING PROPER STATE 4HE NEXT TWO SECTIONS DISCUSS THE PRACTICAL ISSUES ASSOCIATED WITH EACH TYPE OF ENTITY BEAN AND THE TRADE OFFS BETWEEN THEM
5SINGõ#ONTAINER -ANAGEDõ0ERSISTENCE !N ENTITY BEANS DEPLOYMENT DESCRIPTOR SPECIFIES THAT AN ENTITY BEAN REQUIRES CONTAINER MANAGED PERSISTENCE 4HE DEPLOYMENT DESCRIPTOR ALSO SPECIFIES THE MAPPING BETWEEN INSTANCE VARIABLES OF THE BEAN AND COLUMNS IN THE UNDERLYING DATABASE 4HE DEPLOYMENT DESCRIPTOR ALSO IDENTIFIES THE PRIMARY KEY THAT UNIQUELY IDENTIFIES THE BEAN AND THE CORRESPONDING DATABASE ROW 4HE PRIMARY KEY VALUE IS USED IN THE DATABASE OPERATIONS THAT STORE AND RETRIEVE VARIABLE VALUES FROM THE DATABASE 7ITH CONTAINER MANAGED PERSISTENCE THE %*" CONTAINER IS RESPONSIBLE FOR MAINTAINING SYNCHRONIZATION BETWEEN THE ENTITY BEAN AND THE DATABASE ROW 4HE CONTAINER CALLS *$"# TO STORE INSTANCE VARIABLE VALUES INTO THE DATABASE TO RESTORE THOSE VALUES TO INSERT A NEW ROW INTO THE DATABASE AND TO DELETE A ROWALL AS REQUIRED BY ACTIONS ON THE BEAN 4HE CONTAINER WILL CALL THE BEANS EJB3TORE CALLBACK METHOD BEFORE IT STORES VALUES IN THE DATABASE TO NOTIFY THE BEAN THAT IT MUST GET ITS VARIABLE VALUES INTO A CONSISTENT STATE 3IMILARLY THE CONTAINER WILL CALL THE BEANS EJB,OAD CALLBACK METHOD AFTER LOADING VALUES FROM THE DATABASE TO ALLOW THE BEAN TO DO APPROPRIATE POSTPROCESSING FOR EXAMPLE CALCULATING A VALUE THAT WAS NOT ITSELF PERSISTED BASED ON VALUES THAT WERE )N THE SAME WAY THE BEANS EJB2EMOVE METHOD WILL BE CALLED BEFORE THE CONTAINER DELETES THE ROW FROM THE DATABASE AND EJB#REATE AND EJB0OST#REATE ARE CALLED IN CONJUNCTION WITH INSERTING A NEW ROW &OR MANY ENTITY BEANS THESE CALLBACK METHODS WILL BE EMPTY SINCE THE CONTAINER HANDLES THE ACTUAL DATABASE OPERATIONS
5SINGõ"EAN -ANAGEDõ0ERSISTENCE )F AN ENTITY BEANS DEPLOYMENT DESCRIPTOR SPECIFIES BEAN MANAGED PERSISTENCE THE CONTAINER ASSUMES THAT THE ENTITY BEAN WILL HANDLE ITS OWN DATABASE INTERACTION 7HEN A NEW ENTITY BEAN IS FIRST CREATED THE CONTAINER CALLS THE BEANS EJB#REATE AND EJB0OST#REATE METHODS 4HE BEAN IS RESPONSIBLE FOR PROCESSING THE CORRESPONDING ).3%24 STATEMENT FOR THE DATABASE 3IMILARLY WHEN AN ENTITY BEAN IS TO BE REMOVED THE CONTAINER CALLS THE BEANS EJB2EMOVE METHOD 4HE BEAN IS RESPONSIBLE FOR PROCESSING THE CORRESPONDING $%,%4% STATEMENT FOR THE DATABASE AND WHEN THE BEAN RETURNS FROM THE EJB2EMOVE METHOD THE CONTAINER IS FREE TO ACTUALLY REMOVE THE BEAN ITSELF AND REUSE ITS STORAGE "EAN LOADING IS SIMILARLY HANDLED BY A CONTAINER CALL TO EJB,OAD AND STORING BY A CALL BY THE CONTAINER TO EJB3TORE 4HE BEAN IS SIMILARLY NOTIFIED OF PASSIVATION AND ACTIVATION BY CALLBACKS FROM THE CONTAINER /F COURSE NOTHING LIMITS THE ENTITY BEANS DATABASE INTERACTION TO THESE CALLBACK METHODS )F THE BEAN NEEDS TO ACCESS THE DATABASE DURING THE EXECUTION OF ONE OF ITS METHODS THE BEAN CAN MAKE WHATEVER *$"# CALLS IT NEEDS 4HE *$"# CALLS WITHIN THE CALLBACK METHODS ARE STRICTLY FOCUSED ON MANAGING BEAN PERSISTENCE
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0ARTç6)ç
31,ç4ODAYçANDç4OMORROW
#ONTAINER -ANAGEDõANDõ"EAN -ANAGEDõ4RADE /FFS 9OU MIGHT NATURALLY ASK WHY YOU WOULD EVER WANT TO USE BEAN MANAGED PERSISTENCE WHEN CONTAINER MANAGED PERSISTENCE ELIMINATES THE NEED TO WORRY ABOUT SYNCHRONIZING WITH THE DATABASE 4HE ANSWER IS THAT CONTAINER MANAGED PERSISTENCE HAS SOME LIMITATIONS s -ULTIPLE DATABASES &OR MOST APPLICATION SERVERS ENTITY BEANS MUST BE MAPPED INTO A SINGLE DATABASE SERVER )F ENTITY BEAN DATA COMES FROM MULTIPLE DATABASES THEN BEAN MANAGED PERSISTENCE MAY BE THE ONLY WAY TO HANDLE DATABASE SYNCHRONIZATION s -ULTIPLE TABLES PER BEAN #ONTAINER MANAGED PERSISTENCE WORKS WELL WHEN ALL OF THE INSTANCE VARIABLES FOR AN ENTITY BEAN COME FROM A SINGLE ROW OF A SINGLE TABLE THAT IS WHEN THERE IS A ONE TO ONE CORRESPONDENCE BETWEEN BEAN INSTANCES AND TABLE ROWS )F AN ENTITY BEAN NEEDS TO MODEL A MORE COMPLEX OBJECT SUCH AS AN ORDER HEADER AND INDIVIDUAL LINE ITEMS OF AN ORDER WHICH COME FROM TWO DIFFERENT RELATED TABLES BEAN MANAGED PERSISTENCE IS USUALLY REQUIRED BECAUSE THE BEANS OWN CODE MUST PROVIDE THE INTELLIGENCE TO MAP TO AND FROM THE DATABASE s 0ERFORMANCE OPTIMIZATIONS 7ITH CONTAINER MANAGED PERSISTENCE A CONTAINER MUST MAKE AN ALL OR NOTHING ASSUMPTION ABOUT PERSISTING INSTANCE VARIABLES %VERY TIME THE VARIABLES MUST BE STORED OR LOADED ALL OF THE VARIABLES MUST BE HANDLED )N MANY APPLICATIONS THE ENTITY BEAN MAY BE ABLE TO DETERMINE THAT DEPENDING ON ITS PARTICULAR STATE ONLY A FEW OF THE VARIABLES NEED TO BE PROCESSED )F THE ENTITY BEAN HOLDS A LOT OF DATA THE PERFORMANCE DIFFERENCE CAN BE SIGNIFICANT s $ATABASE OPTIMIZATIONS )F THE METHODS OF AN ENTITY BEAN THAT IMPLEMENT ITS BUSINESS LOGIC INVOLVE HEAVY DATABASE ACCESS QUERIES AND UPDATES THEN SOME OF THE DATABASE OPERATIONS THAT THE CONTAINER WILL CARRY OUT IN A CONTAINER MANAGED PERSISTENCE SCHEME MAY BE REDUNDANT )F BEAN MANAGED PERSISTENCE IS USED INSTEAD THE BEAN MAY BE ABLE TO DETERMINE EXACTLY WHEN DATABASE OPERATIONS ARE REQUIRED FOR SYNCHRONIZATION AND WHEN THE DATABASE IS ALREADY UP TO DATE )N PRACTICE THESE LIMITATIONS OFTEN PREVENT THE USE OF CONTAINER MANAGED PERSISTENCE IN TODAYS DEPLOYMENTS %NHANCEMENTS IN NEWER VERSIONS OF THE %*" SPECIFICATION ARE DESIGNED TO ADDRESS MANY OF THESE SHORTCOMINGS (OWEVER BEAN MANAGED PERSISTENCE REMAINS A VERY IMPORTANT TECHNIQUE WITH THE CURRENTLY AVAILABLE APPLICATION SERVERS
%*"õõ%NHANCEMENTS %*" PUBLISHED IN !PRIL REPRESENTED A MAJOR REVISION TO THE %*" SPECIFICATION -ANY OF THE ENHANCEMENTS IN %*" WERE INCOMPATIBLE WITH THE CORRESPONDING CAPABILITIES IN %*" X 4O AVOID BREAKING %*" X COMPATIBLE BEANS %*" PROVIDES COMPLEMENTARY CAPABILITIES IN THESE AREAS ALLOWING SIDE BY SIDE COEXISTENCE OF %*" X AND %*" BEANS ! COMPLETE DESCRIPTION OF THE DIFFERENCES BETWEEN %*" X AND %*" IS WELL BEYOND THE SCOPE OF THIS BOOK (OWEVER SEVERAL OF THE DIFFERENCES WERE MOTIVATED BY DIFFICULTIES IN USING CONTAINER MANAGED PERSISTENCE UNDER THE %*" X SPECIFICATION AND THOSE CHANGES DIRECTLY AFFECT DATABASE PROCESSING WITHIN %*"S
#HAPTERçç
31,çANDç!PPLICATIONç3ERVERSç
/NE DIFFICULTY WITH %*" X HAS ALREADY BEEN MENTIONEDTHE DIFFICULTY OF MODELING COMPLEX OBJECTS THAT DRAW THEIR DATA FROM MULTIPLE DATABASE TABLES OR THAT CONTAIN NONRELATIONAL STRUCTURES LIKE ARRAYS AND HIERARCHICAL DATA 7ITH %*" X YOU COULD MODEL A COMPLEX OBJECT AS A FAMILY OF INTER RELATED ENTITY BEANS EACH DRAWN FROM ONE TABLE 4HIS APPROACH ALLOWED THE USE OF CONTAINER MANAGED PERSISTENCE BUT THE RELATIONSHIPS BETWEEN PIECES OF THE OBJECT NEED TO BE IMPLEMENTED IN APPLICATIONS CODE WITHIN THE BEAN )DEALLY THESE INTERNAL DETAILS WITHIN THE COMPLEX OBJECT SHOULD BE HIDDEN FROM APPLICATIONS CODE !LTERNATIVELY WITH %*" X YOU COULD MODEL A COMPLEX OBJECT AS A SINGLE ENTITY BEAN WITH DATA IN THE BEANS INSTANCE VARIABLES DRAWN FROM MULTIPLE RELATED TABLES 4HIS ACHIEVES THE DESIRED APPLICATION CODE TRANSPARENCY BUT CONTAINER MANAGED PERSISTENCE COULD BE USED WHEN AN ENTITY BEAN DRAWS ITS DATA FROM MULTIPLE TABLES %*" ADDRESSED THIS ISSUE THROUGH THE USE OF ABSTRACT ACCESSOR METHODS WHICH ARE USED TO SET AND RETRIEVE EVERY PERSISTENT INSTANCE VARIABLE WITHIN AN ENTITY BEAN 4HE CONTAINER ACTUALLY MAINTAINS THE STORAGE FOR THE VARIABLES AND THE VARIABLE VALUES 4HE BEAN EXPLICITLY CALLS A GET ACCESSOR METHOD TO RETRIEVE AN INSTANCE VARIABLE VALUE AND A SET ACCESSOR METHOD TO SET ITS VALUE 3IMILARLY THERE ARE GET AND SET ABSTRACT ACCESSOR METHODS FOR EVERY RELATIONSHIP THAT LINKS THE ROWS IN THE DATABASE THAT CONTRIBUTE DATA TO THE ENTITY BEAN -ANY TO MANY RELATIONSHIPS ARE EASILY HANDLED BY MAPPING THEM INTO *AVA COLLECTION VARIABLES 7ITH THESE NEW FEATURES THE CONTAINER HAS COMPLETE KNOWLEDGE OF ALL THE INSTANCE VARIABLES USED BY A BEAN AND OF EVERY ACCESS THAT CODE WITHIN THE BEAN MAKES TO THE INSTANCE VARIABLES 4HE ENTITY BEAN CAN REPRESENT A COMPLEX OBJECT THAT DRAWS DATA FROM MULTIPLE DATABASE TABLES HIDING THE DETAILS FROM THE APPLICATIONS CODE "UT CONTAINER MANAGED PERSISTENCE CAN NOW BE USED BECAUSE THE CONTAINER hKNOWSv ALL ABOUT THE VARIOUS PARTS OF THE OBJECT AND THE RELATIONSHIPS AMONG THE PARTS !NOTHER PROBLEM WITH THE %*" X SPECIFICATION IS THAT WHILE DATABASE INTERACTIONS WERE STANDARDIZED THE FINDER METHODS THAT ARE USED TO SEARCH THE ACTIVE ENTITY BEANS WERE NOT 4HE FINDER METHODS IMPLEMENT CAPABILITIES LIKE SEARCHING FOR A PARTICULAR ENTITY BEAN BY PRIMARY KEY OR SEARCHING FOR THE SET OF BEANS THAT MATCH A PARTICULAR CRITERION 7ITHOUT THIS STANDARDIZATION PORTABILITY ACROSS APPLICATION SERVERS WAS COMPROMISED AND SEARCHES OF ENTITY BEANS OFTEN REQUIRED RECOURSE TO SEARCHING THE UNDERLYING DATABASE %*" ADDRESSED THE SEARCHING LIMITATIONS THROUGH THE USE OF ABSTRACT SELECT METHODS THAT SEARCH ENTITY BEANS 4HE SELECT METHODS USE A NEWLY DEFINED %*" 1UERY ,ANGUAGE %*"1, 7HILE THE QUERY LANGUAGE IS BASED ON 31, IT INCLUDES CONSTRUCTS SUCH AS PATH EXPRESSIONS THAT ARE DECIDEDLY NONRELATIONAL &INALLY %*" WAS DESIGNED TO ALIGN WITH THE 31, STANDARD AND ITS ABSTRACT DATA TYPES 3UPPORT FOR THESE TYPES SOMEWHAT SIMPLIFIES THE INTERACTION BETWEEN ENTITY BEANS AND THE DATABASE FOR $"-3 PRODUCTS THAT SUPPORT ABSTRACT TYPES !T THIS TIME FEW $"-3 PRODUCTS SUPPORT THEM
%*"õõ%NHANCEMENTS
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4HE %*" SPECIFICATION PUBLISHED IN DRAFT FORM IN AND IN FINAL FORM IN MAKES THE CONTAINER DO MORE WORK THUS MAKING PROGRAMMING LESS WORK AND MUCH SIMPLER )T DECREASES THE AMOUNT OF PROGRAM CODE THAT DEVELOPERS MUST PROVIDE INCLUDING ELIMINATING THE REQUIREMENT FOR EJBMETHOD CALLBACK METHODS AND REDUCES THE COMPLEXITY OF ENTITY BEAN PROGRAMMING
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31,ç4ODAYçANDç4OMORROW
%*" SIMPLIFIES THE APPLICATION PROGRAMMING INTERFACE !0) IN SEVERAL WAYS s -ETADATA ANNOTATIONS CAN BE USED AS AN ALTERNATIVE TO MORE COMPLEX DEPLOYMENT DESCRIPTIONS !NNOTATIONS CAN BE USED TO SPECIFY BEAN TYPES TRANSACTION AND SECURITY SETTINGS OBJECT RELATIONAL MAPPING AND FOR THE INJECTION OF ENVIRONMENT OR RESOURCE REFERENCES s $EPENDENCY INJECTION CAN BE USED INSTEAD OF %*" ENVIRONMENT AND RESOURCE REFERENCES s "EAN DEVELOPERS CAN DESIGNATE ANY ARBITRARY METHOD AS A CALLBACK METHOD MAKING THE USE OF SPECIFIC CALLBACK METHODS UNNECESSARY s )NTERCEPTOR METHODS MAY BE DEFINED IN SESSION BEANS STATELESS OR STATEFUL OR IN MESSAGE DRIVEN BEANS !N INTERCEPTOR METHOD IS A METHOD THAT INTERCEPTS A BUSINESS METHOD INVOCATION !N INTERCEPTOR CLASS MAY ALSO BE USED INSTEAD OF DEFINING THE INTERCEPTOR METHOD IN THE BEAN CLASS s #LIENTS CAN DIRECTLY INVOKE A METHOD ON THE %*" WITHOUT HAVING TO CREATE A BEAN INSTANCE 3ESSION BEANS HAVE BEEN ENHANCED AND SIMPLIFIED IN A NUMBER OF WAYS s 3ESSION BEANS ARE SIMPLER IN %*" BECAUSE THEY ARE PURE *AVA CLASSES THAT DO NOT HAVE TO IMPLEMENT SESSION BEAN INTERFACES ! SESSION BEAN MAY HAVE REMOTE LOCAL OR BOTH REMOTE AND LOCAL INTERFACES AND THE HOME INTERFACE IS OPTIONAL s -ETADATA ANNOTATIONS ARE USED TO SPECIFY BEAN OR INTERFACE AND RUNTIME PROPERTIES OF SESSION BEANS s #ALLBACK LISTENERS ARE SUPPORTED FOR BOTH STATEFUL AND STATELESS SESSION BEANS s $EVELOPERS CAN USE EITHER ANNOTATIONS OR DEPLOYMENT DESCRIPTORS TO INJECT ENVIRONMENT ENTITIES RESOURCES OR %*" CONTEXT s )NTERCEPTOR METHODS OR CLASSES ARE SUPPORTED FOR BOTH STATELESS AND STATEFUL SESSION BEANS -ESSAGE DRIVEN BEANS HAVE BEEN ENHANCED AND SIMPLIFIED IN SEVERAL WAYS s 4HEY CAN IMPLEMENT THE -ESSAGE,ISTENER INTERFACE INSTEAD OF THE -ESSAGE$RIVEN INTERFACE s -ETADATA ANNOTATION SIMPLIFIES THE SPECIFICATION OF THE BEAN OR INTERFACE AND RUNTIME PROPERTIES s #ALLBACK LISTENERS ARE SUPPORTED s $EPENDENCY MAY BE USED INSTEAD OF DEPLOYMENT DESCRIPTORS s )NTERCEPTOR METHODS OR CLASSES CAN BE USED 4HE ENTITY BEANS PERSISTENCE !0) HAS BEEN ENHANCED AND SIMPLIFIED IN SEVERAL WAYS &IRST %*" STANDARDIZES THE 0/*/ 0LAIN /LD *AVA /BJECT PERSISTENCE MODEL AND SIMPLIFIES ENTITY BEANS %NTITY BEANS BECOME CONCRETE *AVA CLASSES THAT DO NOT REQUIRE ANY INTERFACES 4HE ENTITY BEAN CLASSES DIRECTLY SUPPORT POLYMORPHISM AND INHERITANCE 3ECOND %*" INCLUDES THE NEW %NTITY-ANAGER !0) FOR USE IN CREATING FINDING REMOVING AND
#HAPTERçç
31,çANDç!PPLICATIONç3ERVERSç
UPDATING ENTITIES 4HIRD ANNOTATIONS CAN BE USED INSTEAD OF DEPLOYMENT DESCRIPTORS TO GREATLY SIMPLIFY THE DEVELOPMENT OF ENTITIES &OURTH THE QUERY LANGUAGE CAPABILITIES FOR ENTITIES ARE GREATLY IMPROVED &IFTH CALLBACK LISTENERS ARE SUPPORTED WITH METHODS SPECIFIED USING EITHER ANNOTATIONS OR DEPLOYMENT DESCRIPTORS &INALLY THE %*" PERSISTENCE ENGINE CAN BE USED OUTSIDE THE CONTAINER
/PENõ3OURCEõ!PPLICATIONõ$EVELOPMENT 4HE DEVELOPMENT AND MATURATION OF THE )NTERNET HAS LED TO MANY INNOVATIONS IN THE AREA OF APPLICATION SERVERS APPLICATION DELIVERY AND HOW THESE RELATE TO 31, BASED DATABASES 4HE OPEN SOURCE COMMUNITY HAS BEEN QUITE ACTIVE IN THESE AREAS !PACHE IS BY FAR THE MOST COMMONLY USED OPEN SOURCE WEB SERVER &OR CONSTRUCTION OF THE WEB APPLICATIONS DEVELOPERS OFTEN USE A COMBINATION OF ASYNCHRONOUS *AVA3CRIPT AND 8-, KNOWN BY THE TERM !JAX OR THE ACRONYM !*!8 FOR !SYNCHRONOUS *AVA3CRIPT AND 8-, /THER SCRIPTING LANGUAGES SUCH AS 0(0 CAN BE USED IN PLACE OF *AVA3CRIPT AND 8-, IS TECHNICALLY NOT REQUIRED WHICH IS WHY THE TERM !JAX IS PREFERRED OVER THE ORIGINAL ACRONYM !*!8 !LTHOUGH THE ACRONYM WAS COINED IN TECHNIQUES FOR ASYNCHRONOUSLY LOADING WEB CONTENT DATE BACK TO THE MID S 7EB APPLICATIONS USING !JAX CAN RETRIEVE DATA ASYNCHRONOUSLY USING A BACKGROUND PROCESS THAT DOES NOT INTERFERE WITH THE DISPLAY AND BEHAVIOR OF THE EXISTING WEB PAGE $ATA IS RETRIEVED USING THE 8-,(TTP2EQUEST OBJECT OR FOR BROWSERS THAT DO NOT SUPPORT THIS OBJECT USING REMOTE SCRIPTING $ATABASES USED WITH !JAX TO STORE AND RETRIEVE PERSISTENT DATA ARE ALMOST ALWAYS OPEN SOURCE RELATIONAL PRODUCTS SUCH AS -Y31, !NOTHER POPULAR PLATFORM FOR DELIVERING CONTENT AND APPLICATIONS VIA WEB PAGES IS ,!-0 ,INUX !PACHE -Y31, AND 0(00YTHON0ERL )N FACT MUCH OF THE h7EB v PHENOMENON IS BUILT ON ,!-0 WHICH PROVIDES A LOW COST 31, DRIVEN INFRASTRUCTURE FOR WEB BASED APPLICATIONS 4ODAY ,!-0 PLAYS A DOMINANT ROLE IN THE )NTERNET AND NEW COMPONENTS HAVE BEEN INTRODUCED TO FORM VARIATIONS SUCH AS ,!-2 WHERE THE LANGUAGE BECOMES 2UBY ON 2AILS 2/2 !DDITIONALLY AS )NTERNET BASED SERVICE SOLUTIONS SUCH AS )NFRASTRUCTURE AS A 3ERVICE )AA3 0LATFORM AS A 3ERVICE 0AA3 AND 3OFTWARE AS A 3ERVICE 3AA3 GAIN POPULARITY ,!-0 APPLICATION SERVER TECHNOLOGIES WILL CONTINUE TO ADVANCE AND EVOLVE 4HESE SERVICES COLLECTIVELY INCORPORATED INTO h#LOUDv COMPUTING WILL RELY HEAVILY ON ,!-0 AND ITS IMMEDIATE SUCCESSORS
!PPLICATIONõ3ERVERõ#ACHING
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/N A HIGH VOLUME WEB SITE DATABASE ACCESS CAN BECOME A BOTTLENECK TO OVERALL WEB SITE PERFORMANCE "ECAUSE OF THE %*" STRUCTURE THE DATABASE ACCESS REQUIRED BY THE BUSINESS LOGIC OF THE APPLICATION IS INCREASED PERHAPS SUBSTANTIALLY BY THE DATABASE ACCESS REQUIRED TO SUPPORT ENTITY BEAN DATABASE SYNCHRONIZATION )F THE WEB SITE IMPLEMENTS HEAVY PERSONALIZATION OF ITS USER INTERACTION THAT IS IF A HIGH PERCENTAGE OF ITS PAGES ARE DYNAMICALLY GENERATED BASED ON THE PROFILE OF THE PARTICULAR USER WHO IS VIEWING THEM THEN THE DATABASE ACCESS LOAD CAN BE EVEN HIGHER !T THE EXTREME EVERY CLICK ON A HIGHLY PERSONALIZED WEB SITE COULD REQUIRE RETRIEVAL OF USER PROFILE DATA FROM THE DATABASE TO DRIVE PAGE GENERATION &INALLY USER INTERACTION WITH A WEB SITE HAPPENS IN REAL TIME AND IS AFFECTED BY PEAK LOAD ACTIVITY 4HE AVERAGE RATE OF CLICK PROCESSING IS LESS IMPORTANT THAN PEAK LOAD ACTIVITY IN DETERMINING WHETHER USERS PERCEIVE THE SITE AS FAST OR SLUGGISH
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0ARTç6)ç
31,ç4ODAYçANDç4OMORROW
4HE 7EB HAS ALREADY SHOWN AN EFFECTIVE ARCHITECTURE FOR DEALING WITH THESE TYPES OF PEAK LOAD )NTERNET VOLUME DEMANDSTHROUGH WEB PAGE CACHING AND HORIZONTAL SCALING 7ITH CACHING COPIES OF HEAVILY ACCESSED WEB PAGES ARE PULLED FORWARD IN THE NETWORK AND REPLICATED !S A RESULT THE TOTAL NETWORK CAPACITY FOR SERVING WEB PAGES IS INCREASED AND THE AMOUNT OF NETWORK TRAFFIC ASSOCIATED WITH THOSE PAGE HITS IS REDUCED 7ITH HORIZONTAL SCALING WEB SITE CONTENT IS REPLICATED ACROSS TWO OR MORE WEB SERVERS UP TO DOZENS OR EVEN HUNDREDS OF SERVERS WHOSE AGGREGATE CAPACITY FOR SERVING PAGES IS MUCH GREATER THAN ANY SINGLE SERVER 3IMILAR CACHING AND HORIZONTAL SCALING ARCHITECTURES ARE USED TO INCREASE THE CAPACITY OF APPLICATION SERVERS -OST COMMERCIAL APPLICATION SERVERS TODAY IMPLEMENT BEAN CACHING WHERE COPIES OF FREQUENTLY USED ENTITY BEANS ARE KEPT IN THE APPLICATION SERVERS MEMORY )N ADDITION APPLICATION SERVERS ARE OFTEN DEPLOYED IN BANKS OR CLUSTERS WITH EACH APPLICATION SERVER PROVIDING IDENTICAL BUSINESS LOGIC AND APPLICATION PROCESSING CAPABILITY )N FACT MANY COMMERCIAL APPLICATION SERVERS USE HORIZONTAL SCALING WITHIN A SINGLE SERVER TO TAKE ADVANTAGE OF SYMMETRIC MULTIPROCESSING 3-0 CONFIGURATIONS )TS TYPICAL FOR AN EIGHT PROCESSOR APPLICATION SERVER TO BE RUNNING UP TO EIGHT INDEPENDENT COPIES OF THE APPLICATION SERVER SOFTWARE OPERATING IN PARALLEL &IGURE SHOWS A TYPICAL APPLICATION SERVER CONFIGURATION WITH THREE FOUR PROCESSOR SERVERS % # #! # #
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#HAPTERçç
31,çANDç!PPLICATIONç3ERVERSç
5NFORTUNATELY HORIZONTAL SCALING AND CACHING TEND TO WORK AGAINST ONE ANOTHER WHEN DEALING WITH STATEFUL DATA SUCH AS THAT STORED IN AN ENTITY BEAN OR A DATABASE 7ITHOUT SPECIAL CACHE SYNCHRONIZATION LOGIC UPDATES MADE TO A BEAN STORED IN THE CACHE OF ONE SERVER INSTANCE WILL NOT AUTOMATICALLY APPEAR IN THE OTHER CACHES WITH THE POTENTIAL TO CAUSE INCORRECT AND INCONSISTENT RESULTS #ONSIDER FOR EXAMPLE WHAT HAPPENS TO QUANTITY ON HAND DATA IF THREE OR FOUR SEPARATE CACHES CONTAIN COPIES OF AN ENTITY BEAN FOR A SINGLE PRODUCT AND THE BUSINESS LOGIC OF THE APPLICATION SERVER UPDATES THOSE VALUES 4HE CACHES WILL VERY QUICKLY CONTAIN DIFFERENT VALUES FOR QUANTITY ON HAND NONE OF WHICH ARE ACCURATE 4HE CACHE SYNCHRONIZATION LOGIC REQUIRED TO DETECT AND PREVENT SUCH A SITUATION UNFORTUNATELY CARRIES WITH IT A GREAT DEAL OF OVERHEAD !BSOLUTE SYNCHRONIZATION REQUIRES A FULL TWO PHASE COMMIT PROTOCOL DESCRIBED IN #HAPTER AMONG THE CACHES $ATABASE CACHES CAN ADDRESS THE PROBLEMS OF MULTIPLE BEAN CACHES WITHIN A SINGLE 3-0 SERVER AS SHOWN IN &IGURE "Y CACHING AT THE DATABASE LEVEL INSTEAD OF THE BEAN LEVEL ONE DATABASE CACHE PROVIDES CONSISTENCY ACROSS ALL OF THE APPLICATION SERVER INSTANCES ON A SINGLE SERVER 3YNCHRONIZATION ACROSS MULTIPLE PHYSICAL SERVERS IS STILL REQUIRED HOWEVER )F THE RATIO OF DATABASE READS TO DATABASE UPDATES IS HIGH AS FOR EXAMPLE IN A HIGHLY PERSONALIZED WEB SITE THE OVERHEAD OF CACHE SYNCHRONIZATION WILL REMAIN RELATIVELY LOW AND THE BENEFITS OF HORIZONTAL SCALING CAN BE SIGNIFICANT
! "
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}
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0ARTç6)ç
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/RACLE HAS USED DATABASE CACHING WITHIN ITS OWN /RACLE !PPLICATION 3ERVER AND HAS ATTEMPTED TO USE CACHING AS A COMPETITIVE ADVANTAGE )"- IS NATURALLY POSITIONED TO OFFER INTEGRATED DATABASE CACHING FOR ITS $" $"-3 BUT HAS NOT INTRODUCED SUCH A CAPABILITY AT THIS WRITING 3EVERAL THIRD PARTY PRODUCTS HAVE BEEN INTRODUCED AS DATABASE CACHES FOR APPLICATION SERVERS INCLUDING PRODUCTS FROM SOME OF THE OBJECT ORIENTED DATABASE VENDORS AND FROM IN MEMORY DATABASE VENDORS 7HETHER DATABASE CACHING WILL SUBSTANTIALLY IMPACT THE APPLICATION SERVER MARKET IS STILL AN OPEN QUESTION
3UMMARY 4HIS CHAPTER DESCRIBED APPLICATION SERVERS AND THE ROLE THEY PLAY LINKING THE 7ORLD 7IDE 7EB TO BACK END ENTERPRISE SYSTEMS INCLUDING ENTERPRISE DATABASES s 0OPULAR APPLICATION SERVERS IMPLEMENT THE *%% SPECIFICATION WHICH STANDARDIZES DATABASE ACCESS THROUGH A *$"# !0) s "USINESS LOGIC WITHIN AN APPLICATION SERVER IS IMPLEMENTED BY %*"S WHICH MAY BE SESSION BEANS OR ENTITY BEANS s 3ESSION BEANS EMBODY USER SESSIONS 4HEY CAN ACCESS DATABASES DIRECTLY THROUGH *$"# CALLS s 3TATELESS SESSION BEANS SUPPORT VERY SIMPLE ONE TRANSACTION PER INVOCATION DATA ACCESS s 3TATEFUL BEANS SUPPORT TRANSACTIONS THAT CROSS INVOCATIONS BUT THEIR LOGIC MUST HANDLE THE NEED TO PERSIST STATE ACROSS PASSIVATIONS AND ACTIVATIONS s %NTITY BEANS EMBODY REAL WORLD OBJECTS AND CORRESPOND TO ROWS IN DATABASE TABLES 4HEY ARE ALWAYS STATEFUL s %NTITY BEANS CAN USE CONTAINER MANAGED PERSISTENCE WHERE THE APPLICATION SERVER AUTOMATICALLY HANDLES ENTITY BEAN DATABASE SYNCHRONIZATION s !LTERNATIVELY ENTITY BEANS CAN TAKE RESPONSIBILITY FOR THEIR OWN DATABASE SYNCHRONIZATION UNDER THE BEAN MANAGED PERSISTENCE SCHEME s /PEN SOURCE ARCHITECTURES SUCH AS !JAX ,!-0 AND ,!-2 CONTINUE TO GROW IN POPULARITY FOR INTEGRATING DATABASES WITH WEB SITES
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VER THE LAST SEVERAL DECADES COMPUTER NETWORKING HAS RADICALLY TRANSFORMED THE LANDSCAPE OF CORPORATE COMPUTING )N MOST COMPANIES EVERY PERSONAL COMPUTER IS CONNECTED TO A LOCAL AREA NETWORK ,!. 0OWERFUL ,!. ATTACHED WORKGROUP SERVERS MEET THE COMPUTING NEEDS OF INDIVIDUAL DEPARTMENTS #ORPORATEWIDE NETWORKS INTERCONNECT THE ,!.S WITHIN A BUILDING OR CAMPUS AND CONNECT THEM TO DIVISIONAL OR CORPORATE DATA CENTERS !DDITIONAL LINKS INTERCONNECT CORPORATE LOCATIONS AROUND THE WORLD 4HE )NTERNET PROVIDES A NETWORK OF NETWORKS LINKING COMPANIES TO ONE ANOTHER AND TO INDIVIDUAL CUSTOMERS !PPLICATION PROGRAMS RUN ON COMPUTERS AT EVERY LEVEL AND AT EVERY LOCATION WITHIN THIS NETWORKED ENVIRONMENT )N THIS NEW HIGHLY NETWORKED ENVIRONMENT COMPUTER DATA DOES NOT RESIDE ON A SINGLE SYSTEM UNDER THE CONTROL OF A SINGLE $"-3 )NSTEAD DATA WITHIN AN ORGANIZATION IS SPREAD ACROSS MANY DIFFERENT SYSTEMS EACH WITH ITS OWN DATABASE MANAGER /FTEN THE VARIOUS COMPUTER SYSTEMS AND DATABASE MANAGEMENT SYSTEMS COME FROM DIFFERENT MANUFACTURERS !S COMPANIES TRY TO INTERCONNECT THEIR DATA PROCESSING SYSTEMS VIA THE )NTERNET THE CHALLENGE BECOMES EVEN GREATER %VEN IF A COMPANY HAS MANAGED TO STANDARDIZE ON A SINGLE COMPANYWIDE $"-3 AND ON DATABASE STRUCTURES THOSE STANDARDS WONT APPLY TO ITS SUPPLIERS OR CUSTOMERS AS IT TRIES TO BUILD EXTERNAL LINKS TO CONDUCT BUSINESS ELECTRONICALLY 4HESE TRENDS HAVE LED TO A STRONG FOCUS IN THE COMPUTER INDUSTRY AND IN THE DATA MANAGEMENT COMMUNITY ON THE PROBLEMS OF DATABASE MANAGEMENT IN A NETWORKED ENVIRONMENT 4HIS CHAPTER DISCUSSES THE CHALLENGES OF MANAGING DISTRIBUTED DATA THE VARIETY OF ARCHITECTURAL APPROACHES AND SOME OF THE PRODUCTS THAT $"-3 VENDORS HAVE OFFERED TO MEET THOSE CHALLENGES
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4HEõ#HALLENGEõOFõ$ISTRIBUTEDõ$ATAõ-ANAGEMENT 7HEN THE FOUNDATIONS OF RELATIONAL DATABASE MANAGEMENT AND THE 31, LANGUAGE WERE BEING LAID IN THE S ALMOST ALL COMMERCIAL DATA PROCESSING HAPPENED ON LARGE CENTRALIZED COMPUTER SYSTEMS 4HE COMPANYS DATA WAS STORED ON MASS STORAGE ATTACHED TO THE CENTRAL SYSTEM 4HE BUSINESS PROGRAMS THAT PROCESSED TRANSACTIONS AND GENERATED REPORTS RAN ON THE CENTRAL SYSTEM AND ACCESSED THE DATA -UCH OF THE WORKLOAD OF THE CENTRAL SYSTEM WAS BATCH PROCESSING /NLINE USERS ACCESSED THE CENTRAL SYSTEM THROUGH hDUMBv COMPUTER TERMINALS WITH NO PROCESSING POWER OF THEIR OWN 4HE CENTRAL SYSTEM FORMATTED INFORMATION TO BE DISPLAYED FOR THE ONLINE USER AND ACCEPTED DATA TYPED BY THE USER FOR PROCESSING )N THIS ENVIRONMENT THE ROLES OF A RELATIONAL DATABASE SYSTEM AND ITS 31, LANGUAGE WERE CLEAR AND WELL CONTAINED 4HE $"-3 HAD RESPONSIBILITY FOR ACCEPTING STORING AND RETRIEVING DATA BASED ON REQUESTS EXPRESSED IN THE 31, 4HE BUSINESS PROCESSING LOGIC RESIDED OUTSIDE THE DATABASE AND WAS THE RESPONSIBILITY OF THE BUSINESS PROGRAMS DEVELOPED AND MAINTAINED BY THE INFORMATION SYSTEMS STAFF 4HE PROGRAMS AND THE $"-3 SOFTWARE EXECUTED ON THE SAME CENTRALIZED SYSTEM WHERE THE DATA WAS STORED SO THE PERFORMANCE OF THE SYSTEM WAS NOT AFFECTED BY EXTERNAL FACTORS LIKE NETWORK TRAFFIC OR OUTSIDE SYSTEM FAILURES #OMMERCIAL DATA PROCESSING IN A MODERN CORPORATION HAS EVOLVED A LONG WAY FROM THE CENTRALIZED ENVIRONMENT OF THE S &IGURE SHOWS A PORTION OF A COMPUTER NETWORK THAT YOU MIGHT FIND IN A MANUFACTURING COMPANY A FINANCIAL SERVICES FIRM OR IN A DISTRIBUTION COMPANY TODAY $ATA IS STORED ON A VARIETY OF COMPUTER SYSTEMS IN THE NETWORK s -AINFRAMES 4HE COMPANYS CORE DATA PROCESSING APPLICATIONS SUCH AS ACCOUNTING AND PAYROLL RUN ON AN )"- MAINFRAME 4HE OLDEST APPLICATIONS DEVELOPED AND MAINTAINED OVER THE LAST OR YEARS STILL STORE THEIR DATA IN HIERARCHICAL )-3 DATABASES 4HE COMPANY HAS A STRATEGY TO MIGRATE THESE APPLICATIONS TO $" OVER TIME AND ALL NEW APPLICATION DEVELOPMENT USES $" AS ITS DATABASE MANAGER MANY OF THOSE RUNNING ON SERVERS INSTEAD OF THE MAINFRAME .OTE THAT THE DISTINCTION BETWEEN MAINFRAMES AND SERVERS HAS BEEN BLURRING OVER TIME AS MAINFRAMES SHRINK IN SIZE AND SERVERS GROW s 7ORKSTATIONS AND 5.)8 AND ,INUX BASED SERVERS 4HE COMPANYS ENGINEERING ORGANIZATION USES 5.)8 BASED WORKSTATIONS AND SERVERS FROM 3UN -ICROSYSTEMS FOR ENGINEERING DESIGN TESTING AND SUPPORT %NGINEERING TEST RESULTS AND SPECIFICATIONS ARE STORED IN AN /RACLE DATABASE 4HE COMPANY ALSO USES /RACLE DATABASES RUNNING ON COMMODITY HARDWARE SERVERS RUNNING ,INUX LOCATED IN ITS SIX DISTRIBUTION CENTERS TO MANAGE INVENTORY AND TO PROCESS ORDERS 4HE ,INUX SERVERS ARE A MORE RECENT ADDITION AND THIS DEPLOYMENT HAS BEEN SUCCESSFUL ENOUGH THAT ADDITIONAL DEPLOYMENTS USING ,INUX ARE PLANNED s ,!. SERVERS !LL OF THE COMPANYS DEPARTMENTS HAVE INDIVIDUAL 0# ,!.S TO SHARE PRINTERS AND FILES 3OME OF THE DEPARTMENTS ALSO HAVE LOCAL DATABASES TO SUPPORT THEIR WORK &OR EXAMPLE THE PERSONNEL DEPARTMENT HAS PURCHASED A HUMAN RESOURCES MANAGEMENT SYSTEM SOFTWARE PACKAGE AND IT USES 31, 3ERVER ON 7INDOWS TO STORE ITS DATA )N THE FINANCIAL PLANNING DEPARTMENT THE DATA PROCESSING STAFF HAS BUILT A CUSTOM WRITTEN CORPORATE PLANNING APPLICATION WHICH USES )NFORMIX 5NIVERSAL 3ERVER s $ESKTOP PERSONAL COMPUTERS !LL OF THE COMPANYS OFFICE WORKERS USE PERSONAL COMPUTERS -ANY OF THE ADMINISTRATIVE ASSISTANTS AND SOME OF THE SENIOR MANAGERS MAINTAIN PERSONAL DATABASES USING %XCEL SPREADSHEETS -ICROSOFT !CCESS OR ONE OF THE PERSONAL $"-3 PRODUCTS SUCH AS /RACLE 0ERSONAL %DITION
#HAPTERçç
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s -OBILE LAPTOP 0#S 4HE COMPANY RECENTLY PURCHASED A SALES FORCE AUTOMATION SOFTWARE PACKAGE AND EQUIPPED EVERY SALESPERSON WITH A LAPTOP 0# 4HE LAPTOP RUNS SALES PRESENTATIONS SENDS AND RECEIVES E MAIL AND ALSO HOLDS A LOCAL LIGHTWEIGHT DATABASE 31, !NYWHERE FROM 3YBASE WITH RECENT PRODUCT PRICING AND AVAILABILITY DATA 4HE DATABASE ALSO CAPTURES ORDERS ENTERED BY THE SALESPERSON !T NIGHT THE LAPTOP 0# CONNECTS TO THE CORPORATE NETWORK OVER WHATEVER )NTERNET CONNECTION THE SALESPERSON HAS AVAILABLE TRANSMITS ITS ORDERS AND RECEIVES UPDATED INFORMATION FOR ITS LOCAL COPY OF THE PRODUCTS DATABASE s (ANDHELD DEVICES 4HE COMPANYS MANAGEMENT TEAM HAS WIDELY ADOPTED HANDHELD )NTERNET CAPABLE PERSONAL DEVICES SMARTPHONES )N ADDITION TO THE PERSONAL CALENDAR AND ADDRESS BOOK FUNCTIONS APPLICATIONS RUNNING ON THE SMARTPHONE CAN USE WIRELESS NETWORK CONNECTIONS TO CHECK PRICES AND ENTER CUSTOMER ORDERS 4HE WIRELESS NETWORK CAN ALSO BE USED TO ALERT USERS VIA THEIR SMARTPHONES OF IMPORTANT DATABASE CHANGES SUCH AS PRICE UPDATES OR PRODUCT SHORTAGES s )NTERNET CONNECTIONS 4HE COMPANY HAS AN )NTERNET WEB SITE WHERE CUSTOMERS DEALERS AND DISTRIBUTORS CAN FIND OUT THE LATEST INFORMATION ABOUT ITS PRODUCTS AND SERVICES !T FIRST THIS WAS AN INFORMATION ONLY WEB SITE BUT COMPETITORS HAVE RECENTLY BEGUN ACCEPTING CUSTOMER ORDERS DIRECTLY VIA THE )NTERNET /NE OF THE CORPORATE )3 DEPARTMENTS HIGHEST PRIORITIES IS TO RESPOND TO THIS COMPETITIVE CHALLENGE BY SUPPORTING E COMMERCE TRANSACTIONS ON THE COMPANYS WEB SITE
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7ITH DATA SPREAD OVER MANY DIFFERENT SYSTEMS ITS EASY TO IMAGINE REQUESTS THAT SPAN MORE THAN ONE DATABASE AND THE POSSIBILITY FOR CONFLICTING DATA AMONG THE DATABASES s !N ENGINEER NEEDS TO COMBINE LAB TEST RESULTS ON AN ENGINEERING WORKSTATION WITH PRODUCTION FORECASTS ON THE MAINFRAME TO CHOOSE AMONG THREE ALTERNATIVE TECHNOLOGIES s ! FINANCIAL PLANNER NEEDS TO LINK FINANCIAL FORECASTS IN AN )NFORMIX DATABASE TO HISTORICAL FINANCIAL DATA ON THE MAINFRAME s ! PRODUCT MANAGER NEEDS TO KNOW HOW MUCH INVENTORY OF A PARTICULAR PRODUCT IS IN EACH DISTRIBUTION CENTER DATA STORED ON SIX ,INUX SERVERS TO PLAN PRODUCT OBSOLESCENCE s #URRENT PRICING DATA NEEDS TO BE DOWNLOADED DAILY FROM THE MAINFRAME TO THE DISTRIBUTION CENTER SERVERS AND ALSO TO ALL OF THE SALES FORCES LAPTOP COMPUTERS s /RDERS NEED TO BE UPLOADED DAILY FROM THE LAPTOP SYSTEMS AND PARCELED OUT TO THE DISTRIBUTION CENTERS AGGREGATE ORDER DATA FROM THE DISTRIBUTION CENTERS MUST BE UPLOADED TO THE MAINFRAME SO THAT THE MANUFACTURING PLAN CAN BE ADJUSTED s 3ALESPEOPLE MAY ACCEPT CUSTOMER ORDERS AND MAKE SHIPMENT DATE ESTIMATES FOR POPULAR PRODUCTS BASED ON THEIR LOCAL DATABASES WITHOUT KNOWING THAT OTHER SALESPEOPLE HAVE MADE SIMILAR COMMITMENTS /RDERS MUST BE RECONCILED AND PRIORITIZED AND REVISED SHIPMENT ESTIMATES PROVIDED TO CUSTOMERS s %NGINEERING CHANGES MADE IN THE WORKSTATION DATABASES MAY AFFECT PRODUCT COSTS AND PRICING 4HESE CHANGES MUST BE PROPAGATED THROUGH THE MAINFRAME SYSTEMS AND OUT TO THE WEB SITE THE DISTRIBUTION CENTERS AND THE SALES FORCE LAPTOPS s -ANAGERS THROUGHOUT THE COMPANY WANT TO QUERY THE VARIOUS SHARED DATABASES USING THE 0#S ON THEIR DESKTOPS !S THESE EXAMPLES SUGGEST EFFECTIVE WAYS OF DISTRIBUTING DATA MANAGING DISTRIBUTED DATA AND PROVIDING ACCESS TO DISTRIBUTED DATA HAVE BECOME CRITICAL AS DATA PROCESSING HAS MOVED TO A DISTRIBUTED COMPUTING MODEL 4HE LEADING $"-3 VENDORS ARE COMMITTED TO DELIVERING DISTRIBUTED DATABASE MANAGEMENT AND CURRENTLY OFFER A VARIETY OF PRODUCTS THAT SOLVE SOME OF THE DISTRIBUTED DATA PROBLEMS ILLUSTRATED BY THESE EXAMPLES $ISTRIBUTED DATA MANAGEMENT HAS ALSO BEEN THE FOCUS OF EXTENSIVE UNIVERSITY AND CORPORATE RESEARCH AND MANY TECHNICAL ARTICLES HAVE BEEN PUBLISHED ABOUT THE THEORY OF DISTRIBUTED DATA MANAGEMENT AND THE TRADE OFFS INVOLVED 4HERE IS GENERAL AGREEMENT AMONG THE RESEARCHERS ABOUT THE IDEAL CHARACTERISTICS THAT SHOULD BE PROVIDED BY A SCHEME TO MANAGE DISTRIBUTED DATABASES s ,OCATION TRANSPARENCY 4HE USER SHOULDNT HAVE TO WORRY ABOUT WHERE THE DATA IS PHYSICALLY LOCATED 4HE $"-3 SHOULD PRESENT ALL DATA AS IF IT WERE LOCAL AND BE RESPONSIBLE FOR MAINTAINING THAT ILLUSION s (ETEROGENEOUS SYSTEMS 4HE $"-3 SHOULD SUPPORT DATA STORED ON DIFFERENT SYSTEMS WITH DIFFERENT ARCHITECTURES AND PERFORMANCE LEVELS INCLUDING 0#S WORKSTATIONS ,!. SERVERS MINICOMPUTERS AND MAINFRAMES s .ETWORK TRANSPARENCY %XCEPT FOR DIFFERENCES IN PERFORMANCE THE $"-3 SHOULD WORK THE SAME WAY OVER DIFFERENT NETWORKS FROM HIGH SPEED ,!.S TO LOW SPEED TELEPHONE LINKS
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31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
s $ISTRIBUTED QUERIES 4HE USER SHOULD BE ABLE TO JOIN DATA FROM ANY OF THE TABLES IN THE DISTRIBUTED DATABASE EVEN IF THE TABLES ARE LOCATED ON DIFFERENT PHYSICAL SYSTEMS s $ISTRIBUTED UPDATES 4HE USER SHOULD BE ABLE TO UPDATE DATA IN ANY TABLE FOR WHICH THE USER HAS THE NECESSARY PRIVILEGES WHETHER THAT TABLE IS ON THE LOCAL SYSTEM OR ON A REMOTE SYSTEM s $ISTRIBUTED TRANSACTIONS 4HE $"-3 SHOULD SUPPORT DISTRIBUTED TRANSACTIONS USING #/--)4 AND 2/,,"!#+ ACROSS SYSTEM BOUNDARIES MAINTAINING THE INTEGRITY OF THE DISTRIBUTED DATABASE EVEN IN THE FACE OF NETWORK FAILURES AND FAILURES OF INDIVIDUAL SYSTEMS s 3ECURITY 4HE $"-3 MUST PROVIDE A SECURITY SCHEME ADEQUATE TO PROTECT THE ENTIRE DISTRIBUTED DATABASE FROM UNAUTHORIZED FORMS OF ACCESS s 5NIVERSAL ACCESS 4HE $"-3 SHOULD PROVIDE UNIVERSAL UNIFORM ACCESS TO ALL OF THE ORGANIZATIONS DATA .O CURRENT DISTRIBUTED $"-3 PRODUCT EVEN COMES CLOSE TO MEETING THIS IDEAL AND ITS UNLIKELY THAT ANY PRODUCT EVER WILL )N PRACTICE FORMIDABLE OBSTACLES MAKE IT DIFFICULT TO PROVIDE EVEN SIMPLE FORMS OF DISTRIBUTED DATABASE MANAGEMENT 4HESE OBSTACLES INCLUDE s 0ERFORMANCE )N A CENTRALIZED DATABASE THE PATH FROM THE $"-3 TO THE DATA HAS AN ACCESS SPEED OF A FEW MILLISECONDS AND A DATA TRANSFER RATE OF MILLIONS OF CHARACTERS PER SECOND %VEN ON A FAST LOCAL AREA NETWORK ACCESS SPEEDS LENGTHEN TO HUNDREDTHS OR TENTHS OF A SECOND AND TRANSFER RATES CAN FALL TO CHARACTERS PER SECOND OR LESS /N A MODEM LINK DATA ACCESS MAY TAKE SECONDS OR MINUTES AND A FEW THOUSAND CHARACTERS PER SECOND MAY BE THE MAXIMUM EFFECTIVE THROUGHPUT 4HIS VAST DIFFERENCE IN SPEEDS CAN DRAMATICALLY SLOW THE PERFORMANCE OF REMOTE DATA ACCESS s )NTEGRITY $ISTRIBUTED TRANSACTIONS REQUIRE ACTIVE COOPERATION BY TWO OR MORE INDEPENDENT COPIES OF THE $"-3 SOFTWARE RUNNING ON DIFFERENT COMPUTER SYSTEMS IF THE TRANSACTIONS ARE TO REMAIN ALL OR NOTHING PROPOSITIONS 3PECIAL TWO PHASE COMMIT TRANSACTION PROTOCOLS MUST BE USED 4HESE PROTOCOLS GENERATE A GREAT DEAL OF NETWORK TRAFFIC AND LOCK PARTS OF THE DATABASES THAT ARE PARTICIPATING IN THE DISTRIBUTED TRANSACTION FOR LONG PERIODS s 3TATIC 31, ! STATIC EMBEDDED 31, STATEMENT IS COMPILED AND STORED IN THE DATABASE AS AN APPLICATION PLAN 7HEN A QUERY COMBINES DATA FROM TWO OR MORE DATABASES WHERE SHOULD ITS APPLICATION PLAN BE STORED -UST THERE BE TWO OR MORE COOPERATING PLANS )F THERE IS A CHANGE IN THE STRUCTURE OF ONE DATABASE HOW ARE THE APPLICATION PLANS IN THE OTHER DATABASES TO BE NOTIFIED 5SING DYNAMIC 31, TO SOLVE THESE PROBLEMS IN A NETWORKED DATABASE ENVIRONMENT ALMOST ALWAYS LEADS TO UNACCEPTABLY SLOW APPLICATION PERFORMANCE DUE TO NETWORK OVERHEAD AND DELAYS
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s $ATA COMPATIBILITY $IFFERENT COMPUTER SYSTEMS SUPPORT DIFFERENT DATA TYPES AND EVEN WHEN TWO SYSTEMS OFFER THE SAME DATA TYPE THEY OFTEN USE DIFFERENT FORMATS &OR EXAMPLE A 7INDOWS 0# AND AN !PPLE -AC STORE BIT INTEGERS DIFFERENTLY )"- MAINFRAMES STORE DATA USING THE %"#$)# CHARACTER SET WHILE 5.)8 AND ,INUX BASED SERVERS AND 0#S USE !3#)) ! DISTRIBUTED $"-3 MUST MASK THESE DIFFERENCES s 3YSTEM CATALOGS !S A $"-3 CARRIES OUT ITS TASKS IT FREQUENTLY ACCESSES ITS SYSTEM CATALOGS 7HERE SHOULD THE CATALOG BE KEPT IN A DISTRIBUTED DATABASE )F IT IS CENTRALIZED ON ONE SYSTEM REMOTE ACCESS TO IT WILL BE SLOW BOGGING DOWN THE $"-3 )F IT IS DISTRIBUTED ACROSS MANY DIFFERENT SYSTEMS CHANGES MUST BE PROPAGATED AROUND THE NETWORK AND SYNCHRONIZED s -IXED VENDOR ENVIRONMENT )TS HIGHLY UNLIKELY THAT ALL THE DATA IN AN ORGANIZATION WILL BE MANAGED BY A SINGLE BRAND OF $"-3 SO DISTRIBUTED DATABASE ACCESS WILL CROSS $"-3 BRAND BOUNDARIES 4HIS REQUIRES ACTIVE COOPERATION BETWEEN $"-3 PRODUCTS FROM HIGHLY COMPETITIVE VENDORSAN UNLIKELY PROSPECT !S THE $"-3 VENDORS SCRAMBLE TO EXTEND THE CAPABILITIES OF THEIR PRODUCTS WITH NEW FEATURES CAPABILITIES AND DATA TYPES THE ABILITY TO SUSTAIN A CROSS VENDOR STANDARD IS EVEN LESS LIKELY s $ISTRIBUTED DEADLOCKS 7HEN TRANSACTIONS ON TWO DIFFERENT SYSTEMS EACH TRY TO ACCESS LOCKED DATA ON THE OTHER SYSTEM A DEADLOCK CAN OCCUR IN THE DISTRIBUTED DATABASE EVEN THOUGH THE DEADLOCK IS NOT VISIBLE ON EITHER OF THE TWO SYSTEMS 4HE $"-3 MUST PROVIDE GLOBAL DEADLOCK DETECTION FOR A DISTRIBUTED DATABASE !GAIN THIS REQUIRES COORDINATION OF PROCESSING ACROSS A NETWORK AND WILL TYPICALLY LEAD TO UNACCEPTABLY SLOW APPLICATION PERFORMANCE s 2ECOVERY )F ONE OF THE SYSTEMS RUNNING A DISTRIBUTED $"-3 FAILS THE OPERATOR OF THAT SYSTEM MUST BE ABLE TO RUN ITS RECOVERY PROCEDURES INDEPENDENTLY OF THE OTHER SYSTEMS IN THE NETWORK AND THE RECOVERED STATE OF THE DATABASE MUST BE CONSISTENT WITH THAT OF THE OTHER SYSTEMS
$ISTRIBUTINGõ$ATAõ0RACTICALõ!PPROACHES "ECAUSE OF THE FORMIDABLE OBSTACLES TO REALIZING THE IDEAL DISTRIBUTED DATABASE $"-3 VENDORS HAVE TAKEN A STEP BY STEP APPROACH TO DATABASES AND NETWORKING 4HEY HAVE FOCUSED ON SPECIFIC FORMS OF NETWORK DATABASE ACCESS DATA DISTRIBUTION AND DISTRIBUTED DATA MANAGEMENT THAT ARE APPROPRIATE FOR PARTICULAR APPLICATION SCENARIOS &OR EXAMPLE A $"-3 VENDOR MAY FIRST PROVIDE TOOLS TO RAPIDLY EXTRACT SUBSET DATA FROM A MASTER DATABASE AND SEND IT ACROSS A NETWORK FOR LOADING INTO A SLAVE DATABASE ,ATER THE VENDOR MAY ENHANCE THE TOOL TO TRACK UPDATES TO THE MASTER DATABASE SINCE THE LAST EXTRACT AND TO EXTRACT AND TRANSMIT ONLY THE CHANGES TO THE MASTER DATABASE ! SUBSEQUENT VERSION OF THE TOOL MAY AUTOMATE THE ENTIRE PROCESS PROVIDING A GRAPHICAL USER INTERFACE '5) FOR SPECIFYING THE DATA TO BE EXTRACTED AND SCRIPTS TO AUTOMATE THE PERIODIC EXTRACT PROCESS 3IMILARLY A $"-3 MAY PROVIDE INITIAL SUPPORT FOR DISTRIBUTED QUERIES BY ALLOWING A USER ON ONE SYSTEM TO QUERY A DATABASE LOCATED ON ANOTHER SYSTEM )N SUBSEQUENT RELEASES THE $"-3 MAY ALLOW THE REMOTE QUERY AS A SUBQUERY WITHIN A QUERY THAT ACCESSES LOCAL DATABASE TABLES 3TILL LATER THE $"-3 MAY ALLOW DISTRIBUTED QUERIES THAT MORE FREELY INTERMIX DATA FROM LOCAL AND REMOTE DATABASES
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31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
2EMOTEõ$ATABASEõ!CCESS /NE OF THE SIMPLEST APPROACHES TO MANAGING DATA STORED IN MULTIPLE LOCATIONS IS REMOTE DATA ACCESS 7ITH THIS CAPABILITY A USER OF ONE DATABASE IS GIVEN THE ABILITY TO REACH OUT ACROSS A NETWORK AND RETRIEVE INFORMATION FROM A DIFFERENT DATABASE )N ITS SIMPLEST FORM THIS MAY INVOLVE CARRYING OUT A SINGLE QUERY AGAINST THE REMOTE DATABASE AS SHOWN IN &IGURE )T MAY ALSO INVOLVE PERFORMING AN ).3%24 50$!4% OR $%,%4% STATEMENT TO MODIFY THE REMOTE DATABASE CONTENTS 4HIS TYPE OF REQUIREMENT OFTEN ARISES WHEN THE LOCAL DATABASE IS A SATELLITE DATABASE SUCH AS A DATABASE IN A LOCAL SALES OFFICE OR DISTRIBUTION CENTER AND THE REMOTE DATABASE IS A CENTRAL CORPORATE DATABASE )N ADDITION TO THE REMOTE DATA ACCESS REQUEST &IGURE ALSO SHOWS A CLIENTSERVER REQUEST TO THE REMOTE DATABASE FROM A DIFFERENT 0# USER .OTE THAT FROM THE STANDPOINT OF THE REMOTE DATABASE THERE IS VERY LITTLE DIFFERENCE BETWEEN PROCESSING THE REQUEST FROM THE 0# CLIENT AND PROCESSING THE REMOTE DATABASE ACCESS REQUEST )N BOTH CASES A 31, REQUEST ARRIVES ACROSS THE NETWORK AND THE REMOTE DATABASE DETERMINES THAT THE USER MAKING THE REQUEST HAS APPROPRIATE PRIVILEGES AND THEN CARRIES OUT THE REQUEST )N BOTH CASES THE STATUS OF THE 31, PROCESSING IS REPORTED BACK ACROSS THE NETWORK 4HE LOCAL DATABASE IN &IGURE MUST DO SOME VERY DIFFERENT WORK THAN THE PROCESS IT NORMALLY USES TO PROCESS LOCAL DATABASE REQUESTS HOWEVER 4HERE ARE SEVERAL COMPLICATIONS FOR THE LOCAL $"-3 s )T MUST DETERMINE WHICH REMOTE DATABASE THE USER WANTS TO ACCESS AND HOW IT CAN BE ACCESSED ON THE NETWORK s )T MUST ESTABLISH A CONNECTION TO THE REMOTE DATABASE FOR CARRYING OUT REMOTE REQUESTS s )T MUST DETERMINE HOW THE LOCAL USER AUTHENTICATION AND PRIVILEGE SCHEME MAPS TO THE REMOTE DATABASE 4HAT IS DOES IT SIMPLY PASS THE USER NAMEPASSWORD SUPPLIED FOR LOCAL DATABASE ACCESS TO THE REMOTE DATABASE OR IS A DIFFERENT REMOTE USER NAME PASSWORD SUPPLIED OR SHOULD SOME KIND OF AUTOMATIC MAPPING BE PERFORMED
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)N EFFECT THE LOCAL $"-3 BECOMES AN AGENT FOR THE USER MAKING THE REMOTE ACCESS REQUEST )T BECOMES A CLIENT IN A CLIENTSERVER CONNECTION TO THE REMOTE $"-3 3EVERAL OF THE LEADING ENTERPRISE $"-3 VENDORS OFFER THE KIND OF REMOTE DATABASE ACCESS CAPABILITY SHOWN IN &IGURE 4HEY DIFFER IN THE SPECIFIC WAY THAT REMOTE ACCESS IS PRESENTED TO THE USER AND TO THE DATABASE ADMINISTRATOR )N SOME CASES THEY INVOLVE EXTENSIONS TO THE 31, LANGUAGE ACCEPTED BY THE $"-3 )N OTHERS THE EXTRA MECHANISMS FOR ESTABLISHING REMOTE ACCESS ARE MOSTLY EXTERNAL TO THE 31, LANGUAGE 3YBASE !DAPTIVE 3ERVER %NTERPRISE !3% OFFERS A SIMPLE ENTRY LEVEL REMOTE DATABASE ACCESS CAPABILITY 7HILE CONNECTED TO A LOCAL 3YBASE INSTALLATION THE USER CAN ISSUE A #/..%#4 4/ 31, STATEMENT NAMING A REMOTE SERVER THAT IS KNOWN TO THE LOCAL SERVER &OR EXAMPLE IF A REMOTE SERVER NAMED #%.42!,(/34 CONTAINS A COPY OF THE SAMPLE DATABASE THEN THIS STATEMENT #/..%#4 4/ #%.42!,(/34
MAKES THAT REMOTE SERVER THE CURRENT SERVER FOR THE SESSION 4HE LOCAL SERVER IN EFFECT ENTERS A PASS THROUGH MODE SENDING ALL 31, STATEMENTS TO THE REMOTE SERVER 4HE REMOTE DATABASE CAN NOW BE PROCESSED DIRECTLY OVER THE CONNECTION WITH STANDARD UNMODIFIED QUERIES AND DATA MANIPULATION STATEMENTS 'ET THE NAMES AND SALES NUMBERS OF ALL SALESPEOPLE WHO ARE ALREADY OVER QUOTA 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 7(%2% 3!,%3 15/4!
7HEN THE REMOTE ACCESS IS COMPLETED A COMPANION 31, STATEMENT $)3#/..%#4
ENDS THE PASS THROUGH MODE AND THE LOCAL SERVER ONCE AGAIN BECOMES THE CURRENT SERVER %XCEPT FOR THE #/..%#4$)3#/..%#4 STATEMENT PAIR THE MECHANISM FOR MANAGING REMOTE ACCESS IS EXTERNAL TO THE 31, LANGUAGE 4HE DATABASE ADMINISTRATOR TELLS THE LOCAL DATABASE ABOUT THE EXISTENCE LOCATIONS AND NAMES OF REMOTE SERVERS THROUGH THE SPADDSERVER AND SPDROPSERVER SYSTEM STORED PROCEDURES 4HE CURRENT LOCAL USER NAME AND PASSWORD ARE USED BY DEFAULT FOR ACCESS TO THE REMOTE SERVER !LTERNATIVELY THE DATABASE ADMINISTRATOR CAN SPECIFY A PROXY USER NAMEPASSWORD THAT IS USED FOR REMOTE SERVER ACCESS AGAIN THROUGH SYSTEM STORED PROCEDURES 3YBASE !3% OFFERS OTHER MORE COMPLEX DISTRIBUTED DATABASE CAPABILITIES BUT THIS BASIC CAPABILITY HAS THE ADVANTAGE OF MAXIMUM SIMPLICITY /RACLE TAKES A SOMEWHAT DIFFERENT APPROACH TO REMOTE DATABASE ACCESS BUT ONE THAT IS SIMILAR TO THE CAPABILITIES PROVIDED BY OTHER $"-3 BRANDS )T REQUIRES THAT /RACLES 31, .ET NETWORKING SOFTWARE BE INSTALLED ALONG WITH THE /RACLE $"-3 ON BOTH THE LOCAL AND THE REMOTE SYSTEM 4HE DATABASE ADMINISTRATOR IS RESPONSIBLE FOR ESTABLISHING ONE OR MORE NAMED DATABASE LINKS FROM THE LOCAL DATABASE TO REMOTE DATABASES %ACH DATABASE LINK SPECIFIES s .ETWORK LOCATION OF THE TARGET REMOTE COMPUTER SYSTEM s #OMMUNICATIONS PROTOCOL TO USE
#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
s .AME OF THE /RACLE DATABASE ON THE REMOTE SERVER s 2EMOTE DATABASE USER NAME AND PASSWORD !LL REMOTE DATABASE ACCESS OCCURS VIA A DATABASE LINK AND IS GOVERNED BY THE PRIVILEGES OF THE SUPPLIED USER NAME IN THE REMOTE SYSTEM 4HE DATABASE LINK THUS EMBODIES THE ANSWERS TO THE hWHICH DATABASE v hHOW TO COMMUNICATE v AND hWHAT PRIVILEGESv QUESTIONS RAISED EARLIER IN THIS SECTION 4HE DATABASE ADMINISTRATOR ASSIGNS THE DATABASE LINK A NAME ,INKS CAN BE PRIVATE CREATED FOR USE BY A SPECIFIC USER OF THE LOCAL SYSTEM OR PUBLIC AVAILABLE FOR USE BY MULTIPLE USERS OF THE LOCAL SYSTEM 4O ACCESS A REMOTE DATABASE OVER A DATABASE LINK THE LOCAL SYSTEM USER USES STANDARD 31, STATEMENTS 4HE NAME OF THE DATABASE LINK IS APPENDED TO THE REMOTE TABLE AND VIEW NAMES FOLLOWING AN hATv SIGN &OR EXAMPLE ASSUME YOU ARE ON A LOCAL COMPUTER SYSTEM THAT IS CONNECTED TO A COPY OF THE SAMPLE DATABASE ON A REMOTE SYSTEM OVER A DATABASE LINK CALLED #%.42!,(/34 4HIS 31, STATEMENT RETRIEVES INFORMATION FROM THE REMOTE 3!,%32%03 TABLE 'ET THE NAMES AND SALES NUMBERS OF ALL SALESPEOPLE WHO ARE ALREADY OVER QUOTA 3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!,%32%03 #%.42!,(/34 7(%2% 3!,%3 15/4!
/RACLE SUPPORTS NEARLY ALL OF THE QUERY CAPABILITIES THAT ARE AVAILABLE FOR THE LOCAL DATABASE AGAINST REMOTE DATABASES 4HE ONLY RESTRICTION IS THAT EVERY REMOTE DATABASE ENTITY TABLE VIEW ETC MUST BE SUFFIXED WITH THE DATABASE LINK NAME !LSO /RACLE DOES NOT SUPPORT $$, OR DATABASE UPDATES VIA A DATABASE LINK (ERE IS A TWO TABLE JOIN EXECUTED ON THE REMOTE /RACLE DATABASE 'ET THE NAMES AND OFlCE CITIES OF ALL SALESPEOPLE WHO ARE ALREADY OVER QUOTA 3%,%#4 .!-% #)49 15/4! 3!,%3 &2/- 3!,%32%03 #%.42!,(/34 /&&)#%3 #%.42!,(/34 7(%2% 3!,%3 15/4! !.$ 2%0?/&&)#% /&&)#%
)NFORMIX 5NIVERSAL 3ERVER PROVIDES CAPABILITIES THAT ARE SIMILAR TO THOSE OFFERED BY /RACLE BUT USES A DIFFERENT MECHANISM FOR IDENTIFYING REMOTE DATABASES AND A DIFFERENT 31, SYNTAX EXTENSION 4HE )NFORMIX ARCHITECTURE DIFFERENTIATES BETWEEN A REMOTE DATABASE SERVER AND A REMOTE DATABASE THAT IS MANAGED BY THE REMOTE SERVER SINCE IT TENDS TO PROVIDE RICH SUPPORT FOR MULTIPLE NAMED DATABASES PER SERVER 3UPPOSE AN )NFORMIX COPY OF THE SAMPLE DATABASE IS CALLED 3!-0,% AND IT RESIDES ON A REMOTE DATABASE SERVER CALLED #%.42!,(/34 4HEN THIS QUERY IS EQUIVALENT TO THE PREVIOUS /RACLE AND 3YBASE EXAMPLES 'ET THE NAMES AND SALES NUMBERS OF ALL SALESPEOPLE WHO ARE ALREADY OVER QUOTA
4HE DATABASE NAME APPEARS AT THE BEGINNING OF THE TABLE NAME AS AN ADDITIONAL QUALIFIER BEFORE THE COLON )F THE DATABASE IS REMOTE THEN THE SERVER NAME APPEARS FOLLOWING THE SIGN AFTER THE DATABASE NAME
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3%,%#4 .!-% 15/4! 3!,%3 &2/- 3!-0,% #%.42!,(/343!,%2%03 7(%2% 3!,%3 15/4!
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31,ç4ODAYçANDç4OMORROW
2EMOTEõ$ATAõ4RANSPARENCY 7ITH ANY OF THE REMOTE DATABASE NAMING CONVENTIONS THAT EXTEND THE USUAL 31, TABLE AND VIEW NAMES THE ADDITIONAL QUALIFIERS CAN QUICKLY BECOME ANNOYING OR CONFUSING &OR EXAMPLE IF TWO TABLES IN THE REMOTE DATABASE HAVE COLUMNS WITH THE SAME NAMES ANY QUERY INVOLVING BOTH TABLES MUST USE QUALIFIED COLUMN NAMESAND THE TABLE NAME QUALIFIERS NOW HAVE THE REMOTE DATABASE QUALIFICATION AS WELL (ERES A QUALIFIED )NFORMIX COLUMN NAME FOR THE .!-% COLUMN IN THE REMOTE 3!,%32%03 TABLE OWNED BY THE USER */% IN A REMOTE DATABASE NAMED 3!-0,% ON THE REMOTE )NFORMIX SERVER #%.42!,(/34 3!-0,% #%.42!,(/34*/%3!,%32%03.!-%
! SINGLE COLUMN REFERENCE HAS GROWN TO HALF A LINE OF 31, TEXT &OR THIS REASON TABLE ALIASES ARE FREQUENTLY USED IN 31, STATEMENTS INVOLVING REMOTE DATABASE ACCESS 3YNONYMS AND ALIASES DESCRIBED IN #HAPTER ARE ALSO VERY USEFUL FOR PROVIDING MORE TRANSPARENT ACCESS TO REMOTE DATABASES (ERES AN )NFORMIX SYNONYM DEFINITION THAT COULD BE ESTABLISHED BY A USER OR A DATABASE ADMINISTRATOR #2%!4% 39./.9- 2%-/4%?2%03 &/2 3!-0,% #%.42!,(/34*/%3!,%32%03
4HE EQUIVALENT /RACLE SYNONYM DEFINITION IS #2%!4% 39./.9- 2%-/4%?2%03 &/2 */%3!,%32%03 #%.42!,(/34
7ITH THIS SYNONYM IN PLACE THE PRECEDING QUALIFIED COLUMN NAME BECOMES SIMPLY 2%-/4%?2%03.!-%
!NY QUERY REFERENCING THE 2%-/4%?2%03 TABLE AND ITS COLUMNS IS ACTUALLY A REMOTE DATABASE QUERY BUT THAT FACT IS TRANSPARENT TO THE USER )N PRACTICE MOST DATABASE INSTALLATIONS WITH FREQUENTLY ACCESSED REMOTE TABLES WILL HAVE A SET OF SYNONYMS DEFINED FOR THEM -OST OF THE $"-3 BRANDS SUPPORT BOTH PUBLIC SYNONYMS AVAILABLE TO ALL USERS AND PRIVATE SYNONYMS THAT ARE CREATED FOR A SPECIFIC USER OR GROUP OF USERS 7ITH THIS STRUCTURE SYNONYMS CAN BECOME AN ADDITIONAL PART OF THE REMOTE ACCESS SECURITY MECHANISM LIMITED ONLY TO THOSE USERS WITH A REAL NEED FOR REMOTE ACCESS 3EVERAL $"-3 BRANDS TAKE THE SYNONYM CAPABILITY FOR TRANSPARENT DATABASE ACCESS ONE STEP FURTHER AND PERMIT VIEWS IN THE LOCAL DATABASE THAT ARE DEFINED IN TERMS OF REMOTE DATABASE TABLES (ERE IS AN /RACLE VIEW DEFINITION THAT CREATES A VIEW CALLED %!34?2%03 IN THE LOCAL DATABASE 4HE VIEW IS A SUBSET OF INFORMATION FROM THE REMOTE SAMPLE DATABASE #REATE A LOCAL VIEW DElNED IN TERMS OF TWO REMOTE TABLES #2%!4% 6)%7 %!34?2%03 !3 3%,%#4 %-0,?.5- .!-% !'% #)49 &2/- 3!,%32%03 #%.42!,(/34 /&&)#%3 #%.42!,(/34 7(%2% 2%0?/&&)#% /&&)#% !.$ 2%0?/&&)#% "%47%%. !.$
!FTER THIS VIEW HAS BEEN DEFINED A USER CAN POSE QUERIES IN TERMS OF THE %!34?2%03 VIEW WITHOUT WORRYING ABOUT DATABASE LINKS OR REMOTE TABLE NAMES 4HE VIEW NOT ONLY PROVIDES TRANSPARENT REMOTE ACCESS BUT ALSO HIDES FROM THE USER THE REMOTE JOIN OPERATION BETWEEN THE /&&)#%3 AND 3!,%32%03 TABLES
#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
4RANSPARENT ACCESS TO REMOTE DATA PROVIDED BY VIEWS AND SYNONYMS IS USUALLY CONSIDERED A VERY DESIRABLE CHARACTERISTIC )T DOES HAVE ONE DRAWBACK HOWEVER "ECAUSE THE REMOTE ASPECT OF THE DATABASE ACCESS IS NOW HIDDEN THE NETWORK OVERHEAD CREATED BY THE ACCESS IS ALSO HIDDEN 4HEREFORE THE POSSIBILITY OF A USER OR PROGRAMMER INADVERTENTLY CREATING A GREAT DEAL OF NETWORK TRAFFIC THROUGH VERY LARGE QUERIES IS INCREASED 4HE DATABASE ADMINISTRATOR MUST MAKE THIS TRADE OFF WHEN DECIDING WHETHER TO PERMIT REMOTE TRANSPARENT SYNONYMS AND VIEWS 4RANSPARENT REMOTE ACCESS ALSO INEVITABLY RAISES ONE ADDITIONAL QUESTION SINCE THE REMOTE TABLES NOW APPEAR AS IF THEY ARE LOCAL CAN THE USER POSE QUERIES THAT INVOLVE BOTH REMOTE AND LOCAL TABLES 4HAT IS CAN A JOIN CROSS THE DATABASE SERVER BOUNDARIES AND RELATE INFORMATION FROM THE REMOTE DATABASE AND THE LOCAL DATABASE %VEN MORE SERIOUS QUESTIONS ARE POSED WHEN THE 31, TRANSACTION SCHEME IS CONSIDERED )F A DATABASE PERMITS TRANSPARENT ACCESS TO A REMOTE DATABASE THEN IS A USER ALLOWED TO UPDATE A ROW IN THE LOCAL DATABASE AND INSERT A ROW IN THE REMOTE DATABASE AND THEN DECIDE TO ROLL BACK THE TRANSACTION 3INCE THE REMOTE RESOURCES HAVE BEEN MADE TO APPEAR AS IF THEY ARE LOCAL IT SEEMS THAT THE ANSWER SHOULD BE h/F COURSETHE LOCAL AND REMOTE DATABASES TOGETHER SHOULD APPEAR AS IF THEY WERE JUST ONE LOCAL INTEGRATED DATABASEv )N FACT SUPPORTING SUCH DISTRIBUTED QUERIES AND TRANSACTIONS ADDS A MAJOR NEW LEVEL OF COMPLEXITY AND POTENTIALLY HUGE NETWORK DATA TRANSMISSION OVERHEAD TO THE REMOTE ACCESS "ECAUSE OF THIS ALTHOUGH SEVERAL COMMERCIAL $"-3 SYSTEMS SUPPORT DISTRIBUTED QUERIES AND TRANSACTIONS THEY ARE NOT HEAVILY USED IN PRACTICE 4HESE CAPABILITIES AND THEIR OVERHEAD IMPLICATIONS ARE MORE FULLY DISCUSSED LATER IN THE h$ISTRIBUTED $ATABASE !CCESSv SECTION 4HE NEXT SECTION DISCUSSES A PRACTICAL ALTERNATIVEDUPLICATING DATA OR DATABASE REPLICATIONTHAT IS MUCH MORE FREQUENTLY USED IN PRACTICE
4ABLEõ%XTRACTS
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2EMOTE DATABASE ACCESS IS VERY CONVENIENT FOR SMALL REMOTE QUERIES AND OCCASIONAL REMOTE DATABASE ACCESS )F AN APPLICATION REQUIRES HEAVY AND FREQUENT ACCESS TO A REMOTE DATABASE HOWEVER THE COMMUNICATIONS OVERHEAD OF REMOTE DATABASE ACCESS CAN BECOME LARGE /NCE REMOTE ACCESS GROWS BEYOND A CERTAIN POINT IT IS OFTEN MORE EFFICIENT TO MAINTAIN A LOCAL COPY OF THE REMOTE DATA IN THE LOCAL DATABASE -ANY OF THE $"-3 VENDORS PROVIDE TOOLS TO SIMPLIFY THE PROCESS OF DATA EXTRACTION AND DISTRIBUTION )N ITS SIMPLEST FORM THE PROCESS EXTRACTS THE CONTENTS OF A TABLE IN A MASTER DATABASE SENDS IT ACROSS A NETWORK TO ANOTHER SYSTEM AND LOADS IT INTO A CORRESPONDING REPLICA TABLE IN A SLAVE DATABASE AS SHOWN IN &IGURE )N PRACTICE THE EXTRACT IS PERFORMED PERIODICALLY AND DURING OFF PEAK TIMES OF DATABASE ACTIVITY 4HIS APPROACH IS VERY APPROPRIATE WHEN THE DATA IN THE REPLICATED TABLE CHANGES SLOWLY OR WHEN CHANGES TO THE TABLE NATURALLY OCCUR IN A BATCH &OR EXAMPLE SUPPOSE SOME TABLES OF THE SAMPLE DATABASE LOCATED ON A REMOTE CENTRAL COMPUTER SYSTEM ARE TO BE REPLICATED IN A LOCAL DATABASE 4HE CONTENTS OF THE /&&)#%3 TABLE HARDLY EVER CHANGE )T WOULD BE AN EXCELLENT CANDIDATE FOR REPLICATION ONTO DISTRIBUTION CENTER OR SALES FORCE AUTOMATION DATABASES /NCE THE INITIAL LOCAL REPLICA TABLES ARE SET UP AND POPULATED THEY MIGHT NEED TO BE UPDATED ONLY ONCE PER MONTH OR WHEN A NEW SALES OFFICE IS OPENED 4HE 02/$5#43 TABLE IS ALSO A GOOD CANDIDATE FOR REPLICATION 0RODUCT PRICE CHANGES OCCUR MORE FREQUENTLY THAN OFFICE CHANGES BUT IN MOST COMPANIES THEY HAPPEN IN BATCHES PERHAPS ONCE A WEEK OR ONCE A DAY 7ITH THIS NATURAL PROCESSING CYCLE IT WOULD BE VERY
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31,ç4ODAYçANDç4OMORROW
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EFFECTIVE TO EXTRACT A TABLE OF PRODUCT PRICE DATA JUST AFTER EACH BATCH OF UPDATES AND TO SEND IT TO THE DISTRIBUTION CENTER DATABASES AND THE SALES FORCE AUTOMATION CENTRAL DATABASE 4HE PRICE DATA IN THESE DATABASES DOES NOT NEED TO BE TIGHTLY LINKED TO THE MAINFRAME DATABASE TO ENSURE THAT IT IS FRESH ! WEEKLY OR DAILY EXTRACTUPDATE CYCLE WILL MAKE THE DATA JUST AS CURRENT WITH A SUBSTANTIALLY SMALLER PROCESSING WORKLOAD )TS POSSIBLE TO IMPLEMENT THIS TYPE OF REPLICATED TABLE STRATEGY WITHOUT ANY SUPPORT FROM THE $"-3 9OU COULD WRITE AN APPLICATION PROGRAM THAT USES 31, ON THE MAINFRAME TO EXTRACT THE PRODUCT PRICING DATA INTO A FILE ! FILE TRANSFER PROGRAM COULD TRANSMIT THE FILE TO THE DISTRIBUTION CENTERS WHERE ANOTHER APPLICATION PROGRAM COULD READ ITS CONTENTS AND GENERATE THE APPROPRIATE $2/0 4!",% #2%!4% 4!",% AND ).3%24 STATEMENTS TO POPULATE THE REPLICATED TABLE 4HE FIRST STEP TOWARD AUTOMATING THIS STRATEGY WAS THE DEVELOPMENT OF HIGH SPEED DATA EXTRACT AND DATA LOADING PROGRAMS 4HESE UTILITY PROGRAMS OFFERED BY THE $"-3 VENDORS TYPICALLY USE PROPRIETARY LOWER LEVEL DATABASE ACCESS TECHNIQUES TO EXTRACT THE DATA AND LOAD THE DATA MUCH MORE RAPIDLY THAN IS POSSIBLE THROUGH 31, 3%,%#4 AND ).3%24 STATEMENTS -ORE RECENTLY SOFTWARE COMPANIES HAVE TARGETED THIS AREA AS AN OPPORTUNITY FOR STAND ALONE SOFTWARE PACKAGES INDEPENDENT OF THE $"-3 VENDORS 4HIS CATEGORY OF SOFTWARE CALLED EXTRACT TRANSFORM AND LOAD %4, SOFTWARE FOCUSES ON LINKING DISPARATE DATABASE SYSTEMS AND FILE FORMATS %4, TOOLS TYPICALLY OFFER A GRAPHICAL USER INTERFACE FOR SPECIFYING THE DATA EXTRACTION AN ARRAY OF TOOLS FOR REFORMATTING DATA BETWEEN THE SOURCE AND DESTINATION SYSTEMS A MESSAGING CAPABILITY FOR TRANSMITTING THE DATA PERHAPS A STORE AND FORWARD CAPABILITY FOR STAGING EXTRACTED DATA BEFORE AND AFTER TRANSMISSION AND UTILITIES FOR MANAGING AND MONITORING THE OVERALL PROCESS 4WO ADDITIONAL CATEGORIES OF INTEGRATION SOFTWARE ARE ENTERPRISE APPLICATION INTEGRATION %!) AND ENTERPRISE INFORMATION INTEGRATION %)) 7HILE THERE IS SOME OVERLAP WITH %4,
#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
THE BEST WAY TO DISTINGUISH THESE IS BY THE TARGET FOR WHICH THE DATA IS INTENDED !S ALREADY MENTIONED THE TARGET FOR %4, IS A DATABASE %!) ON THE OTHER HAND PROVIDES A FRAMEWORK FOR CAPTURING DATA FROM ONE APPLICATION AND DELIVERING IT TO ANOTHER APPLICATION USUALLY USING SOME FORM OF MESSAGING TECHNOLOGY 4HE TARGET OF %!) IS AN APPLICATION &OR EXAMPLE %!) COULD CAPTURE NEW CUSTOMERS AS THEY ARE ADDED BY THE #USTOMER -ANAGEMENT APPLICATION AND SEND THOSE TO THE #USTOMER 3ERVICE APPLICATION SO THAT THE CUSTOMERS SERVICES COULD BE SET UP )N CONTRAST %)) IS A FRAMEWORK FOR DELIVERING DATA FROM DISPARATE SOURCES TO A USER GENERALLY IN THE FORM OF QUERY RESULTS 4HE TARGET OF %)) IS A USER 3OME %)) TOOLS PROVIDE AGENTS THAT MAKE DISPARATE FILES LOOK LIKE RELATIONAL DATABASES TO THE USER WHO CAN THEN QUERY THEM USING 31, 7HILE THERE IS COMMON CONFUSION OF THE TERMS %4, %!) AND %)) IT IS %4, THAT PROVIDES THE CAPABILITY TO LOAD OR RELOAD DATABASE TABLES ON A SCHEDULED BASIS
4ABLEõ2EPLICATION 3EVERAL $"-3 VENDORS HAVE MOVED BEYOND THEIR EXTRACT AND LOAD UTILITY PROGRAMS TO OFFER SUPPORT FOR TABLE EXTRACTION WITHIN THE $"-3 ITSELF /RACLE FOR EXAMPLE OFFERS A MATERIALIZED VIEW FACILITY CALLED SNAPSHOTS PRIOR TO /RACLEI TO AUTOMATICALLY CREATE A LOCAL COPY OF A REMOTE TABLE ! MATERIALIZED VIEW IS A VIEW THAT ACTUALLY STORES THE ROWS DEFINED BY THE QUERY INCLUDED IN THE VIEW DEFINITION )N ITS SIMPLEST FORM THE LOCAL TABLE IS A READ ONLY REPLICA OF THE REMOTE MASTER TABLE THAT IS LOADED WHEN THE VIEW IS DEFINED (OWEVER MATERIALIZED VIEWS CAN BE DEFINED SO THEY ARE AUTOMATICALLY REFRESHED BY THE /RACLE $"-3 ON A PERIODIC BASIS (ERE IS AN /RACLE 31, STATEMENT TO CREATE A LOCAL COPY OF PRODUCT PRICING DATA ASSUMING THAT THE REMOTE MASTER DATABASE INCLUDES A 02/$5#43 TABLE LIKE THE ONE IN THE SAMPLE DATABASE #REATE A LOCAL REPLICA OF PRICING INFORMATION FROM THE REMOTE 02/$5#43 TABLE #2%!4% -!4%2)!,):%$ 6)%7 02/$02)#% !3 3%,%#4 -&2?)$ 02/$5#4?)$ 02)#% &2/- 02/$5#43 2%-/4%?,).+
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4HIS STATEMENT EFFECTIVELY CREATES A LOCAL /RACLE TABLE NAMED 02/$02)#% )T CONTAINS THREE COLUMNS SPECIFIED BY THE 3%,%#4 STATEMENT AGAINST THE REMOTE MASTER DATABASE 4HE SIGN AND NAME 2%-/4%?,).+ IN THE STATEMENT TELL /RACLE THAT THE 02/$5#43 TABLE FROM WHICH THE DATA IS TO BE REPLICATED IS A REMOTE TABLE ACCESSIBLE VIA THE /RACLE DATABASE LINK NAMED 2%-/4%?,).+ 4HE /RACLE DATABASE ADMINISTRATOR SETS UP THESE REMOTE DATABASE LINKS AS PART OF THE DISTRIBUTED /RACLE CAPABILITIESTHEY ARE REQUIRED FOR ACCESS TO A REMOTE DATABASE USING /RACLE 31, (OWEVER MATERIALIZED VIEWS CAN BE CREATED BASED ON LOCAL DATABASE OBJECTS AS WELL AS REMOTE ONES )N FACT THIS IS COMMONLY DONE IN DATA WAREHOUSES AND DATA MARTS WHERE MATERIALIZED VIEWS ARE FORMED WITH SUMMARY INFORMATION THAT IS REQUIRED FOR ANALYSIS &INALLY THIS #2%!4% -!4%2)!,):%$ 6)%7 STATEMENT WILL ACTUALLY CAUSE THE LOCAL 02/$02)#% MATERIALIZED VIEW TO BE POPULATED WITH DATA FROM THE REMOTE 02/$5#43 TABLE AND TO BE STORED PHYSICALLY ON THE LOCAL DATABASE 7ITH THIS TYPE OF READ ONLY MATERIALIZED VIEW USERS ARE NOT ALLOWED TO CHANGE THE MATERIALIZED VIEW WITH ).3%24 50$!4% OR $%,%4% STATEMENTS !LL DATABASE UPDATES OCCUR IN THE MASTER REMOTE TABLE AND ARE ONLY PROPAGATED TO THE MATERIALIZED VIEW WHEN IT IS REFRESHED 4HE DATABASE ADMINISTRATOR CAN MANUALLY REFRESH THE MATERIALIZED VIEW AS DESIRED USING THE $"-3?-6)%72%&2%3( STORED PROCEDURE SUPPLIED BY /RACLE
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0ARTç6)ç
31,ç4ODAYçANDç4OMORROW
4HE #2%!4% -!4%2)!,):%$ 6)%7 STATEMENT ALSO INCLUDES RATHER COMPREHENSIVE FACILITIES FOR SPECIFYING AUTOMATIC REFRESHES (ERE ARE SOME EXAMPLES #REATE A LOCAL REPLICA OF PRICING INFORMATION FROM THE REMOTE 02/$5#43 TABLE 2EFRESH THE DATA ONCE PER WEEK WITH A COMPLETE RELOAD OF THE DATA #2%!4% -!4%2)!,):%$ 6)%7 02/$02)#% 2%&2%3( #/-0,%4% 34!24 7)4( 393$!4% .%84 393$!4% !3 3%,%#4 -&2?)$ 02/$5#4?)$ 02)#% &2/- 02/$5#43 2%-/4%?,).+
#REATE A LOCAL REPLICA OF PRICING INFORMATION FROM THE REMOTE 02/$5#43 TABLE 2EFRESH THE DATA ONCE PER DAY SENDING ONLY CHANGES FROM THE MASTER TABLE #2%!4% -!4%2)!,):%$ 6)%7 02/$02)#% 2%&2%3( &!34 34!24 7)4( 393$!4% .%84 393$!4% !3 3%,%#4 -&2?)$ 02/$5#4?)$ 02)#% &2/- 02/$5#43 2%-/4%?,).+
)N THE LATTER EXAMPLE THE &!34 OPTION SPECIFIES THAT THE MATERIALIZED VIEW IS REFRESHED BY TRANSMITTING ONLY CHANGES FROM THE REMOTE 02/$5#43 TABLE /RACLE IMPLEMENTS THIS CAPABILITY BY MAINTAINING A LOG OF CHANGES ON THE REMOTE SYSTEM AND UPDATING THE LOG EVERY TIME AN UPDATE TO THE 02/$5#43 TABLE WOULD AFFECT THE MATERIALIZED VIEW 7HEN THE TIME FOR A REFRESH ARRIVES INFORMATION FROM THE CHANGE LOG IS USED #OMPLETE REFRESHES CAN BE EXPENSIVE IN TERMS OF RESOURCES BECAUSE THE ENTIRE QUERY MUST BE RUN AGAINST THE SOURCE TABLES SENDING ALL QUALIFYING ROWS TO THE MATERIALIZED VIEW &OR APPLICATIONS LIKE THIS ONE WHERE PRODUCT PRICE CHANGES PROBABLY AFFECT ONLY A SMALL PERCENTAGE OF THE OVERALL TABLE THIS STRATEGY IS EFFECTIVE 4HE ADDITIONAL OVERHEAD OF MAINTAINING THE LOG FOR THE MASTER TABLE IS MORE THAN OFFSET BY THE REDUCED NETWORK TRAFFIC OF TRANSMITTING ONLY CHANGED DATA )N OTHER APPLICATIONS WHERE A LARGE PERCENTAGE OF THE ROWS IN THE MASTER TABLE WILL BE MODIFIED BETWEEN REFRESHES IT MAY BE MORE EFFICIENT TO SIMPLY DO A COMPLETE REFRESH AND ELIMINATE THE OVERHEAD OF MAINTAINING THE LOG "Y DEFAULT /RACLE IDENTIFIES ROWS TO DETERMINE WHETHER THEY ARE CHANGED BASED ON THEIR PRIMARY KEY )F THE PRIMARY KEY IS NOT PART OF THE REPLICATED DATA THIS CAN CAUSE CONFUSION ABOUT WHICH ROWS HAVE BEEN UPDATED IN THIS CASE /RACLE USES AN INTERNAL ROW ID NUMBER AN OPTION THAT CAN BE SPECIFIED WHEN THE MATERIALIZED VIEW IS CREATED TO IDENTIFY THE MODIFIED ROWS FOR REFRESHES TO THE MATERIALIZED VIEW 4HE 3%,%#4 STATEMENT THAT DEFINES THE MATERIALIZED VIEW OFFERS A VERY GENERAL CAPABILITY FOR DATA EXTRACTION )T CAN INCLUDE A 3%,%#4 CLAUSE TO EXTRACT ONLY SELECTED ROWS OF THE MASTER TABLE #REATE A LOCAL REPLICA OF PRICING INFORMATION FOR HIGH PRICED PRODUCTS FROM THE REMOTE 02/$5#43 TABLE 2EFRESH THE DATA ONCE PER DAY SENDING ONLY CHANGES FROM THE MASTER TABLE #2%!4% -!4%2)!,):%$ 6)%7 02/$02)#% 2%&2%3( &!34 34!24 7)4( 393$!4% .%84 393$!4% !3 3%,%#4 -&2?)$ 02/$5#4?)$ 02)#% &2/- 02/$5#43 2%-/4%?,).+ 7(%2% 02)#%
#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
.OTE THAT THE 7(%2% PREDICATE DOESNT AFFECT THE CHANGE LOG !LL CHANGES TO THE 02/$5#43 TABLE MUST STILL BE LOGGED BECAUSE MULTIPLE MATERIALIZED VIEWS CAN BE REFRESHED FROM THE CHANGE LOG REGARDLESS OF THE PREDICATES USED IN THEIR DEFINITIONS 4HE MATERIALIZED VIEW CAN ALSO BE CREATED AS A JOINED TABLE EXTRACTING ITS DATA FROM TWO OR MORE MASTER TABLES IN THE REMOTE DATABASE #REATE A LOCAL REPLICA OF SALESPERSON DATA REFRESHED WEEKLY #2%!4% -!4%2)!,):%$ 6)%7 3!,%34%!- 2%&2%3( &!34 34!24 7)4( 393$!4% .%84 393$!4% !3 3%,%#4 .!-% 15/4! 3!,%3 #)49 &2/- 3!,%32%03 2%-/4% /&&)#%3 2%-/4% 7(%2% 2%0?/&&)#% /&&)#%
!DDING TO THE COMPLEXITY THE MATERIALIZED VIEW CAN BE DEFINED BY A GROUPED QUERY #REATE A LOCAL SUMMARY OF CUSTOMER ORDER VOLUME REFRESHED DAILY #2%!4% -!4%2)!,):%$ 6)%7 #534/2$ 2%&2%3( &!34 34!24 7)4( 393$!4% .%84 393$!4% !3 3%,%#4 #/-0!.9 35-!-/5.4 &2/- #534/-%23 2%-/4% /2$%23 2%-/4% 7(%2% #534 #534?.5-
/F COURSE WITH EACH LEVEL OF ADDITIONAL COMPLEXITY THE OVERHEAD OF MANAGING THE MATERIALIZED VIEW AND THE REFRESH PROCESS INCREASES 2EGARDLESS OF HOW SIMPLE OR COMPLEX THE DEFINITION OF THE MATERIALIZED VIEW HOWEVER THE OVERALL PRINCIPLES REMAIN THE SAME )NSTEAD OF HAVING QUERIES AGAINST THE REPLICATED DATA TRAVEL ACROSS THE NETWORK TO THE REMOTE DATABASE THE REMOTE DATA IS BROUGHT DOWN INTO THE MATERIALIZED VIEW 4HE REFRESHES TO THE MATERIALIZED VIEW STILL GENERATE NETWORK TRAFFIC BUT THE DAY TO DAY QUERIES AGAINST THE MATERIALIZED VIEW DATA ARE CARRIED OUT LOCALLY AND DO NOT GENERATE NETWORK TRAFFIC &OR SITUATIONS WHERE THE QUERY WORKLOAD IS MUCH HIGHER THAN THE OVERHEAD OF MAINTAINING THE MATERIALIZED VIEW THIS CAN BE AN EFFECTIVE WAY TO IMPROVE OVERALL DATABASE PERFORMANCE
5PDATEABLEõ2EPLICAS
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)N THE SIMPLEST IMPLEMENTATIONS A TABLE AND ITS REPLICAS HAVE A STRICT MASTERSLAVE RELATIONSHIP AS SHOWN IN &IGURE 4HE CENTRALMASTER COPY CONTAINS THE REAL DATA )T IS ALWAYS UP TO DATE AND ALL UPDATES TO THE TABLE MUST OCCUR ON THIS COPY OF THE TABLE 4HE OTHER SLAVE COPIES ARE POPULATED BY PERIODIC UPDATES MANAGED BY THE $"-3 "ETWEEN UPDATES THEY MAY BECOME SLIGHTLY OUT OF DATE BUT IF THE DATABASE IS CONFIGURED IN THIS WAY THEN IT IS AN ACCEPTABLE PRICE TO PAY FOR THE ADVANTAGE OF HAVING A LOCAL COPY OF THE DATA 5PDATES TO THE SLAVE COPIES ARE NOT PERMITTED )F THEY ARE ATTEMPTED THE $"-3 RETURNS AN ERROR CONDITION "Y DEFAULT THE /RACLE #2%!4% -!4%2)!,):%$ 6)%7 STATEMENT CREATES THIS TYPE OF SLAVE REPLICA OF A TABLE (OWEVER MORE ADVANCED FUNCTIONS SUCH AS MULTIPLE UPDATEABLE REPLICAS OF THE SAME MASTER TABLE REQUIRE USE OF THE /RACLE !DVANCED 2EPLICATION FACILITY WHICH IS BEYOND THE SCOPE OF THIS BOOK )N THE -ICROSOFT 31, 3ERVER STRUCTURE FOR REPLICATION THE MASTERSLAVE RELATIONSHIP IS IMPLICIT 4HE 31, SERVER ARCHITECTURE DEFINES THE MASTER AS THE PUBLISHER OF THE DATA AND THE SLAVES AS SUBSCRIBERS TO THE DATA )N THE DEFAULT CONFIGURATION THERE IS A SINGLE UPDATEABLE
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PUBLISHER AND THERE MAY BE MULTIPLE READ ONLY SUBSCRIBERS 4HE 31, 3ERVER ARCHITECTURE CARRIES THIS ANALOGY ONE STEP FURTHER SUPPORTING BOTH THE NOTION OF PUSH UPDATES THE PUBLISHER ACTIVELY SENDS THE UPDATE DATA TO THE SUBSCRIBERS AND PULL UPDATES THE SUBSCRIBERS HAVE PRIMARY RESPONSIBILITY FOR GETTING UPDATES FROM THE PUBLISHER &OR SOME APPLICATIONS TABLE REPLICATION IS AN EXCELLENT TECHNIQUE WITHOUT THE MASTER SLAVE RELATIONSHIP &OR EXAMPLE APPLICATIONS THAT DEMAND HIGH AVAILABILITY USE REPLICATED TABLES TO MAINTAIN IDENTICAL COPIES OF DATA ON TWO DIFFERENT COMPUTER SYSTEMS )F ONE SYSTEM FAILS THE OTHER CONTAINS CURRENT DATA AND CAN CARRY ON PROCESSING !N )NTERNET APPLICATION MAY DEMAND VERY HIGH DATABASE ACCESS RATES AND ACHIEVE THIS SCALABILITY BY REPLICATING A TABLE MANY TIMES ON DIFFERENT COMPUTER SYSTEMS AND THEN SPREADING OUT THE WORKLOAD ACROSS THE SYSTEMS ! SALES FORCE AUTOMATION APPLICATION WILL PROBABLY CONTAIN ONE CENTRAL #534/-%2 TABLE AND HUNDREDS OF REPLICAS ON LAPTOP SYSTEMS AND INDIVIDUAL SALESPEOPLE SHOULD BE ABLE TO ENTER NEW CUSTOMERS OR CHANGE CUSTOMER CONTACT INFORMATION ON THE LAPTOP REPLICAS )N THESE CONFIGURATIONS AND OTHERS THE MOST EFFICIENT USE OF THE COMPUTER RESOURCES IS ACHIEVED IF ALL OF THE REPLICAS CAN ACCEPT UPDATES TO THE TABLE AS SHOWN IN &IGURE ! REPLICATED TABLE WHERE MULTIPLE COPIES CAN ACCEPT UPDATES CREATES A NEW SET OF DATA INTEGRITY ISSUES 7HAT HAPPENS IF THE SAME ROW OF THE TABLE IS UPDATED IN ONE OR MORE REPLICAS 7HEN THE $"-3 TRIES TO SYNCHRONIZE THE REPLICAS WHICH OF THE TWO UPDATES SHOULD APPLY OR SHOULD NEITHER APPLY OR BOTH 7HAT HAPPENS IF A ROW IS DELETED FROM ONE COPY OF THE TABLE BUT IT IS UPDATED IN ANOTHER COPY OF THE TABLE )N $"-3 SYSTEMS THAT SUPPORT UPDATEABLE REPLICAS THESE ISSUES ARE ADDRESSED BY CREATING A SET OF CONFLICT RESOLUTION RULES THAT THE REPLICATION SYSTEM APPLIES &OR EXAMPLE WHEN REPLICATION IS SET UP BETWEEN A CENTRAL #534/-%2 TABLE AND LAPTOP VERSIONS OF THE TABLE THE REPLICATION RULE MAY SAY THAT CHANGES TO THE CENTRAL CUSTOMER DATABASE ALWAYS WIN OVER CHANGES ENTERED ON A LAPTOP SYSTEM !LTERNATIVELY THE REPLICATION RULE MIGHT SAY THAT THE MOST RECENT UPDATE ALWAYS WINS )N ADDITION TO THE BUILT IN RULES PROVIDED BY THE $"-3 ITSELF THE REPLICATION DEFINITION MAY INCLUDE THE CAPABILITY TO PASS CONFLICTS TO A USER WRITTEN PROCEDURE SUCH AS A STORED PROCEDURE WITHIN THE DATABASE FOR SELECTION OF THE WINNER AND LOSER REPLICAS
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31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
2EPLICATIONõ4RADE /FFS 0RACTICAL REPLICATION STRATEGIES ALWAYS INVOLVE A TRADE OFF BETWEEN THE DESIRE TO KEEP DATA AS CURRENT AS POSSIBLE AND THE DESIRE TO KEEP NETWORK TRAFFIC DOWN TO A PRACTICAL LEVEL AND PROVIDE ADEQUATE PERFORMANCE 4HESE TRADE OFFS USUALLY INVOLVE NOT JUST TECHNICAL CONSIDERATIONS BUT BUSINESS PRACTICES AND POLICIES AS WELL &OR EXAMPLE CONSIDER AN ORDER PROCESSING APPLICATION USING THE SAMPLE DATABASE AND ASSUME THAT ORDER PROCESSING IS DISTRIBUTED ACROSS FIVE DIFFERENT CALL CENTERS THAT ARE GEOGRAPHICALLY DISTRIBUTED AROUND THE WORLD %ACH CALL CENTER HAS ITS OWN COMPUTER SYSTEM AND DATABASE )NCOMING ORDERS ARE CHECKED AGAINST THE 02/$5#43 TABLE TO BE CERTAIN THAT ENOUGH INVENTORY IS ON HAND TO FILL THE ORDER 4HE 02/$5#43 TABLE KEEPS TRACK OF PRODUCT ON HAND QUANTITIES FOR ALL OF THE COMPANYS WAREHOUSES WORLDWIDE 3UPPOSE THE COMPANYS POLICY IS THAT THE ORDER PROCESSING CLERK MUST BE ABLE TO ABSOLUTELY GUARANTEE A CUSTOMER THAT PRODUCTS CAN BE SHIPPED WITHIN HOURS OF THE TIME AN ORDER IS ACCEPTED )N THIS CASE THE 02/$5#43 TABLE MUST CONTAIN ABSOLUTELY UP TO THE MINUTE DATA REFLECTING THE INVENTORY IMPACT OF ORDERS TAKEN JUST SECONDS EARLIER /NLY TWO DESIGNS COULD WORK FOR THE DATABASE IN THIS CASE 9OU COULD HAVE A SINGLE CENTRAL COPY OF THE 02/$5#43 TABLE SHARED BY ALL USERS AT ALL FIVE ORDER PROCESSING SITES !LTERNATIVELY YOU COULD HAVE A FULLY MIRRORED COPY OF THE 02/$5#43 TABLE AT EACH OF THE FIVE SITES 4HE FULLY MIRRORED SOLUTION IS ALMOST CERTAINLY IMPRACTICAL BECAUSE THE FREQUENT UPDATES TO THE 02/$5#43 TABLE AS EACH ORDER IS TAKEN WILL CAUSE EXCESSIVE NETWORK TRAFFIC TO KEEP THE FIVE COPIES OF THE TABLE IN PERFECT SYNCHRONIZATION "UT SUPPOSE THE COMPANY BELIEVES IT CAN STILL MAINTAIN ADEQUATE CUSTOMER SATISFACTION WITH A POLICY THAT IS SLIGHTLY LESS STRICTFOR EXAMPLE IT PROMISES TO NOTIFY ANY CUSTOMER WITHIN HOURS IF THE ORDER CANNOT BE FILLED IMMEDIATELY AND TO GIVE THE CUSTOMER AN OPPORTUNITY TO CANCEL THE ORDER )N THIS CASE A REPLICATED 02/$5#43 TABLE BECOMES AN EXCELLENT SOLUTION /NCE A DAY UPDATES TO THE 02/$5#43 TABLE CAN BE DOWNLOADED TO THE REPLICATED COPY AT EACH OF THE FIVE SITES $URING THE DAY ORDERS ARE VERIFIED AGAINST THE LOCAL COPY OF THE 02/$5#43 TABLE BUT ONLY THE LOCAL 02/$5#43 TABLE IS UPDATED 4HIS PREVENTS THE COMPANY FROM TAKING AN ORDER FOR WHICH THERE WAS NOT ADEQUATE STOCK ON HAND AT THE BEGINNING OF THE DAY BUT IT DOES NOT PREVENT ORDERS TAKEN AT TWO OR THREE DIFFERENT SITES FROM EXCEEDING THE AVAILABLE STOCK 4HE NEXT NIGHT WHEN DATA COMMUNICATIONS COSTS ARE LOWER THAN THEY ARE DURING THE DAY THE ORDERS FROM EACH SITE ARE TRANSMITTED TO A CENTRAL SITE WHICH PROCESSES THEM AGAINST A CENTRAL COPY OF THE 02/$5#43 TABLE /RDERS THAT CANNOT BE FILLED FROM INVENTORY ARE FLAGGED AND A REPORT OF THEM IS GENERATED 7HEN PROCESSING IS COMPLETE THE UPDATED 02/$5#43 TABLE ALONG WITH THE PROBLEM ORDERS REPORT IS TRANSMITTED BACK TO EACH OF THE FIVE SITES TO PREPARE FOR THE NEXT DAYS PROCESSING 7HICH IS THE CORRECT ARCHITECTURE FOR SUPPORTING THE OPERATION OF THIS GLOBAL BUSINESS !S THE EXAMPLE SHOWS IT IS NOT SO MUCH A DATABASE ARCHITECTURE QUESTION AS A BUSINESS POLICY QUESTION 4HE INTERDEPENDENCE OF COMPUTER SYSTEMS ARCHITECTURES AND BUSINESS OPERATIONS IS ONE OF THE REASONS WHY DECISIONS ABOUT REPLICATION AND DATA DISTRIBUTION INEVITABLY MAKE CERTAIN TYPES OF BUSINESS OPERATIONS EASIER AND OTHERS HARDER
)N MANY CASES ITS POSSIBLE TO STRUCTURE AN APPLICATION THAT INVOLVES REPLICATED DATA SO THAT CONFLICTS BETWEEN REPLICA UPDATES ARE AVOIDED OR GREATLY MINIMIZED 4HE $"-3 CONFLICT RESOLUTION RULES ARE THEN APPLIED AS A LAST RESORT WHEN A CONFLICT ARISES DESPITE THE DESIGN OF THE APPLICATION 4HE NEXT FEW SECTIONS DESCRIBE SOME TYPICAL REPLICATED TABLE SCENARIOS AND THE APPLICATION STRUCTURE THAT IS OFTEN USED IN EACH SCENARIO TO MINIMIZE REPLICATION CONFLICTS
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4YPICALõ2EPLICATIONõ!RCHITECTURES
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(ORIZONTALõ4ABLEõ3UBSETS /NE EFFICIENT WAY TO REPLICATE PARTS OF A TABLE ACROSS A NETWORK IS TO DIVIDE THE TABLE HORIZONTALLY PLACING DIFFERENT ROWS OF THE TABLE ON DIFFERENT SYSTEMS &IGURE SHOWS A SIMPLE EXAMPLE WHERE A HORIZONTAL TABLE SPLIT IS USEFUL )N THIS APPLICATION A COMPANY OPERATES THREE DISTRIBUTION CENTERS EACH WITH ITS OWN COMPUTER SYSTEM AND $"-3 TO MANAGE AN INVENTORY DATABASE AND ORDER PROCESSING ! CENTRAL DATABASE IS ALSO MAINTAINED FOR PRODUCTION PLANNING PURPOSES 4O SUPPORT THIS ENVIRONMENT THE 02/$5#43 TABLE IS SPLIT HORIZONTALLY INTO THREE PARTS AND EXPANDED TO INCLUDE A ,/#!4)/. COLUMN THAT TELLS WHERE THE INVENTORY IS LOCATED 4HE CENTRAL COPY OF THE TABLE CONTAINS ALL OF THE ROWS 4HE ROWS OF THE TABLE THAT DESCRIBE INVENTORY IN EACH DISTRIBUTION CENTER ARE REPLICATED IN THE LOCAL DATABASE MANAGED BY THAT CENTERS $"-3 )N THIS CASE MOST UPDATES TO THE 02/$5#43 TABLE TAKE PLACE AT THE DISTRIBUTION CENTER ITSELF AS IT PROCESSES ORDERS "ECAUSE DISTRIBUTION CENTER REPLICAS ARE MUTUALLY EXCLUSIVE THAT IS A ROW FROM THE 02/$5#43 TABLE APPEARS IN ONLY ONE DISTRIBUTION CENTER REPLICA UPDATE CONFLICTS ARE AVOIDED 4HE REPLICAS IN THE DISTRIBUTION CENTER CAN PERIODICALLY TRANSMIT UPDATES TO THE CENTRAL DATABASE TO KEEP IT UP TO DATE
6ERTICALõ4ABLEõ3UBSETS !NOTHER EFFICIENT WAY TO MANAGE TABLE REPLICATION IS TO DIVIDE THE TABLE VERTICALLY REPLICATING DIFFERENT COLUMNS OF THE TABLE ON DIFFERENT SYSTEMS &IGURE SHOWS A SIMPLE EXAMPLE OF A VERTICAL TABLE SPLIT 4HE 3!,%32%03 TABLE HAS BEEN EXPANDED TO INCLUDE NEW COLUMNS OF PERSONNEL INFORMATION PHONE NUMBER MARITAL STATUS ETC AND ITS INFORMATION IS NEEDED IN TWO DATABASESONE IN THE ORDER PROCESSING DEPARTMENT AND THE OTHER IN THE PERSONNEL DEPARTMENT -OST OF THE ACTIVITY IN EACH DEPARTMENT FOCUSES ON ONE OR TWO COLUMNS OF THE TABLE BUT MANY QUERIES AND REPORTS USE BOTH PERSONNEL RELATED AND ORDER RELATED COLUMNS
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4O ACCOMMODATE THIS APPLICATION THE 3!,%32%03 TABLE IS REPLICATED ON BOTH SYSTEMS BUT CONCEPTUALLY IT IS SPLIT VERTICALLY INTO TWO PARTS 4HE COLUMNS OF THE TABLE THAT STORE PERSONNEL DATA .!-% !'% ()2%?$!4% 0(/.% -!22)%$ ARE OWNED BY THE PERSONNEL SYSTEM )T WINS ANY CONFLICTS RELATED TO UPDATES ON THESE COLUMNS 4HE OTHER COLUMNS %-0,?.5- 15/4! 3!,%3 2%0?/&&)#% ARE OWNED BY THE ORDER PROCESSING SYSTEM )T WINS UPDATE CONFLICTS RELATED TO THESE COLUMNS "ECAUSE THE ENTIRE TABLE IS REPLICATED ON BOTH SYSTEMS EITHER SYSTEM CAN BE USED TO GENERATE REPORTS AND HANDLE AD HOC INQUIRIES AND ALL OF THESE CAN BE PROCESSED LOCALLY /NLY UPDATES INVOLVE THE REPLICATION MECHANISM GENERATE NETWORK TRAFFIC AND POTENTIALLY REQUIRE CONFLICT RESOLUTION
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7HEN TABLE REPLICATION IS USED TO ACHIEVE HIGH AVAILABILITY THAT IS RESISTANCE TO COMPUTER OR DATABASE FAILURE THE ENTIRE TABLE IS TYPICALLY MIRRORED AS SHOWN IN &IGURE 4HE EASIEST WAY TO IMPLEMENT THIS CONFIGURATION IS IF ONE SYSTEM IS THE ACTIVE SYSTEM AND ANOTHER IS A HOT STANDBY )N THIS SCHEME ALL DATABASE UPDATE ACTIVITY NORMALLY FLOWS TO THE ACTIVE SYSTEM 3YSTEM ! WHICH REPLICATES THE UPDATES TO THE STANDBY SYSTEM 3YSTEM " /NLY IN THE EVENT OF SYSTEM FAILURE DOES THE UPDATE TRANSACTION ACCESS SWITCH OVER TO THE STANDBY SYSTEM BUT IT HAS FRESH DATA BECAUSE OF THE REPLICATED TABLE )N MOST VENDOR IMPLEMENTATIONS THE STANDBY SYSTEM IS AVAILABLE FOR READ ONLY ACCESS SUCH AS QUERIES AND REPORTING 4HE DISADVANTAGE OF THIS SCHEME IS THAT HIGH LEVELS OF MIRRORED UPDATES CAN ADVERSELY AFFECT READ ONLY ACCESS PERFORMANCE AND VICE VERSA A PROBLEM EASILY SOLVED WITH PROPER TUNING AND THE EXPECTATION THAT READ ONLY ACCESS TO THE STANDBY DATABASE MUST BE A LOWER PRIORITY )N IMPLEMENTATIONS WHERE THE STANDBY DATABASE IS NOT ACCESSIBLE FOR READ ONLY ACCESS THE STANDBY DATABASE DOESNT ADD ANY DATA PROCESSING CAPABILITY BUT THE ORGANIZATION MUST STILL ABSORB THE COST OF PURCHASING AND MAINTAINING IT
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&OR THIS REASON HIGH AVAILABILITY SYSTEMS ARE OFTEN DESIGNED TO ALSO PROVIDE LOAD BALANCING AS SHOWN IN &IGURE )N THIS CONFIGURATION SOME FRONT END SOFTWARE INTERCEPTS $"-3 ACCESS REQUESTS AND EVENLY DISTRIBUTES THEM BETWEEN THE TWO OR MORE COMPUTER SYSTEMS 5NDER NORMAL OPERATION BOTH ALL SYSTEMS CONTRIBUTE DATA PROCESSING POWER NONE IS WASTED &URTHERMORE ITS CONCEPTUALLY EASY TO GROW THE DATA PROCESSING POWER BY ADDING MORE COMPUTER SYSTEMS WITH A COPY OF THE REPLICATED TABLE
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#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
4HIS TYPE OF MIRRORED TABLE APPROACH CAN BE HIGHLY EFFECTIVE IF THE RATIO OF DATABASE QUERIES TO DATABASE UPDATES IS VERY HIGH FOR EXAMPLE PERCENT READ ACCESS PERCENT UPDATE ACCESS )F THE PERCENTAGE OF UPDATES IS TOO HIGH THE POTENTIAL FOR CONFLICTS AND THE REPLICATION OVERHEAD CAN DIMINISH THE EFFECTIVENESS AND SCALABILITY OF THE OVERALL CONFIGURATION %FFICIENCY ALSO DECREASES WITH EACH INCREASE IN THE NUMBER OF REPLICATED SYSTEMS SINCE THE REPLICATION OVERHEAD RISES /NE COMMON WAY TO GET MORE EFFICIENCY OUT OF A MIRRORED TABLE CONFIGURATION LIKE THE ONE IN &IGURE IS TO DIVIDE UPDATES TO THE TABLE BASED ON SOME RULE &OR EXAMPLE IF THE MIRRORED TABLE IS A CUSTOMER TABLE THE PRIMARY KEY MAY BE THE CUSTOMER NAME 4HE FRONT END LOAD BALANCING SOFTWARE CAN THEN BE WRITTEN SO THAT UPDATES FOR CUSTOMER NAMES STARTING WITH ! THROUGH - ARE ROUTED TO THE ONE SYSTEM AND UPDATES FOR CUSTOMER NAMES STARTING WITH . THROUGH : ARE ROUTED TO THE OTHER SYSTEM 4HIS ELIMINATES THE POSSIBILITY OF UPDATE CONFLICTS "ECAUSE THE TABLE REMAINS FULLY REPLICATED UNDER THIS SCENARIO READ ACCESS REQUESTS CAN STILL BE DISTRIBUTED RANDOMLY BETWEEN THE TWO SYSTEMS TO BALANCE THE WORKLOAD 4HIS TYPE OF APPROACH CAN BE QUITE EFFECTIVE IN ACHIEVING SCALABLE DATABASE PERFORMANCE WITH REPLICATED TABLES )T CAN BE FAIRLY EASILY EXTENDED FROM A TWO WAY SCHEME TO AN . WAY SCHEME WHERE UPDATES ARE SPLIT AMONG THREE OR MORE DATABASE SERVERS
$ISTRIBUTEDõ$ATABASEõ!CCESS /VER THE LAST SEVERAL YEARS RESEARCH INTO FULLY DISTRIBUTED DATABASE ACCESS HAS SLOWLY BUT SURELY FOUND ITS WAY INTO COMMERCIAL PRODUCTS 4ODAY MANY OF THE MAINSTREAM ENTERPRISE DATABASE PRODUCTS OFFER AT LEAST SOME LEVEL OF TRANSPARENT DISTRIBUTED DATABASE ACCESS !S NOTED EARLIER IN THE h2EMOTE $ATA 4RANSPARENCYv SECTION THE PERFORMANCE IMPLICATIONS OF DISTRIBUTED DATABASE ACCESS AND UPDATES CAN BE QUITE SUBSTANTIAL 4WO VERY SIMILAR LOOKING QUERIES CAN CREATE MASSIVELY DIFFERENT AMOUNTS OF NETWORK TRAFFIC AND OVERHEAD ! SINGLE QUERY CARRIED OUT IN A BRUTE FORCE METHOD OR AN OPTIMIZED METHOD CAN CREATE THE SAME DIFFERENCES DEPENDING ON THE QUALITY OF THE OPTIMIZATION DONE BY THE $"-3 "ECAUSE OF THESE CHALLENGES ALL OF THE VENDORS HAVE TAKEN A STEP BY STEP APPROACH TO DELIVERING DISTRIBUTED DATABASE ACCESS 7HEN )"- FIRST ANNOUNCED ITS BLUEPRINT FOR DISTRIBUTED DATA MANAGEMENT IN ITS 31, PRODUCTS IT DEFINED A FOUR STAGE APPROACH )"-S FOUR STAGES SHOWN IN 4ABLE PROVIDE AN EXCELLENT FRAMEWORK FOR UNDERSTANDING DISTRIBUTED DATA MANAGEMENT CAPABILITIES AND THEIR IMPLICATIONS iÃVÀ«Ì
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4HE )"- SCHEME PROVIDES A SIMPLE MODEL FOR DEFINING THE DISTRIBUTED DATA ACCESS PROBLEM A USER OF ONE COMPUTER SYSTEM NEEDS TO ACCESS DATA STORED ON ONE OR MORE OTHER COMPUTER SYSTEMS 4HE SOPHISTICATION OF THE DISTRIBUTED ACCESS INCREASES AT EACH STAGE 4HUS THE CAPABILITIES PROVIDED BY A GIVEN $"-3 CAN BE DESCRIBED IN TERMS OF WHICH STAGE IT HAS REACHED )N ADDITION WITHIN EACH STAGE A DISTINCTION CAN BE MADE BETWEEN READ ONLY ACCESS WITH THE 3%,%#4 STATEMENT AND UPDATE ACCESS WITH THE ).3%24 $%,%4% AND 50$!4% STATEMENTS ! $"-3 PRODUCT OFTEN PROVIDES READ ONLY CAPABILITY FOR A GIVEN STAGE BEFORE FULL UPDATE CAPABILITY IS PROVIDED
2EMOTEõ2EQUESTS 4HE FIRST STAGE OF DISTRIBUTED DATA ACCESS AS DEFINED BY )"- IS A REMOTE REQUEST SHOWN IN &IGURE )N THIS STAGE THE 0# USER MAY ISSUE A 31, STATEMENT THAT QUERIES OR UPDATES DATA IN A SINGLE REMOTE DATABASE %ACH INDIVIDUAL 31, STATEMENT OPERATES AS ITS OWN TRANSACTION SIMILAR TO THE AUTOCOMMIT MODE PROVIDED BY MANY INTERACTIVE 31, PROGRAMS 4HE USER CAN ISSUE A SEQUENCE OF 31, STATEMENTS FOR VARIOUS DATABASES BUT THE $"-3 DOESNT SUPPORT MULTISTATEMENT TRANSACTIONS 2EMOTE REQUESTS ARE VERY USEFUL WHEN A 0# USER NEEDS TO QUERY CORPORATE DATA 5SUALLY THE REQUIRED DATA IS LOCATED WITHIN A SINGLE DATABASE SUCH AS A DATABASE OF ORDER PROCESSING OR MANUFACTURING DATA 5SING A REMOTE REQUEST THE 0# PROGRAM CAN RETRIEVE THE REMOTE DATA FOR PROCESSING BY A 0# SPREADSHEET GRAPHICS PROGRAM OR DESKTOP PUBLISHING PACKAGE 4HE REMOTE REQUEST CAPABILITY IS NOT POWERFUL ENOUGH FOR MOST TRANSACTION PROCESSING APPLICATIONS &OR EXAMPLE CONSIDER A 0# BASED ORDER ENTRY APPLICATION THAT ACCESSES A CORPORATE DATABASE 4O PROCESS A NEW ORDER THE 0# PROGRAM MUST CHECK INVENTORY LEVELS ADD THE ORDER TO THE DATABASE DECREASE THE INVENTORY TOTALS AND ADJUST CUSTOMER AND SALES TOTALS INVOLVING PERHAPS HALF A DOZEN DIFFERENT 31, STATEMENTS !S EXPLAINED IN #HAPTER DATABASE INTEGRITY CAN BE CORRUPTED IF THESE STATEMENTS DO NOT EXECUTE AS A SINGLE TRANSACTION (OWEVER THE REMOTE REQUEST STAGE DOES NOT SUPPORT MULTISTATEMENT TRANSACTIONS SO IT CANNOT SUPPORT THIS APPLICATION
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2EMOTEõ4RANSACTIONS
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4HE SECOND STAGE OF DISTRIBUTED DATA ACCESS AS DEFINED BY )"- IS A REMOTE TRANSACTION CALLED A REMOTE UNIT OF WORK BY )"- SHOWN IN &IGURE 2EMOTE TRANSACTIONS EXTEND THE REMOTE REQUEST STAGE TO INCLUDE MULTISTATEMENT TRANSACTION SUPPORT 4HE 0# USER CAN ISSUE A SERIES OF 31, STATEMENTS THAT QUERY OR UPDATE DATA IN A REMOTE DATABASE AND THEN COMMIT OR ROLL BACK THE ENTIRE SERIES OF STATEMENTS AS A SINGLE TRANSACTION 4HE $"-3 GUARANTEES THAT THE ENTIRE TRANSACTION WILL SUCCEED OR FAIL AS A UNIT AS IT DOES FOR TRANSACTIONS ON A LOCAL DATABASE (OWEVER ALL OF THE 31, STATEMENTS THAT MAKE UP THE TRANSACTION MUST REFERENCE A SINGLE REMOTE DATABASE 2EMOTE TRANSACTIONS OPEN THE DOOR FOR DISTRIBUTED TRANSACTION PROCESSING APPLICATIONS &OR EXAMPLE IN AN ORDER PROCESSING APPLICATION A 0# BASED ORDER ENTRY PROGRAM CAN NOW PERFORM A SEQUENCE OF QUERIES UPDATES AND INSERTS IN THE INVENTORY DATABASE TO PROCESS A NEW ORDER 4HE PROGRAM ENDS THE STATEMENT SEQUENCE WITH A #/--)4 OR 2/,,"!#+ FOR THE TRANSACTION 2EMOTE TRANSACTION CAPABILITY TYPICALLY REQUIRES A $"-3 OR AT LEAST TRANSACTION PROCESSING LOGIC ON THE 0# AS WELL AS ON THE SYSTEM WHERE THE DATABASE IS 4HE TRANSACTION LOGIC OF THE $"-3 MUST BE EXTENDED ACROSS THE NETWORK TO ENSURE THAT THE LOCAL AND REMOTE SYSTEMS ALWAYS HAVE THE SAME OPINION ABOUT WHETHER A TRANSACTION HAS BEEN COMMITTED (OWEVER THE ACTUAL RESPONSIBILITY FOR MAINTAINING DATABASE INTEGRITY REMAINS WITH THE REMOTE $"-3 2EMOTE TRANSACTION CAPABILITY IS OFTEN THE HIGHEST LEVEL OF DISTRIBUTED DATABASE ACCESS PROVIDED BY DATABASE GATEWAYS THAT LINK ONE VENDORS $"-3 TO OTHER $"-3 BRANDS &OR EXAMPLE MOST OF THE INDEPENDENT ENTERPRISE DATABASE VENDORS 3YBASE /RACLE )NFORMIX PROVIDE GATEWAYS FROM THEIR 5.)8 OR ,INUX BASED $"-3 SYSTEMS TO )"-S MAINFRAME $" IMPLEMENTATION 3OME GATEWAY PRODUCTS GO BEYOND THE BOUNDS OF REMOTE TRANSACTIONS ALLOWING A USER TO JOIN IN A SINGLE QUERY TABLES FROM A LOCAL DATABASE WITH TABLES FROM A REMOTE DATABASE MANAGED BY A DIFFERENT BRAND OF $"-3 (OWEVER THESE GATEWAYS DO NOT AND CANNOT WITHOUT SUPPORT FROM THE REMOTE $"-3 PROVIDE THE UNDERLYING TRANSACTION LOGIC REQUIRED TO SUPPORT THE HIGHER STAGES OF DISTRIBUTED ACCESS AS DEFINED BY )"- 4HE GATEWAY CAN ENSURE THE INTEGRITY OF THE LOCAL AND REMOTE DATABASES INDIVIDUALLY BUT IT CANNOT GUARANTEE THAT A TRANSACTION WILL NOT BE COMMITTED IN ONE AND ROLLED BACK IN THE OTHER
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$ISTRIBUTEDõ4RANSACTIONS 4HE THIRD STAGE OF DISTRIBUTED DATA ACCESS AS DEFINED BY )"- IS A DISTRIBUTED TRANSACTION A DISTRIBUTED UNIT OF WORK IN )"- PARLANCE SHOWN IN &IGURE !T THIS STAGE EACH INDIVIDUAL 31, STATEMENT STILL QUERIES OR UPDATES A SINGLE DATABASE ON A SINGLE REMOTE COMPUTER SYSTEM (OWEVER THE SEQUENCE OF 31, STATEMENTS WITHIN A TRANSACTION MAY ACCESS TWO OR MORE DATABASES LOCATED ON DIFFERENT SYSTEMS 7HEN THE TRANSACTION IS COMMITTED OR ROLLED BACK THE $"-3 GUARANTEES THAT ALL PARTS OF THE TRANSACTION ON ALL OF THE SYSTEMS INVOLVED IN THE TRANSACTION WILL BE COMMITTED OR ROLLED BACK 4HE $"-3 SPECIFICALLY GUARANTEES THAT THERE WILL NOT BE A PARTIAL TRANSACTION WHERE THE TRANSACTION IS COMMITTED ON ONE SYSTEM AND ROLLED BACK ON ANOTHER $ISTRIBUTED TRANSACTIONS SUPPORT THE DEVELOPMENT OF VERY SOPHISTICATED TRANSACTION PROCESSING APPLICATIONS &OR EXAMPLE IN THE CORPORATE NETWORK OF &IGURE A 0# ORDER PROCESSING APPLICATION CAN QUERY THE INVENTORY DATABASES ON TWO OR THREE DIFFERENT DISTRIBUTION CENTER SERVERS TO CHECK THE INVENTORY OF A SCARCE PRODUCT AND THEN UPDATE THE DATABASES TO COMMIT INVENTORY FROM MULTIPLE LOCATIONS TO A CUSTOMERS ORDER 4HE $"-3 ENSURES THAT OTHER CONCURRENT ORDERS DO NOT INTERFERE WITH THE REMOTE ACCESS OF THE FIRST TRANSACTION $ISTRIBUTED TRANSACTIONS ARE MUCH MORE DIFFICULT TO PROVIDE THAN THE FIRST TWO STAGES OF DISTRIBUTED DATA ACCESS )TS IMPOSSIBLE TO PROVIDE DISTRIBUTED TRANSACTIONS WITHOUT THE ACTIVE COOPERATION OF THE INDIVIDUAL $"-3 SYSTEMS INVOLVED IN THE TRANSACTION &OR THIS REASON THE $"-3 BRANDS THAT SUPPORT DISTRIBUTED TRANSACTIONS ALMOST ALWAYS SUPPORT THEM ONLY FOR A HOMOGENEOUS NETWORK OF DATABASES ALL MANAGED BY THE SAME $"-3 BRAND THAT IS AN ALL /RACLE OR ALL 3YBASE NETWORK ! SPECIAL TRANSACTION PROTOCOL CALLED THE TWO PHASE COMMIT PROTOCOL IS USED TO IMPLEMENT DISTRIBUTED TRANSACTIONS AND ENSURE THAT THEY PROVIDE THE ALL OR NOTHING REQUIREMENT OF A 31, TRANSACTION 4HE DETAILS OF THIS PROTOCOL ARE DESCRIBED LATER IN THE SECTION h4HE 4WO 0HASE #OMMIT 0ROTOCOLv
$ISTRIBUTEDõ2EQUESTS 4HE FINAL STAGE OF DISTRIBUTED DATA ACCESS IN THE )"- MODEL IS A DISTRIBUTED REQUEST SHOWN IN &IGURE !T THIS STAGE A SINGLE 31, STATEMENT MAY REFERENCE TABLES FROM TWO OR MORE DATABASES LOCATED ON DIFFERENT COMPUTER SYSTEMS 4HE $"-3 IS RESPONSIBLE FOR AUTOMATICALLY CARRYING OUT THE STATEMENT ACROSS THE NETWORK ! SEQUENCE OF DISTRIBUTED REQUEST STATEMENTS CAN BE GROUPED TOGETHER AS A TRANSACTION !S IN THE PREVIOUS DISTRIBUTED TRANSACTION STAGE THE $"-3 MUST GUARANTEE THE INTEGRITY OF THE DISTRIBUTED TRANSACTION ON ALL SYSTEMS THAT ARE INVOLVED
#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
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4HE DISTRIBUTED REQUEST STAGE DOESNT MAKE ANY NEW DEMANDS ON THE $"-3 TRANSACTION PROCESSING LOGIC BECAUSE THE $"-3 ALREADY HAD TO SUPPORT TRANSACTIONS ACROSS SYSTEM BOUNDARIES AT THE PREVIOUS DISTRIBUTED TRANSACTION STAGE (OWEVER DISTRIBUTED REQUESTS POSE MAJOR NEW CHALLENGES FOR THE $"-3 OPTIMIZATION LOGIC 4HE OPTIMIZER MUST NOW CONSIDER NETWORK SPEED WHEN IT EVALUATES ALTERNATE METHODS FOR CARRYING OUT A 31, STATEMENT )F THE LOCAL $"-3 MUST REPEATEDLY ACCESS PART OF A REMOTE TABLE FOR EXAMPLE WHEN MAKING A JOIN IT MAY BE FASTER TO COPY PART OF THE TABLE ACROSS THE NETWORK IN ONE LARGE BULK TRANSFER RATHER THAN REPEATEDLY RETRIEVING INDIVIDUAL ROWS ACROSS THE NETWORK 4HE RELATIVE SIZES OF THE TABLES ON THE LOCAL AND REMOTE SYSTEM ARE ALSO RELEVANT OPTIMIZATION FACTORS AS IS THE SELECTIVITY OF ANY SEARCH CONDITIONS IN THE 3%,%#4 CLAUSE &OR SOME QUERIES THE SEARCH CONDITIONS MAY SELECT ONLY ONE OR A FEW ROWS ON THE LOCAL SYSTEM AND HUNDREDS OF ROWS ON THE REMOTE SYSTEM SO THEY SHOULD BE APPLIED LOCALLY FIRST &OR OTHER QUERIES INVOLVING THE SAME TABLES THE RELATIVE SELECTIVITY MAY BE REVERSED AND THE REMOTE SEARCH CONDITION SHOULD BE APPLIED &OR STILL OTHER QUERIES THE JOIN CONDITION ITSELF MAY LIMIT THE ROWS THAT PARTICIPATE IN BOTH THE LOCAL AND REMOTE SYSTEMS AND IT MAY BE MOST EFFICIENT TO APPLY IT FIRST )N EACH CASE THE COST OF THE QUERY IS NOT JUST THE COST OF THE DATABASE ACCESS BUT ALSO THE COST OF SHIPPING THE RESULTS OF INTERMEDIATE QUERY EXECUTION STEPS BACK AND FORTH ACROSS THE NETWORK 4HE OPTIMIZER MUST ALSO DECIDE WHICH COPY OF THE $"-3 SHOULD HANDLE STATEMENT EXECUTION )F MOST OF THE TABLES ARE ON A REMOTE SYSTEM IT MAY BE A GOOD IDEA FOR THE REMOTE $"-3 ON THAT SYSTEM TO EXECUTE THE STATEMENT (OWEVER THAT MAY BE A BAD CHOICE IF THE REMOTE SYSTEM IS HEAVILY LOADED 4HUS THE OPTIMIZERS TASK IS BOTH MORE COMPLEX AND MUCH MORE IMPORTANT IN A DISTRIBUTED REQUEST 5LTIMATELY THE GOAL OF THE DISTRIBUTED REQUEST STAGE IS TO MAKE THE ENTIRE DISTRIBUTED DATABASE LOOK LIKE ONE LARGE DATABASE TO THE USER )DEALLY THE USER WOULD HAVE FULL ACCESS TO ANY TABLE IN THE DISTRIBUTED DATABASE AND COULD USE 31, TRANSACTIONS WITHOUT KNOWING ANYTHING ABOUT THE PHYSICAL LOCATION OF THE DATA 5NFORTUNATELY THIS IDEAL SCENARIO WOULD QUICKLY PROVE IMPRACTICAL IN REAL NETWORKS )N A NETWORK OF ANY SIZE THE NUMBER OF TABLES IN THE DISTRIBUTED DATABASE WOULD QUICKLY BECOME VERY LARGE AND USERS WOULD FIND IT IMPOSSIBLE TO FIND DATA OF INTEREST 4HE USER IDS OF EVERY DATABASE IN THE ORGANIZATION WOULD HAVE TO BE COORDINATED TO MAKE SURE THAT A GIVEN USER ID UNIQUELY IDENTIFIED A USER IN ALL DATABASES $ATABASE ADMINISTRATION WOULD ALSO BE VERY DIFFICULT
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)N PRACTICE THEREFORE DISTRIBUTED REQUESTS MUST BE IMPLEMENTED SELECTIVELY $ATABASE ADMINISTRATORS MUST DECIDE WHICH REMOTE TABLES ARE TO BE MADE VISIBLE TO LOCAL USERS AND WHICH WILL REMAIN HIDDEN 4HE COOPERATING $"-3 COPIES MUST TRANSLATE USER IDS FROM ONE SYSTEM TO ANOTHER ALLOWING EACH DATABASE TO BE ADMINISTERED AUTONOMOUSLY WHILE PROVIDING SECURITY FOR REMOTE DATA ACCESS $ISTRIBUTED REQUESTS THAT WOULD CONSUME TOO MANY $"-3 OR NETWORK RESOURCES MUST BE DETECTED AND PROHIBITED BEFORE THEY IMPACT OVERALL $"-3 PERFORMANCE "ECAUSE OF THEIR COMPLEXITY DISTRIBUTED REQUESTS ARE NOT FULLY SUPPORTED BY ANY COMMERCIAL 31, BASED $"-3 TODAY AND IT WILL BE SOME TIME BEFORE EVEN A MAJORITY OF THEIR FEATURES ARE AVAILABLE /NE MAJOR STEP TOWARD DISTRIBUTED PROCESSING ACROSS DATABASE BRANDS HAS BEEN THE STANDARDIZATION OF A DISTRIBUTED TRANSACTION PROTOCOL 4HE 8! PROTOCOL ORIGINALLY DEVELOPED TO COORDINATE AMONG MULTIPLE TRANSACTION MONITORS IS BEING ACTIVELY APPLIED TO DISTRIBUTED DATABASE TRANSACTIONS AS WELL ! *AVA VERSION OF THE SAME CAPABILITY CALLED *AVA 4RANSACTION 0ROTOCOL *40 PROVIDES A DISTRIBUTED TRANSACTION INTERFACE FOR *AVA BASED APPLICATIONS AND APPLICATION SERVERS 4ODAY MOST COMMERCIAL $"-3 PRODUCTS DESIGNED TO BE USED IN A NETWORK ENVIRONMENT SUPPORT 8! AND *4! INTERFACES
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! DISTRIBUTED $"-3 MUST PRESERVE THE ALL OR NOTHING QUALITY OF A 31, TRANSACTION IF IT IS TO PROVIDE DISTRIBUTED TRANSACTIONS 4HE USER OF THE DISTRIBUTED $"-3 EXPECTS THAT A COMMITTED TRANSACTION WILL BE COMMITTED ON ALL OF THE SYSTEMS WHERE DATA RESIDES AND THAT A ROLLED BACK TRANSACTION WILL BE ROLLED BACK ON ALL OF THE SYSTEMS AS WELL &URTHER FAILURES IN A NETWORK CONNECTION OR IN ONE OF THE SYSTEMS SHOULD CAUSE THE $"-3 TO ABORT A TRANSACTION AND ROLL IT BACK RATHER THAN LEAVING THE TRANSACTION IN A PARTIALLY COMMITTED STATE !LL COMMERCIAL $"-3 SYSTEMS THAT SUPPORT DISTRIBUTED TRANSACTIONS USE A TECHNIQUE CALLED TWO PHASE COMMIT TO PROVIDE THAT SUPPORT 9OU DONT HAVE TO UNDERSTAND THE TWO PHASE COMMIT SCHEME TO USE DISTRIBUTED TRANSACTIONS )N FACT THE WHOLE POINT OF THE SCHEME IS TO SUPPORT DISTRIBUTED TRANSACTIONS WITHOUT YOUR KNOWING IT (OWEVER UNDERSTANDING THE MECHANICS OF A TWO PHASE COMMIT CAN HELP YOU PLAN EFFICIENT DATABASE ACCESS 4O UNDERSTAND WHY A SPECIAL TWO PHASE COMMIT PROTOCOL IS NEEDED CONSIDER THE DATABASE IN &IGURE 4HE USER LOCATED ON 3YSTEM ! HAS UPDATED A TABLE ON 3YSTEM " AND A TABLE ON 3YSTEM # AND NOW WANTS TO COMMIT THE TRANSACTION 3UPPOSE THE $"-3 SOFTWARE ON 3YSTEM ! TRIED TO COMMIT THE TRANSACTION BY SIMPLY SENDING A #/--)4 MESSAGE TO 3YSTEM " AND 3YSTEM # AND THEN WAITING FOR THEIR AFFIRMATIVE REPLIES 4HIS STRATEGY WORKS AS LONG AS 3YSTEMS " AND # CAN BOTH SUCCESSFULLY COMMIT THEIR PART OF THE TRANSACTION "UT WHAT HAPPENS IF A PROBLEM SUCH AS A DISK FAILURE OR A DEADLOCK CONDITION PREVENTS 3YSTEM # FROM COMMITTING AS REQUESTED 3YSTEM " WILL COMMIT ITS PART OF THE TRANSACTION AND SEND BACK AN ACKNOWLEDGMENT 3YSTEM # WILL ROLL BACK ITS PART OF THE TRANSACTION BECAUSE OF THE ERROR AND SEND BACK AN ERROR MESSAGE AND THE USER ENDS UP WITH A PARTIALLY COMMITTED PARTIALLY ROLLED BACK TRANSACTION .OTE THAT 3YSTEM ! CANT CHANGE ITS MIND AT THIS POINT AND ASK 3YSTEM " TO ROLL BACK THE TRANSACTION 4HE TRANSACTION ON 3YSTEM " HAS BEEN COMMITTED AND OTHER USERS MAY ALREADY HAVE MODIFIED THE DATA ON 3YSTEM " BASED ON THE CHANGES MADE BY THE TRANSACTION
#HAPTERçç
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4HE TWO PHASE COMMIT PROTOCOL ELIMINATES THE PROBLEMS OF THE SIMPLE STRATEGY SHOWN IN &IGURE &IGURE ILLUSTRATES THE STEPS INVOLVED IN A TWO PHASE COMMIT 4HE PROGRAM ON 3YSTEM ! ISSUES A #/--)4 FOR THE CURRENT DISTRIBUTED TRANSACTION WHICH HAS UPDATED TABLES ON 3YSTEM " AND 3YSTEM # 3YSTEM ! WILL ACT AS THE COORDINATOR OF THE COMMIT PROCESS COORDINATING THE ACTIVITIES OF THE $"-3 SOFTWARE ON 3YSTEMS " AND #
3YSTEM ! SENDS A '%4 2%!$9 MESSAGE TO BOTH 3YSTEM " AND 3YSTEM # AND NOTES THE MESSAGE IN ITS OWN TRANSACTION LOG
7HEN THE $"-3 ON 3YSTEM " OR # RECEIVES THE '%4 2%!$9 MESSAGE IT MUST PREPARE TO EITHER COMMIT OR ROLL BACK THE CURRENT TRANSACTION )F THE $"-3 CAN GET INTO THIS hREADY TO COMMITv STATE IT REPLIES 9%3 TO 3YSTEM ! AND NOTES THAT FACT IN ITS LOCAL TRANSACTION LOG IF IT CANNOT GET INTO THIS STATE IT REPLIES ./
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3YSTEM ! WAITS FOR REPLIES TO ITS '%4 2%!$9 MESSAGE )F ALL OF THE REPLIES ARE 9%3 3YSTEM ! SENDS A #/--)4 MESSAGE TO BOTH 3YSTEM " AND 3YSTEM # AND NOTES THE DECISION IN ITS TRANSACTION LOG )F ANY OF THE REPLIES IS ./ OR IF ALL OF THE REPLIES ARE NOT RECEIVED WITHIN SOME TIMEOUT PERIOD 3YSTEM ! SENDS A 2/,,"!#+ MESSAGE TO BOTH SYSTEMS AND NOTES THAT DECISION IN ITS TRANSACTION LOG
7HEN THE $"-3 ON 3YSTEM " OR # RECEIVES THE #/--)4 OR 2/,,"!#+ MESSAGE IT MUST DO AS IT IS TOLD 4HE $"-3 GAVE UP THE CAPABILITY TO DECIDE THE TRANSACTIONS FATE AUTONOMOUSLY WHEN IT REPLIED 9%3 TO THE '%4 2%!$9 MESSAGE IN 3TEP 4HE $"-3 COMMITS OR ROLLS BACK ITS PART OF THE TRANSACTION AS REQUESTED WRITES THE #/--)4 OR 2/,,"!#+ MESSAGE IN ITS TRANSACTION LOG AND RETURNS AN /+ MESSAGE TO 3YSTEM !
7HEN 3YSTEM ! HAS RECEIVED ALL THE /+ MESSAGES IT KNOWS THE TRANSACTION HAS BEEN COMMITTED OR ROLLED BACK AND RETURNS THE APPROPRIATE 31,#/$% VALUE TO THE PROGRAM
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4HIS PROTOCOL PROTECTS THE DISTRIBUTED TRANSACTION AGAINST ANY SINGLE FAILURE IN 3YSTEM " 3YSTEM # OR THE COMMUNICATIONS NETWORK 4HESE TWO EXAMPLES ILLUSTRATE HOW THE PROTOCOL PERMITS RECOVERY FROM FAILURES s 3UPPOSE A FAILURE OCCURS ON 3YSTEM # BEFORE IT SENDS A 9%3 MESSAGE IN 3TEP 3YSTEM ! WILL NOT RECEIVE A 9%3 REPLY AND WILL BROADCAST A 2/,,"!#+ MESSAGE CAUSING 3YSTEM " TO ROLL BACK THE TRANSACTION 4HE $"-3 RECOVERY FACILITY ON 3YSTEM # WILL NOT FIND THE 9%3 MESSAGE OR A #/--)4 MESSAGE IN THE LOCAL TRANSACTION LOG AND IT WILL ROLL BACK THE TRANSACTION ON 3YSTEM # AS PART OF THE RECOVERY PROCESS !LL PARTS OF THE TRANSACTION WILL HAVE BEEN ROLLED BACK AT THIS POINT s 3UPPOSE A FAILURE OCCURS ON 3YSTEM # AFTER IT SENDS A 9%3 MESSAGE IN 3TEP 3YSTEM ! WILL DECIDE WHETHER TO COMMIT OR ROLL BACK THE DISTRIBUTED TRANSACTION BASED ON THE REPLY FROM 3YSTEM " 4HE $"-3 RECOVERY FACILITY ON 3YSTEM # WILL FIND THE 9%3 MESSAGE IN THE LOCAL TRANSACTION LOG BUT WILL NOT FIND A #/--)4 OR 2/,,"!#+ MESSAGE TO MARK THE END OF THE TRANSACTION 4HE RECOVERY FACILITY THEN ASKS THE COORDINATOR 3YSTEM ! WHAT THE FINAL DISPOSITION OF THE TRANSACTION WAS AND ACTS ACCORDINGLY .OTE THAT 3YSTEM ! MUST MAINTAIN A RECORD OF ITS DECISION TO COMMIT OR ROLL BACK THE TRANSACTION UNTIL IT RECEIVES THE FINAL OKAY FROM ALL OF THE PARTICIPANTS SO THAT IT CAN RESPOND TO THE RECOVERY FACILITY IN CASE OF FAILURE 4HE TWO PHASE COMMIT PROTOCOL GUARANTEES THE INTEGRITY OF DISTRIBUTED TRANSACTIONS BUT IT GENERATES A GREAT DEAL OF NETWORK TRAFFIC )F N SYSTEMS ARE INVOLVED IN THE TRANSACTION THE COORDINATOR MUST SEND AND RECEIVE A TOTAL OF N MESSAGES TO SUCCESSFULLY COMMIT THE TRANSACTION .OTE THAT THESE MESSAGES ARE IN ADDITION TO THE MESSAGES THAT ACTUALLY CARRY THE 31, STATEMENTS AND QUERY RESULTS AMONG THE SYSTEMS (OWEVER THERES NO WAY TO AVOID THE MESSAGE TRAFFIC IF A DISTRIBUTED TRANSACTION IS TO PROVIDE DATABASE INTEGRITY IN THE FACE OF SYSTEM FAILURES "ECAUSE OF THEIR HEAVY NETWORK OVERHEAD DISTRIBUTED TRANSACTIONS CAN HAVE A SERIOUS NEGATIVE EFFECT ON DATABASE PERFORMANCE &OR THIS REASON DISTRIBUTED DATABASES MUST BE CAREFULLY DESIGNED SO THAT FREQUENTLY ACCESSED OR AT LEAST FREQUENTLY UPDATED DATA IS ON A LOCAL SYSTEM OR ON A SINGLE REMOTE SYSTEM )F POSSIBLE TRANSACTIONS THAT UPDATE TWO OR MORE REMOTE SYSTEMS SHOULD BE RELATIVELY RARE
.ETWORKõ!PPLICATIONSõANDõ$ATABASEõ!RCHITECTURE
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)NNOVATIONS IN COMPUTER NETWORKING HAVE BEEN CLOSELY LINKED TO MANY OF THE INNOVATIONS IN RELATIONAL DATABASE ARCHITECTURES AND 31, OVER THE YEARS 0OWERFUL MINICOMPUTERS WITH MAINFRAME NETWORK CONNECTIONS SUCH AS $IGITALS 6!8 FAMILY WERE THE FIRST POPULAR PLATFORM FOR 31, BASED DATABASES 4HEY OFFERED A PLATFORM FOR DECISION SUPPORT BASED ON DATA OFFLOADED FROM MAINFRAME SYSTEMS 4HEY ALSO SUPPORTED LOCAL DATA PROCESSING APPLICATIONS FOR CAPTURING BUSINESS DATA AND UPLOADING IT TO CORPORATE MAINFRAME APPLICATIONS 5.)8 BASED SERVERS AND POWERFUL LOCAL AREA NETWORKS SUCH AS 3UNS SERVER PRODUCTS DROVE ANOTHER WAVE OF $"-3 GROWTH AND INNOVATION 4HIS ERA OF DATABASES AND NETWORKS GAVE BIRTH TO THE CLIENTSERVER ARCHITECTURE THAT DOMINATED ENTERPRISE DATA PROCESSING IN THE S ,ATER THE RISE OF ENTERPRISEWIDE NETWORKS AND APPLICATIONS SUCH AS %NTERPRISE 2ESOURCE 0LANNING CREATED A NEED FOR A NEW LEVEL OF DATABASE SCALABILITY AND DISTRIBUTED DATABASE CAPABILITY 4ODAY THE EXPLODING POPULARITY OF THE )NTERNET AND OPEN SOURCE PRODUCTS IS DRIVING STILL ANOTHER WAVE OF INNOVATION AS VERY HIGH PEAK LOAD TRANSACTION RATES AND PERSONALIZED USER INTERACTION DRIVE DATABASE CACHING AND MAIN MEMORY DATABASE TECHNOLOGIES
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#LIENT3ERVERõ!PPLICATIONSõANDõ$ATABASEõ!RCHITECTURE 7HEN 31, BASED DATABASES WERE FIRST DEPLOYED ON MINICOMPUTER SYSTEMS THE DATABASE AND APPLICATION ARCHITECTURE WAS VERY SIMPLEALL OF THE PROCESSING FROM SCREEN DISPLAY PRESENTATION TO CALCULATION AND DATA PROCESSING BUSINESS LOGIC TO DATABASE ACCESS OCCURRED ON THE MINICOMPUTERS #05 4HE ADVENT OF POWERFUL PERSONAL COMPUTERS AND SERVER PLATFORMS DROVE A MAJOR CHANGE IN THAT ARCHITECTURE FOR SEVERAL REASONS 4HE GRAPHICAL USER INTERFACE '5) OF POPULAR 0# OFFICE AUTOMATION SOFTWARE SPREADSHEETS WORD PROCESSORS ETC SET A NEW STANDARD FOR EASE OF USE AND COMPANIES DEMANDED THE SAME STYLE OF INTERFACE FROM CORPORATE APPLICATIONS 3UPPORTING A '5) IS PROCESSOR INTENSIVE AND DEMANDS A HIGH BANDWIDTH PATH FROM THE PROCESSOR TO THE DISPLAY MEMORY THAT HOLDS THE SCREEN IMAGE 7HILE SOME PROTOCOLS EMERGED FOR RUNNING A '5) OVER THE ,!. THE 8 WINDOWS PROTOCOL THE BEST PLACE TO RUN A PRODUCTION APPLICATIONS PRESENTATION LAYER CODE WAS CLEARLY ON THE 0# ITSELF %CONOMICS WAS ALSO A FACTOR 0ERSONAL COMPUTER SYSTEMS WERE MUCH CHEAPER ON A COST PER PROCESSING POWER BASIS THAN MINICOMPUTERS OR 5.)8 BASED SERVERS )F MORE OF THE PROCESSING FOR A BUSINESS APPLICATION COULD TAKE PLACE ON LOWER COST 0#S THE OVERALL HARDWARE COST OF DEPLOYING AN APPLICATION WOULD BE REDUCED 4HIS WAS AN ARGUMENT FOR MOVING NOT JUST THE PRESENTATION LAYER BUT MUCH OF THE BUSINESS LOGIC LAYER ONTO THE 0# AS WELL $RIVEN BY THESE AND OTHER FACTORS THE FIRST CLIENTSERVER ARCHITECTURES EMERGED SHOWN IN &IGURE -ANY 0# BASED APPLICATIONS ARE STILL BEING DEPLOYED TODAY USING THIS ARCHITECTURE 31, PLAYS A KEY ROLE AS THE CLIENTSERVER LANGUAGE 2EQUESTS ARE SENT FROM THE APPLICATION LOGIC ON THE 0# TO THE $"-3 ON THE SERVER EXPRESSED IN 31, STATEMENTS 4HE ANSWERS COME BACK ACROSS THE NETWORK IN THE FORM OF 31, COMPLETION STATUS CODES FOR DATABASE UPDATES OR 31, QUERY RESULTS FOR INFORMATION REQUESTS
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31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
#LIENT3ERVERõ!PPLICATIONSõWITHõ3TOREDõ0ROCEDURES 7HENEVER AN APPLICATION IS SPLIT ACROSS TWO OR MORE NETWORKED COMPUTER SYSTEMS AS IN &IGURE ONE OF THE MAJOR ISSUES IS THE INTERFACE BETWEEN THE TWO HALVES OF THE SPLIT APPLICATION %ACH INTERACTION ACROSS THIS INTERFACE NOW GENERATES NETWORK TRAFFIC AND THE NETWORK IS ALWAYS THE SLOWEST PART OF THE OVERALL SYSTEM BOTH IN ITS DATA TRANSMISSION CAPACITY BANDWIDTH AND IN ROUND TRIP MESSAGING DELAYS LATENCY 7ITH THE ARCHITECTURE SHOWN IN &IGURE EACH DATABASE ACCESS THAT IS EACH 31, STATEMENT GENERATES AT LEAST ONE ROUND TRIP ACROSS THE NETWORK )N AN /,40 APPLICATION TYPICAL TRANSACTIONS MAY REQUIRE AS MANY AS A DOZEN INDIVIDUAL 31, STATEMENTS &OR EXAMPLE TO TAKE A CUSTOMERS ORDER FOR A SINGLE PRODUCT IN THE SIMPLE STRUCTURE OF THE SAMPLE DATABASE THE ORDER PROCESSING APPLICATION MIGHT s 2ETRIEVE THE CUSTOMER NUMBER BASED ON THE CUSTOMER NAME SINGLE ROW 3%,%#4 s 2ETRIEVE THE CUSTOMERS CREDIT LIMIT TO VERIFY CREDITWORTHINESS SINGLE ROW 3%,%#4 s 2ETRIEVE PRODUCT INFORMATION SUCH AS PRICE AND QUANTITY AVAILABLE SINGLE ROW 3%,%#4 s !DD A ROW TO THE /2$%23 TABLE FOR THE NEW ORDER ).3%24 s 5PDATE THE PRODUCT INFORMATION TO REFLECT THE LOWER QUANTITY AVAILABLE 50$!4% s 5PDATE THE CUSTOMERS CREDIT LIMIT REDUCING THE AVAILABLE CREDIT 50$!4% s #OMMIT THE ENTIRE TRANSACTION #/--)4 FOR A TOTAL OF SEVEN ROUND TRIPS BETWEEN THE APPLICATION AND THE DATABASE )N A REAL WORLD APPLICATION THE NUMBER OF DATABASE ACCESSES MIGHT BE TWO OR THREE TIMES THIS AMOUNT !S TRANSACTION VOLUMES GROW THE AMOUNT OF NETWORK TRAFFIC CAN BE VERY SIGNIFICANT $ATABASE STORED PROCEDURES PROVIDE AN ALTERNATIVE ARCHITECTURE THAT CAN DRAMATICALLY REDUCE THE AMOUNT OF NETWORK TRAFFIC AS SHOWN IN &IGURE ! STORED PROCEDURE WITHIN THE DATABASE ITSELF INCORPORATES THE SEQUENCE OF STEPS AND THE DECISION MAKING LOGIC REQUIRED TO CARRY OUT ALL OF THE DATABASE OPERATIONS ASSOCIATED WITH THE TRANSACTION
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"ASICALLY PART OF THE BUSINESS LOGIC THAT FORMERLY RESIDED WITHIN THE APPLICATION ITSELF HAS BEEN PUSHED ACROSS THE NETWORK ONTO THE DATABASE SERVER )NSTEAD OF SENDING INDIVIDUAL 31, STATEMENTS TO THE $"-3 THE APPLICATION CALLS THE STORED PROCEDURE PASSING THE CUSTOMER NAME THE PRODUCT TO BE ORDERED AND THE QUANTITY DESIRED )F ALL GOES WELL THE STORED PROCEDURE RETURNS SUCCESSFULLY )F A PROBLEM ARISES SUCH AS LACK OF AVAILABLE PRODUCT OR A CUSTOMER CREDIT PROBLEM A RETURNED ERROR CODE AND MESSAGE DESCRIBES IT "Y USING THE STORED PROCEDURE THE NETWORK TRAFFIC IS REDUCED TO A SINGLE CLIENTSERVER INTERACTION 4HERE ARE SEVERAL OTHER ADVANTAGES TO USING STORED PROCEDURES BUT THE REDUCTION IN NETWORK TRAFFIC IS ONE OF THE MAJOR ONES )T WAS A MAJOR SELLING ADVANTAGE OF 3YBASE 31, 3ERVER WHEN IT WAS FIRST INTRODUCED AND HELPED TO POSITION 3YBASE AS A $"-3 SPECIALIZED FOR HIGH PERFORMANCE /,40 APPLICATIONS 7ITH THE POPULARITY OF STORED PROCEDURES EVERY MAJOR GENERAL PURPOSE ENTERPRISE $"-3 NOW OFFERS THIS CAPABILITY
%NTERPRISEõ!PPLICATIONSõANDõ$ATAõ#ACHING 4ODAY MAJOR APPLICATIONS FROM THE LARGE PACKAGED ENTERPRISE SOFTWARE VENDORS ARE ALL BASED ON 31, AND RELATIONAL DATABASES %XAMPLES INCLUDE LARGE %NTERPRISE 2ESOURCE 0LANNING %20 3UPPLY #HAIN -ANAGEMENT 3#- (UMAN 2ESOURCES -ANAGEMENT (2- #USTOMER 2ELATIONSHIP -ANAGEMENT #2- FINANCIAL MANAGEMENT AND OTHER PACKAGES FROM VENDORS SUCH AS 3!0 )NFOR 'LOBAL 3OLUTIONS FORMERLY "!!. /RACLE WHICH ACQUIRED BOTH 0EOPLE3OFT AND 3IEBEL 3YSTEMS THE 3AGE 'ROUP -ICROSOFT )"- I 4ECHNOLOGIES AND OTHERS 4HESE LARGE SCALE APPLICATIONS TYPICALLY RUN ON LARGE 5.)8 OR 7INDOWS SERVER SYSTEMS AND PLACE A HEAVY WORKLOAD ON THE SUPPORTING $"-3 4O ISOLATE THE APPLICATIONS AND $"-3 PROCESSING AND APPLY MORE TOTAL PROCESSING POWER TO THE APPLICATION THEY OFTEN USE A THREE TIER ARCHITECTURE SHOWN IN &IGURE
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31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
%VEN WITH THE USE OF STORED PROCEDURES TO MINIMIZE NETWORK TRAFFIC THE NETWORK AND DATABASE ACCESS DEMANDS OF THE MOST DATA INTENSIVE OF THESE ENTERPRISE APPLICATIONS CAN OUTSTRIP THE AVAILABLE NETWORK BANDWIDTH AND $"-3 TRANSACTION RATES &OR EXAMPLE CONSIDER A SUPPLY CHAIN PLANNING APPLICATION THAT HELPS A MANUFACTURING COMPANY DETERMINE THE PARTS THAT IT MUST ORDER FROM SUPPLIERS 4O GENERATE A COMPLETE PLAN THE APPLICATION MUST EXAMINE EVERY OPEN ORDER AND APPLY THE PRODUCT BILL OF MATERIALS TO IT ! COMPLEX PRODUCT MIGHT INVOLVE HUNDREDS OF PARTS SOME OF WHICH ARE THEMSELVES SUBASSEMBLIES CONSISTING OF DOZENS OR HUNDREDS OF PARTS )F WRITTEN USING STRAIGHTFORWARD PROGRAMMING TECHNIQUES THE PLANNING APPLICATION MUST PERFORM A DATABASE INQUIRY TO DETERMINE THE PARTS MAKEUP OF EVERY PRODUCT AND THEN EVERY SUBASSEMBLY FOR EVERY ORDER AND IT WILL ACCUMULATE THE TOTAL NEEDED INFORMATION IN THE PLANNING DATABASE FOR EACH OF THESE PARTS 5SING THIS TECHNIQUE THE APPLICATION WILL TAKE HOURS TO PROCESS THE HUNDREDS OF THOUSANDS OF ORDERS THAT MAY BE CURRENTLY ON THE BOOKS )N FACT THE APPLICATION WILL PROBABLY RUN SO LONG THAT IT CANNOT POSSIBLY COMPLETE ITS WORK DURING THE TYPICAL OVERNIGHT LOW VOLUME BATCH PROCESSING WINDOW OF TIME DURING WHICH THE COMPANY NORMALLY RUNS SUCH APPLICATIONS 4O DELIVER ACCEPTABLE PERFORMANCE ALL DATA INTENSIVE ENTERPRISE APPLICATIONS EMPLOY CACHING TECHNIQUES PULLING THE DATA FORWARD OUT OF THE DATABASE SERVER CLOSER TO THE APPLICATION )N MOST CASES THE APPLICATION USES RELATIVELY PRIMITIVE CACHING TECHNIQUES &OR EXAMPLE IT MIGHT READ THE BILL OF MATERIALS ONCE AND LOAD IT INTO MAIN MEMORY DATA TABLES WITHIN THE APPLICATION PROGRAM "Y ELIMINATING THE HEAVILY REPEATED PRODUCT STRUCTURE QUERIES THE PROGRAM CAN DRAMATICALLY IMPROVE ITS PERFORMANCE 2ECENTLY ENTERPRISE APPLICATION VENDORS HAVE BEGUN TO USE MORE COMPLEX CACHING TECHNIQUES 4HEY MAY REPLICATE THE MOST HEAVILY ACCESSED DATA THE HOT DATA IN A DUPLICATE DATABASE TABLE ON THE SAME SYSTEM AS THE APPLICATION ITSELF -AIN MEMORY DATABASES OFFER AN EVEN HIGHER PERFORMANCE ALTERNATIVE AND ARE ALREADY BEING USED WHERE THERE IS A RELATIVELY SMALL AMOUNT OF HOT DATA TENS TO HUNDREDS OF MEGABYTES 7ITH THE ADVENT OF BIT OPERATING SYSTEM ARCHITECTURES AND CONTINUING DECLINES IN MEMORY PRICES IT IS BECOMING PRACTICAL TO CACHE LARGER AMOUNTS OF DATA TENS OR HUNDREDS OF GIGABYTES !DVANCED CACHING AND REPLICATION WILL BECOME MORE IMPORTANT IN RESPONSE TO EMERGING BUSINESS REQUIREMENTS ,EADING EDGE MANUFACTURING COMPANIES WANT TO MOVE TOWARD REAL TIME PLANNING WHERE INCOMING CUSTOMER ORDERS AND CHANGES IMMEDIATELY IMPACT PRODUCTION PLANS 4HEY WANT TO OFFER MORE CUSTOMIZED PRODUCTS IN MORE CONFIGURATIONS TO MORE CLOSELY MATCH CUSTOMER DESIRES 4HESE AND SIMILAR TRENDS WILL CONTINUE TO RAISE THE VOLUME AND COMPLEXITY OF DATABASE ACCESS
(IGH 6OLUMEõ)NTERNETõ$ATAõ-ANAGEMENT
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(IGH VOLUME )NTERNET APPLICATIONS ARE ALSO DRIVING THE TREND TO DATABASE CACHING AND REPLICATION IN NETWORKED DATABASE ARCHITECTURES &OR EXAMPLE FINANCIAL SERVICES FIRMS ARE COMPETING FOR ONLINE BROKERAGE CLIENTS BY OFFERING MORE AND MORE ADVANCED REAL TIME STOCK REPORTING AND ANALYSIS CAPABILITIES 4HE DATA MANAGEMENT TO SUPPORT THIS TYPE OF APPLICATION INVOLVES REAL TIME DATA FEEDS TO ENSURE THAT PRICING AND VOLUME INFORMATION IN THE DATABASE IS CURRENT AND PEAK LOAD DATABASE INQUIRIES OF TENS OF THOUSANDS OF TRANSACTIONS PER SECOND 3IMILAR VOLUME DEMANDS ARE FOUND IN APPLICATIONS FOR MANAGING AND MONITORING HIGH VOLUME )NTERNET SITES 4HE TREND TO PERSONALIZE WEB SITES DETERMINING ON THE FLY WHICH BANNER ADS TO DISPLAY WHICH PRODUCTS TO FEATURE ETC AND MEASURE THE EFFECTIVENESS OF SUCH PERSONALIZATION IS ANOTHER TREND DRIVING PEAK LOAD DATA ACCESS AND DATA CAPTURE RATES
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4HE 7EB HAS ALREADY PROVED TO BE AN EFFECTIVE ARCHITECTURE FOR DEALING WITH THESE TYPES OF PEAK LOAD )NTERNET VOLUME DEMANDSTHROUGH WEB SITE CACHING #OPIES OF HEAVILY ACCESSED WEB PAGES ARE PULLED FORWARD IN THE NETWORK AND REPLICATED !S A RESULT THE TOTAL NETWORK CAPACITY FOR SERVING WEB PAGES IS INCREASED AND THE AMOUNT OF NETWORK TRAFFIC ASSOCIATED WITH THOSE PAGE HITS IS REDUCED 3IMILAR ARCHITECTURES ARE BEGINNING TO EMERGE FOR HIGH VOLUME )NTERNET DATABASE MANAGEMENT AS SHOWN IN &IGURE )N THIS CASE AN )NTERNET INFORMATION SERVICES APPLICATION CACHES HOT DATA SUCH AS THE MOST RECENT NEWS AND FINANCIAL INFORMATION IN A VERY HIGH PERFORMANCE MAIN MEMORY DATABASE SUCH AS /RACLE 4IMES4EN AND -Y31, #LUSTER 3ERVER )T ALSO STORES SUMMARY USER PROFILE INFORMATION IN A MAIN MEMORY DATABASE WHICH IS USED TO PERSONALIZE USERS EXPERIENCES AS THEY INTERACT WITH THE WEB SITE !S &IGURE SHOWS THE METHODS FOR HANDLING HIGH PERFORMANCE DATA MANAGEMENT ARE BEGINNING TO FOLLOW THOSE ALREADY ESTABLISHED FOR HIGH PERFORMANCE WEB PAGE MANAGEMENT 4HE ISSUES FOR DATABASES ARE MORE COMPLEX BECAUSE OF DATABASE INTEGRITY ISSUES BUT THE EMERGING TECHNIQUES ARE SIMILARREPLICATION HIGH VOLUME READ ACCESS MEMORY RESIDENT DATABASES AND HIGHLY FAULT TOLERANT ARCHITECTURES 4HESE DEMANDS WILL ONLY GROW AS )NTERNET TRAFFIC AND PERSONALIZATION CONTINUE TO INCREASE LEADING TO MORE ADVANCED NETWORK DATABASE ARCHITECTURES
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#HAPTERçç
31,ç.ETWORKINGçANDç$ISTRIBUTEDç$ATABASESç
3UMMARY 4HIS CHAPTER DESCRIBED THE DISTRIBUTED DATA MANAGEMENT CAPABILITIES OFFERED BY VARIOUS $"-3 PRODUCTS AND THE TRADE OFFS INVOLVED IN PROVIDING ACCESS TO REMOTE DATA s ! DISTRIBUTED DATABASE IS IMPLEMENTED BY A NETWORK OF COMPUTER SYSTEMS EACH RUNNING ITS OWN COPY OF THE $"-3 SOFTWARE AND OPERATING AUTONOMOUSLY FOR LOCAL DATA ACCESS 4HE COPIES OF THE $"-3 COOPERATE TO PROVIDE REMOTE DATA ACCESS WHEN REQUIRED s 4HE IDEAL DISTRIBUTED DATABASE IS ONE IN WHICH THE USER DOESNT KNOW AND DOESNT CARE THAT THE DATA IS DISTRIBUTED TO THE USER ALL OF THE RELEVANT DATA APPEARS AS IF IT WERE ON THE LOCAL SYSTEM s "ECAUSE THIS IDEAL DISTRIBUTED $"-3 IS VERY DIFFICULT TO PROVIDE AND INVOLVES TOO MANY PERFORMANCE TRADE OFFS COMMERCIAL $"-3 PRODUCTS ARE PROVIDING DISTRIBUTED DATABASE CAPABILITY IN PHASES s 2EMOTE DATABASE ACCESS CAN BE USEFUL IN SITUATIONS WHERE THE REMOTE ACCESS IS A SMALL PART OF TOTAL DATABASE ACTIVITY IN THIS CASE ITS MORE PRACTICAL TO LEAVE THE DATA IN THE REMOTE LOCATION AND INCUR THE NETWORK OVERHEAD FOR EACH DATABASE ACCESS s $ATABASE REPLICATION IS VERY USEFUL IN SITUATIONS WHERE THERE IS RELATIVELY HEAVY ACCESS TO DATA IN MULTIPLE LOCATIONS IT BRINGS THE DATA CLOSER TO THE POINT OF ACCESS BUT AT THE COST OF NETWORK OVERHEAD FOR REPLICA SYNCHRONIZATION AND DATA THAT IS NOT PERCENT UP TO DATE s 4HE PARTICULAR TRADE OFFS OF REMOTE DATA ACCESS AND REPLICATION STRATEGIES HAVE IMPLICATIONS BEYOND TECHNOLOGY DECISIONS THEY SHOULD REFLECT UNDERLYING TRADE OFFS IN BUSINESS PRIORITIES AS WELL s %NTERPRISEWIDE DISTRIBUTED APPLICATIONS )NTERNET BASED APPLICATIONS DATA WAREHOUSING AND OTHER TRENDS ARE INCREASING THE COMPLEXITY OF THE DISTRIBUTED DATA MANAGEMENT ENVIRONMENT 4HE . TIER ARCHITECTURES THEY USE WILL REQUIRE SMART DATA CACHING AND REPLICATION STRATEGIES TO DELIVER ADEQUATE PERFORMANCE
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4
HE ONLY SERIOUS CHALLENGE TO THE DOMINANCE OF 31, AND RELATIONAL DATABASE MANAGEMENT OVER THE LAST DECADE OR SO HAS COME FROM THE EMERGENCE OF AN EQUALLY SIGNIFICANT TRENDTHE GROWING POPULARITY OF OBJECT ORIENTED TECHNOLOGIES /BJECT ORIENTED PROGRAMMING LANGUAGES SUCH AS # AND *AVA OBJECT ORIENTED DEVELOPMENT TOOLS AND OBJECT ORIENTED NETWORKING INCLUDING OBJECT REQUEST BROKERS AND MORE RECENTLY 7EB 3ERVICES HAVE EMERGED AS FOUNDATION TECHNOLOGIES FOR MODERN SOFTWARE DEVELOPMENT /BJECT TECHNOLOGIES GAINED MUCH OF THEIR INITIAL POPULARITY FOR BUILDING PERSONAL COMPUTER APPLICATIONS WITH GRAPHICAL USER INTERFACES '5)S "UT THEIR IMPACT HAS GROWN AND THEY ARE BEING USED TODAY TO BUILD AND MORE IMPORTANTLY TO LINK TOGETHER ENTERPRISEWIDE NETWORK BASED APPLICATIONS FOR LARGE CORPORATIONS )N THE EARLY S A GROUP OF VENTURE BACKED OBJECT ORIENTED DATABASE COMPANIES WAS FORMED WITH THE GOAL OF APPLYING OBJECT ORIENTED PRINCIPLES TO DATABASE MANAGEMENT 4HESE COMPANIES BELIEVED THAT THEIR OBJECT ORIENTED DATABASES WOULD SUPPLANT THE OUTDATED RELATIONAL DATABASES AS SURELY AS THE RELATIONAL MODEL HAD SUPPLANTED EARLIER DATA MODELS (OWEVER THEY MET WITH LIMITED MARKETPLACE SUCCESS IN THE FACE OF ENTRENCHED RELATIONAL TECHNOLOGIES AND 31, )N RESPONSE TO THE OBJECT CHALLENGE MANY RELATIONAL DATABASE VENDORS MOVED AGGRESSIVELY TO GRAFT OBJECT TECHNOLOGIES ONTO THEIR RELATIONAL SYSTEMS CREATING HYBRID OBJECT RELATIONAL MODELS 4HIS CHAPTER DESCRIBES THE OBJECT DATABASE CHALLENGE TO 31, AND THE RESULTING OBJECT RELATIONAL FEATURES PROVIDED BY SOME MAJOR $"-3 VENDORS
/BJECT /RIENTEDõ$ATABASES #ONSIDERABLE ACADEMIC RESEARCH ON DATABASE TECHNOLOGY OVER THE PAST DECADE HAS BEEN FOCUSED ON NEW POST RELATIONAL DATA MODELS *UST AS THE RELATIONAL MODEL PROVIDED CLEAR CUT ADVANTAGES OVER THE EARLIER HIERARCHICAL AND NETWORK MODELS THE GOAL OF THIS RESEARCH WAS TO DEVELOP NEW DATA MODELS THAT WOULD OVERCOME SOME OF THE DISADVANTAGES OF THE RELATIONAL MODEL -UCH OF THIS RESEARCH HAS FOCUSED ON HOW TO MERGE THE PRINCIPLES OF OBJECT ORIENTED PROGRAMMING AND DESIGN WITH TRADITIONAL DATABASE CHARACTERISTICS SUCH AS PERSISTENT STORAGE AND TRANSACTION MANAGEMENT
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)N ADDITION TO THE ACADEMIC RESEARCH IN THE EARLY AND MID S SOME LARGE VENTURE CAPITAL INVESTMENTS FLOWED INTO A GROUP OF STARTUP SOFTWARE COMPANIES WHOSE GOAL WAS TO BUILD A NEW GENERATION OF DATA MANAGEMENT TECHNOLOGIES 4HESE COMPANIES TYPICALLY STARTED WITH THE OBJECT DATA STRUCTURES USED BY AN OBJECT ORIENTED PROGRAM TO MANAGE ITS IN MEMORY DATA AND EXTENDED THEM FOR DISK BASED STORAGE AND MULTIUSER ACCESS 4HESE EARLY COMMERCIAL PRODUCTS INCLUDED 'EMSTONE 3ERVIO ,OGIC LATER RENAMED TO 'EMSTONE 3YSTEMS 'BASE 'RAPHAEL AND 6BASE /NTOLOGIC 0RODUCTS INTRODUCED IN THE MID S INCLUDED )4!3#! )TASCA 3YSTEMS *ASMINE &UJITSU MARKETED BY #OMPUTER !SSOCIATES /BJECTIVITY$" /BJECTIVITY )NC /BJECT3TORE 0ROGRESS 3OFTWARE ACQUIRED BY E8CELON WHICH WAS ORIGINALLY /BJECT $ESIGN -ATISSE -ATISSE 3OFTWARE / / 4ECHNOLOGY EVENTUALLY ACQUIRED BY )NFORMIX WHICH WAS ACQUIRED BY )"- /.4/3 /NTOS )NC FORMERLY /NTOLOGIC 0/%4 0OET 3OFTWARE NOW &AST/BJECTS FROM 6ERSANT 6ERSANT /BJECT $ATABASE 6ERSANT #ORPORATION AND 6/33 ,OGIC !RTS %NTHUSIASTIC SUPPORTERS OF THESE OBJECT ORIENTED DATABASES //$"S FIRMLY BELIEVED THAT THEY WOULD MOUNT A SERIOUS CHALLENGE TO THE RELATIONAL MODEL AND BECOME THE DOMINANT DATABASE ARCHITECTURE BY THE END OF THE DECADE 4HAT SCENARIO PROVED FAR OFF THE MARK BUT THE OBJECT DATABASE VENDORS HAVE HAD A SIGNIFICANT IMPACT ON THEIR RELATIONAL RIVALS
/BJECT /RIENTEDõ$ATABASEõ#HARACTERISTICS 5NLIKE THE RELATIONAL DATA MODEL WHERE #ODDS PAPER PROVIDED A CLEAR MATHEMATICAL DEFINITION OF A RELATIONAL DATABASE THE OBJECT ORIENTED DATABASE HAS NO SINGLE DEFINITION (OWEVER THE CORE PRINCIPLES EMBODIED IN MOST OBJECT ORIENTED DATABASES INCLUDE s /BJECTS )N AN OBJECT ORIENTED DATABASE EVERYTHING IS AN OBJECT AND IS MANIPULATED AS AN OBJECT 4HE TABULAR ROWCOLUMN ORGANIZATION OF A RELATIONAL DATABASE IS REPLACED BY THE NOTION OF COLLECTIONS OF OBJECTS 'ENERALLY A COLLECTION OF OBJECTS IS ITSELF AN OBJECT AND CAN BE MANIPULATED IN THE SAME WAY THAT OTHER OBJECTS ARE MANIPULATED s #LASSES /BJECT ORIENTED DATABASES REPLACE THE RELATIONAL NOTION OF ATOMIC DATA TYPES WITH A HIERARCHICAL NOTION OF CLASSES AND SUBCLASSES &OR EXAMPLE 6%()#,%3 MIGHT BE A CLASS OF OBJECT AND INDIVIDUAL MEMBERS INSTANCES OF THAT CLASS WOULD INCLUDE A CAR A BICYCLE A TRAIN OR A BOAT 4HE 6%()#,%3 CLASS MIGHT INCLUDE SUBCLASSES CALLED #!23 AND "/!43 REPRESENTING A MORE SPECIALIZED FORM OF VEHICLE 3IMILARLY THE #!23 CLASS MIGHT INCLUDE A SUBCLASS CALLED #/.6%24)",%3 AND SO ON s )NHERITANCE /BJECTS INHERIT CHARACTERISTICS FROM THEIR CLASS AND FROM ALL OF THE HIGHER LEVEL CLASSES TO WHICH THEY BELONG &OR EXAMPLE ONE OF THE CHARACTERISTICS OF A VEHICLE MIGHT BE hNUMBER OF PASSENGERSv !LL MEMBERS OF THE #!23 "/!43 AND #/.6%24)",%3 CLASSES ALSO HAVE THIS ATTRIBUTE BECAUSE THEY ARE SUBCLASSES OF 6%()#,%3 4HE #!23 CLASS MIGHT ALSO HAVE THE ATTRIBUTE hNUMBER OF DOORS v AND THE #/.6%24)",%3 CLASS WOULD INHERIT THIS ATTRIBUTE (OWEVER THE "/!43 CLASS WOULD NOT INHERIT THE ATTRIBUTE s !TTRIBUTES 4HE CHARACTERISTICS THAT AN OBJECT POSSESSES ARE MODELED BY ITS ATTRIBUTES %XAMPLES INCLUDE THE COLOR OF AN OBJECT OR THE NUMBER OF DOORS THAT IT HAS AND ITS %NGLISH LANGUAGE NAME 4HE ATTRIBUTES ARE RELATED TO THE OBJECT THEY DESCRIBE IN ROUGHLY THE SAME WAY THAT THE COLUMNS OF A TABLE RELATE TO ITS ROWS
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31,çANDç/BJECTSç
s -ESSAGES AND METHODS /BJECTS COMMUNICATE WITH ONE ANOTHER BY SENDING AND RECEIVING MESSAGES 7HEN IT RECEIVES A MESSAGE AN OBJECT RESPONDS BY EXECUTING A METHOD A PROGRAM STORED WITHIN THE OBJECT THAT DETERMINES HOW IT PROCESSES THE MESSAGE 4HUS AN OBJECT INCLUDES A SET OF BEHAVIORS DESCRIBED BY ITS METHODS 5SUALLY AN OBJECT SHARES MANY OF THE SAME METHODS WITH OTHER OBJECTS IN HIGHER LEVEL CLASSES s %NCAPSULATION 4HE INTERNAL STRUCTURE AND DATA OF OBJECTS IS HIDDEN FROM THE OUTSIDE WORLD ENCAPSULATED BEHIND A LIMITED SET OF WELL DEFINED INTERFACES 4HE ONLY WAY TO FIND OUT ABOUT AN OBJECT OR TO ACT ON IT IS THROUGH ITS METHODS WHOSE FUNCTIONS AND BEHAVIORS ARE CLEARLY SPECIFIED 4HIS MAKES THE OBJECT MORE PREDICTABLE AND LIMITS THE OPPORTUNITIES FOR ACCIDENTAL DATA CORRUPTION s /BJECT IDENTITY /BJECTS CAN BE DISTINGUISHED FROM ONE ANOTHER THROUGH UNIQUE OBJECT IDENTIFIERS USUALLY IMPLEMENTED AS AN ABSTRACT POINTER KNOWN AS AN OBJECT HANDLE (ANDLES ARE FREQUENTLY USED TO REPRESENT RELATIONSHIPS AMONG OBJECTS AN OBJECT POINTS TO A RELATED OBJECT BY STORING THE OBJECTS HANDLE AS ONE OF ITS DATA ITEMS ATTRIBUTES 4HESE PRINCIPLES AND TECHNIQUES MAKE OBJECT ORIENTED DATABASES WELL SUITED TO APPLICATIONS INVOLVING COMPLEX DATA TYPES SUCH AS COMPUTER AIDED DESIGN OR COMPOUND DOCUMENTS THAT COMBINE TEXT GRAPHICS AND SPREADSHEETS 4HE DATABASE PROVIDES A NATURAL WAY TO REPRESENT THE HIERARCHIES THAT OCCUR IN COMPLEX DATA &OR EXAMPLE AN ENTIRE DOCUMENT CAN BE REPRESENTED AS A SINGLE OBJECT COMPOSED OF SMALLER OBJECTS SECTIONS COMPOSED OF STILL SMALLER OBJECTS PARAGRAPHS GRAPHS ETC 4HE CLASS HIERARCHY ALLOWS THE DATABASE TO TRACK THE TYPE OF EACH OBJECT IN THE DOCUMENT PARAGRAPHS CHARTS ILLUSTRATIONS TITLES FOOTNOTES ETC &INALLY THE MESSAGE MECHANISM OFFERS NATURAL SUPPORT FOR A '5) 4HE APPLICATION PROGRAM CAN SEND A hDRAW YOURSELFv MESSAGE TO EACH PART OF THE DOCUMENT ASKING IT TO DRAW ITSELF ON THE SCREEN )F THE USER CHANGES THE SHAPE OF THE WINDOW DISPLAYING THE DOCUMENT THE APPLICATION PROGRAM CAN RESPOND BY SENDING A hRESIZE YOURSELFv MESSAGE TO EACH DOCUMENT PART AND SO ON %ACH OBJECT IN THE DOCUMENT BEARS RESPONSIBILITY FOR ITS OWN DISPLAY SO NEW OBJECTS CAN EASILY BE ADDED TO THE DOCUMENT ARCHITECTURE
0ROSõANDõ#ONSõOFõ/BJECT /RIENTEDõ$ATABASES
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/BJECT ORIENTED DATABASES HAVE STIRRED UP A STORM OF CONTROVERSY IN THE DATABASE COMMUNITY 0ROPONENTS SAY THAT OBJECT DATABASES ARE ESSENTIAL TO CREATE A PROPER MATCH BETWEEN THE PROGRAMMING AND DATABASE DATA MODELS 4HEY SAY THAT THE RIGID FIXED ROW COLUMN STRUCTURE OF RELATIONAL TABLES IS A HOLDOVER FROM THE PUNCH CARD ERA OF DATA PROCESSING WITH ITS FIXED DATA FIELDS AND RECORD ORIENTATION ! MORE FLEXIBLE MODEL WHERE CLASSES OF OBJECTS CAN BE SIMILAR TO ONE ANOTHER THAT IS SHARE CERTAIN ATTRIBUTES BUT ALSO DIFFERENT FROM ONE ANOTHER IS ESSENTIAL THEY SAY TO EFFECTIVELY MODEL REAL WORLD SITUATIONS !NOTHER ASSERTION IS THAT THE MULTITABLE JOINS THAT ARE AN INTEGRAL PART OF THE RELATIONAL DATA MODEL INHERENTLY CREATE DATABASE OVERHEAD AND MAKE RELATIONAL TECHNOLOGY UNSUITABLE FOR THE EVER INCREASING PERFORMANCE DEMANDS OF TODAYS APPLICATIONS &INALLY SINCE OBJECTS ARE WELL ESTABLISHED AS THE IN MEMORY DATA MODEL FOR MODERN PROGRAMS THE PROPONENTS SAY THAT THE ONLY NATURAL DATA MODEL IS ONE THAT TRANSPARENTLY EXTENDS THE IN MEMORY MODEL TO PERMANENT SHARED DISK BASED MULTIUSER STORAGE
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/PPONENTS OF OBJECT ORIENTED DATABASES ARE JUST AS ADAMANT SAYING THAT OBJECT ORIENTED DATABASES ARE UNNECESSARY AND OFFER NO REAL SUBSTANTIVE ADVANTAGES OVER THE RELATIONAL MODEL 4HEY SAY THAT THE HANDLES OF OBJECT ORIENTED DATABASES ARE NOTHING MORE THAN THE EMBEDDED DATABASE POINTERS OF PRERELATIONAL HIERARCHICAL AND NETWORK DATABASES RECYCLED WITH DIFFERENT NAMES 4HEY POINT OUT THAT LIKE THESE EARLIER DATABASE TECHNOLOGIES THE OBJECT ORIENTED DATABASES LACK THE STRONG UNDERLYING MATHEMATICAL THEORY THAT FORMS THE BASIS OF RELATIONAL DATABASES 4HEY ADD THAT THE LACK OF OBJECT DATABASE STANDARDS AND THE ABSENCE OF A STANDARDIZED QUERY LANGUAGE LIKE 31, ARE REFLECTIONS OF THIS DEFICIENCY AND HAVE PREVENTED THE DEVELOPMENT OF VENDOR INDEPENDENT TOOLS AND APPLICATIONS THAT HAVE BEEN ESSENTIAL TO THE DEVELOPMENT OF THE DATABASE INDUSTRY )N RESPONSE TO CLAIMS OF INFERIOR PERFORMANCE THEY POINT TO THE USE OF RELATIONAL TECHNOLOGY IN SOME OF THE MOST PERFORMANCE DEMANDING ENTERPRISE APPLICATIONS 4HEY ALSO ARE CAREFUL TO DRAW A DISTINCTION BETWEEN THE EXTERNAL RELATIONAL MODEL OF DATA AND THE UNDERLYING IMPLEMENTATION WHICH MAY WELL CONTAIN EMBEDDED POINTERS FOR PERFORMANCE ACCELERATION &INALLY THEY SAY THAT ANY MISMATCH BETWEEN OBJECT ORIENTED PROGRAMMING AND RELATIONAL DATABASES CAN BE ADDRESSED BY TECHNOLOGIES LIKE *$"# AND OTHER OBJECT TO RELATIONAL INTERFACES
/BJECTSõANDõTHEõ$ATABASEõ-ARKET )N THE MARKETPLACE PURE OBJECT ORIENTED DATABASES HAVE GAINED SOME SUCCESS IN APPLICATIONS WITH VERY COMPLEX DATA MODELS AND THOSE WHERE THE OBJECT ORIENTED MODEL OF CLASSES AND INHERITANCE CLOSELY PARALLELS THE REAL WORLD (OWEVER THE OBJECT DATABASE COMPANIES HAVE HAD REAL DIFFICULTY BREAKING THROUGH INTO THE MAINSTREAM -ANY HAVE NOT SURVIVED INTO THE FIRST DECADE OF THE ST CENTURY 4HE SURVIVORS HAVE HAD A HARD TIME REACHING THE MILLION ANNUAL REVENUE MARK AND ACHIEVING SUSTAINABLE PROFITS AND HAVE EXPERIENCED SIGNIFICANT MANAGEMENT CHANGES )N CONTRAST THE LARGEST RELATIONAL DATABASE VENDORS HAVE CONTINUED TO EXPERIENCE STEADY GROWTH 4HE LARGEST HAVE ANNUAL REVENUES MEASURED IN BILLIONS OF DOLLARS PER YEAR PROVING THAT RELATIONAL DATABASE TECHNOLOGY CONTINUES TO DOMINATE THE DATABASE MARKET TODAY .OT SURPRISINGLY THE OBJECT ORIENTED AND RELATIONAL CAMPS HAVE HAD A SUBSTANTIAL IMPACT ON ONE ANOTHER 7ITH THE SLOW MARKETPLACE ACCEPTANCE OF OBJECT ORIENTED TECHNOLOGY THE OBJECT ORIENTED VENDORS HAVE FOCUSED ON SOME OF THE FACTORS THAT CREATED THE SUCCESS OF THE RELATIONAL GENERATION TWO DECADES AGO 4HEY HAVE FORMED STANDARDS GROUPS SUCH AS THE /BJECT $ATA -ANAGEMENT 'ROUP /$-' TO STANDARDIZE OBJECT ORIENTED DATABASE TECHNOLOGY 3EVERAL HAVE ADDED RELATIONAL ADAPTERS WITH STANDARD INTERFACES SUCH AS /$"# AND 31, AS OPTIONAL LAYERS FOR RELATIONAL ACCESS TO THEIR DATABASES 3EVERAL HAVE FOCUSED ON THE INTERNATIONAL STANDARDS PROCESS AND HAVE WORKED TO PUT STRONG OBJECT ORIENTED CAPABILITIES INTO THE 31, STANDARD 4HE NET RESULT HAS BEEN A TREND TOWARD EMBRACING OR COEXISTING WITH THE RELATIONAL WORLD RATHER THAN COMPETING WITH IT 4HE OBJECT ORIENTED CHALLENGE HAS HAD A SIGNIFICANT IMPACT ON THE RELATIONAL MAINSTREAM AS WELL 3EVERAL FEATURES THAT BEGAN AS RELATIONAL CAPABILITIES FOR EXAMPLE STORED PROCEDURES ARE NOW BEING TOUTED AS PROVIDING OBJECT ORIENTED ADVANTAGES FOR EXAMPLE ENCAPSULATION 6ENDORS HAVE ALSO STEADILY ADDED SELECTED OBJECT ORIENTED CAPABILITIES SUCH AS ABSTRACT DATA TYPES ONTO THEIR RELATIONAL DATABASES 4HE RESULTING OBJECT RELATIONAL DATABASES PROVIDE A HYBRID OF RELATIONAL AND OBJECT CAPABILITIES 4HEY STRETCH THE RELATIONAL MODELSOME WOULD SAY PAST THE BREAKING POINTTO INCORPORATE FEATURES SUCH AS TABLES WITHIN TABLES WHICH MODEL THE RELATIONSHIPS BETWEEN OBJECT CLASSES
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31,çANDç/BJECTSç
/NE OF THE MAJOR VENDORS )NFORMIX 3OFTWARE SINCE ACQUIRED BY )"- GAINED ITS OBJECT RELATIONAL CAPABILITIES BY ACQUISITION BUYING )LLUSTRA 3OFTWARE )LLUSTRAS OBJECT RELATIONAL TECHNOLOGY WAS BASED ON THE 0OSTGRES WORK AT THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEY A FOLLOW UP TO THE UNIVERSITYS PIONEERING RELATIONAL DATABASE SYSTEM )NGRES 4HE )NFORMIX VERSION OF THE )LLUSTRA PRODUCT WAS RENAMED )NFORMIX 5NIVERSAL 3ERVER !NOTHER OF THE MAJOR VENDORS /RACLE #ORPORATION EVOLVED ITS OWN MAINSTREAM DATABASE SYSTEM TO INCLUDE OBJECT RELATIONAL TECHNOLOGIES /RACLE INTRODUCED IN EMBODIES SEVERAL YEARS OF INTENSIVE /RACLE DEVELOPMENT IN THIS AREA AND SUBSEQUENT VERSIONS FURTHER EXPANDED IT 4HE OBJECT ORIENTED DATABASE VENDORS AND THE RELATIONAL VENDORS RESPONSE TO IT HAVE ALSO HAD A MAJOR IMPACT ON THE 31, STANDARDS EFFORTS 4HE MOST SIGNIFICANT CHANGE IN THE 31, VERSION OF THE STANDARD FORMALLY KNOWN AS 31, WAS THE ADDITION OF OBJECT CAPABILITIES 4HE NEW OBJECT ORIENTED CAPABILITIES NEARLY DOUBLED THE SIZE OF THE 31, SPECIFICATION IN TERMS OF PAGE COUNT 4HE ACQUISITION AND DEVELOPMENT OF OBJECT RELATIONAL DATABASES BY THE INDUSTRY LEADERS AND THE FORMAL ADOPTION OF OBJECT EXTENSIONS TO 31, SIGNAL THE GROWING SYNERGY BETWEEN 31, AND THE WORLD OF OBJECT TECHNOLOGY
/BJECT 2ELATIONALõ$ATABASES /BJECT RELATIONAL DATABASES TYPICALLY BEGIN WITH A RELATIONAL DATABASE FOUNDATION AND ADD SELECTED FEATURES THAT PROVIDE OBJECT ORIENTED CAPABILITIES 4HIS APPROACH SIMPLIFIES THE ADDITION OF OBJECT CAPABILITIES FOR THE MAJOR 2$"-3 VENDORS WHOSE ENTERPRISE CLASS 2$"-3 PRODUCTS HAVE BEEN DEVELOPED OVER THE COURSE OF OR MORE YEARS AND WOULD BE TREMENDOUSLY COSTLY TO REPRODUCE FROM SCRATCH )T ALSO RECOGNIZES THE LARGE INSTALLED BASE OF RELATIONAL SYSTEMS AND GIVES THOSE CUSTOMERS A SMOOTHER UPGRADE PATH NOT TO MENTION AN UPGRADE REVENUE STREAM FOR THE VENDORS 4HE OBJECT EXTENSIONS THAT ARE COMMONLY FOUND IN OBJECT RELATIONAL DATABASES ARE s ,ARGE DATA OBJECTS 4RADITIONAL RELATIONAL DATA TYPES ARE SMALLINTEGERS DATES SHORT CHARACTER STRINGS LARGE DATA OBJECTS CAN STORE DOCUMENTS AUDIO AND VIDEO CLIPS WEB PAGES AND OTHER NEW MEDIA DATA TYPES s 3TRUCTUREDABSTRACT DATA TYPES 2ELATIONAL DATA TYPES ARE ATOMIC AND INDIVISIBLE STRUCTURED DATA TYPES ALLOW GROUPS OF INDIVIDUAL DATA ITEMS TO BE GROUPED INTO HIGHER LEVEL STRUCTURES THAT CAN BE TREATED AS ENTITIES OF THEIR OWN s 5SER DEFINED DATA TYPES 2ELATIONAL DATABASES TYPICALLY PROVIDE A LIMITED RANGE OF BUILT IN DATA TYPES OBJECT ORIENTED SYSTEMS AND DATABASES EMPHASIZE THE USERS ABILITY TO DEFINE HIS OR HER OWN NEW DATA TYPES s 4ABLES WITHIN TABLES 2ELATIONAL DATABASE COLUMNS STORE INDIVIDUAL DATA ITEMS OBJECT RELATIONAL DATABASES ALLOW COLUMNS TO CONTAIN COMPLEX DATA ITEMS SUCH AS STRUCTURED TYPES OR EVEN ENTIRE TABLES 4HIS CAN BE USED TO REPRESENT OBJECT HIERARCHIES
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s 3EQUENCES SETS AND ARRAYS )N A TRADITIONAL RELATIONAL DATABASE SETS OF DATA ARE REPRESENTED BY ROWS IN THEIR OWN TABLE LINKED TO AN OWNING ENTITY BY A FOREIGN KEY OBJECT RELATIONAL DATABASES MAY ALLOW THE DIRECT STORAGE OF COLLECTIONS OF DATA ITEMS SEQUENCES SETS ARRAYS WITHIN A SINGLE COLUMN
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s 3TORED PROCEDURES 4RADITIONAL RELATIONAL DATABASES PROVIDE SET BASED INTERFACES SUCH AS 31, FOR STORING SELECTING AND RETRIEVING DATA OBJECT RELATIONAL DATABASES PROVIDE PROCEDURAL INTERFACES SUCH AS STORED PROCEDURES THAT ENCAPSULATE THE DATA AND PROVIDE STRICTLY DEFINED INTERACTIONS s (ANDLES AND OBJECT IDS ! PURE RELATIONAL DATABASE REQUIRES THAT DATA WITHIN EACH ROW OF THE DATABASE ITSELF THE PRIMARY KEY UNIQUELY IDENTIFIES THE ROW OBJECT RELATIONAL DATABASES PROVIDE BUILT IN SUPPORT FOR ROW IDS OR OTHER UNIQUE IDENTIFIERS FOR OBJECTS
,ARGEõ/BJECTõ3UPPORT 2ELATIONAL DATABASES HAVE TRADITIONALLY FOCUSED ON BUSINESS DATA PROCESSING 4HEY STORE AND MANIPULATE DATA ITEMS THAT REPRESENT MONEY AMOUNTS NAMES ADDRESSES UNIT QUANTITIES DATES TIMES AND THE LIKE 4HESE DATA TYPES ARE RELATIVELY SIMPLE AND REQUIRE SMALL AMOUNTS OF STORAGE SPACE FROM A FEW BYTES FOR AN INTEGER THAT HOLDS ORDER OR INVENTORY QUANTITIES TO A FEW DOZEN BYTES FOR A CUSTOMER NAME EMPLOYEE ADDRESS OR PRODUCT DESCRIPTION 2ELATIONAL DATABASES HAVE BEEN OPTIMIZED TO MANAGE ROWS CONTAINING UP TO A FEW DOZEN COLUMNS OF THIS TYPE OF DATA 4HE TECHNIQUES THEY USE TO MANAGE DISK STORAGE AND TO INDEX DATA ASSUME THAT DATA ROWS WILL OCCUPY A FEW HUNDRED TO A FEW THOUSAND BYTES 4HE PROGRAMS THAT STORE AND RETRIEVE DATA CAN EASILY HOLD DOZENS OR HUNDREDS OF THESE TYPES OF DATA ITEMS IN MEMORY AND CAN EASILY STORE AND RETRIEVE ENTIRE ROWS OF DATA AT A TIME THROUGH REASONABLY SIZED MEMORY BUFFERS 4HE ROW AT A TIME PROCESSING TECHNIQUES FOR RELATIONAL QUERY RESULTS WORK WELL -ANY MODERN TYPES OF DATA HAVE QUITE DIFFERENT CHARACTERISTICS FROM TRADITIONAL BUSINESS DATA ! SINGLE HIGH RESOLUTION GRAPHICAL IMAGE TO BE DISPLAYED ON A 0# SCREEN CAN REQUIRE HUNDREDS OF THOUSANDS OF BYTES OF STORAGE OR MORE ! WORD PROCESSING DOCUMENT SUCH AS A CONTRACT OR THE TEXT OF THIS BOOK CAN TAKE EVEN MORE STORAGE 4HE (4-, TEXT THAT DEFINES WEB PAGES AND THE 0OST3CRIPT AND 0$& FILES THAT DEFINE PRINTED IMAGES ARE OTHER EXAMPLES OF LARGER DOCUMENT ORIENTED DATA ITEMS %VEN A RELATIVELY SHORT HIGH QUALITY AUDIO TRACK CAN OCCUPY MILLIONS OF BYTES AND VIDEO CLIPS CAN RUN TO HUNDREDS OF MEGABYTES OR EVEN GIGABYTES OF DATA !S MULTIMEDIA APPLICATIONS HAVE BECOME MORE IMPORTANT USERS HAVE WANTED TO MANAGE THESE TYPES OF DATA ALONG WITH THE OTHER DATA IN THEIR DATABASES 4HE CAPABILITY TO EFFICIENTLY MANAGE LARGE OBJECTS OFTEN CALLED ,/"S WAS ONE OF THE EARLIEST ADVANTAGES CLAIMED FOR OBJECT ORIENTED DATABASES
,/"SõINõTHEõ2ELATIONALõ-ODEL 4HE FIRST APPROACH TO SUPPORTING ,/"S IN RELATIONAL DATABASES WAS THROUGH THE UNDERLYING OPERATING SYSTEM AND ITS FILE SYSTEM )N EARLY IMPLEMENTATIONS EACH INDIVIDUAL ,/" DATA ITEM WAS STORED IN ITS OWN OPERATING SYSTEM FILE 4HE NAME OF THE FILE WAS PLACED IN A CHARACTER VALUED COLUMN WITHIN A TABLE AS A POINTER TO THE FILE 4HE TABLES OTHER COLUMNS COULD BE SEARCHED TO FIND ROWS THAT MET CERTAIN CRITERIA 7HEN AN APPLICATION NEEDED TO MANIPULATE THE ,/" CONTENT ASSOCIATED WITH ONE OF THE ROWS IT READ THE NAME OF THE FILE AND RETRIEVED THE ,/" DATA FROM IT -ANAGEMENT OF THE FILE INPUTOUTPUT WAS THE RESPONSIBILITY OF THE APPLICATION PROGRAM 4HIS APPROACH WORKED BUT IT WAS ERROR PRONE AND REQUIRED THAT A PROGRAMMER UNDERSTAND BOTH THE 2$"-3 AND THE FILE SYSTEM INTERFACES 4HE LACK OF INTEGRATION BETWEEN THE ,/" CONTENTS AND THE DATABASE WAS READILY APPARENT &OR EXAMPLE YOU COULDNT ASK THE DATABASE TO COMPARE TWO ,/" DATA ITEMS TO SEE IF THEY WERE THE SAME AND THE DATABASE COULDNT PROVIDE EVEN BASIC TEXT SEARCHING CAPABILITY FOR ,/" CONTENTS
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31,çANDç/BJECTSç
4ODAY MOST MAJOR ENTERPRISE CLASS $"-3 SYSTEMS PROVIDE DIRECT SUPPORT FOR THE !.3) )3/ STANDARD ,/" DATA TYPES ",/" FOR BINARY DATA #,/" FOR CHARACTER DATA AND .#,/" FOR CHARACTER DATA IN A MULTIBYTE NATIONAL LANGUAGE STORAGE FORMAT 9OU CAN DEFINE A COLUMN AS CONTAINING ONE OF THESE ,/" DATA TYPES AND USE IT IN CERTAIN SITUATIONS IN 31, STATEMENTS 4HERE ARE TYPICALLY SUBSTANTIAL RESTRICTIONS ON THE ,/" DATA SUCH AS NOT ALLOWING ITS USE IN A JOIN CONDITION OR IN A '2/50 "9 CLAUSE 3YBASE PROVIDES TWO LARGE OBJECT DATA TYPES )TS 4%84 DATA TYPE CAN STORE UP TO BILLION BYTES OF VARIABLE LENGTH TEXT DATA 9OU CAN USE A LIMITED SET OF 31, CAPABILITIES SUCH AS THE ,)+% TEXT SEARCH OPERATOR TO SEARCH THE CONTENTS OF 4%84 COLUMNS ! COMPANION )-!'% DATA TYPE CAN STORE UP TO BILLION BYTES OF VARIABLE LENGTH BINARY DATA -ICROSOFT 31, 3ERVER SUPPORTS THESE TYPES PLUS AN .4%84 DATA TYPE THAT ALLOWS UP TO BILLION CHARACTERS OF BYTE NATIONAL LANGUAGE TEXT )"-S $" PROVIDES A SIMILAR SET OF DATA TYPES ! $" CHARACTER LARGE OBJECT #,/" TYPE STORES UP TO BILLION BYTES OF TEXT ! $" DOUBLE BYTE CHARACTER LARGE OBJECT $"#,/" TYPE STORES UP TO BILLION BYTE CHARACTERS ! $" BINARY LARGE OBJECT ",/" STORES UP TO BILLION BYTES OF BINARY DATA /RACLE HISTORICALLY PROVIDED TWO LARGE OBJECT DATA TYPES ! ,/.' DATA TYPE STORED UP TO BILLION BYTES OF TEXT DATA ! ,/.' 2!7 DATA TYPE STORED UP TO BILLION BYTES OF BINARY DATA /RACLE RESTRICTED THE USE OF EITHER ,/.' TYPE TO ONLY A SINGLE COLUMN PER TABLE 7ITH THE INTRODUCTION OF /RACLE SUPPORT FOR ,/" DATA WAS EXPANDED SUBSTANTIALLY s !N /RACLE ",/" TYPE STORES UP TO TERABYTES OF BINARY DATA WITHIN THE DATABASE s !N /RACLE #,/" TYPE STORES UP TO TERABYTES OF SINGLE BYTE CHARACTER DATA WITHIN THE DATABASE s !N /RACLE .#,/" TYPE STORES MULTIBYTE CHARACTER DATA AS A ",/" s !N /RACLE "&),% TYPE STORES LONG BINARY DATA IN A FILE EXTERNAL TO THE DATABASE 4HE ",/" #,/" AND .#,/" TYPES ARE TIGHTLY INTEGRATED INTO /RACLES OPERATION INCLUDING TRANSACTION SUPPORT "&),% DATA IS MANAGED THROUGH A POINTER WITHIN THE DATABASE TO AN EXTERNAL OPERATING SYSTEM FILE )T IS NOT SUPPORTED BY /RACLE TRANSACTION SEMANTICS 3PECIAL /RACLE 0,31, FUNCTIONS ARE PROVIDED TO MANIPULATE ",/" #,/" AND .#,/" DATA FROM WITHIN 0,31, STORED PROCEDURES AS DESCRIBED IN THE NEXT SECTION )NFORMIX 5NIVERSAL 3ERVERS SUPPORT FOR LARGE OBJECT DATA IS SIMILAR TO THAT OF /RACLE )T SUPPORTS SIMPLE LARGE OBJECTS AND SMART LARGE OBJECTS s !N )NFORMIX "94% TYPE IS A SIMPLE LARGE OBJECT THAT STORES BINARY DATA s !N )NFORMIX 4%84 TYPE IS A SIMPLE LARGE OBJECT THAT STORES TEXT DATA s !N )NFORMIX ",/" TYPE IS A SMART LARGE OBJECT THAT STORES BINARY DATA s !N )NFORMIX #,/" TYPE IS A SMART LARGE OBJECT THAT STORES TEXT CHARACTER DATA
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)NFORMIX SIMPLE LARGE OBJECTS STORE UP TO GIGABYTES OF DATA 4HE ENTIRE LARGE OBJECT MUST BE RETRIEVED OR STORED AS A UNIT FROM THE APPLICATION PROGRAM OR IT CAN BE COPIED BETWEEN THE DATABASE AND AN OPERATING SYSTEM FILE 3MART LARGE OBJECTS CAN STORE UP TO TERABYTES OF DATA 3PECIAL )NFORMIX FUNCTIONS ARE PROVIDED TO PROCESS SMART LARGE OBJECTS IN SMALLER MORE MANAGEABLE CHUNKS 4HESE FUNCTIONS PROVIDE RANDOM ACCESS TO THE CONTENTS OF AN )NFORMIX
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SMART OBJECT SIMILAR TO THE RANDOM ACCESS TYPICALLY PROVIDED FOR OPERATING SYSTEM FILES )NFORMIX ALSO PROVIDES ADVANCED CONTROLS OVER LOGGING TRANSACTION MANAGEMENT AND DATA INTEGRITY FOR SMART LARGE OBJECTS
3PECIALIZEDõ,/"õ0ROCESSING "ECAUSE ,/"S CAN BE VERY LARGE COMPARED WITH THE DATA ITEMS TYPICALLY HANDLED BY 2$"-3 SYSTEMS THEY POSE SPECIAL PROBLEMS IN SEVERAL AREAS s $ATA STORAGE AND OPTIMIZATION 3TORING A ,/" ITEM INLINE WITH THE OTHER CONTENTS OF A TABLES ROW WOULD DESTROY THE OPTIMIZATION THAT THE $"-3 PERFORMS TO FIT DATABASE DATA NEATLY INTO PAGES THAT MATCH THE SIZE OF DISK PAGES &OR THIS REASON ,/" DATA IS NEARLY ALWAYS STORED OUT OF LINE IN SEPARATE STORAGE AREAS -OST $"-3 BRANDS THAT SUPPORT ,/"S PROVIDE SPECIAL ,/" STORAGE OPTIONS INCLUDING NAMED STORAGE SPACES THAT ARE SPECIFIED WHEN THE ,/" TYPE COLUMN IS CREATED s 3TORING ,/" DATA IN THE DATABASE "ECAUSE A ,/" CAN BE TENS OR HUNDREDS OF MEGABYTES IN SIZE MOST PROGRAMS CANT HOLD THE ENTIRE CONTENTS OF A ,/" IN A MEMORY BUFFER AT ONCE 4HEY PROCESS PORTIONS OF THE ,/" AT A TIME FOR EXAMPLE PAGES OF A LONG DOCUMENT OR INDIVIDUAL FRAMES OF A VIDEO CLIP "UT EMBEDDED 31, AND NORMAL 31, !0)S ARE DESIGNED FOR ROW AT A TIME PROCESSING THROUGH ).3%24 AND 50$!4% STATEMENTS THAT STORES THE VALUES FOR ALL COLUMNS IN THE ROW AT ONCE 3PECIAL TECHNIQUES ARE REQUIRED TO PUT DATA INTO A DATABASE ,/" COLUMN PIECE BY PIECE THROUGH MULTIPLE !0) CALLS PER ,/" COLUMN s 2ETRIEVING ,/" DATA FROM THE DATABASE 4HIS IS THE SAME ISSUE AS STORING THE DATA BUT IN REVERSE %MBEDDED 31, AND NORMAL 31, !0)S ARE DESIGNED FOR 3%,%#4 STATEMENT OR &%4#( STATEMENT PROCESSING THAT RETRIEVES DATA VALUES FOR ALL COLUMNS OF A ROW AT ONCE "UT BECAUSE A STORED ,/" VALUE CAN BE TENS OR HUNDREDS OF MEGABYTES IN SIZE MOST PROGRAMS CANT POSSIBLY PROCESS IT ALL AT ONCE IN A MEMORY BUFFER 3PECIAL TECHNIQUES ARE REQUIRED TO RETRIEVE THE DATABASE ,/" COLUMN DATA PIECE BY PIECE SO THAT IT CAN BE PROCESSED BY THE APPLICATION s 4RANSACTION LOGGING -OST $"-3S SUPPORT TRANSACTIONS BY MAINTAINING BEFORE AND AFTER IMAGES OF MODIFIED DATA IN A TRANSACTION LOG "ECAUSE OF THE POTENTIALLY LARGE SIZE OF ,/" DATA THE LOGGING OVERHEAD COULD BE EXTREME &OR THIS REASON MANY $"-3S DONT SUPPORT LOGGING FOR ,/" DATA OR THEY ALLOW LOGGING BUT PROVIDE THE ABILITY TO TURN IT ON AND OFF 3EVERAL $"-3S ADDRESS THESE ISSUES THROUGH EXTENDED !0)S THAT SPECIFICALLY SUPPORT ,/" MANIPULATION 4HESE CALLS PROVIDE RANDOM ACCESS TO INDIVIDUAL SEGMENTS OF THE ,/" CONTENTS ALLOWING THE PROGRAM TO RETRIEVE OR STORE THE ,/" IN MANAGEABLE CHUNKS /RACLE INTRODUCED THIS CAPABILITY FOR MANIPULATING ITS ,/" DATA TYPES WITHIN STORED PROCEDURES WRITTEN IN THE /RACLE 0,31, LANGUAGE )TS CAPABILITIES ARE SIMILAR TO THOSE PROVIDED BY OTHER OBJECT RELATIONAL DATABASES SUCH AS )NFORMIX 5NIVERSAL 3ERVER 7HEN A STORED PROCEDURE READS AN /RACLE ,/" COLUMN FROM A TABLE /RACLE DOES NOT ACTUALLY RETURN THE CONTENTS OF THE COLUMN )NSTEAD A LOCATOR FOR THE ,/" DATA IN OBJECT PARLANCE A HANDLE FOR THE ,/" IS RETURNED 4HE LOCATOR IS USED IN CONJUNCTION WITH MORE THAN SPECIAL ,/" PROCESSING FUNCTIONS THAT THE STORED PROCEDURE $"-3?,/" CAN THEN USE
#HAPTERçç
31,çANDç/BJECTSç
TO MANIPULATE THE ACTUAL DATA STORED IN THE ,/" COLUMN OF THE DATABASE (ERE IS A BRIEF DESCRIPTION OF SOME OF ,/" PROCESSING FUNCTIONS AVAILABLE IN THE $"-3?,/" STORED PROCEDURE s $"-3?,/"2%!$LOCATOR LENGTH OFFSET BUFFER 2EADS INTO THE 0,31, BUFFER THE INDICATED NUMBER OF BYTESCHARACTERS FROM THE ,/" IDENTIFIED BY THE LOCATOR STARTING AT THE OFFSET s $"-3?,/"72)4%LOCATOR LENGTH OFFSET BUFFER 7RITES THE INDICATED NUMBER OF BYTESCHARACTERS FROM THE 0,31, BUFFER INTO THE ,/" IDENTIFIED BY THE LOCATOR STARTING AT THE OFFSET s $"-3?,/"!00%.$LOCATOR LOCATOR !PPENDS THE ENTIRE CONTENTS OF THE ,/" IDENTIFIED BY LOCATOR TO THE END OF THE CONTENTS OF THE ,/" IDENTIFIED BY LOCATOR s $"-3?,/"%2!3%LOCATOR LENGTH OFFSET %RASES THE CONTENTS OF THE ,/" IDENTIFIED BY THE LOCATOR AT OFFSET FOR LENGTH BYTESCHARACTERS FOR CHARACTER BASED ,/"S SPACES ARE INSERTED AND FOR BINARY ,/"S BINARY ZEROES ARE INSERTED s $"-3?,/"#/09LOCATOR LOCATOR LENGTH OFFSET OFFSET #OPIES LENGTH BYTESCHARACTERS FROM THE ,/" IDENTIFIED BY LOCATOR AT OFFSET INTO THE ,/" IDENTIFIED BY LOCATOR AT OFFSET s $"-3?,/"42)-LOCATOR LENGTH 4RIMS THE ,/" IDENTIFIED BY THE LOCATOR TO THE INDICATED NUMBER OF BYTESCHARACTERS s $"-3?,/"35"342LOCATOR LENGTH OFFSET 2ETURNS AS A TEXT STRING RETURN VALUE THE INDICATED NUMBER OF BYTESCHARACTERS FROM THE ,/" IDENTIFIED BY THE LOCATOR STARTING AT THE OFFSET THE RETURN VALUE FROM THIS FUNCTION MAY BE ASSIGNED INTO A 0,31, 6!2#(!2 VARIABLE s $"-3?,/"'%4,%.'4(LOCATOR 2ETURNS AS AN INTEGER VALUE THE LENGTH IN BYTESCHARACTERS OF THE ,/" IDENTIFIED BY THE LOCATOR s $"-3?,/"#/-0!2%LOCATOR LOCATOR LENGTH OFFSET OFFSET #OMPARES THE ,/" IDENTIFIED BY LOCATOR TO THE ,/" IDENTIFIED BY LOCATOR STARTING AT OFFSET AND OFFSET RESPECTIVELY FOR LENGTH BYTES CHARACTERS RETURNS ZERO IF THEY ARE THE SAME AND NONZERO IF THEY ARE NOT s $"-3?,/").342LOCATOR PATTERN OFFSET I 2ETURNS AS AN INTEGER VALUE THE POSITION WITHIN THE ,/" IDENTIFIED BY THE LOCATOR WHERE THE ITH OCCURRENCE OF PATTERN IS MATCHED THE RETURNED VALUE MAY BE USED AS AN OFFSET IN SUBSEQUENT ,/" PROCESSING CALLS
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/RACLE IMPOSES ONE FURTHER RESTRICTION ON UPDATES AND MODIFICATIONS TO ,/" VALUES THAT ARE PERFORMED THROUGH THESE FUNCTIONS ,/"S CAN IMPOSE AN UNACCEPTABLY HIGH OVERHEAD ON /RACLES TRANSACTION MECHANISMS SO /RACLE NORMALLY DOES NOT LOCK THE CONTENTS OF A ,/" DATA ITEM WHEN THE ROW CONTAINING THE ,/" IS READ BY AN APPLICATION PROGRAM OR A 0,31, ROUTINE )F THE ,/" DATA IS TO BE UPDATED THE ROW MUST BE EXPLICITLY LOCKED PRIOR TO MODIFYING IT 4HIS IS DONE BY INCLUDING A &/2 50$!4% CLAUSE IN THE 3%,%#4 STATEMENT THAT RETRIEVES THE ,/" LOCATOR (ERE IS A 0,31, FRAGMENT THAT
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RETRIEVES A ROW CONTAINING A ,/" THAT CONTAINS DOCUMENT TEXT AND THAT UPDATES CHARACTERS IN THE MIDDLE OF THE ,/" DATA DECLARE LOB #,/" TEXTBUF VARCHAR BEGIN 0UT TEXT TO BE INSERTED INTO BUFFER 'ET LOB LOCATOR AND LOCK ,/" FOR UPDATE SELECT DOCUMENT?LOB INTO LOB FROM DOCUMENTS WHERE DOCUMENT?ID gg FOR UPDATE 7RITE NEW TEXT BYTES INTO ,/" DBMS?LOBWRITELOB TEXTBUF COMMIT END
!BSTRACTõ3TRUCTURED õ$ATAõ4YPES 4HE DATA TYPES ENVISIONED BY THE RELATIONAL DATA MODEL ARE SIMPLE INDIVISIBLE ATOMIC DATA VALUES )F A DATA ITEM SUCH AS AN ADDRESS IS ACTUALLY COMPOSED OF A STREET ADDRESS CITY STATE AND POSTAL CODE AS A DATABASE DESIGNER YOU HAVE TWO CHOICES 9OU CAN TREAT THE ADDRESS AS FOUR SEPARATE DATA ITEMS EACH STORED IN ITS OWN COLUMN SO THAT YOU CAN SEARCH AND RETRIEVE THE ITEMS INDIVIDUALLY /R YOU CAN TREAT THE ADDRESS AS A SINGLE UNIT IN WHICH CASE YOU CANNOT PROCESS ITS INDIVIDUAL COMPONENT PARTS WITHIN THE DATABASE 4HERE IS NO MIDDLE GROUND THAT ALLOWS YOU TO TREAT THE ADDRESS AS A UNIT FOR CERTAIN SITUATIONS AND TO ACCESS ITS COMPONENT PARTS FOR OTHERS -ANY PROGRAMMING LANGUAGES INCLUDING EVEN NONnOBJECT ORIENTED LANGUAGES LIKE # OR 0ASCAL DO PROVIDE SUCH A MIDDLE GROUND 4HEY SUPPORT COMPOUND DATA TYPES OR NAMED DATA STRUCTURES 4HE DATA STRUCTURE IS COMPOSED OF INDIVIDUAL DATA ITEMS OR LOWER LEVEL STRUCTURES WHICH CAN BE ACCESSED INDIVIDUALLY "UT THE ENTIRE DATA STRUCTURE CAN ALSO BE TREATED AS A SINGLE UNIT WHEN THAT IS MOST CONVENIENT 3TRUCTURED OR COMPOSITE DATA TYPES IN OBJECT RELATIONAL DATABASES PROVIDE THIS SAME CAPABILITY IN A $"-3 CONTEXT )NFORMIX 5NIVERSAL 3ERVER SUPPORTS ABSTRACT DATA TYPES THROUGH ITS CONCEPT OF ROW DATA TYPES 9OU CAN THINK OF A ROW TYPE AS A STRUCTURED SEQUENCE OF INDIVIDUAL DATA ITEMS CALLED FIELDS (ERE IS AN )NFORMIX #2%!4% 4!",% STATEMENT FOR A SIMPLE 0%23/..%, TABLE THAT USES A ROW DATA TYPE TO STORE BOTH NAME AND ADDRESS INFORMATION #2%!4% 4!",% 0%23/..%, %-0,?.5- ).4%'%2 .!-% 2/7
#HAPTERçç
31,çANDç/BJECTSç
&?.!-% 6!2#(!2 -?).)4 #(!2 ,?.!-% 6!2#(!2 !$$2%33 2/7 342%%4 6!2#(!2 #)49 6!2#(!2 34!4% #(!2 0/34#/$% 2/7 -!). ).4%'%2 3&8 ).4%'%2
4HIS TABLE HAS THREE COLUMNS 4HE FIRST ONE %-0,?.5- HAS AN INTEGER DATA TYPE 4HE LAST TWO .!-% AND !$$2%33 HAVE A ROW DATA TYPE INDICATED BY THE KEYWORD 2/7 FOLLOWED BY A PARENTHESIZED LIST OF THE FIELDS THAT MAKE UP THE ROW 4HE .!-% COLUMNS ROW DATA TYPE HAS THREE FIELDS WITHIN IT 4HE !$$2%33 COLUMNS ROW DATA TYPE HAS FOUR FIELDS 4HE LAST OF THESE FOUR FIELDS 0/34#/$% ITSELF HAS A ROW DATA TYPE AND CONSISTS OF TWO FIELDS )N THIS SIMPLE EXAMPLE THE HIERARCHY IS ONLY TWO LEVELS DEEP BUT THE CAPABILITY CAN BE AND OFTEN IS EXTENDED TO ADDITIONAL LEVELS )NDIVIDUAL FIELDS WITHIN THE COLUMNS OF THE TABLE ARE ACCESSIBLE IN 31, STATEMENTS THROUGH AN EXTENSION OF THE 31, DOT NOTATION THAT IS ALREADY USED TO QUALIFY COLUMN NAMES WITH TABLE NAMES AND USER NAMES !DDING A DOT AFTER A COLUMN NAME ALLOWS YOU TO SPECIFY THE NAMES OF INDIVIDUAL FIELDS WITHIN A COLUMN 4HIS 3%,%#4 STATEMENT RETRIEVES THE EMPLOYEE NUMBERS AND FIRST AND LAST NAMES OF ALL PERSONNEL WITH A SPECIFIED MAIN POSTAL CODE 3%,%#4 %-0,?.5- .!-%&?.!-% .!-%,?.!-% &2/- 0%23/..%, 7(%2% !$$2%330/34#/$%-!). gg
3UPPOSE ANOTHER TABLE WITHIN THE DATABASE NAMED -!.!'%23 HAD THE SAME .!-% STRUCTURE AS ONE OF ITS COLUMNS 4HEN THIS QUERY RETRIEVES THE EMPLOYEE NUMBERS OF EMPLOYEES WHO ARE ALSO MANAGERS 3%,%#4 %-0,?.5- &2/- 0%23/..%, -!.!'%23 7(%2% 0%23/..%,.!-% -!.!'%23.!-%
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)N THE FIRST OF THESE TWO QUERIES IT MAKES SENSE TO RETRIEVE THE INDIVIDUAL FIELDS WITHIN THE .!-% COLUMN 4HE SECOND QUERY SHOWS A SITUATION WHERE ITS MORE CONVENIENT TO USE THE ENTIRE NAME COLUMN ALL THREE FIELDS AS THE BASIS FOR COMPARISON )TS CLEARLY A LOT MORE CONVENIENT TO ASK THE $"-3 TO COMPARE THE TWO ABSTRACT DATA TYPED COLUMNS THAN IT IS TO SPECIFY SEPARATE COMPARISONS FOR EACH OF THE INDIVIDUAL FIELDS 4OGETHER THESE EXAMPLES SHOW THE ADVANTAGES OF THE ROW DATA TYPE IN ALLOWING ACCESS TO THE FIELDS AT ANY LEVEL OF THE HIERARCHY 4HE ROW DATA TYPE COLUMNS REQUIRE SPECIAL HANDLING WHEN YOURE INSERTING DATA INTO THE DATABASE 4HE 0%23/..%, TABLE HAS THREE COLUMNS SO AN ).3%24 STATEMENT FOR THE TABLE MUST HAVE THREE ITEMS IN ITS 6!,5%3 CLAUSE 4HE COLUMNS THAT HAVE A ROW DATA TYPE REQUIRE A SPECIAL 2/7 VALUE CONSTRUCTOR TO PUT TOGETHER THE INDIVIDUAL DATA ITEMS INTO A ROW TYPE
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ITEM THAT MATCHES THE DATA TYPE OF THE COLUMN (ERE IS A VALID ).3%24 STATEMENT FOR THE TABLE THAT ILLUSTRATES THE USE OF THE 2/7 CONSTRUCTOR ).3%24 ).4/ 0%23/..%, 6!,5%3 2/7g*OHNg g*g g*ONESg 2/7g 2OSE 3Tg g#HICAGOg g),g 2/7
$EFININGõ!BSTRACTõ$ATAõ4YPES 7ITH THE )NFORMIX ROW DATA TYPE CAPABILITIES ILLUSTRATED SO FAR EACH INDIVIDUAL STRUCTURED COLUMN IS DEFINED IN ISOLATION )F TWO TABLES NEED TO USE THE SAME ROW DATA TYPE STRUCTURE IT IS DEFINED WITHIN EACH TABLE 4HIS VIOLATES ONE OF THE KEY PRINCIPLES OF OBJECT ORIENTED DESIGN WHICH IS REUSABILITY )NSTEAD OF HAVING EACH OBJECT THE TWO COLUMNS IN THE TWO DIFFERENT TABLES HAVE ITS OWN DEFINITION THE ROW DATA TYPE SHOULD BE DEFINED ONCE AND THEN REUSED FOR THE TWO COLUMNS )NFORMIX 5NIVERSAL 3ERVER PROVIDES THIS CAPABILITY THROUGH ITS NAMED ROW TYPE FEATURE 4HE ROW DATA TYPES SHOWN IN PREVIOUS EXAMPLES ARE UNNAMED ROW DATA TYPES 9OU CREATE AN )NFORMIX NAMED ROW TYPE WITH THE #2%!4% 2/7 490% STATEMENT (ERE ARE EXAMPLES FOR THE 0%23/..%, TABLE #2%!4% 2/7 490% .!-%?490% &?.!-% 6!2#(!2 -?).)4 #(!2 ,?.!-% 6!2#(!2 #2%!4% 2/7 490% 0/34?490% -!). ).4%'%2 3&8 ).4%'%2 #2%!4% 2/7 490% !$$2?490% 342%%4 6!2#(!2 #)49 6!2#(!2 34!4% #(!2 0/34#/$% 0/34?490%
.OTE THAT THE DEFINITION OF A NAMED ROW TYPE CAN DEPEND ON OTHER PREVIOUSLY CREATED NAMED ROW TYPES AS SHOWN BY THE !$$2?490% CONTAINING A COLUMN 0/34#/$% THAT USES THE 0/34?490% ROW TYPE 7ITH THESE ROW DATA TYPES DEFINED THE NAME AND ADDRESS COLUMNS IN THE 0%23/..%, TABLE AND ANY OTHER COLUMNS HOLDING NAME OR ADDRESS DATA IN OTHER TABLES OF THE DATABASE CAN BE DEFINED USING IT 4HE AGGRESSIVE USE OF ABSTRACT DATA TYPES CAN THUS HELP TO ENFORCE UNIFORMITY IN NAMING AND DATA TYPING WITHIN AN OBJECT RELATIONAL DATABASE (ERE IS THE NEW )NFORMIX DEFINITION OF THE 0%23/..%, TABLE USING THE JUST DEFINED ABSTRACT DATA TYPES #2%!4% 4!",% 0%23/..%, %-0,?.5- ).4%'%2 .!-% .!-%?490% !$$2%33 !$$2?490%
#HAPTERçç
31,çANDç/BJECTSç
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&IGURE SHOWS SOME SAMPLE DATA FOR THIS TABLE AND THE HIERARCHICAL COLUMNFIELD STRUCTURE CREATED BY THE ABSTRACT DATA TYPES /RACLE SUPPORTS ABSTRACT DATA TYPES THROUGH A VERY SIMILAR STRUCTURE WITH SLIGHTLY DIFFERENT 31, SYNTAX (ERE IS THE /RACLE #2%!4% 490% STATEMENT TO CREATE THE SAME ABSTRACT DATA STRUCTURE FOR NAMES AND ADDRESSES #2%!4% 490% .!-%?490% !3 /"*%#4 &?.!-% 6!2#(!2 -?).)4 #(!2 ,?.!-% 6!2#(!2 #2%!4% 490% 0/34?490% !3 /"*%#4 -!). .5-"%2 3&8 .5-"%2 #2%!4% 490% !$$2?490% !3 /"*%#4 342%%4 6!2#(!2 #)49 6!2#(!2 34!4% #(!2 0/34#/$% 0/34?490%
/RACLE CALLS THE ABSTRACT DATA TYPE AN OBJECT INSTEAD OF A ROW TYPE )N FACT THE TYPE IS FUNCTIONING AS AN OBJECT CLASS IN THE USUAL OBJECT ORIENTED TERMINOLOGY %XTENDING THE OBJECT ORIENTED TERMINOLOGY FURTHER THE INDIVIDUAL COMPONENTS OF AN /RACLE ABSTRACT DATA TYPE ARE REFERRED TO AS ATTRIBUTES CORRESPONDING TO THE )NFORMIX FIELDS DESCRIBED EARLIER 4HE !$$2? 490% TYPE HAS FOUR ATTRIBUTES IN THIS EXAMPLE 4HE FOURTH ATTRIBUTE 0/34#/$% IS ITSELF AN ABSTRACT DATA TYPE "OTH /RACLE AND )NFORMIX USE THE EXTENDED DOT NOTATION TO REFER TO INDIVIDUAL DATA ELEMENTS WITHIN ABSTRACT DATA TYPES 7ITH NESTED ABSTRACT TYPES IT TAKES SEVERAL LEVELS OF DOT DELIMITED NAMES TO IDENTIFY AN INDIVIDUAL DATA ITEM 4HE MAIN POSTAL CODE WITHIN THE 0%23/..%, TABLE IS IDENTIFIED AS
)F THE TABLE WERE OWNED BY ANOTHER USER 3AM THE QUALIFIED NAME WOULD BECOME EVEN LONGER 3!-0%23/..%,!$$2%330/34#/$%-!).
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)NFORMIX ALLOWS THE USE OF ROW TYPES TO GO ONE STEP BEYOND THEIR ROLE AS DATA TYPE TEMPLATES FOR INDIVIDUAL COLUMNS 9OU CAN USE A ROW TYPE TO DEFINE THE STRUCTURE OF AN ENTIRE TABLE &OR EXAMPLE WITH THIS ROW TYPE DEFINITION #2%!4% 2/7 490% 0%23?490% %-0,?.5- ).4%'%2 .!-% .!-%?490% !$$2%33 !$$2?490%
YOU CAN DEFINE THE 0%23/..%, TABLE USING THE ROW TYPE AS A MODEL #2%!4% 4!",% 0%23/..%, /& 490% 0%23?490%
4HE COLUMNS OF THIS 0%23/..%, TABLE WILL BE EXACTLY AS THEY WERE IN THE PREVIOUS #2%!4% 4!",% EXAMPLES BUT NOW 0%23/..%, IS A TYPED TABLE 4HE MOST BASIC USE OF THE TYPED TABLE CAPABILITY IS TO FORMALIZE THE OBJECT STRUCTURE IN THE DATABASE %ACH OBJECT CLASS HAS ITS OWN ROW TYPE AND THE TYPED TABLE THAT HOLDS OBJECTS ROWS OF THAT CLASS IS DEFINED IN TERMS OF THE ROW TYPE "EYOND THIS USAGE TYPED TABLES ARE ALSO A KEY COMPONENT OF THE )NFORMIX NOTION OF TABLE INHERITANCE DESCRIBED LATER IN THE h)NHERITANCEv SECTION
-ANIPULATINGõ!BSTRACTõ$ATAõ4YPES 5NFORTUNATELY STRUCTURED DATA TYPES CREATE NEW COMPLEXITY FOR DATABASE UPDATE STATEMENTS THAT MUST INSERT OR MODIFY THEIR STRUCTURED DATA VALUES )NFORMIX 5NIVERSAL 3ERVER IS FAIRLY LIBERAL IN ITS DATA TYPE CONVERSION REQUIREMENTS FOR UNNAMED ROW TYPES 4HE DATA YOU ASSIGN INTO A ROW TYPE COLUMN MUST SIMPLY HAVE THE SAME NUMBER OF FIELDS OF THE SAME DATA TYPES 4HE 2/7 CONSTRUCTOR IS USED AS SHOWN IN PREVIOUS EXAMPLES TO ASSEMBLE INDIVIDUAL DATA ITEMS INTO A ROW TYPE VALUE FOR INSERTING OR UPDATING DATA &OR NAMED ROW TYPES THE REQUIREMENT IS MORE STRINGENT THE DATA YOU ASSIGN INTO A NAMED ROW TYPE COLUMN MUST ACTUALLY HAVE THE SAME NAMED ROW TYPE 9OU CAN ACHIEVE THIS IN THE ).3%24 STATEMENT BY EXPLICITLY CASTING THE CONSTRUCTED ROW VALUE TO HAVE THE .!-%?490% DATA TYPE ).3%24 ).4/ 0%23/..%, 6!,5%3 2/7g*OHNg g*g g*ONESg .!-%?490% 2/7g 2OSE 3Tg g#HICAGOg g),g 2/7
4HE DOUBLE COLON OPERATOR CASTS THE CONSTRUCTED THREE FIELD ROW AS A .!-%?490% ROW AND MAKES THE 6!,5%3 CLAUSE COMPATIBLE WITH THE DATA TYPES OF THE COLUMNS IN THE TABLE /RACLE USES A SLIGHTLY DIFFERENT APPROACH TO CONSTRUCTING STRUCTURED DATA ITEMS AND INSERTING THEM INTO COLUMNS THAT HAVE ABSTRACT DATA TYPES 7HEN YOU CREATE AN /RACLE ABSTRACT DATA TYPE USING THE #2%!4% 490% STATEMENT /RACLE AUTOMATICALLY DEFINES A CONSTRUCTOR METHOD FOR THE TYPE 9OU CAN THINK OF THE CONSTRUCTOR METHOD AS A FUNCTION THAT TAKES AS ITS ARGUMENTS THE INDIVIDUAL COMPONENTS OF THE ABSTRACT DATA TYPE AND THAT RETURNS AN ABSTRACT DATA TYPE VALUE WITH THE INDIVIDUAL COMPONENTS ALL PACKAGED TOGETHER 4HE CONSTRUCTOR IS USED IN THE 6!,5%3 CLAUSE OF THE ).3%24 STATEMENT TO GLUE THE INDIVIDUAL
#HAPTERçç
31,çANDç/BJECTSç
DATA ITEM VALUES TOGETHER INTO A STRUCTURED DATA VALUE THAT MATCHES THE COLUMN DEFINITION (ERE IS AN ).3%24 STATEMENT FOR THE 0%23/..%, TABLE ).3%24 ).4/ 0%23/..%, 6!,5%3 .!-%?490%g*OHNg g*g g*ONESg !$$2?490%g 2OSE 3Tg g#HICAGOg g),g 0/34?490%
4HE CONSTRUCTORS .!-%?490% !$$2?490% 0/34?490% PERFORM THE SAME FUNCTIONS AS THE 2/7 CONSTRUCTOR DOES FOR )NFORMIX AND ALSO PROVIDE THE CASTING REQUIRED TO ENSURE STRICT DATA TYPE CORRESPONDENCE
)NHERITANCE 3UPPORT FOR ABSTRACT DATA TYPES GIVES THE RELATIONAL DATA MODEL A FOUNDATION FOR OBJECT BASED CAPABILITIES 4HE ABSTRACT DATA TYPE CAN EMBODY THE REPRESENTATION OF AN OBJECT AND THE VALUES OF ITS INDIVIDUAL FIELDS OR SUBCOLUMNS ARE ITS ATTRIBUTES !NOTHER IMPORTANT FEATURE OF THE OBJECT ORIENTED MODEL IS INHERITANCE 7ITH INHERITANCE NEW OBJECTS CAN BE DEFINED AS BEING A PARTICULAR TYPE OF AN EXISTING OBJECT TYPE CLASS AND INHERIT THE PREDEFINED ATTRIBUTES AND BEHAVIORS OF THAT TYPE &IGURE SHOWS AN EXAMPLE OF HOW INHERITANCE MIGHT WORK IN A MODEL OF A COMPANYS EMPLOYEE DATA !LL EMPLOYEES ARE MEMBERS OF THE CLASS 0%23/..%, AND THEY ALL HAVE THE ATTRIBUTES ASSOCIATED WITH BEING AN EMPLOYEE EMPLOYEE NUMBER NAME AND ADDRESS 3OME EMPLOYEES ARE SALESPEOPLE AND THEY HAVE ADDITIONAL ATTRIBUTES SUCH AS A SALES QUOTA AND THE IDENTITY OF THEIR SALES MANAGER /THER EMPLOYEES ARE ENGINEERS WITH A DIFFERENT SET OF ATTRIBUTES SUCH AS THE ACADEMIC DEGREES THEY HOLD OR THE CURRENT PROJECT TO WHICH THEY ARE ASSIGNED %ACH OF THESE EMPLOYEE TYPES HAS ITS OWN CLASS WHICH IS A SUBCLASS OF 0%23/..%, 4HE SUBCLASS INHERITS ALL OF THE CHARACTERISTICS OF THE CLASS ABOVE IT IN THE HIERARCHY 7E WANT TO TRACK ALL OF THE CORE PERSONNEL DATA FOR ENGINEERS AND SALESPEOPLE TOO (OWEVER THE SUBCLASSES HAVE ADDITIONAL INFORMATION THAT IS UNIQUE TO THEIR TYPE OF OBJECT )N &IGURE THE CLASS HIERARCHY GOES DOWN TO A THIRD LAYER FOR ENGINEERS DIFFERENTIATING BETWEEN TECHNICIANS AND MANAGERS
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)NFORMIX 5NIVERSAL 3ERVERS ABSTRACT DATA TYPE INHERITANCE MECHANISM PROVIDES AN EASY WAY TO DEFINE ABSTRACT DATA TYPES )NFORMIX ROW TYPES THAT CORRESPOND TO THE NATURAL HIERARCHY IN &IGURE !SSUME THAT THE )NFORMIX 0%23?490% ROW TYPE HAS ALREADY BEEN CREATED AS IN THE EXAMPLE FROM THE h$EFINING !BSTRACT $ATA 4YPESv SECTION EARLIER IN THIS CHAPTER AND A TYPED TABLE NAMED 0%23/..%, HAS BEEN CREATED BASED ON THIS ROW TYPE 5SING THE )NFORMIX INHERITANCE CAPABILITIES HERE ARE SOME #2%!4% 2/7 490% STATEMENTS FOR OTHER TYPES IN THE HIERARCHY #2%!4% 2/7 490% 3!,%3?490% 3,3?-'2 ).4%'%2 EMPLOYEE NUMBER OF SALES MGR 3!,!29 $%#)-!, ANNUAL SALARY 15/4! $%#)-!, 5.$%2 0%23?490% #2%!4% 2/7 490% %.'2?490% 3!,!29 $%#)-!, ANNUAL SALARY 923?%80%2 ).4%'%2 YEARS OF EXPERIENCE 5.$%2 0%23?490% #2%!4% 2/7 490% -'2?490% "/.53 $%#)-!, ANNUAL BONUS 5.$%2 %.'2?490% #2%!4% 2/7 490% 4%#(?490% 7!'%?2!4% $%#)-!, HOURLY WAGE RATE 5.$%2 %.'2?490%
4HE TYPE DEFINED FOR TECHNICIANS 4%#(?490% IS A SUBTYPE SUBCLASS OF THE ENGINEER TYPE %.'2?490% SO IT INHERITS ALL OF THE FIELDS FOR THE PERSONNEL TYPE 0%23?490% PLUS THE FIELDS ADDED AT THE %.'2?490% LEVEL PLUS THE ADDITIONAL FIELD ADDED IN ITS OWN DEFINITION !N ABSTRACT TYPE THAT IS DEFINED 5.$%2 ANOTHER TYPE AND THAT INHERITS ITS FIELDS IS CALLED A SUBTYPE OF THE HIGHER LEVEL TYPE #ONVERSELY THE HIGHER LEVEL TYPE IS A SUPERTYPE OF THE LOWER LEVEL TYPES DEFINED 5.$%2 IT 7ITH THIS TYPE HIERARCHY DEFINED ITS EASY TO CREATE )NFORMIX TYPED TABLES THAT USE THEM (ERE ARE SOME )NFORMIX STATEMENTS THAT CREATE A TABLE FOR ENGINEERS SEPARATE TABLES FOR MANAGERS AND TECHNICIANS AND ANOTHER TABLE TO HOLD SALESPERSON DATA #2%!4% 4!",% %.').%%23 /& 490% %.'2?490% #2%!4% 4!",% 4%#(.)#)!.3 /& 490% 4%#(?490% #2%!4% 4!",% -!.!'%23 /& 490% -'2?490% #2%!4% 4!",% 2%03 /& 490% 3!,%3?490%
4HE TYPE HIERARCHY HAS PUSHED THE COMPLEXITY INTO THE DATA TYPE DEFINITIONS AND MADE THE TABLE STRUCTURE VERY SIMPLE AND EASY TO DEFINE !LL OTHER CHARACTERISTICS OF THE TABLE CAN AND MUST STILL BE DEFINED WITHIN THE TABLE DEFINITION &OR EXAMPLE THE 2%03 TABLE CONTAINS
#HAPTERçç
31,çANDç/BJECTSç
A COLUMN THAT IS ACTUALLY A FOREIGN KEY TO THE 0%23/..%, TABLE SO ITS TABLE DEFINITIONS SHOULD PROBABLY INCLUDE A &/2%)'. +%9 CLAUSE LIKE THIS #2%!4% 4!",% 2%03 /& 490% 3!,%3?490% &/2%)'. +%9 3,3?-'2 2%&%2%.#%3 0%23/..%,%-0,?.5-
4YPE INHERITANCE CREATES AMONG THE STRUCTURE OF THE TABLES A RELATIONSHIP THAT IS BASED ON THE DEFINED ROW TYPES BUT THE TABLES REMAIN INDEPENDENT OF ONE ANOTHER IN TERMS OF THE DATA THAT THEY CONTAIN 2OWS INSERTED INTO THE 4%#(.)#)!.3 TABLE DONT AUTOMATICALLY APPEAR IN EITHER THE %.').%%23 TABLE OR IN THE 0%23/..%, TABLE %ACH IS A TABLE IN ITS OWN RIGHT CONTAINING ITS OWN DATA ! DIFFERENT KIND OF INHERITANCE TABLE INHERITANCE PROVIDES A VERY DIFFERENT LEVEL OF LINKAGE BETWEEN THE TABLES CONTENTS ACTUALLY TURNING THE TABLES INTO SOMETHING MUCH CLOSER TO OBJECT CLASSES )T IS DESCRIBED IN THE NEXT SECTION
4ABLEõ)NHERITANCEõ)MPLEMENTINGõ/BJECTõ#LASSES )NFORMIX 5NIVERSAL 3ERVER PROVIDES A CAPABILITY CALLED TABLE INHERITANCE THAT MOVES THE TABLE STRUCTURE OF A DATABASE AWAY FROM THE TRADITIONAL RELATIONAL MODEL AND MAKES IT MUCH CLOSER TO THE CONCEPT OF AN OBJECT CLASS 5SING TABLE INHERITANCE ITS POSSIBLE TO CREATE A HIERARCHY OF TYPED TABLES CLASSES SUCH AS THE ONE SHOWN IN &IGURE 4HE TABLES ARE STILL BASED ON A DEFINED TYPE HIERARCHY BUT NOW THE TABLES THEMSELVES HAVE A PARALLEL HIERARCHY (ERE IS A SET OF #2%!4% 4!",% STATEMENTS THAT IMPLEMENTS THIS TABLE INHERITANCE #2%!4% 4!",% %.').%%23 /& 490% %.'2?490% 5.$%2 0%23/..%, #2%!4% 4!",% 4%#(.)#)!.3 /& 490% 4%#(?490% 5.$%2 %.').%%23 #2%!4% 4!",% -!.!'%23 /& 490% -'2?490% 5.$%2 %.').%%23 #2%!4% 4!",% 2%03 /& 490% 3!,%3?490% 5.$%2 0%23/..%, 1, ÊÓ{ÎÊ Ê ÊvÀÝÊÌ>LiÊ
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7HEN A TABLE IS DEFINED IN THIS WAY AS UNDER ANOTHER TABLE IT INHERITS MANY MORE CHARACTERISTICS FROM ITS SUPERTABLE THAN JUST THE COLUMN STRUCTURE )T INHERITS THE FOREIGN KEY PRIMARY KEY REFERENTIAL INTEGRITY AND CHECK CONSTRAINTS OF THE SUPERTABLE ANY TRIGGERS DEFINED ON THE SUPERTABLE AS WELL AS INDEXES STORAGE AREAS AND OTHER )NFORMIX SPECIFIC CHARACTERISTICS )TS POSSIBLE TO OVERRIDE THIS INHERITANCE BY SPECIFICALLY INCLUDING THE OVERRIDDEN CHARACTERISTICS IN THE #2%!4% 4!",% STATEMENTS FOR THE SUBTABLES ! TABLE TYPE HIERARCHY HAS A PROFOUND IMPACT ON THE WAY THAT THE 5NIVERSAL 3ERVER $"-3 TREATS THE ROWS STORED IN THE TABLES 4HE TABLES IN THE HIERARCHY NOW FORM A COLLECTION OF NESTED SETS OF ROWS AS SHOWN IN &IGURE 7HEN A ROW IS INSERTED INTO THE TABLE HIERARCHY IT IS STILL INSERTED INTO A SPECIFIC TABLE *OE *ONES FOR EXAMPLE IS IN THE 4%#(.)#)!.3 TABLE WHILE 3AM 7ILSON IS IN THE %.').%%23 TABLE AND 3UE -ARSH IS IN THE 0%23/..%, TABLE 31, QUERIES BEHAVE QUITE DIFFERENTLY HOWEVER 7HEN YOU PERFORM A DATABASE QUERY ON ONE OF THE TABLES IN THE HIERARCHY IT RETURNS ROWS NOT ONLY FROM THE TABLE ITSELF BUT ALSO FROM ALL OF THE INCLUDED SUBTABLES OF THAT TABLE 4HIS QUERY 3%,%#4 &2/- 0%23/..%,
RETURNS ROWS FROM THE 0%23/..%, TABLE AND ROWS FROM THE %.').%%23 4%#(.)#)!.3 -!.!'%23 AND 2%03 TABLES 3IMILARLY THIS QUERY 3%,%#4 &2/- %.').%%23
RETURNS ROWS FROM 4%#(.)#)!.3 AND -!.!'%23 IN ADDITION TO %.').%%23 4HE $"-3 IS NOW TREATING THE TABLES AS A NESTED COLLECTION OF ROWS AND A QUERY ON A TABLE ROWSET APPLIES TO ALL ROWS INCLUDED IN THE SET )F YOU WANT TO RETRIEVE ONLY THE ROWS THAT APPEAR IN THE TOP LEVEL TABLE ITSELF YOU MUST USE THE /.,9 KEYWORD 3%,%#4 &2/- /.,9%.').%%23
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4HE $"-3 APPLIES THE SAME SET OF ROWS LOGIC TO $%,%4% OPERATIONS 4HIS $%,%4% STATEMENT $%,%4% &2/- 0%23/..%, 7(%2% %-0,?.5-
SUCCESSFULLY DELETES THE ROW FOR EMPLOYEE NUMBER REGARDLESS OF WHICH TABLE IN THE HIERARCHY ACTUALLY CONTAINS THE ROW 4HE STATEMENT IS INTERPRETED AS h$ELETE ANY ROWS FROM THE 0%23/..%, SET THAT MATCH THESE CRITERIAv !S WITH THE QUERIES IF YOU WANT TO DELETE ONLY ROWS THAT APPEAR IN THE %.').%%23 TABLE OF THE HIERARCHY BUT NOT ROWS FROM ANY OF ITS SUBTABLES YOU CAN USE THIS STATEMENT $%,%4% &2/- /.,9%.').%%23 7(%2% %-0,?.5-
4HE SAME LOGIC HOLDS FOR 50$!4% STATEMENTS 4HIS ONE CHANGES THE EMPLOYEE NUMBER REGARDLESS OF WHICH TABLE IN THE HIERARCHY ACTUALLY HOLDS THE ROW FOR THE EMPLOYEE 50$!4% 0%23/..%, 3%4 ,?.!-% g(ARRISONg 7(%2% %-0,?.5-
!GAIN THE /.,9 CONSTRUCT MAY BE USED TO RESTRICT THE SCOPE OF THE 50$!4% OPERATION TO ONLY ROWS THAT ACTUALLY APPEAR IN THE NAMED TABLE AND NOT TO THOSE THAT APPEAR IN ITS SUBTABLES /F COURSE WHEN OPERATING AT A GIVEN LEVEL WITHIN THE TABLE HIERARCHY YOUR 31, STATEMENTS CAN REFERENCE ONLY COLUMNS THAT ARE DEFINED AT THAT LEVEL 9OU CANNOT USE THIS STATEMENT $%,%4% &2/- 0%23/..%, 7(%2% 3!,!29
BECAUSE THE 3!,!29 COLUMN DOESNT EXIST IN THE TOP LEVEL 0%23/..%, TABLE CLASS )T IS DEFINED ONLY FOR SOME OF ITS SUBTABLES SUBCLASSES 9OU CAN USE THIS STATEMENT $%,%4% &2/- -!.!'%23 7(%2% 3!,!29
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BECAUSE 3!,!29 IS DEFINED AT THIS LEVEL OF THE TABLE CLASS HIERARCHY !S NOTED TABLE INHERITANCE MOVES THE OPERATION OF )NFORMIX 5NIVERSAL 3ERVER FAIRLY FAR OUT OF THE RELATIONAL DATABASE REALM AND INTO THE OBJECT ORIENTED WORLD 2ELATIONAL PURISTS POINT TO EXAMPLES LIKE THE PREVIOUS ONES TO CLAIM THAT OBJECT RELATIONAL DATABASES BRING WITH THEM DANGEROUS INHERENT INCONSISTENCIES 4HEY ASK h7HY SHOULD AN ).3%24 OF A ROW INTO ONE TABLE CAUSE IT TO SUDDENLY APPEAR IN TWO OTHER TABLES v AND h7HY SHOULD A SEARCHED $%,%4% STATEMENT THAT DOESNT MATCH ANY ROWS OF A TABLE CAUSE OTHER ROWS IN OTHER TABLES TO DISAPPEAR v /F COURSE THE TABLE HIERARCHY HAS STOPPED BEHAVING STRICTLY AS IF IT WERE A SET OF RELATIONAL TABLES AND INSTEAD HAS TAKEN ON MANY OF THE CHARACTERISTICS OF AN OBJECT CLASS AND OBJECT CLASS HIERARCHY 7HETHER THIS IS GOOD OR BAD DEPENDS ON YOUR POINT OF VIEW )T DOES MEAN THAT YOU MUST BE VERY CAREFUL ABOUT APPLYING RELATIONAL DATABASE ASSUMPTIONS TO AN OBJECT RELATIONAL IMPLEMENTATION
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3ETS õ!RRAYS õANDõ#OLLECTIONS )N A RELATIONAL DATABASE TABLES ARE THE ONLY DATABASE STRUCTURE USED TO REPRESENT A SET OF OBJECTS &OR EXAMPLE THE SET OF ENGINEERS IN OUR 0%23/..%, DATABASE IS REPRESENTED BY THE ROWS IN THE %.').%%23 TABLE 3UPPOSE EACH ENGINEER HAS A SET OF ACADEMIC DEGREES A "3 IN SCIENCE FROM -)4 A 0H$ IN ELECTRICAL ENGINEERING FROM -ICHIGAN ETC THAT ARE TO BE STORED IN THE DATABASE 4HE NUMBER OF DEGREES FOR EACH ENGINEER WILL VARYFROM NONE FOR SOME ENGINEERS TO PERHAPS HALF A DOZEN FOR OTHERS ! PURE RELATIONAL DATABASE HAS ONLY ONE CORRECT WAY TO ADD THIS INFORMATION TO THE DATA MODEL ! NEW TABLE $%'2%%3 MUST BE CREATED AS SHOWN IN &IGURE %ACH ROW IN THE $%'2%%3 TABLE REPRESENTS ONE INDIVIDUAL ACADEMIC DEGREE HELD BY ONE OF THE ENGINEERS ! COLUMN IN THE $%'2%%3 TABLE HOLDS THE EMPLOYEE NUMBER OF THE ENGINEER HOLDING THE DEGREE DESCRIBED BY THAT PARTICULAR ROW AND SERVES AS A FOREIGN KEY TO THE %.').%%23 TABLE LINKING THE TWO TABLES IN A PARENTCHILD RELATIONSHIP 4HE OTHER COLUMNS IN THE $%'2%%3 TABLE DESCRIBE THE PARTICULARS OF THE DEGREE 9OU HAVE SEEN THE TYPE OF PARENTCHILD RELATIONAL TABLE STRUCTURE SHOWN IN &IGURE MANY TIMES IN THE EARLIER CHAPTERS OF THIS BOOK AND IT HAS BEEN A BASIC CONSTRUCT OF RELATIONAL DATABASES SINCE THE BEGINNING (OWEVER THERE ARE SOME DISADVANTAGES TO HAVING THIS BE THE ONLY WAY IN WHICH SETS OF DATA ATTRIBUTES CAN BE MODELED &IRST THE DATABASE TENDS TO HAVE A GREAT MANY TABLES AND FOREIGN KEY RELATIONSHIPS AND BECOMES HARD TO UNDERSTAND 3ECOND MANY COMMON QUERIES NEED TO JOIN THREE FOUR OR MORE TABLES TO GET THE REQUIRED ANSWERS 4HIRD WITH THE IMPLEMENTATIONS OF RELATIONAL JOINS PROVIDED BY MOST $"-3 SYSTEMS THE PERFORMANCE OF QUERIES WILL DETERIORATE AS THEY INVOLVE MORE AND MORE JOINS 4HE TABLE STRUCTURE OF &IGURE CANNOT BE IMPLEMENTED DIRECTLY IN AN OBJECT ORIENTED MODEL 4HE DEGREES ARE NOT SUBSTANTIAL OBJECTS IN THEIR OWN RIGHT AND DO NOT DESERVE THEIR OWN TABLE )NSTEAD THEY ARE MUST BE IMPLEMENTED AS ATTRIBUTES OF THE ENGINEER HOLDING THE DEGREES 4RUE A VARIABLE NUMBER OF DEGREES IS ASSOCIATED WITH EACH ENGINEER BUT THE OBJECT ORIENTED MODEL WOULD HAVE NO PROBLEM WITH REPRESENTING THIS SITUATION AS AN ARRAY OR A SET OF DATA WITHIN THE ENGINEER OBJECT
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4HE OBJECT RELATIONAL DATABASES SUPPORT THIS OBJECT ORIENTED VIEW OF DATA BY SUPPORTING SETS ARRAYS OR OTHER COLLECTION DATA TYPES ! COLUMN WITHIN A TABLE CAN BE DEFINED TO HAVE ONE OF THESE DATA TYPES )T WILL THEN CONTAIN NOT A SINGLE DATA ITEM VALUE BUT A SET OF DATA ITEM VALUES 3PECIAL 31, EXTENSIONS ALLOW A USER OR MORE OFTEN A STORED PROCEDURE TO MANIPULATE THE SET OF DATA ITEMS AS A WHOLE OR TO ACCESS INDIVIDUAL MEMBERS OF THE SET
$EFININGõ#OLLECTIONS )NFORMIX 5NIVERSAL 3ERVER SUPPORTS COLLECTIONS OF ATTRIBUTES THROUGH ITS COLLECTION DATA TYPES 4HREE DIFFERENT COLLECTION DATA TYPES ARE SUPPORTED s ,ISTS ! LIST IS AN ORDERED COLLECTION OF DATA ITEMS ALL OF WHICH HAVE THE SAME TYPE 7ITHIN A LIST IS THE CONCEPT OF A FIRST ITEM A LAST ITEM AND THE NTH ITEM 4HE ITEMS IN THE LIST ARE NOT REQUIRED TO BE UNIQUE &OR EXAMPLE A LIST OF THE FIRST NAMES OF THE EMPLOYEES HIRED IN THE LAST YEAR IN ORDER OF HIRE MIGHT BE [@*IM @-ARY @3AM @*IM @*OHN] s -ULTISETS ! MULTISET IS AN UNORDERED COLLECTION OF DATA ITEMS ALL OF WHICH HAVE THE SAME TYPE 4HERE IS NO CONCEPT OF SEQUENCING THE ITEMS IN A MULTISET ITS ITEMS HAVE NO IMPLIED ORDERING 4HE ITEMS ARE NOT REQUIRED TO BE UNIQUE 4HE LIST OF EMPLOYEE FIRST NAMES COULD BE CONSIDERED A MULTISET IF YOU DIDNT CARE ABOUT THE ORDER OF HIRE [@*IM @3AM @*OHN @*IM @-ARY] s 3ETS ! SET IS AN UNORDERED COLLECTION OF UNIQUE DATA ITEMS ALL OF WHICH HAVE THE SAME TYPE !S IN A MULTISET THERE IS NO CONCEPT OF FIRST OR LAST THE SET HAS NO IMPLIED ORDER 4HE ITEMS MUST HAVE UNIQUE VALUES 4HE FIRST NAMES IN THE PREVIOUS EXAMPLES WOULDNT QUALIFY BUT THE LAST NAMES MIGHT [@*OHNSON @3AMUELS @7RIGHT @*ONES @3MITH] 4O ILLUSTRATE THE CONCEPT OF COLLECTION DATA WE WILL EXPAND THE TABLES IN OUR EXAMPLE OBJECT RELATIONAL DATABASE AS FOLLOWS s 4HE 2%03 TABLE WILL INCLUDE SALES TARGETS FOR EACH OF THE FIRST SECOND THIRD AND FOURTH QUARTERS 4HE QUARTERLY TARGETS CAN NATURALLY BE REPRESENTED AS A LIST COLUMN ADDED TO THE 2%03 TABLE 4HE QUARTERS HAVE A NATURAL ORDERING FIRST THROUGH FOURTH THE QUOTA FOR EACH QUARTER HAS THE SAME DATA TYPE $%#)-!, AND THE VALUES ARE NOT NECESSARILY UNIQUE THAT IS THE QUOTAS FOR THE FIRST AND SECOND QUARTERS MIGHT BE THE SAME s 4HE %.').%%23 TABLE WILL INCLUDE INFORMATION ABOUT THE ACADEMIC DEGREES THAT EACH ENGINEER HOLDS 4WO ITEMS OF DATA WILL ACTUALLY BE STORED ABOUT EACH DEGREE THE ACTUAL DEGREE "3 0H$ -"! ETC AND THE SCHOOL 4HIS DATA WILL BE STORED AS A MULTISET COLUMN ADDED TO THE %.').%%23 TABLE BECAUSE ITS POSSIBLE TO HAVE TWO IDENTICAL ENTRIESFOR EXAMPLE AN ENGINEER MAY HAVE A "3 DEGREE IN ENGINEERING AND A "3 DEGREE IN BUSINESS FROM THE SAME SCHOOL
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s 4HE 4%#(.)#)!.3 TABLE WILL INCLUDE INFORMATION ABOUT THE PROJECTS TO WHICH EACH TECHNICIAN IS ASSIGNED %ACH TECHNICIAN MAY BE ASSIGNED TO TWO OR MORE PROJECTS BUT EACH PROJECT HAS A UNIQUE NAME 4HIS DATA WILL BE STORED AS A SET COLUMN ADDED TO THE 4%#(.)#)!.3 TABLE 4HE DATA VALUES MUST BE UNIQUE BUT NO PARTICULAR ORDER IS ASSOCIATED WITH THEM
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(ERE ARE SOME )NFORMIX !,4%2 4!",% STATEMENTS THAT IMPLEMENT THESE CHANGES TO THE PREVIOUSLY DEFINED TABLES !,4%2 4!",% 2%03 !$$ 142?4'4 ,)34$%#)-!, FOUR QUARTERLY TARGETS !,4%2 4!",% 4%#(.)#)!.3 !$$ 02/*%#4 3%46!2#(!2 PROJECTS ASSIGNED !,4%2 4!",% %.').%%23 !$$ $%'2%%3 -5,4)3%42/7 DEGREE INFO $%'2%% 6!2#(!2 3#(//, 6!2#(!2
4HESE COLLECTION COLUMN TYPES CREATE A ROW WITHIN A ROW STRUCTURE WITHIN THE TABLE THAT CONTAINS THEM AS SHOWN IN &IGURE )N THE CASE OF THE %.').%%23 TABLE THE STRUCTURE MIGHT MORE ACCURATELY BE DESCRIBED AS A TABLE WITHIN A TABLE #LEARLY THE RELATIONAL MODEL OF ROWCOLUMN TABLES WITH ATOMIC DATA ITEMS HAS BEEN STRETCHED CONSIDERABLY BY THE INTRODUCTION OF COLLECTION DATA TYPES )NFORMIX 5NIVERSAL 3ERVER ALLOWS COLLECTIONS TO BE USED QUITE GENERALLY AND TO BE INTERMIXED WITH OTHER OBJECT RELATIONAL EXTENSIONS ! COLLECTION CAN BE A FIELD OF A ROW DATA TYPE 4HE ITEMS OF A COLLECTION CAN BE ROW DATA TYPES )TS ALSO POSSIBLE TO DEFINE COLLECTIONS WITHIN COLLECTIONS WHERE THAT MAKES SENSE &OR EXAMPLE THE PROJECTS IN THIS EXAMPLE MIGHT HAVE SUBPROJECTS THAT MUST BE TRACKED FOR EACH TECHNICIAN !T EACH LEVEL OF ADDITIONAL COMPLEXITY THE COMPLEXITY OF THE STORED PROCEDURE LANGUAGE 30, AND OF THE 31, EXPRESSIONS THAT ARE REQUIRED TO MANIPULATE THE DATA ITEMS AND PROCESS THEM INCREASES ACCORDINGLY /RACLE ALSO PROVIDES EXTENSIVE SUPPORT FOR COLLECTION TYPE DATA THROUGH TWO DIFFERENT /RACLE OBJECT RELATIONAL EXTENSIONS s 6ARYING ARRAYS ! VARYING ARRAY IS AN ORDERED COLLECTION OF DATA ITEMS ALL HAVING THE SAME DATA TYPE 4HERE IS NO REQUIREMENT THAT THE ITEMS IN THE ARRAY BE UNIQUE 9OU DEFINE THE MAXIMUM NUMBER OF DATA ITEMS THAT CAN OCCUR WHEN YOU SPECIFY A VARYING ARRAY TYPE FOR A COLUMN /RACLE PROVIDES EXTENSIONS TO 31, TO ACCESS THE INDIVIDUAL ITEMS WITHIN THE ARRAY s .ESTED TABLES ! NESTED TABLE IS AN ACTUAL TABLE WITHIN A TABLE ! COLUMN WITH A NESTED TABLE TYPE CONTAINS INDIVIDUAL DATA ITEMS THAT ARE THEMSELVES TABLES /RACLE ACTUALLY STORES THE NESTED TABLE DATA SEPARATELY FROM THE MAIN TABLE THAT CONTAINS IT BUT IT USES 31, EXTENSIONS TO PROCESS NESTED REFERENCES TO THE INNER TABLE 5NLIKE A VARYING ARRAY A NESTED TABLE CAN CONTAIN ANY NUMBER OF ROWS
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! COLUMN WITHIN A TABLE CAN BE DECLARED TO HAVE A 6!22!9 VARYING ARRAY OR 4!",% /& NESTED TABLE STRUCTURE (ERE ARE SOME /RACLE #2%!4% 490% AND #2%!4% 4!",% STATEMENTS THAT USE VARYING ARRAYS AND NESTED TABLES TO ACHIEVE TABLE STRUCTURES LIKE THOSE SHOWN IN &IGURE #2%!4% 490% 4'4?!22!9 !3 6!22!9 /& .5-"%2 #2%!4% 4!",% 2%03 %-0,?.5- .5-"%2 .!-% .!-%?490% !$$2%33 !$$2?490% 3,3?-'2 .5-"%2 EMPLOYEE NUMBER OF MGR 3!,!29 .5-"%2 ANNUAL SALARY 15/4! .5-"%2 SALES QUOTA 142?4'4 4'4?!22!9 FOUR QUARTERLY TGTS #2%!4% 490% $%'2?490% !3 /"*%#4 $%'2%% 6!2#(!2 3#(//, 6!2#(!2 #2%!4% 490% $%'2?4!",% !3 4!",% /& $%'2?490% #2%!4% 4!",% %.').%%23 %-0,?.5- .5-"%2 .!-% .!-%?490% !$$2%33 !$$2?490% 3!,!29 .5-"%2 ANNUAL SALARY 923?%80%2 .5-"%2 YEARS OF EXPERIENCE $%'2%%3 $%'2?4!",% .%34%$ 4!",% $%'2%%3 34/2% !3 %.').%%23?$%'2%%3
4HE QUARTERLY TARGET INFORMATION FOR THE 2%03 TABLE IS MOST EASILY REPRESENTED AS AN /RACLE VARYING ARRAY COLUMN 4HERE WILL BE EXACTLY FOUR QUARTERS OF INFORMATION SO THE MAXIMUM SIZE OF THE ARRAY IS KNOWN IN ADVANCE )N THIS EXAMPLE THE VARYING ARRAY CONTAINS A SIMPLE DATA ITEM AS ITS ELEMENT BUT ITS ALSO COMMON TO DEFINE VARYING ARRAYS WHOSE ITEMS ARE THEMSELVES ABSTRACT STRUCTURED DATA TYPES 4HE ACADEMIC DEGREE INFORMATION FOR THE %.').%%23 TABLE IS REPRESENTED AS A NESTED TABLE &OR A DATA ITEM LIKE THIS ONE YOU COULD DECIDE TO PLACE AN UPPER LIMIT ON THE NUMBER OF ROWS AND USE A VARYING ARRAY STRUCTURE INSTEAD BUT IN GENERAL IF THE MAXIMUM NUMBER OF ITEMS IS UNKNOWN A NESTED TABLE IS THE RIGHT CHOICE )N THIS CASE THE NESTED TABLE HAS AN ABSTRACT DATA TYPE COMPOSED OF TWO ATTRIBUTES %ACH ROW OF THE NESTED TABLE WILL CONTAIN INFORMATION ABOUT A DEGREE GRANTED AND THE SCHOOL THAT GRANTED IT
1UERYINGõ#OLLECTIONõ$ATA #OLLECTION VALUED COLUMNS COMPLICATE THE PROCESS OF QUERYING THE TABLES THAT CONTAIN THEM )N THE 3%,%#4 ITEM LIST THEY GENERATE MULTIPLE DATA VALUES FOR EACH ROW OF QUERY RESULTS )N SEARCH CONDITIONS THEY DONT CONTAIN INDIVIDUAL DATA ITEMS BUT ITS SOMETIMES CONVENIENT TO TREAT THEM AS SETS OF DATA 4HE OBJECT RELATIONAL DATABASES TYPICALLY PROVIDE A LIMITED SET OF
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31,çANDç/BJECTSç
31, EXTENSIONS OR EXTEND EXISTING 31, CONCEPTS TO PROVIDE SIMPLE QUERIES INVOLVING COLLECTION DATA &OR MORE ADVANCED QUERIES THEY REQUIRE YOU TO WRITE STORED PROCEDURE LANGUAGE PROGRAMS WITH LOOP STRUCTURES THAT PROCESS THE COLLECTION DATA ITEMS ONE BY ONE &OR QUERY PURPOSES )NFORMIX TREATS THE COLLECTION TYPES AS IF THEY WERE A SET OF DATA VALUES LIKE THE VALUES THAT MIGHT BE RETURNED BY A SUBQUERY 9OU CAN MATCH INDIVIDUAL ITEMS WITHIN A COLLECTION USING THE 31, ). SEARCH CONDITION (ERE IS A QUERY THAT FINDS ANY TECHNICIANS WHO WORK ON A PROJECT NAMED hBINGOv 3%,%#4 %-0,?.5- .!-% &2/- 4%#(.)#)!.3 7(%2% gBINGOg ). 02/*%#43
4HE NAME OF THE COLLECTION VALUED COLUMN IN THIS CASE THE SET VALUED COLUMN 02/*%#43 APPEARS IN PARENTHESES )NFORMIX TREATS THE MEMBERS OF THE COLLECTION AS A SET AND APPLIES THE ). MATCHING CONDITION )N INTERACTIVE 31, YOU CAN PUT A COLLECTION VALUED COLUMN IN THE SELECT ITEM LIST )NFORMIX DISPLAYS THE COLLECTION OF DATA AS A 3%4 ,)34 OR -5,4)3%4 IN THE DISPLAYED OUTPUT 4O PROCESS COLLECTION VALUED DATA IN THE SELECT LIST OF A PROGRAMMATIC REQUEST THAT IS FROM A PROGRAM USING %31, OR A CALL LEVEL !0) YOU MUST USE SPECIAL !0) EXTENSIONS ANDOR EXTENSIONS TO THE )NFORMIX STORED PROCEDURE LANGUAGE /RACLE PROVIDES ADDITIONAL CAPABILITIES FOR PROCESSING NESTED TABLES WITHIN 31, QUERIES .EWER VERSIONS OFFER A SPECIAL FUNCTION NAMED 4!",% THAT FLATTENS THE NESTED TABLE PRODUCING IN EFFECT AN UNNESTED TABLE WITH ONE ROW FOR EACH ROW OF THE NESTED TABLE WITHIN EACH ROW OF THE MAIN TABLE )N OLDER VERSIONS OF /RACLE A SPECIAL KEYWORD 4(% NOW DEPRECATED PROVIDED THE SAME RESULT BUT WITH SUBSTANTIALLY DIFFERENT SYNTAX (ERES A QUERY THAT USES THE 4!",% FUNCTION TO SHOW THE SCHOOLS FROM WHICH ONE OF THE ENGINEERS HAS RECEIVED DEGREES 3%,%#4 43#(//, &2/- %.').%%23 4 4!",%4$%'2%%3 4 7(%2% %-0,?.5-
-ANIPULATINGõ#OLLECTIONõ$ATA %XTENSIONS TO STANDARD 31, SYNTAX ARE USED TO INSERT NEW ROWS INTO A TABLE CONTAINING COLLECTION VALUED COLUMNS )NFORMIX PROVIDES A TRIO OF CONSTRUCTORSTHE 3%4 CONSTRUCTOR
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4HE &2/- CLAUSE FIRST REFERENCES THE %.').%%23 TABLE THAT CONTAINS THE NESTED TABLE $%'2%%3 GIVING IT THE ALIAS NAME 4 4HE 4!",% FUNCTION THEN USES THE ALIAS 4 TO QUALIFY THE NAME OF THE NESTED TABLE $%'2%%3 9OU CAN USE THE REAL TABLE NAME IF YOU QUALIFY IT WITH THE NESTED TABLE SUCH AS %.').%%23$%'2%%3 4HE FUNCTION FLATTENS THE NESTED TABLE CREATING A ROW FOR EACH NESTED ROW WITHIN EACH ROW OF THE MAIN TABLE MUCH LIKE YOU WOULD SEE IF $%'2%%3 WERE A SEPARATE TABLE AND YOU JOINED IT WITH THE MAIN TABLE 7ITH THIS SYNTAX THE 3%,%#4 CLAUSE IN THIS EXAMPLE IS QUITE SIMPLE IT SELECTS ONE COLUMN THAT ORIGINATED IN THE NESTED TABLE 4HE ABILITY TO FLATTEN NESTED TABLES IN THIS WAY AND PROCESS THEM AS IF THEY WERE ACTUALLY JOINED VERSIONS OF TWO SEPARATE TABLES IS ACTUALLY QUITE POWERFUL )T ALLOWS MANY QUERIES TO BE EXPRESSED IN HIGH LEVEL 31, THAT WOULD OTHERWISE REQUIRE YOU TO RESORT TO STORED PROCEDURES (OWEVER THE LOGIC BEHIND SUCH QUERIES AND THE TASK OF ACTUALLY CONSTRUCTING THEM CORRECTLY CAN BE COMPLICATED AS EVEN THIS SIMPLE EXAMPLE BEGINS TO SHOW
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-5,4)3%4 CONSTRUCTOR AND ,)34 CONSTRUCTORFOR THIS PURPOSE 4HEY TRANSFORM A LIST OF DATA ITEMS INTO THE CORRESPONDING COLLECTIONS TO BE INSERTED (ERE IS A PAIR OF )NFORMIX ).3%24 STATEMENTS THAT ILLUSTRATES THEIR USE WITH THE TABLES IN &IGURE ).3%24 ).4/ 4%#(.)#)!.3 6!,5%3 2/7g3AMg g2g g*ONESg 2/7g %LM 3Tg g(IGHLANDg g),g 2/7 3%4[gATLASg gCHECKMATEg gBINGOg] ).3%24 ).4/ %.').%%23 6!,5%3 2/7g*EFFg g2g g!MESg 2/7g 'REEN 3Tg g%LGINg g),g 2/7 -5,4)3%4[2/7g"3g g-ICHIGANg 2/7g"3g g-ICHIGANg 2/7g0H$g g3TANFORDg ]
4HE FIRST STATEMENT INSERTS A SINGLE ROW INTO THE 4%#(.)#)!.3 TABLE WITH A THREE ITEM SET IN THE 02/*%#43 COLUMN 4HE SECOND INSERTS A SINGLE ROW INTO THE %.').%%23 TABLE WITH A THREE ITEM MULTISET IN THE $%'2%%3 COLUMN "ECAUSE THE MEMBERS OF THIS PARTICULAR MULTISET ARE THEMSELVES ROW TYPES THE ROW CONSTRUCTOR MUST BE USED FOR EACH ITEM /RACLE USES A DIFFERENT APPROACH TO CONSTRUCTING THE COLLECTION VALUED DATA ITEMS FOR INSERTION INTO THE TABLE 2ECALL FROM THE DISCUSSION OF /RACLE ABSTRACT DATA TYPES THAT EACH /RACLE ABSTRACT DATA TYPE AUTOMATICALLY HAS AN ASSOCIATED CONSTRUCTOR METHOD THAT IS USED TO BUILD A DATA ITEM OF THE ABSTRACT TYPE OUT OF INDIVIDUAL DATA ITEMS 4HIS CONCEPT IS EXTENDED TO VARYING ARRAYS AND NESTED TABLES ! CONSTRUCTOR METHOD IS AUTOMATICALLY SUPPLIED FOR EACH VARYING ARRAY OR NESTED TABLE AND IT IS USED IN THE ).3%24 STATEMENTS ).3%24 ).4/ 2%03 %-0,?.5- .!-% !$$2%33 142?4'4 6!,5%3 .!-%?490%g-ARYg g8g g*ONESg !$$2?490%g %LM 3Tg g(IGHLANDg g),g 0/34?490% 4'4?!22!9 ).3%24 ).4/ %.').%%23 %-0,?.5- .!-% !$$2%33 $%'2%%3 6!,5%3 .!-%?490%g*EFFg g2g g!MESg !$$2?490%g 'REEN 3Tg g%LGINg g),g 0/34?490% $%'2?4!",%$%'2?490%g"3g g-ICHIGANg $%'2?490%g"3g g-ICHIGANg $%'2?490%g0H$g g3TANFORDg
#OLLECTIONSõANDõ3TOREDõ0ROCEDURES #OLLECTIONS POSE SPECIAL PROBLEMS FOR STORED PROCEDURES THAT ARE RETRIEVING AND MANIPULATING DATA IN TABLES THAT CONTAIN THEM "OTH /RACLE AND )NFORMIX PROVIDE SPECIAL STORED PROCEDURE LANGUAGE FACILITIES FOR THIS PURPOSE )N )NFORMIX SPECIAL 30, COLLECTION
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VARIABLES MUST BE USED (ERE IS AN 30, STORED PROCEDURE FRAGMENT THAT HANDLES THE 02/*%#43 COLLECTION COLUMN FROM THE 4%#(.)#)!.3 TABLE DEFINE PROJ?COLL COLLECTION HOLDS PROJECT COLLECTION DEFINE A?PROJECT VARCHAR HOLDS INDIVIDUAL PROJECT DEFINE PROJ?CNT INTEGER NUMBER OF PROJECTS DEFINE EMPL?NAME NAME?TYPE BUFFER FOR TECH NAME #HECK HOW MANY PROJECTS THE TECHNICIAN IS SUPPORTING SELECT CARDINALITYPROJECTS INTO PROJ?CNT FROM TECHNICIANS WHERE EMPL?NUM )F TOO MANY PROJECTS THEN REFUSE TO ADD A NEW ONE IF PROJ?CNT THEN 2ETRIEVE ROW INCLUDING PROJECT SET FOR THE TECHNICIAN SELECT NAME PROJECTS INTO EMPL?NAME PROJ?COLL FROM TECHNICIANS WHERE EMPL?NUM !DD THE gGONZOg PROJECT TO THE LIST FOR THIS TECH INSERT INTO TABLEPROJ?COLL VALUES gGONZOg 3EARCH THROUGH PROJECT LIST ONE BY ONE FOREACH PROJ?CURSOR FOR SELECT INTO A?PROJECT FROM TABLEPROJ?COLL IF A?PROJECT gATLASg THEN BEGIN UPDATE TABLEPROJ?COLL PROJECT SET PROJECT gBINGOg WHERE CURRENT OF PROJ?CURSOR EXIT FOREACH END END IF END FOREACH 5PDATE THE DATABASE ROW WITH MODIFIED PROJECT LIST UPDATE TECHNICIANS SET PROJECTS PROJ?COLL WHERE EMPL?NUM
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4HE EXAMPLE SHOWS SEVERAL ASPECTS OF COLLECTION HANDLING IN )NFORMIX 30, &IRST THE COLLECTION IS RETRIEVED FROM THE DATABASE INTO AN 30, VARIABLE AS A COLLECTION DATA TYPE )T WOULD ALSO BE POSSIBLE TO RETRIEVE IT INTO A VARIABLE EXPLICITLY DECLARED AS HAVING A 3%4 TYPE OR IN OTHER SITUATIONS A ,)34 OR -5,4)3%4 TYPE 4HE COLLECTION STORED IN THE VARIABLE IS THEN EXPLICITLY TREATED AS A TABLE FOR MANIPULATING ITEMS WITHIN THE COLLECTION 4O ADD A NEW PROJECT AN ).3%24 IS PERFORMED INTO THE COLLECTION TABLE 4O FIND AND MODIFY A SPECIFIC PROJECT A CURSOR IS USED TO SEARCH THROUGH THE COLLECTION TABLE AND A CURSOR BASED 50$!4%
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STATEMENT IS USED TO CHANGE THE VALUE OF ONE MEMBER OF THE COLLECTION .OTE THAT THE &/2%!#( LOOP RETRIEVES EACH ITEM OF THE COLLECTION INTO A VARIABLE SO THAT THE 30, ROUTINE CAN PROCESS IT &INALLY THE COLLECTION VARIABLES CONTENTS ARE USED TO UPDATE THE COLLECTION COLUMN WITHIN THE TABLE /RACLE TAKES A SIMILAR APPROACH TO PROCESSING VARYING ARRAYS 4HE INDIVIDUAL ELEMENTS OF AN ARRAY WITHIN AN ABSTRACT DATA TYPE ARE AVAILABLE THROUGH SUBSCRIPTED REFERENCES WITHIN A STRUCTURED DATA TYPE 4HE TYPICAL /RACLE 0,31, PROCESS FOR ACCESSING VARIABLE ARRAY ELEMENTS IS
2ETRIEVE THE ROW FROM THE TABLE CONTAINING THE VARYING ARRAY INTO A LOCAL VARIABLE WHOSE DATA TYPE IS DEFINED TO MATCH THE ROW STRUCTURE OF THE TABLE OR OF THE PARTICULAR COLUMNS BEING RETRIEVED
%XECUTE A &/2 LOOP WITH AN INDEX VARIABLE N THAT COUNTS FROM TO THE NUMBER OF ELEMENTS IN THE VARYING ARRAY 4HE NUMBER OF ELEMENTS IS AVAILABLE THROUGH THE VALUE OF A SPECIAL ATTRIBUTE OF THE ARRAY COLUMN NAMED #/5.4
7ITHIN THE &/2 LOOP A SUBSCRIPT IS USED ON THE VARYING ARRAY NAME TO ACCESS THE NTH ELEMENT OF THE VARYING ARRAY
! SIMILAR TECHNIQUE CAN BE USED TO PROCESS NESTED TABLES HOWEVER ITS USUALLY NOT NECESSARY )NSTEAD THE 4!",% FUNCTION IS GENERALLY USED TO FLATTEN THE TABLE IN A 31, QUERY AND THE RESULTS ARE PROCESSED WITH A SINGLE CURSOR DRIVEN &/2 LOOP 4HE PROCESSING MAY STILL BE COMPLEX )N PARTICULAR THE STORED PROCEDURE MAY NEED TO DETECT WHETHER A PARTICULAR ROW COMING FROM THE QUERY RESULTS IS FROM THE SAME MAIN TABLE ROW AS THE PREVIOUS ROW AND UPON DETECTING A CHANGE IN MAIN TABLE ROWS PERFORM SPECIAL PROCESSING SUCH AS COMPUTING SUBTOTALS )N THIS ASPECT THE PROCESSING OF BOTH VARYING ARRAYS AND NESTED TABLES BEGINS TO RESEMBLE THE NESTED LOOP PROCESSING TYPICAL OF THE #/"/, REPORT WRITING PROGRAMS OF YEARS AGO THAT HANDLED MASTER AND DETAIL RECORDS !S THE DISCUSSION IN THIS SECTION HAS ILLUSTRATED COLLECTION TYPES AND THE PROCESSING OF INDIVIDUAL COLLECTION ITEMS TEND TO CALL FOR PROGRAMMATIC ACCESS THROUGH STORED PROCEDURES RATHER THAN FOR AD HOC 31, USE /NE OF THE CRITICISMS OF OBJECT ORIENTED DATABASES IS THAT THEY ARE A REGRESSION FROM THE SIMPLICITY OF THE RELATIONAL MODEL AND THAT THEY REINTRODUCE THE NEED FOR EXPLICIT DATABASE NAVIGATION THAT WAS PART OF THE PRERELATIONAL DATABASES %XAMPLES LIKE THESE PROVIDE EVIDENCE THAT THERE IS AT LEAST A CERTAIN AMOUNT OF TRUTH IN THE CRITICISM
5SER $EFINEDõ$ATAõ4YPES /BJECT RELATIONAL DATA MANAGEMENT SYSTEMS GENERALLY PROVIDE A MECHANISM THROUGH WHICH A USER CAN EXTEND THE BUILT IN DATA TYPES PROVIDED BY THE $"-3 WITH ADDITIONAL USER DEFINED DATA TYPES &OR EXAMPLE A MAPPING APPLICATION MIGHT NEED TO OPERATE ON A ,/#!4)/. DATA TYPE THAT CONSISTS OF A PAIR OF LATITUDE AND LONGITUDE MEASUREMENTS EACH CONSISTING OF HOURS MINUTES AND SECONDS 4O EFFECTIVELY PROCESS LOCATION DATA THE APPLICATION MAY NEED TO DEFINE SPECIAL FUNCTIONS SUCH AS A $)34!.#%8 9 FUNCTION THAT COMPUTES THE DISTANCE BETWEEN TWO LOCATIONS 4HE MEANINGS OF SOME BUILT IN OPERATIONS SUCH AS A TEST FOR EQUALITY WILL NEED TO BE REDEFINED FOR LOCATION TYPE DATA
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31,çANDç/BJECTSç
/NE WAY THAT )NFORMIX 5NIVERSAL 3ERVER SUPPORTS USER DEFINED DATA TYPES IS THROUGH ITS /0!15% DATA TYPE !N /0!15% DATA TYPE IS NOT SURPRISINGLY OPAQUE TO THE $"-3 4HE $"-3 CAN STORE AND RETRIEVE DATA WITH THIS TYPE BUT IT HAS NO KNOWLEDGE OF THE INTERNAL WORKINGS OF THE TYPE )N OBJECT ORIENTED TERMS THE DATA IS COMPLETELY ENCAPSULATED 4HE USER MUST EXPLICITLY PROVIDE IN EXTERNAL ROUTINES WRITTEN IN # OR SOME SIMILAR PROGRAMMING LANGUAGE THE DATA STRUCTURE FOR THE TYPE CODE TO IMPLEMENT THE FUNCTIONS OR OPERATIONS THAT CAN BE PERFORMED ON THE TYPE SUCH AS COMPARING TWO DATA ITEMS OF THE TYPE FOR EQUALITY AND CODE TO CONVERT THE OPAQUE TYPE BETWEEN INTERNAL AND EXTERNAL REPRESENTATIONS 4HUS /0!15% DATA TYPES REPRESENT A LOW LEVEL CAPABILITY TO EXTEND THE CORE FUNCTIONALITY OF THE $"-3 WITH DATA TYPES THAT APPEAR AS IF THEY WERE BUILT IN ! MORE BASIC USER DEFINED DATA TYPE CAPABILITY IS PROVIDED BY THE IMPLEMENTATION OF $)34).#4 DATA TYPES WITHIN )NFORMIX ! $)34).#4 TYPE IS USEFUL TO DISTINGUISH AMONG DIFFERENT TYPES OF DATA ALL OF WHICH USE ONE OF THE $"-3 BUILT IN DATA TYPES &OR EXAMPLE THE CITY AND COMPANY NAME DATA ITEMS IN A DATABASE MIGHT BOTH BE DEFINED WITH THE DATA TYPE 6!2#(!2 %VEN THOUGH THEY SHARE THE SAME UNDERLYING $"-3 DATA TYPE THESE DATA ITEMS REALLY REPRESENT QUITE DIFFERENT TYPES OF DATA 9OU WOULD NEVER NORMALLY COMPARE A CITY VALUE TO A COMPANY NAME AND YET THE $"-3 WILL LET YOU DO THIS BECAUSE THE TWO 6!2#(!2 COLUMNS ARE DIRECTLY COMPARABLE 4O MAINTAIN A HIGHER LEVEL OF DATABASE INTEGRITY YOU COULD DEFINE EACH OF THESE TWO DATA ITEMS AS HAVING A $)34).#4 DATA TYPE #2%!4% $)34).#4 490% #)49?490% !3 6!2#(!2 #2%!4% $)34).#4 490% #/?.!-%?490% !3 6!2#(!2
.OW TABLES CAN BE CREATED CONTAINING CITY AND CUSTOMER NAME DATA ITEMS IN TERMS OF THE #)49?490% AND #/?.!-%?490% DATA TYPES )F YOU TRY TO COMPARE COLUMNS WITH THESE TWO DIFFERENT DATA TYPES THE $"-3 AUTOMATICALLY DETECTS THE SITUATION AND GENERATES AN ERROR 9OU CAN COMPARE THEM BUT ONLY BY EXPLICITLY CASTING THE DATA TYPE OF ONE ITEM TO MATCH THE DATA TYPE OF THE OTHER !S A RESULT THE DISTINCT DATA TYPES ASSIGNED TO THE DIFFERENT COLUMNS HELP TO MAINTAIN THE INTEGRITY OF THE DATABASE AND PREVENT INADVERTENT ERRORS IN PROGRAMS AND AD HOC QUERIES THAT USE THE DATABASE 7HILE /RACLE DOES NOT SUPPORT $)34).#4 DATA TYPES USER DEFINED TYPES CONSISTING OF SINGLE COLUMNS CAN BE USED FOR THE SAME EFFECT #2%!4% 490% #)49?490% !3 /"*%#4 #/, 6!2#(!2 #2%!4% 490% #/?.!-%?490% !3 /"*%#4 #/, 6!2#(!2
-ETHODSõANDõ3TOREDõ0ROCEDURES
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)N OBJECT ORIENTED LANGUAGES OBJECTS ENCAPSULATE BOTH THE DATA AND PROGRAMMING CODE THAT THEY CONTAIN THE DETAILS OF THE DATA STRUCTURES WITHIN AN OBJECT AND THE PROGRAMMING INSTRUCTIONS THAT MANIPULATE THOSE DATA STRUCTURES ARE EXPLICITLY HIDDEN FROM VIEW 4HE ONLY WAY TO MANIPULATE THE OBJECT AND OBTAIN INFORMATION ABOUT IT IS THROUGH METHODS WHICH ARE EXPLICITLY DEFINED PROCEDURES ASSOCIATED WITH THE OBJECT OR MORE ACCURATELY WITH THE OBJECT CLASS &OR EXAMPLE ONE METHOD ASSOCIATED WITH A CUSTOMER OBJECT MIGHT OBTAIN THE CUSTOMERS CURRENT CREDIT LIMIT !NOTHER METHOD MIGHT PROVIDE THE ABILITY TO CHANGE THE CREDIT LIMIT 4HE CREDIT LIMIT DATA ITSELF IS ENCAPSULATED HIDDEN WITHIN THE CUSTOMER OBJECT
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4HE DATA WITHIN THE TABLES OF A RELATIONAL DATABASE IS INHERENTLY NOT ENCAPSULATED 4HE DATA AND ITS STRUCTURE ARE DIRECTLY VISIBLE TO OUTSIDE USERS )N FACT ONE OF THE MAIN ADVANTAGES OF A RELATIONAL DATABASE IS THAT 31, CAN BE USED TO CARRY OUT AD HOC QUERIES AGAINST THE DATABASE 7HEN THE SYSTEM CATALOG OF A RELATIONAL DATABASE IS CONSIDERED THE CONTRAST WITH THE OBJECT ORIENTED IDEAL IS EVEN MORE EXTREME 7ITH THE CATALOG THE DATABASE IS SELF DESCRIBING SO THAT EVEN APPLICATIONS THAT DONT KNOW THE INTERNAL STRUCTURE OF THE DATABASE IN ADVANCE CAN USE 31, QUERIES TO FIND OUT WHAT IT IS 3TORED PROCEDURES PROVIDE A WAY FOR RELATIONAL DATABASES TO OFFER CAPABILITIES THAT RESEMBLE THOSE OF OBJECT ORIENTED METHODS !T THE EXTREME ALL USERS OF A RELATIONAL DATABASE COULD BE GRANTED PERMISSION TO EXECUTE ONLY A LIMITED SET OF STORED PROCEDURES AND NO UNDERLYING DATA ACCESS PERMISSIONS ON THE BASE TABLES AT ALL )N THIS CASE THE USERS ACCESS WOULD APPROACH THE ENCAPSULATION OF THE OBJECT ORIENTED IDEAL )N PRACTICE STORED PROCEDURES ARE OFTEN USED TO PROVIDE APPLICATION DESIGNERS WITH THE LIMITED DATABASE ACCESS THEY NEED (OWEVER THE AD HOC CAPABILITIES OF THE DATABASE ARE ALMOST ALWAYS EXPLOITED BY QUERY TOOLS OR REPORTING PROGRAMS /RACLE FORMALIZES THE LINKAGE BETWEEN OBJECT METHODS AND DATABASE STORED PROCEDURES BY ALLOWING YOU TO EXPLICITLY DEFINE A STORED PROCEDURE AS A MEMBER FUNCTION OF AN ABSTRACT DATA TYPE /NCE DEFINED IN THIS WAY THE MEMBER FUNCTION CAN BE USED IN QUERIES INVOLVING THE ABSTRACT DATA TYPE JUST AS IF IT WERE A BUILT IN FUNCTION OF THE $"-3 DESIGNED TO WORK ON THAT TYPE (ERE IS A REDEFINITION OF THE !$$2?490% ABSTRACT DATA TYPE THAT IS USED TO STORE ADDRESSES WITH A RELATIVELY SIMPLE MEMBER FUNCTION NAMED '%4?&5,,?0/34 4HE FUNCTION TAKES THE POSTAL CODE PART OF THE ADDRESS WHICH STORES BOTH A FIVE DIGIT MAIN POSTAL CODE AND A FOUR DIGIT SUFFIX AS TWO SEPARATE NUMBERS AND COMBINES THEM INTO ONE NINE DIGIT NUMBER WHICH IT RETURNS #2%!4% 490% !$$2?490% !3 /"*%#4 342%%4 6!2#(!2 #)49 6!2#(!2 34!4% #(!2 0/34#/$% 0/34?490% -%-"%2 &5.#4)/. '%4?&5,,?0/340/34#/$% ). 0/34?490% 2%452. .5-"%2 02!'-! 2%342)#4?2%&%2%.#%3'%4?&5,,?0/34 7.$3 #2%!4% 490% "/$9 !$$2?490% !3 -%-"%2 &5.#4)/. '%4?&5,,?0/340/34#/$% 0/34?490% 2%452. .5-"%2 )3 "%'). 2%452.0/34#/$%-!). 0/34#/$%3&8 %.$ %.$
4HE MEMBER FUNCTION IS IDENTIFIED AS SUCH WITHIN THE #2%!4% 490% STATEMENT FOR THE ABSTRACT DATA TYPE FOLLOWING THE LINES THAT DESCRIBE THE DATA ITEMS 4HE ADDITIONAL 02!'-! CLAUSE TELLS /RACLE THAT THE FUNCTION DOES NOT MODIFY THE CONTENTS OF THE DATABASE WHICH IS
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31,çANDç/BJECTSç
A REQUIREMENT FOR A FUNCTION THAT IS TO BE USED WITHIN QUERY EXPRESSIONS 4HERE ARE SEVERAL MORE OPTIONS WHICH ARE BEYOND THE SCOPE OF THIS DISCUSSION ! SEPARATE #2%!4% 490% "/$9 STATEMENT DEFINES THE ACTUAL PROCEDURAL CODE FOR THE FUNCTION !FTER THE FIRST FEW WORDS OF THE STATEMENT IT FOLLOWS THE SAME FORMAT AS THE STANDARD #2%!4% 02/#%$52% OR #2%!4% &5.#4)/. STATEMENTS /NCE THE MEMBER FUNCTION IS DEFINED IT CAN BE USED IN QUERY EXPRESSIONS LIKE THIS ONE WHICH FINDS EMPLOYEES LIVING IN POSTAL CODE !$$2?490%'%4?&5,,?0/34
)NFORMIX 5NIVERSAL 3ERVER DOESNT HAVE AN EXTENDED MECHANISM LIKE /RACLES TO TURN STORED PROCEDURES INTO OBJECT ORIENTED METHODS )NSTEAD ITS POSSIBLE TO USE AN )NFORMIX ROW TYPE CORRESPONDING TO AN /RACLE OBJECT TYPE AS THE PARAMETER OF A STORED FUNCTION 7HEN CALLED THE FUNCTION IS PASSED A DATA ITEM WITH THE APPROPRIATE ROW TYPE SUCH AS THE 0/34#/$% ABSTRACT DATA ITEM IN THE PRECEDING /RACLE EXAMPLE AND CAN PERFORM APPROPRIATE CALCULATIONS ON IT 9OU COULD FOR EXAMPLE DEFINE AN )NFORMIX STORED FUNCTION '%4?&5,,?0/34 WITH A SINGLE PARAMETER OF TYPE 0/34?490% 7ITH THAT DEFINITION THE PRECEDING /RACLE 3%,%#4 STATEMENT COULD BE USED UNMODIFIED IN THE EQUIVALENT )NFORMIX DATABASE !NOTHER POWERFUL FEATURE ASSOCIATED WITH OBJECT RELATIONAL STORED PROCEDURES IS THE OVERLOADING OF PROCEDURE DEFINITIONS TO ALLOW THEM TO PROCESS DIFFERENT TYPES OF DATA )N AN OBJECT CLASS HIERARCHY ITS FREQUENTLY NECESSARY TO DEFINE A METHOD THAT CARRIES OUT THE SAME OR VERY SIMILAR OPERATIONS ON DIFFERENT CLASSES OF OBJECTS &OR EXAMPLE YOU MAY WANT TO DEFINE A '%4?4'4?7!'%3 METHOD FUNCTION THAT CAN OBTAIN THE TARGET TOTAL ANNUAL WAGES FOR ANY OF THE SUBCLASSES OF THE 0%23/..%, CLASS IN OUR EXAMPLE DATABASE 4HE METHOD WHICH WILL BE IMPLEMENTED AS A STORED FUNCTION SHOULD RETURN THE TARGET TOTAL WAGES FOR THE EMPLOYEE TO WHICH IT IS APPLIED 4HE PARTICULARS OF THE CALCULATION DIFFER DEPENDING ON THE TYPE CLASS OF EMPLOYEE s &OR TECHNICIANS TOTAL WAGES ARE THE HOURLY RATE ¾ A NORMAL HOUR WEEK ¾ WEEKS PER YEAR s &OR MANAGERS TOTAL WAGES ARE EQUAL TO THEIR ANNUAL SALARY PLUS BONUS s &OR ALL OTHER ENGINEERS TOTAL WAGES ARE EQUAL TO THEIR ANNUAL SALARY
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4O SOLVE THIS PROBLEM A DIFFERENT '%4?4'4?7!'%3 ROUTINE IS DEFINED FOR EACH CLASS 4HE ROUTINE TAKES AN OBJECT A ROW OF THE 4%#(.)#)!.3 %.').%%23 OR -!.!'%23 TABLE AS ITS PARAMETER AND RETURNS THE CALCULATED AMOUNT 4HE THREE ROUTINES ARE IDENTICALLY NAMED WHICH IS THE REASON WHY THE PROCEDURE NAME IS SAID TO BE OVERLOADEDA SINGLE NAME IS ASSOCIATED WITH MORE THAN ONE ACTUAL STORED PROCEDURE 7HEN THE ROUTINE IS CALLED THE $"-3 LOOKS AT THE PARTICULAR DATA TYPE OF THE ARGUMENT THAT IS THE PARTICULAR CLASS OF THE OBJECT AND DETERMINES WHICH OF THE ROUTINES IS THE APPROPRIATE ONE TO CALL )NFORMIX 5NIVERSAL 3ERVER IMPLEMENTS THIS STORED PROCEDURE OVERLOADING CAPABILITY WITHOUT ANY ADDITIONAL OBJECT ORIENTED EXTENSIONS )T ALLOWS YOU TO DEFINE MANY DIFFERENT STORED PROCEDURES WITH IDENTICAL NAMES PROVIDED THAT NO TWO OF THEM HAVE THE IDENTICAL
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NUMBER OF ARGUMENTS WITH IDENTICAL DATA TYPES )N THE PREVIOUS EXAMPLE THERE WOULD BE THREE #2%!4% &5.#4)/. DEFINITIONS LIKE THIS #ALCULATES TARGET WAGES FOR A TECHNICIAN #2%!4% &5.#4)/. '%4?4'4?7!'%30%23/. 4%#(?490% 2%452.3 $%#)-!, !3 2%452. 0%23/.7!'%?2!4% %.$ &5.#4)/. #ALCULATES TARGET WAGES FOR A MANAGER #2%!4% &5.#4)/. '%4?4'4?7!'%30%23/. -'2?490% 2%452.3 $%#)-!, !3 2%452. 0%23/.3!,!29 0%23/."/.53 %.$ &5.#4)/. #ALCULATES TARGET WAGES FOR AN ENGINEER #2%!4% &5.#4)/. '%4?4'4?7!'%30%23/. %.'2?490% 2%452.3 $%#)-!, !3 2%452. 0%23/.3!,!29 %.$ &5.#4)/.
7ITH THESE DEFINITIONS IN PLACE YOU CAN INVOKE THE '%4?4'4?7!'%3 FUNCTION AND PASS IT A ROW FROM THE %.').%%23 -!.!'%23 OR 4%#(.)#)!.3 TABLE 4HE $"-3 AUTOMATICALLY FIGURES OUT WHICH OF THE FUNCTIONS TO USE AND RETURNS THE APPROPRIATE CALCULATED VALUE 3TORED PROCEDURES ARE MADE EVEN MORE VALUABLE FOR TYPED TABLES THROUGH )NFORMIX 5NIVERSAL 3ERVERS SUBSTITUTABILITY FEATURE )F YOU CALL A STORED PROCEDURE WHOSE ARGUMENT IS A ROW TYPE AND PASS IT ONE OF THE ROWS FROM A TYPED TABLE )NFORMIX WILL FIRST SEARCH FOR A STORED PROCEDURE WITH THE APPROPRIATE NAME WHOSE ARGUMENT DATA TYPE IS AN EXACT MATCH &OR EXAMPLE IF YOU CALL A '%4?,.!-% STORED PROCEDURE TO EXTRACT THE LAST NAME FROM A 4%#(?490% ROW PROBABLY FROM THE 4%#(.)#)!.3 TABLE )NFORMIX SEARCHES FOR A PROCEDURE WRITTEN TO PROCESS 4%#(?490% DATA "UT IF )NFORMIX DOESNT FIND SUCH A STORED PROCEDURE IT DOES NOT IMMEDIATELY RETURN WITH AN ERROR )NSTEAD IT SEARCHES UPWARDS IN THE TYPE HIERARCHY TRYING TO FIND A PROCEDURE WITH THE SAME NAME THAT IS DEFINED FOR A SUPERTYPE OF 4%#(?490% )F THERE IS A '%4?,.!-% STORED PROCEDURE DEFINED FOR THE %.'2?490% TYPE )NFORMIX WILL EXECUTE THAT STORED PROCEDURE TO OBTAIN THE REQUIRED INFORMATION )F NOT IT WILL CONTINUE UP THE HIERARCHY LOOKING FOR A '%4?,.!-% STORED PROCEDURE DEFINED FOR THE 0%23?490% TYPE 4HUS SUBSTITUTABILITY MEANS THAT YOU CAN DEFINE STORED PROCEDURES METHODS FOR THE HIGHEST LEVEL TYPE IN THE HIERARCHY TO WHICH THEY APPLY 4HE STORED PROCEDURES ARE AUTOMATICALLY AVAILABLE TO PROCESS ALL SUBTYPES OF THAT TYPE 4HAT IS ALL SUBCLASSES INHERIT THE METHOD FROM THE CLASS
/BJECTõ3UPPORTõINõTHEõ31,õ3TANDARD !S MENTIONED AT THE BEGINNING OF THIS CHAPTER THE LARGEST AREA OF 31, EXPANSION IN THE 31, STANDARD WAS OBJECT RELATIONAL SUPPORT .EW STATEMENTS CLAUSES AND EXPRESSIONS WERE ADDED TO THE SPECIFICATION OF THE 31, IN THESE AREAS s 5SER DEFINED DATA TYPES s #OMPOSITE ABSTRACT DATA TYPES s !RRAY VALUES
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s /VERLOADED POLYMORPHIC STORED PROCEDURES s 2OW CONSTRUCTORS AND TABLE CONSTRUCTORS SUPPORTING ABSTRACT TYPES s 2OW VALUED AND TABLE VALUED EXPRESSIONS SUPPORTING ABSTRACT TYPES 4HE 31, STANDARD OBJECT EXTENSIONS DONT EXACTLY MATCH ANY OF THE MAJOR COMMERCIAL OBJECT RELATIONAL $"-3 PRODUCTS IN THEIR SPECIFICS BUT THE UNDERLYING CONCEPTS ARE THE SAME AS THOSE ILLUSTRATED IN THE EARLIER SECTIONS FOR SPECIFIC PRODUCTS )TS LIKELY THAT THIS AREA OF 31, WILL FOLLOW THE PATTERN OF OTHERS WITH RESPECT TO THE STANDARD 3LOWLY OVER A SERIES OF MAJOR RELEASES THE MAJOR $"-3 VENDORS ARE PROVIDING SUPPORT FOR THE 31, STANDARD SYNTAX WHERE IT CAN BE ADDED IN PARALLEL TO THEIR OWN WELL ESTABLISHED PROPRIETARY SYNTAX 4HIS PROCESS IS WELL UNDER WAY FOR 31, OBJECT SUPPORT &OR THE NEXT SEVERAL YEARS THE OBJECT RELATIONAL CAPABILITIES THAT MATTER FOR REAL WORLD IMPLEMENTATIONS WILL CONTINUE TO BE A MIXTURE OF STANDARD FEATURES AUGMENTED WITH VENDOR PROPRIETARY CAPABILITIES
3UMMARY /BJECT ORIENTED DATABASES WILL LIKELY PLAY AN INCREASING ROLE IN SPECIALIZED MARKET SEGMENTS SUCH AS ENGINEERING DESIGN COMPOUND DOCUMENT PROCESSING AND '5)S 4HEY HAVE NOT BEEN WIDELY ADOPTED FOR MAINSTREAM ENTERPRISE DATA PROCESSING APPLICATIONS (OWEVER HYBRID OBJECT RELATIONAL DATABASES ARE BEING OFFERED BY SOME OF THE LEADING ENTERPRISE $"-3 VENDORS s 4HE OBJECT RELATIONAL DATABASES SIGNIFICANTLY EXTEND THE 31, AND STORED PROCEDURE LANGUAGES WITH OBJECT ORIENTED STATEMENTS STRUCTURES AND CAPABILITIES s #OMMON OBJECT RELATIONAL STRUCTURES INCLUDE ABSTRACTSTRUCTURED DATA TYPES TABLES WITHIN TABLES AND EXPLICIT SUPPORT FOR OBJECT IDENTIFIERS 4HESE CAPABILITIES STRETCH THE SIMPLE RELATIONAL MODEL A GREAT DEAL AND TEND TO ADD COMPLEXITY FOR CASUAL OR AD HOC USERS s 4HE OBJECT RELATIONAL EXTENSIONS ADDED BY THE VARIOUS $"-3 VENDORS ARE HIGHLY PROPRIETARY 4HERE ARE SIGNIFICANT CONCEPTUAL DIFFERENCES IN THE APPROACHES AS WELL AS DIFFERENCES IN IMPLEMENTATION APPROACH s /BJECT RELATIONAL CAPABILITIES ARE PARTICULARLY WELL SUITED FOR MORE COMPLEX DATA MODELS WHERE THE OVERALL DESIGN OF THE DATABASE MAY BE SIMPLER EVEN THOUGH INDIVIDUAL TABLESOBJECTS ARE MORE COMPLEX s /BJECT RELATIONAL CAPABILITIES ARE A MAJOR FOCUS OF THE 31, STANDARDS EFFORTS AND MORE RELATIONAL DATABASES ARE LIKELY TO INCORPORATE THEM IN THE FUTURE
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HE %XTENSIBLE -ARKUP ,ANGUAGE 8-, IS ONE OF THE MOST IMPORTANT NEW TECHNOLOGIES TO COME OUT OF THE EVOLUTION OF THE )NTERNET AND THE 7EB 8-, IS A STANDARD LANGUAGE FOR REPRESENTING AND EXCHANGING STRUCTURED DATA 31, IS A STANDARD LANGUAGE FOR DEFINING ACCESSING AND UPDATING THE STRUCTURED DATA STORED IN RELATIONAL DATABASES )T SEEMS OBVIOUS ON THE SURFACE THAT THERE SHOULD BE A RELATIONSHIP BETWEEN 8-, AND 31, 4HE NATURAL QUESTION IS WHAT IS THE RELATIONSHIP AND ARE THE TWO TECHNOLOGIES NATURALLY IN CONFLICT OR COMPLEMENTARY TO ONE ANOTHER 4HE ANSWER IS A LITTLE BIT OF BOTH 4HIS CHAPTER PROVIDES AN OVERVIEW OF 8-, BASICS AND THEN EXAMINES THE EVOLVING RELATIONSHIP OF 8-, AND 31, AND HOW 8-, IS BEING INTEGRATED INTO MAJOR 31, PRODUCTS
7HATõ)Sõ8-, !S IMPLIED BY ITS NAME 8-, IS A MARKUP LANGUAGE )T SHARES MANY CHARACTERISTICS WITH ITS MORE FAMILIAR COUSIN THE (YPER4EXT -ARKUP ,ANGUAGE (4-, WHICH HAS BECOME WILDLY POPULAR AS THE CORE TECHNOLOGY ENABLING THE 7EB AND WEB BROWSERS 4HE LANGUAGES HAVE COMMON ORIGINS IN DOCUMENT MARKUP A TECHNIQUE THAT IS AS OLD AS THE PRINTING AND PUBLISHING BUSINESS 7HEN A COMPLEX DOCUMENT SUCH AS THIS BOOK OR A NEWSLETTER OR A MAGAZINE IS TO BE PRINTED IT CAN BE THOUGHT OF AS HAVING TWO RELATED LOGICAL PARTS 4HE CONTENT OF THE DOCUMENT WHICH USUALLY CONSISTS OF TEXT AND GRAPHICS CONTAINS ITS MEANING 4HE STRUCTURE OF THE DOCUMENT TITLES SUBTITLES PARAGRAPHS CAPTIONS AND THE ACCOMPANYING FORMATTING FONTS INDENTATIONS PAGE LAYOUTS HELP TO ORGANIZE THE CONTENTS AND ENSURE THAT THEY ARE PRESENTED IN A MEANINGFUL WAY 3INCE THE EARLIEST DAYS OF PRINTING AND PUBLISHING EDITORS HAVE EMPLOYED MARKUP SYMBOLS AND FORMATTING MARKS EMBEDDED WITHIN THE CONTENTS OF THE DOCUMENT ITSELF TO INDICATE THE DOCUMENTS STRUCTURE AND HOW IT SHOULD BE FORMATTED FOR PRINTING 7HEN COMPUTERIZED PUBLISHING SYSTEMS ARRIVED ON THE SCENE MARKUP COMMANDS EMBEDDED WITHIN THE CONTENTS OF A DOCUMENT BECAME INSTRUCTIONS FOR THE PUBLISHING SOFTWARE PROGRAMS %ACH TYPE OF PUBLISHING SOFTWARE OR EQUIPMENT HAD ITS OWN PROPRIETARY MARKUP COMMANDS MAKING IT DIFFICULT TO MOVE FROM ONE SYSTEM TO ANOTHER 4HE 3TANDARD 'ENERALIZED -ARKUP ,ANGUAGE 3'-, WAS DEVELOPED AS A WAY TO STANDARDIZE MARKUP LANGUAGES AND EVENTUALLY WAS ADOPTED AS AN )3/ STANDARD -ORE PRECISELY 3'-, IS A METALANGUAGE FOR DEFINING SPECIFIC MARKUP LANGUAGES )TS INVENTORS RECOGNIZED THAT NO SINGLE
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MARKUP LANGUAGE COULD COVER ALL OF THE POSSIBLE MARKUP REQUIREMENTS BUT THAT ALL MARKUP LANGUAGES HAD COMMON ELEMENTS "Y STANDARDIZING THESE COMMON ELEMENTS A FAMILY OF CLOSELY RELATED MARKUP LANGUAGES COULD BE CREATED (4-, IS ONE SUCH MARKUP LANGUAGE FOCUSED ESPECIALLY ON THE USE OF HYPERTEXT TO LINK DOCUMENTS TOGETHER 8-, IS ANOTHER SUCH LANGUAGE FOCUSED ESPECIALLY ON STRONG TYPING AND TIGHT STRUCTURING OF DOCUMENT CONTENTS 4HEIR COMMON ROOTS IN 3'-, MAKE (4-, AND 8-, COUSIN LANGUAGES AND ACCOUNT FOR THEIR SIMILARITY "OTH (4-, AND 8-, ARE 7ORLD 7IDE 7EB #ONSORTIUM 7# RECOMMENDATIONS DEFINED BY SPECIFICATIONS THAT ARE DEVELOPED BY VOTED ON AND THEN PUBLISHED BY THE 7# 4HE 7# IS AN INDEPENDENT NONPROFIT CONSORTIUM WHOSE PURPOSE IS TO DEVELOP AND ADVOCATE THE USE OF STANDARDS ASSOCIATED WITH THE )NTERNET AND THE 7EB 7# RECOMMENDATIONS HAVE hOFFICIALLY ADOPTEDv STATUS THE TERMINOLOGY MEANS THAT THE 7# ADVOCATES AND RECOMMENDS THEIR USE 4HROUGH THIS PROCESS (4-, AND 8-, ARE VENDOR INDEPENDENT INDUSTRY STANDARDS (4-, WAS THE FIRST 3'-, BASED LANGUAGE TO GAIN WIDESPREAD POPULARITY 4HE CONTENTS OF MANY WEB PAGES ON NEARLY EVERY WEB SITE ON THE )NTERNET ARE EXPRESSED AS AN (4-, DOCUMENT 3PECIAL MARKUP ELEMENTS CALLED TAGS WITHIN AN (4-, DOCUMENT INDICATE GRAPHICAL ELEMENTS SUCH AS BUTTONS TO BE DISPLAYED BY A WEB BROWSER 4HE TAGS ALSO DESCRIBE THE HYPERTEXT LINKS TO OTHER DOCUMENTS THAT THE BROWSER SHOULD FOLLOW WHEN A BUTTON IS CLICKED /THER TAGS IDENTIFY GRAPHICAL ELEMENTS THAT ARE TO BE INSERTED INTO THE (4-, TEXT WHEN IT IS DISPLAYED !S THE USE OF THE 7EB EXPLODED IN THE S (4-, WAS RAPIDLY ADAPTED TO DISPLAY MUCH RICHER CONTENT ON HIGHLY FORMATTED WEB PAGES (4-, TAGS WERE QUICKLY INVENTED TO CONTROL THE FORMATTING OF WEB PAGES DIRECTING THE DISPLAY OF BOLDFACE OR ITALIC TEXT CENTERING AND INDENTS AND TEXT LOCATION WITHIN THE PAGE )N SOME CASES THESE TAGS WERE EVEN UNIQUE TO A SPECIFIC WEB BROWSER SUCH AS THE .ETSCAPE BROWSER OR -ICROSOFTS )NTERNET %XPLORER /VER TIME A GREAT DEAL OF THE MARKUP WITHIN AN (4-, PAGE BECAME FOCUSED ON FORMATTING AND PRESENTATION OF INFORMATION 4HIS HAD THE BENEFIT THAT WEB PAGE FORMATTING WAS TIGHTLY SPECIFIED SO PAGES TENDED TO BE DISPLAYED IN THE SAME WAY REGARDLESS OF THE BROWSER OR DEVICE ON WHICH IT WAS DISPLAYED )T HAD THE DISADVANTAGE THAT THE LOGICAL STRUCTURE OF WEB PAGE CONTENT TENDED TO GET LOST IN THE FORMATTING AND PRESENTATION DETAILS !N IMPORTANT ORIGINAL GOAL OF 3'-, WAS THAT A GIVEN LOGICAL ELEMENT SUCH AS A PAGE TITLE OR A WEB PAGE SUBSECTION COULD BE CONSISTENTLY IDENTIFIED ACROSS HUNDREDS OF DOCUMENTS FOR EXAMPLE ACROSS HUNDREDS OF PAGES ON A WEB SITE ! SIMPLE DIRECTIVE TO THE BROWSER SUCH AS hDISPLAY ALL SUBSECTION TITLES IN BLUE BOLDFACED POINT 4IMES .EW 2OMAN FONT v WOULD THEN ENSURE CONSISTENT PRESENTATION OF ALL PAGES )NSTEAD WEB PAGE AUTHORS TENDED TO EXPLICITLY MARK EVERY ELEMENT SUCH AS THOSE SUBSECTION TITLES WITH ITS OWN DETAILED FORMATTING INSTRUCTIONS 4HESE COULD EASILY BECOME INCONSISTENT AND WORSE A CHANGE TO THE FORMATTING INSTRUCTIONS WOULD REQUIRE HUNDREDS OF INDIVIDUAL PAGE EDITS RATHER THAN BEING SPECIFIED ONCE FOR ALL PAGES /NE OF THE MAIN DRIVING FORCES BEHIND THE DEVELOPMENT OF 8-, WAS TO RESTORE A MORE LOGICAL LEVEL RATHER THAN FORMATTING LEVEL APPROACH TO MARKUP 8-, IMPLEMENTS MUCH MORE RIGID RULES ABOUT DOCUMENT STRUCTURE THAN (4-, -OST OF ITS COMPONENTS AND CAPABILITIES ARE SQUARELY FOCUSED ON REPRESENTING LOGICAL DOCUMENT STRUCTURE #OMPANION STANDARDS SUCH AS 8-, 3CHEMA WHICH SPECIFIES TYPES OF DOCUMENTS EXTEND THIS FOCUS OF 8-, EVEN FARTHER
#HAPTERçç
31,çANDç8-,ç
8-,õ"ASICS 4O UNDERSTAND THE INTERACTIONS BETWEEN 8-, AND 31, YOU NEED A BASIC UNDERSTANDING OF 8-, AND HOW IT IS USED )F YOU ALREADY UNDERSTAND OR USE 8-, FEEL FREE TO SKIP THIS SECTION AND GO ON TO THE NEXT )F YOU ARE NOT FAMILIAR WITH 8-, THIS SECTION PROVIDES A SIMPLE INTRODUCTION BASED ON SOME EXAMPLES OF 8-, DOCUMENTS &IGURE SHOWS A TYPICAL 8-, REPRESENTATION OF A TEXT DOCUMENT A PORTION OF 0ART )) OF THIS BOOK 4HIS EXAMPLE HAS LITTLE TO DO WITH DATA PROCESSING OR 31, BUT IT SHOWS 8-, IN 1, ÊÓx£Ê Ê 8 Ê`VÕiÌÊvÀÊ «>ÀÌÊvÊ>ÊL
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ITS ORIGINAL ENVIRONMENT AND IT ILLUSTRATES KEY 8-, CONCEPTS %ACH ELEMENT OF THE 8-, DOCUMENT IN THE FIGUREEACH COMPONENT PARTIS REPRESENTED BY A CORRESPONDING 8-, ELEMENT WITH THE SIMPLE STRUCTURE SHOWN IN &IGURE 4HE ELEMENT IS IDENTIFIED BY AN OPENING TAG WHICH CONTAINS THE NAME OF THE ELEMENT TYPE ENCLOSED BETWEEN LESS THAN AND GREATER THAN SYMBOLS )N &IGURE PARAGRAPHS ARE IDENTIFIED BY AN OPENING PARA TAG AND HEADERS ARE IDENTIFIED BY AN OPENING HEADER TAG 4HE END OF EACH ELEMENT IS IDENTIFIED BY A CLOSING TAG WHICH AGAIN CONTAINS THE NAME OF THE ELEMENT TYPE PRECEDED BY A SLASH CHARACTER AGAIN ENCLOSED BETWEEN LESS THAN AND GREATER THAN SYMBOLS )N &IGURE PARAGRAPHS END WITH A PARA TAG AND HEADERS END WITH A HEADER TAG "ETWEEN THE OPENING AND CLOSING TAGS IS THE CONTENT OF THE ELEMENT -UCH OF THE CONTENT IN &IGURE IS TEXT ENCLOSED IN QUOTES 9OU CAN USE SINGLE OR DOUBLE QUOTES TO ENCLOSE THE TEXT AS LONG AS YOU USE THE SAME TYPE OF QUOTATION MARK FOR THE BEGINNING AND ENDING OF A PIECE OF TEXT &IGURE SHOWS THE HIERARCHY OF ELEMENTS TYPICAL OF MOST 8-, DOCUMENTS !T THE TOP LEVEL IS THE BOOK0ART ELEMENT )TS CONTENTS ARE NOT TEXT BUT OTHER ELEMENTSA SEQUENCE OF CHAPTER ELEMENTS %ACH CHAPTER ELEMENT CONTAINS A TITLE ELEMENT POSSIBLY SOME INTRODUCTORY PARA ELEMENTS AND THEN A SERIES OF SECTION ELEMENTS %ACH SECTION ELEMENT CONTAINS A HEADER ELEMENT AND ONE OR MORE PARA ELEMENTS POSSIBLY INTERSPERSED WITH SOME FIGURE ELEMENTS AND SOME TABLE ELEMENTS %ACH PARA ELEMENT HAS ONLY TEXT AS ITS CONTENTS )N ADDITION TO THE ELEMENT HIERARCHY &IGURE SHOWS SOME EXAMPLES OF ATTRIBUTES ANOTHER FUNDAMENTAL 8-, STRUCTURE !N ATTRIBUTE IS ASSOCIATED WITH A SPECIFIC 8-, ELEMENT AND DESCRIBES SOME CHARACTERISTIC OF THE ELEMENT %ACH ATTRIBUTE HAS AN ATTRIBUTE NAME AND A VALUE )N &IGURE THE CHAPTER ELEMENT HAS AN ATTRIBUTE CALLED CHAP.UM WHOSE VALUE IS THE CHAPTER NUMBER ASSOCIATED WITH THAT PARTICULAR CONTENT 4HE CHAPTER ELEMENT HAS ANOTHER ATTRIBUTE CALLED REV3TATUS WHOSE VALUE INDICATES WHETHER THE CHAPTER IS IN ITS ORIGINAL DRAFT BEING REWRITTEN OR IN FINAL FORM )NDIVIDUAL HEADER ELEMENTS IN &IGURE ALSO HAVE AN ATTRIBUTE CALLED HDR,EVEL THAT INDICATES WHETHER THE HEADER IS TOP LEVEL LEVEL OR LOWER LEVEL LEVEL OR 4HE FIRST LINE OF THE 8-, DOCUMENT IN &IGURE IDENTIFIES IT AS AN 8-, DOCUMENT %VERY OTHER PART OF THE DOCUMENT DESCRIBES THE ELEMENT STRUCTURE ELEMENT CONTENTS OR ATTRIBUTES OF ELEMENTS 8-, DOCUMENTS CAN BECOME CONSIDERABLY MORE COMPLEX BUT THESE FUNDAMENTAL COMPONENTS ARE THE ONES THAT ARE IMPORTANT FOR 8-,DATABASE INTERACTION .OTE THAT ELEMENT NAMES AND ATTRIBUTE NAMES ARE CASE SENSITIVE !N ELEMENT NAMED BOOK0ART AND ONE NAMED BOOKPART ARE NOT CONSIDERED THE SAME ELEMENT 4HIS IS DIFFERENT FROM THE USUAL 31, CONVENTION FOR TABLE AND COLUMN NAMES WHICH ARE USUALLY CASE INSENSITIVE /NE ADDITIONAL 8-, SHORTHAND NOTATION IS NOT SHOWN IN &IGURE FOR CLARITY BUT IS VERY USEFUL IN PRACTICE &OR ELEMENTS THAT HAVE NO CONTENT OF THEIR OWN BUT ONLY ATTRIBUTES THE END OF THE ELEMENT CAN BE INDICATED WITHIN THE SAME PAIR OF LESS THAN AND GREATER THAN SYMBOLS AS THE OPENING TAG INDICATED BY A SLASH JUST BEFORE THE GREATER THAN SYMBOL 5SING THIS CONVENTION THIS ELEMENT FROM &IGURE FIGURE FIG.UM FIGURE
#HAPTERçç
31,çANDç8-,ç
CAN BE INSTEAD REPRESENTED AS FIGURE FIG.UM
4HE 8-, SPECIFICATION DEFINES CERTAIN RULES THAT EVERY 8-, DOCUMENT SHOULD FOLLOW )T DICTATES THAT ELEMENTS WITHIN AN 8-, DOCUMENT MUST BE STRICTLY NESTED WITHIN ONE ANOTHER 4HE CLOSING TAG FOR A LOWER LEVEL ELEMENT MUST APPEAR BEFORE THE CLOSING TAG FOR A HIGHER LEVEL ELEMENT THAT CONTAINS IT 4HE STANDARD ALSO DICTATES THAT AN ATTRIBUTE MUST BE UNIQUELY NAMED WITHIN ITS ELEMENT IT IS ILLEGAL TO HAVE TWO ATTRIBUTES WITH THE SAME NAME ATTACHED TO A SINGLE ELEMENT 8-, DOCUMENTS THAT OBEY THE RULES ARE DESCRIBED AS WELL FORMED 8-, DOCUMENTS
8-,õFORõ$ATA !LTHOUGH THE ROOTS OF 8-, ARE IN DOCUMENTS AND DOCUMENT PROCESSING 8-, CAN BE QUITE USEFUL FOR REPRESENTING THE STRUCTURED DATA COMMONLY FOUND IN DATA PROCESSING APPLICATIONS AS WELL &IGURE SHOWS A TYPICAL 8-, DOCUMENT FROM THE DATA PROCESSING WORLD A VERY SIMPLIFIED PURCHASE ORDER 4HIS IS QUITE A DIFFERENT TYPE OF DOCUMENT FROM THE BOOK EXCERPT IN &IGURE BUT THE KEY COMPONENTS OF THE DOCUMENT ARE THE SAME )NSTEAD OF A CHAPTER THE TOP LEVEL ELEMENT IS A PURCHASE/RDER )TS CONTENTS LIKE THOSE OF THE CHAPTER ARE SUBELEMENTSA CUSTOMER.UMBER AN ORDER.UMBER AN ORDER$ATE AND AN ORDER)TEM 4HE ORDER)TEM IN TURN IS COMPOSED OF FURTHER SUBELEMENTS &IGURE ALSO SHOWS SOME BUSINESS TERMS ASSOCIATED WITH THE PURCHASE ORDER AS ATTRIBUTES OF THE TERMS ELEMENT 4HE SHIP ATTRIBUTE SPECIFIES HOW THE ORDER IS TO BE SHIPPED 4HE BILL ATTRIBUTE SPECIFIES THE CREDIT TERMS FOR THE ORDER
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)T SHOULD BE OBVIOUS THAT THE SIMPLE 8-, PURCHASE ORDER DOCUMENT IN &IGURE HAS A STRONG RELATIONSHIP TO THE /2$%23 TABLE IN THE SAMPLE DATABASE 9OU MAY WANT TO COMPARE IT WITH THE STRUCTURE OF THE /2$%23 TABLE SHOWN IN !PPENDIX ! &IGURE ! 4HE LOWEST LEVEL ELEMENTS IN THE DOCUMENT MOSTLY MATCH THE INDIVIDUAL COLUMNS OF THE /2$%23 TABLE EXCEPT FOR THE TERMS ELEMENT 4HE TOP LEVEL ELEMENT IN THE DOCUMENT REPRESENTS AN ENTIRE ROW OF THE TABLE 4HE TRANSFORMATION BETWEEN A GROUP OF DOCUMENTS LIKE THE ONE IN &IGURE AND A SET OF ROWS IN THE /2$%23 TABLE IS A STRAIGHTFORWARD MECHANICAL ONE WHICH CAN BE AUTOMATICALLY PERFORMED BY A SIMPLE COMPUTER PROGRAM 5NLIKE THE /2$%23 TABLE THE 8-, DOCUMENT IMPOSES ONE MIDDLE LEVEL OF HIERARCHY GROUPING TOGETHER THE INFORMATION ABOUT THE ORDERED PRODUCTTHE MANUFACTURER )$ PRODUCT )$ QUANTITY AND TOTAL AMOUNT )N A REAL WORLD PURCHASE ORDER THIS GROUP OF DATA ITEMS MIGHT BE REPEATED SEVERAL TIMES FORMING MULTIPLE LINE ITEMS ON THE ORDER 4HE 8-, DOCUMENT COULD BE EASILY EXTENDED TO SUPPORT THIS STRUCTURE BY ADDING A SECOND OR THIRD ORDER)TEM ELEMENT AFTER THE FIRST ONE 4HE SAMPLE DATABASE CANNOT BE SO EASILY EXTENDED 4O SUPPORT ORDERS WITH MULTIPLE LINE ITEMS THE /2$%23 TABLE WOULD PROBABLY BE SPLIT INTO TWO TABLES ONE HOLDING THE ORDER HEADER INFORMATION ORDER NUMBER DATE CUSTOMER )$ ETC AND THE OTHER HOLDING INDIVIDUAL ORDER LINE ITEMS
8-,õANDõ31, 4HE 3'-, ORIGINS GIVE 8-, SEVERAL UNIQUE AND USEFUL CHARACTERISTICS WHICH HAVE STRONG PARALLELS TO THE 31, LANGUAGE s $ESCRIPTIVE APPROACH 8-, APPROACHES DOCUMENT STRUCTURE BY TELLING WHAT EACH ELEMENT OF A DOCUMENT IS RATHER THAN HOW TO PROCESS IT 9OU MAY RECALL THIS IS ALSO A CHARACTERISTIC OF 31, WHICH FOCUSES ON WHICH DATA IS REQUESTED RATHER THAN HOW TO RETRIEVE IT s "UILDING BLOCKS 8-, DOCUMENTS ARE BUILT UP FROM A VERY SMALL NUMBER OF BASIC BUILDING BLOCKS INCLUDING TWO FUNDAMENTAL CONCEPTS ELEMENTS AND ATTRIBUTES 4HERE ARE SOME STRONG BUT NOT PERFECT PARALLELS BETWEEN AN 8-, ELEMENT AND A 31, TABLE AND BETWEEN AN 8-, ATTRIBUTE AND A 31, COLUMN s $OCUMENT TYPES 8-, DEFINES AND VALIDATES DOCUMENTS AS CONFORMING TO SPECIFIC DOCUMENT TYPES THAT PARALLEL REAL WORLD DOCUMENTS SUCH AS A PURCHASE ORDER DOCUMENT OR A BUSINESS REPLY DOCUMENT OR A VACATION REQUEST DOCUMENT !GAIN THERE ARE STRONG PARALLELS TO 31, WHERE TABLES REPRESENT DIFFERENT TYPES OF REAL WORLD ENTITIES !LTHOUGH THERE ARE SOME STRONG PARALLELS BETWEEN 8-, AND 31, THEY ALSO HAVE SOME VERY STRONG DIFFERENCES s $OCUMENT VS DATA ORIENTATION 4HE CORE CONCEPTS OF 8-, ARISE OUT OF TYPICAL DOCUMENT STRUCTURES 8-, IS TEXT CENTRIC AND IT IMPLEMENTS A STRONG DISTINCTION BETWEEN THE CONTENT ITSELF THE ELEMENTS OF A DOCUMENT AND CHARACTERISTICS OF THE CONTENT ATTRIBUTES 4HE CORE CONCEPTS OF 31, ARISE OUT OF TYPICAL DATA PROCESSING RECORD STRUCTURES )T IS DATA CENTRIC WITH A RANGE OF DATA TYPES IN THEIR BINARY REPRESENTATIONS AND ITS STRUCTURES TABLES AND COLUMNS FOCUS ON CONTENT DATA 4HIS MISMATCH BETWEEN THE FUNDAMENTAL 8-, AND 31, MODELS CAN CAUSE SOME CONFLICTS OR DIFFICULT CHOICES WHEN YOURE USING THEM TOGETHER
#HAPTERçç
31,çANDç8-,ç
s (IERARCHICAL VS TABULAR STRUCTURE .ATURAL 8-, STRUCTURES ARE HIERARCHICAL REFLECTING THE HIERARCHY OF ELEMENTS IN MOST TYPES OF DOCUMENTS &OR EXAMPLE A BOOK CONTAINS CHAPTERS CHAPTERS CONTAIN SECTIONS AND SECTIONS CONTAIN A HEADING PARAGRAPHS AND FIGURES 4HE STRUCTURES ARE ALSO FLEXIBLE AND VARIABLE /NE SECTION MAY CONTAIN FIVE PARAGRAPHS AND A SINGLE FIGURE THE NEXT ONE THREE PARAGRAPHS AND TWO FIGURES AND THE NEXT ONE SIX PARAGRAPHS AND NO FIGURES )N CONTRAST 31, STRUCTURES ARE TABULAR NOT HIERARCHICAL AND THEY REFLECT THE RECORDS TYPICAL OF DATA PROCESSING APPLICATIONS 31, STRUCTURES ARE ALSO QUITE RIGID %VERY ROW OF A TABLE CONTAINS EXACTLY THE SAME COLUMNS IN THE SAME ORDER %ACH COLUMN HAS THE SAME DATA TYPE IN EVERY ROW 4HERE ARE NO OPTIONAL COLUMNS EVERY COLUMN MUST APPEAR IN EVERY ROW 4HESE DIFFERENCES CAN ALSO CAUSE CONFLICTS WHEN USING 8-, AND 31, TOGETHER s /BJECTS VS OPERATIONS 4HE CORE PURPOSE OF THE 8-, IS TO REPRESENT OBJECTS )F YOU TAKE A MEANINGFUL PIECE OF 8-, CODE AND ASK h7HAT DOES THIS REPRESENT v THE ANSWER WILL BE AN OBJECT A PARAGRAPH A PURCHASE ORDER OR A CUSTOMER ADDRESS FOR EXAMPLE 4HE 31, LANGUAGE HAS A BROADER PURPOSE BUT MOST OF IT IS FOCUSED ON MANIPULATING OBJECTS )F YOU TAKE A MEANINGFUL PIECE OF 31, CODE AND ASK h7HAT DOES THIS REPRESENT v THE ANSWER WILL USUALLY BE AN OPERATION ON AN OBJECT CREATING AN OBJECT DELETING AN OBJECT FINDING ONE OR MORE OBJECTS OR UPDATING OBJECT CONTENTS 4HESE DIFFERENCES MAKE THE TWO LANGUAGES FUNDAMENTALLY COMPLEMENTARY IN THEIR PURPOSE AND USE
%LEMENTSõVSõ!TTRIBUTES 4HE RELATIONAL MODEL OFFERS ONLY ONE WAY TO REPRESENT DATA VALUES WITHIN THE DATABASEAS VALUES OF INDIVIDUAL COLUMNS WITHIN INDIVIDUAL ROWS OF A TABLE 4HE 8-, DOCUMENT MODEL OFFERS TWO WAYS TO REPRESENT DATA s %LEMENTS !N ELEMENT WITHIN AN 8-, DOCUMENT HAS CONTENTS AND THE CONTENTS CAN INCLUDE A DATA VALUE IN THE FORM OF TEXT FOR THAT ELEMENT 7HEN REPRESENTED IN THIS WAY THE DATA VALUE IS A FUNDAMENTAL PART OF THE 8-, DOCUMENT HIERARCHY THE HIERARCHY IS BUILT UP FROM ELEMENTS )NCIDENTALLY IT IS THE HIERARCHICAL TREE STRUCTURE THAT HAS LED PRACTITIONERS TO USE THE TERM FOREST FOR A COLLECTION OF RELATED 8-, DOCUMENT ELEMENTS /FTEN AN ELEMENT CONTAINING A DATA VALUE WILL BE A LEAF NODE IN THE 8-, DOCUMENT TREE THAT ELEMENT WILL BE A CHILD OF HIGHER LEVEL ELEMENTS BUT IT WILL NOT ITSELF HAVE ANY CHILDREN 4HIS WILL ALMOST ALWAYS BE TRUE OF ELEMENTS THAT REPRESENT DATA THAT COMES FROM A RELATIONAL DATABASE (OWEVER 8-, DOES SUPPORT MIXED ELEMENTS WHICH CONTAIN A COMBINATION OF TEXT CONTENT AND OTHER SUBELEMENTS
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s !TTRIBUTES !N ELEMENT WITHIN AN 8-, DOCUMENT MAY HAVE ONE OR MORE NAMED ATTRIBUTES AND EACH ATTRIBUTE HAS A TEXT VALUE 4HE ATTRIBUTES ARE ATTACHED TO AN ELEMENT WITHIN THE 8-, HIERARCHY BUT ARE NOT THE CONTENT OF THE ELEMENT 4HE NAMES OF DIFFERENT ATTRIBUTES OF AN ELEMENT MUST BE DIFFERENT SO YOU CANT HAVE TWO ATTRIBUTES WITH THE SAME NAME !LSO 8-, TREATS THE ORDER OF THE ATTRIBUTES OF AN ELEMENT AS INSIGNIFICANT THEY CAN APPEAR IN ANY ORDER 4HIS DIFFERS FROM THE 8-, TREATMENT OF ELEMENTS WHICH HAVE A DEFINITE POSITION WITHIN AN 8-, DOCUMENT AND WHERE THE DIFFERENCE BETWEEN THE FIRST SECOND AND THIRD CHILD ELEMENTS OF A HIGHER LEVEL ELEMENT IS SIGNIFICANT
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4HE EXISTENCE OF TWO DIFFERENT WAYS TO REPRESENT DATA IN 8-, MEANS THAT YOU HAVE TWO DIFFERENT LEGITIMATE WAYS TO EXPRESS THE CONTENTS OF A RELATIONAL DATABASE AS 8-, 4HESE TWO ROWS OF DATA /2$%2?.5- -&2 02/$5#4 149 !-/5.4
!#) !#)
MIGHT BE REPRESENTED BY THIS 8-, DOCUMENT WHEN ELEMENTS ARE USED TO REPRESENT COLUMN VALUES XML VERSION QUERY2ESULTS ROW ORDER.UM ORDER.UM MFR !#) MFR PRODUCT PRODUCT QTY QTY AMOUNT AMOUNT ROW ROW ORDER.UM ORDER.UM MFR !#) MFR PRODUCT PRODUCT QTY QTY AMOUNT AMOUNT ROW QUERY2ESULTS
AND WOULD BE REPRESENTED BY THIS 8-, DOCUMENT WHEN ATTRIBUTES ARE USED XML VERSION QUERY2ESULTS ROW ORDER.UM MFR !#) PRODUCT QTY AMOUNT ROW ROW ORDER.UM MFR !#) PRODUCT QTY AMOUNT ROW QUERY2ESULTS
#HAPTERçç
31,çANDç8-,ç
!S YOU MIGHT EXPECT BOTH THE ELEMENT REPRESENTATION AND THE ATTRIBUTE REPRESENTATION METHODS HAVE STRONG ADVOCATES WITH STRONGLY HELD BELIEFS !DVOCATES OF THE ELEMENT APPROACH MAKE THESE ARGUMENTS s %LEMENTS ARE MORE FUNDAMENTAL TO THE 8-, MODEL THAN ATTRIBUTES THEY ARE THE CARRIERS OF CONTENT IN ALL MARKUP LANGUAGES (4-, 8-, 3'-, ETC AND THE CONTENT OF THE DATABASE COLUMN VALUES SHOULD BE REPRESENTED AS CONTENT IN 8-, s %LEMENT ORDER MATTERS AND IN SOME CASES SO DOES THE ORDERING OF DATA IN A $"-3 FOR EXAMPLE WHEN IDENTIFYING A COLUMN BY NUMBER IN A QUERY SPECIFICATION OR WHEN USING A COLUMN NUMBER TO RETRIEVE QUERY RESULTS WITH AN !0) s %LEMENTS PROVIDE A UNIFORM WAY OF REPRESENTING COLUMN DATA REGARDLESS OF WHETHER THE COLUMN HAS A SIMPLE ATOMIC DATA TYPE INTEGER STRING OR MORE COMPLEX COMPOUND USER DEFINED DATA TYPES SUPPORTED BY THE OBJECT RELATIONAL EXTENSIONS IN THE 31, STANDARD !TTRIBUTES DONT PROVIDE THIS CAPABILITY !TTRIBUTE VALUES ARE ATOMIC !DVOCATES OF THE ATTRIBUTE APPROACH MAKE THESE ARGUMENTS s !TTRIBUTES ARE A FUNDAMENTAL MATCH FOR THE COLUMNS IN THE RELATIONAL MODEL )NDIVIDUAL ROWS REPRESENT ENTITIES SO THEY SHOULD BE MAPPED INTO ELEMENTS #OLUMN VALUES DESCRIBE ATTRIBUTES OF THE ENTITY ROW IN WHICH THEY APPEAR THEY SHOULD BE REPRESENTED AS ATTRIBUTE VALUES IN 8-, s 4HE RESTRICTION OF UNIQUE ATTRIBUTE NAMES WITHIN AN ELEMENT MATCHES THE UNIQUENESS REQUIRED OF COLUMN NAMES WITHIN A TABLE 4HE UNORDERED NATURE OF ATTRIBUTES MATCHES THE UNORDERED NATURE OF COLUMNS IN THE FUNDAMENTAL RELATIONAL MODEL 4HE PLACES WHERE COLUMN POSITION IS USED ARE SHORTCUTS FOR CONVENIENCE NOT FUNDAMENTAL TO THE UNDERLYING RELATIONS s 4HE ATTRIBUTE REPRESENTATION IS MORE COMPACT SINCE COLUMN NAMES APPEAR ONLY ONCE IN THE 8-, FORM NOT AS BOTH OPENING AND CLOSING TAGS 4HIS IS A PRACTICAL ADVANTAGE WHEN STORING OR TRANSMITTING 8-, "OTH THE ELEMENT CENTRIC AND ATTRIBUTE CENTRIC STYLES ARE FOUND IN TODAYS 8-, AND 31, PRODUCTS 4HE CHOICE DEPENDS ON THE PREFERENCES OF THE DOCUMENT AUTHOR AND THE CONVENTIONS OF THE ORGANIZATION USING 8-, WITH 31, )N ADDITION STANDARDS IMPOSED BY INDUSTRY BODIES FOR DOCUMENT EXCHANGE USING 8-, MAY DICTATE ONE STYLE OR THE OTHER
5SINGõ8-,õWITHõ$ATABASES 7ITH THE RAPIDLY GROWING POPULARITY OF 8-, DATABASE PRODUCT VENDORS HAVE MOVED QUICKLY TO OFFER 8-, SUPPORT IN THEIR PRODUCTS 4HE FORM OF 8-, SUPPORT VARIES BUT TENDS TO FALL INTO ONE OR MORE OF THESE CATEGORIES
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s 8-, OUTPUT !N 8-, DOCUMENT CAN EASILY REPRESENT THE DATA IN ONE OR MORE ROWS OF QUERY RESULTS 7ITH THIS SUPPORT THE $"-3 GENERATES AN 8-, DOCUMENT AS ITS RESPONSE TO A 31, QUERY INSTEAD OF THE USUAL ROWCOLUMN QUERY RESULTS 4HE 31, STANDARD SPECIFIES A NUMBER OF 31, FUNCTIONS THAT CAN BE USED TO TRANSFORM DATA RETRIEVED FROM RELATIONAL TABLES INTO 8-,
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s 8-, INPUT !N 8-, DOCUMENT CAN EASILY REPRESENT THE DATA TO BE INSERTED AS ONE OR MORE NEW ROWS OF A TABLE )T CAN ALSO REPRESENT DATA TO UPDATE A ROW OF A TABLE OR THE IDENTIFICATION OF A ROW TO BE DELETED 7ITH THIS SUPPORT THE $"-3 ACCEPTS AN 8-, DOCUMENT AS INPUT INSTEAD OF A 31, REQUEST s 8-, DATA EXCHANGE 8-, IS A NATURAL WAY TO EXPRESS DATA THAT IS TO BE EXCHANGED BETWEEN DIFFERENT $"-3 SYSTEMS OR AMONG $"-3 SERVERS $ATA FROM THE SOURCE DATABASE IS TRANSFORMED INTO AN 8-, DOCUMENT AND SHIPPED TO THE DESTINATION DATABASE WHERE IT IS TRANSFORMED BACK INTO A DATABASE FORMAT 4HIS SAME STYLE OF DATA EXCHANGE IS USEFUL FOR MOVING DATA BETWEEN RELATIONAL DATABASES AND NON $"-3 APPLICATIONS SUCH AS CORPORATE %NTERPRISE 2ESOURCE 0LANNING %20 ENTERPRISE APPLICATION INTEGRATION %!) ENTERPRISE INFORMATION INTEGRATION %)) AND EXTRACT TRANSFORM LOAD %4, SYSTEMS s 8-, STORAGE ! RELATIONAL DATABASE CAN EASILY ACCEPT AN 8-, DOCUMENT WHICH IS A STRING OF TEXT CHARACTERS AS A PIECE OF VARIABLE LENGTH CHARACTER STRING 6!2#(!2 OR CHARACTER LARGE OBJECT #,/" DATA !T THE MOST BASIC LEVEL OF 8-, SUPPORT AN ENTIRE 8-, DOCUMENT BECOMES THE CONTENT OF ONE COLUMN IN ONE ROW OF THE DATABASE 3LIGHTLY STRONGER 8-, SUPPORT MAY BE POSSIBLE IF THE $"-3 ALLOWS THE COLUMN TO BE DECLARED WITH AN EXPLICIT 8-, DATA TYPE !LTHOUGH THE !.3))3/ 31, STANDARD CONTAINS SPECIFICATIONS FOR AN 8-, DATA TYPE 8-, NO VENDOR IMPLEMENTATION EXACTLY SUPPORTS THE STANDARD (OWEVER /RACLE $" 5$" AND 31, 3ERVER ALL SUPPORT AN 8-, TYPE IN PROPRIETARY IMPLEMENTATIONS s 8-, DATA INTEGRATION ! MORE SOPHISTICATED LEVEL OF INTEGRATED 8-, STORAGE IS POSSIBLE IF THE $"-3 CAN PARSE AN 8-, DOCUMENT DECOMPOSE IT INTO ITS COMPONENT ELEMENTS AND STORE THE INDIVIDUAL ELEMENTS IN INDIVIDUAL COLUMNS /RDINARY 31, CAN THEN BE USED TO SEARCH THOSE COLUMNS PROVIDING SEARCH SUPPORT FOR ELEMENTS WITHIN THE 8-, DOCUMENT )N RESPONSE TO A QUERY THE $"-3 CAN RECOMPOSE THE 8-, DOCUMENT FROM ITS STORED COMPONENT ELEMENTS
8-,õ/UTPUT /NE OF THE MOST STRAIGHTFORWARD COMBINATIONS OF 8-, AND DATABASE TECHNOLOGY IS TO USE 8-, AS A FORMAT FOR 31, QUERY RESULTS 1UERY RESULTS HAVE A STRUCTURED TABULAR FORMAT THAT CAN EASILY BE TRANSLATED INTO AN 8-, REPRESENTATION #ONSIDER THIS SIMPLE QUERY FROM THE SAMPLE DATABASE 3%,%#4 /2$%2?.5- -&2 02/$5#4 149 !-/5.4 &2/- /2$%23 7(%2% #534 /2$%2?.5- -&2 02/$5#4 149 !-/5.4
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#HAPTERçç
31,çANDç8-,ç
)F THE $"-3 IS INSTRUCTED TO OUTPUT THE QUERY RESULTS IN 8-, FORMAT INSTEAD HERE IS THE OUTPUT THAT MIGHT RESULT 3%,%#4 /2$%2?.5- -&2 02/$5#4 149 !-/5.4 &2/- /2$%23 7(%2% #534 XML VERSION QUERY2ESULTS ROW ORDER?NUM ORDER?NUM MFR !#) MFR PRODUCT PRODUCT QTY QTY AMOUNT AMOUNT ROW ROW ORDER?NUM ORDER?NUM MFR !#) MFR PRODUCT PRODUCT QTY QTY AMOUNT AMOUNT ROW ROW ORDER?NUM ORDER?NUM MFR !#) MFR PRODUCT PRODUCT QTY QTY AMOUNT AMOUNT ROW ROW ORDER?NUM ORDER?NUM MFR !#) MFR PRODUCT 9 PRODUCT QTY QTY AMOUNT AMOUNT ROW QUERY2ESULTS
4HIS IS TYPICAL OF THE OUTPUT YOU COULD ACTUALLY RECEIVE FROM SOME OF THE POPULAR $"-3 PRODUCTS THAT CURRENTLY SUPPORT 8-, OUTPUT 4HE QUERY RESULTS ARE A WELL FORMED SELF CONTAINED 8-, DOCUMENT )F YOU SUBMIT THE RESULTS TO AN 8-, PARSER PARSERS ARE DESCRIBED IN THE h,ARGE /BJECTS AND 0ARSERSv SECTION LATER IN THIS CHAPTER THE PARSER WILL CORRECTLY INTERPRET THEM AS HAVING s /NE ROOT ELEMENT QUERY2ESULTS s &IVE SUBELEMENTS BENEATH EACH ROW ELEMENT AND IN THIS CASE ALL FIVE SUBELEMENTS APPEAR FOR EVERY ROW ELEMENT AND IN THE SAME ORDER
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7HILE THE PRECEDING EXAMPLE OF AN 8-, DOCUMENT GENERATED DIRECTLY FROM THE DATABASE IS IDEAL SUPPORT VARIES WIDELY FROM ONE IMPLEMENTATION TO ANOTHER &OR EXAMPLE -ICROSOFT PARTICIPATED IN THE DEVELOPMENT OF THE 31,8-, SPECIFICATION IN THE !.3))3/ 31, STANDARD THEY LATER CHOSE NOT TO IMPLEMENT IT AND INSTEAD DEVELOPED A PROPRIETARY SOLUTION )N 31, 3ERVER A &/2 8-, CLAUSE IS SUPPORTED THAT DIRECTS THE $"-3 TO OUTPUT THE RESULTS IN 8-, FORMAT 7HILE THE GENERATED RESULTS DO NOT INCLUDE WELL FORMED 8-, DOCUMENTS THEY DO INCLUDE VALID 8-, ELEMENTS THAT CAN BE EASILY INCORPORATED INTO 8-, DOCUMENTS (ERE IS THE PREVIOUS EXAMPLE RUN IN 31, 3ERVER 3%,%#4 /2$%2?.5- -&2 02/$5#4 149 !-/5.4 &2/- /2$%23 7(%2% #534 &/2 8-, !54/ /2$%23 /2$%2?.5- -&2 !#) 02/$5#4 149 !-/5.4 /2$%23 /2$%2?.5- -&2 !#) 02/$5#4 149 !-/5.4 /2$%23 /2$%2?.5- -&2 !#) 02/$5#4 9 149 !-/5.4 /2$%23 /2$%2?.5- -&2 !#) 02/$5#4 149 !-/5.4
(AVING 8-, FORMATTED QUERY OUTPUT CAN BE A SIGNIFICANT ADVANTAGE &OR FURTHER PROCESSING THE OUTPUT CAN BE SENT DIRECTLY TO PROGRAMS THAT ACCEPT 8-, DOCUMENTS AS INPUT 4HE OUTPUT CAN BE SENT ACROSS A NETWORK TO ANOTHER SYSTEM AND BECAUSE OF ITS 8-, FORMAT ITS ELEMENTS ARE SELF DESCRIBINGEVERY RECEIVING SYSTEM OR APPLICATION WILL INTERPRET THE QUERY RESULTS IN THE SAME WAYAS FOUR ROWS OF FIVE ELEMENTS EACH "ECAUSE THE OUTPUT IS IN PURE TEXT FORMAT IT WONT BE MISINTERPRETED BECAUSE OF DIFFERENCES IN BINARY DATA REPRESENTATIONS BETWEEN SENDING AND RECEIVING SYSTEMS &INALLY IF THE 8-, IS TRANSMITTED OVER AN (440 LINK USING THE 3IMPLE /BJECT !CCESS 0ROTOCOL 3/!0 STANDARDS THE 8-, FORMATTED MESSAGE CAN TYPICALLY MOVE THROUGH CORPORATE FIREWALLS AND LINK AN ORIGINATING APPLICATION IN ONE COMPANY WITH A RECEIVING APPLICATION IN A DIFFERENT COMPANY 4HE 8-, FORMATTED OUTPUT ALSO HAS SOME DISADVANTAGES /NE IS THE RAW SIZE OF THE DATA !BOUT FOUR TIMES AS MANY CHARACTERS ARE IN THE 8-, FORMATTED RESULTS AS IN THE TABULAR FORMAT )F THE 8-, FORM IS BEING STORED ON DISK IT REQUIRES FOUR TIMES THE STORAGE )F ITS BEING SENT TO ANOTHER COMPUTER SYSTEM OVER A NETWORK IT WILL TAKE FOUR TIMES AS LONG TO TRANSMIT OR IT WILL REQUIRE A NETWORK WITH FOUR TIMES THE BANDWIDTH TO PRESERVE THE SAME TRANSMISSION TIME 4HESE ARENT SERIOUS PROBLEMS FOR THE SMALL AMOUNT OF DATA IN THE EXAMPLE BUT THEY CAN BE VERY SIGNIFICANT FOR RESULTS WITH THOUSANDS OR TENS OF THOUSANDS OF ROWS MULTIPLIED BY HUNDREDS OF APPLICATIONS IN AN ENTERPRISE DATA CENTER 4HIS SIMPLE 8-, OUTPUT FORMAT ALSO LOSES SOME INFORMATION ABOUT THE DATA 4HE CURRENCY SYMBOL THAT APPEARED IN THE TABULAR DISPLAY HAS DISAPPEARED SO ITS IMPOSSIBLE TO DETERMINE FROM THE 8-, CONTENT ITSELF WHETHER THE DATA HAS A CURRENCY TYPE AND WHAT KIND OF CURRENCY IT IS 4HE 8-, 3CHEMA CAPABILITY PROVIDES A WAY TO GAIN BACK THIS INFORMATION AS DESCRIBED LATER IN THE h8-, 3CHEMAv SECTION BUT AT THE EXPENSE OF STILL MORE INCREASE IN THE SIZE OF THE QUERY RESULTS TEXT
#HAPTERçç
31,çANDç8-,ç
!LSO CONSIDER THE QUESTION OF STANDARD DATA DEFINITIONS 7HILE 8-, ITSELF IS A STANDARD TWO COMPANIES EXCHANGING PURCHASE ORDERS FORMATTED IN 8-, WILL BE UNABLE TO INTERPRET EACH OTHERS ORDERS IN THE SAME WAY UNLESS THE TAGS USED WITHIN THE 8-, DOCUMENT HAVE THE SAME NAMES AND DEFINITIONS &OR EXAMPLE IF THE FIRST COMPANY USES THE TAG PRODUCT CODE FOR THE IDENTIFIER OF THE PRODUCT BEING ORDERED AND THE SECOND COMPANY USES 3+5 STOCK KEEPING UNIT INSTEAD THEN THE PURCHASE ORDERS CANNOT BE INTERPRETED IN THE SAME WAY /NE OF THE EMERGING SOLUTIONS IS INDUSTRY 8-, DOCUMENT CODING STANDARDS SUCH AS (2 8-, DEVELOPED FOR THE HUMAN RESOURCES INDUSTRY BY THE (2 8-, #ONSORTIUM 4HIS IS LIKELY TO BE PARALLEL TO THE %NTERPRISE $ATA )NTERCHANGE %$) STANDARDS THAT WERE DEVELOPED DURING THE PAST TWO DECADES
31,8-,õ&UNCTIONS 4HE 31, STANDARD SPECIFIES A NUMBER OF FUNCTIONS THAT CAN BE USED TO FORM COLUMN DATA INTO 8-, ELEMENTS ! 31,8-, FUNCTION ALSO CALLED AN 8-, VALUE FUNCTION IS SIMPLY A FUNCTION THAT RETURNS A VALUE AS AN 8-, TYPE &OR EXAMPLE A QUERY CAN BE WRITTEN THAT SELECTS NON 8-, DATA THAT IS DATA STORED IN DATA TYPES OTHER THAN 8-, AND THAT FORMATS THE QUERY RESULTS INTO AN 8-, DOCUMENT SUITABLE FOR DISPLAY ON A WEB PAGE OR TRANSMISSION TO SOME OTHER PARTY 4ABLE SHOWS THE BASIC 31,8-, FUNCTIONS
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4HERE ARE MORE FUNCTIONS THAN THOSE LISTED IN 4ABLE AND 31,8-, FUNCTIONS CAN BE USED IN COMBINATION TO FORM EXTREMELY POWERFUL IF NOT COMPLICATED QUERIES !LSO THE FUNCTIONS AVAILABLE VARY ACROSS 31, IMPLEMENTATIONS (ERE ARE SIMPLE EXAMPLES TO CLARIFY HOW THESE FUNCTIONS CAN BE USED USING THE 8-,%,%-%.4 AND 8-,&/2%34 FUNCTIONS 3%,%#4 8-,%,%-%.4/RDER.UMBER /2$%2?.5- &2/- /2$%23 7(%2% /2$%2?.5- /RDER.UMBER /RDER.UMBER 3%,%#4 8-,&/2%34/2$%2?.5- !3 /RDER.UMBER -&2 02/$5#4 149 !-/5.4 &2/- /2$%23 7(%2% /2$%2?.5- /RDER.UMBER /RDER.UMBER -&2 !#) -&2 02/$5#4 02/$5#4 149 149 !-/5.4 !-/5.4
.OTICE THAT THE 8-, ELEMENT NAMES ARE TAKEN FROM THE COLUMN NAMES IN UPPERCASE WITH UNDERSCORES AS IS CUSTOMARY IN 31, (OWEVER USING THE COLUMN ALIAS AS ) DID FOR THE /2$%2?.5- COLUMN YOU CAN CHANGE THE COLUMN NAMES TO JUST ABOUT ANYTHING YOU WANT
8-,õ)NPUT *UST AS 8-, CAN BE USED TO REPRESENT A ROW OF QUERY RESULTS THAT IS OUTPUT FROM A DATABASE 8-, CAN EASILY BE USED TO REPRESENT A ROW OF DATA TO BE INSERTED INTO A DATABASE 4O PROCESS THE 8-, DATA THE $"-3 MUST ANALYZE THE 8-, DOCUMENT CONTAINING THE DATA TO BE INSERTED AND IDENTIFY THE INDIVIDUAL DATA ITEMS REPRESENTED AS EITHER ELEMENTS OR ATTRIBUTES 4HE $"-3 MUST THEN MATCH USUALLY USING COLUMN NAMES OR TRANSLATE USING A $"-3 SPECIFIC SCHEME THE CORRESPONDING ELEMENT OR ATTRIBUTE NAMES TO COLUMNS IN THE TARGET TABLE THAT IS TO RECEIVE THE NEW DATA #ONCEPTUALLY THIS SIMPLE ).3%24 STATEMENT ).3%24 ).4/ /&&)#%3 /&&)#% #)49 2%')/. 3!,%3 6!,5%3 g3AN &RANCISCOg g7ESTERNg
CAN BE EASILY TRANSLATED INTO AN EQUIVALENT HYBRID 31,8-, STATEMENT LIKE THIS ONE ).3%24 7)4( XML VERSION ).4/ /&&)#%3 /&&)#% #)49 2%')/. 3!,%3 6!,5%3 ROW OFFICE OFFICE CITY 3AN &RANCISCO CITY REGION 7ESTERN REGION SALES SALES ROW
5PDATES TO THE DATABASE CAN BE SIMILARLY HANDLED 4HIS SIMPLE 50$!4% STATEMENT 50$!4% /&&)#%3 3%4 4!2'%4 -'2 7(%2% /&&)#%
#HAPTERçç
31,çANDç8-,ç
CAN BE TRANSLATED INTO THIS EQUIVALENT HYBRID 31,8-, STATEMENT 50$!4% 7)4( XML VERSION /&&)#%3 7(%2% /&&)#% UPDATE?INFO VALUES TARGET TARGET MGR MGR VALUES WHERE OFFICE WHERE UPDATE?INFO
AND A $%,%4% STATEMENT REQUIRES ONLY THE SPECIFICATION OF THE 7(%2% CLAUSE USING THE SAME CONVENTIONS 7HILE SEVERAL 31, $"-3 BRANDS HAVE ADDED THE CAPABILITY TO PROCESS 8-, BASED ).3%24 50$!4% AND $%,%4% OPERATIONS USING THIS TYPE OF APPROACH THE SPECIFIC TECHNIQUES FOR REPRESENTING TABLE AND COLUMN NAMES AND DATA VALUES IN THE 8-, TEXT AND FOR MAPPING THEM TO CORRESPONDING DATABASE STRUCTURES ARE $"-3 SPECIFIC 7HILE THE !.3))3/ 31, STANDARD INCLUDES THE SPECIFICATION FOR USING ).3%24 50$!4% AND $%,%4% STATEMENTS AND COLUMNS WITH THE 8-, DATA TYPE AND FOR THE 7)4( CLAUSE THAT SUPPORTS PROVIDING 8-, OPTIONS IN 31, STATEMENTS THERE ARE NO STANDARDS YET FOR THE TYPE OF HYBRID 31,8-, SYNTAX IN THESE EXAMPLES !LTHOUGH REPRESENTING INPUT AND UPDATE VALUES AS SMALL 8-, DOCUMENTS IS CONCEPTUALLY STRAIGHTFORWARD IT REPRESENTS SOME SIGNIFICANT $"-3 PROCESSING ISSUES &OR EXAMPLE THE COLUMN LIST IN A 31, ).3%24 STATEMENT APPEARS TO BE REDUNDANT IF THE 8-, DOCUMENT CONTAINING THE DATA VALUES TO BE INSERTED ALSO CONTAINS THE COLUMN NAMES AS EITHER ELEMENT OR ATTRIBUTE NAMES 7HY NOT SIMPLY DROP THE COLUMN LIST AND LET THE 8-, DOCUMENTS SPECIFY WHICH COLUMNS TO INSERT &OR INTERACTIVE 31, THERE IS NO PROBLEM IN DOING THIS BUT THE 8-, FORMAT IS UNLIKELY TO BE USED FOR AN INTERACTIVE 31, SESSION &OR PROGRAMMATIC USE OF 31, THE PROBLEM IS THAT THE 8-, DOCUMENT AND THE DATA VALUES THAT IT CONTAINS WILL BE SUPPLIED TO THE $"-3 AT RUNTIME )F THE COLUMN NAMES OR EVEN THE TABLE NAME ARE ALSO SUPPLIED ONLY IN THE 8-, DOCUMENT THEN THE $"-3 CANNOT KNOW UNTIL RUNTIME WHICH TABLES AND COLUMNS ARE AFFECTED )N THIS SITUATION THE $"-3 MUST USE DYNAMIC 31, TO HANDLE THE PROCESSING AS DESCRIBED IN #HAPTER WITH ALL OF ITS ASSOCIATED PERFORMANCE PENALTIES 3IMILAR PROBLEMS ARISE WITH THE 7(%2% CLAUSE IN AN 50$!4% OR $%,%4% STATEMENT AND THE 3%4 CLAUSE OF THE 50$!4% STATEMENT 4O GET THE PERFORMANCE AND EFFICIENCY OF STATIC 31, THE $"-3 MUST KNOW IN ADVANCE WHEN THE PROGRAM IS COMPILED WHICH SEARCH CONDITIONS WILL BE USED AND WHICH COLUMNS WILL BE UPDATED /NE APPROACH TO THIS PROBLEM IS TO USE THE PARAMETERIZED FORM OF THESE STATEMENTS (ERE IS THE SAME 50$!4% EXAMPLE USING THIS APPROACH
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7ITH THIS STYLE THE 8-, TEXT AND THE 31, TEXT ARE ACTUALLY QUITE SEPARATE 4HE 31, TEXT IS SELF CONTAINED AND CAN BE PROCESSED AT COMPILE TIME 4HE 8-, TEXT IS SELF CONTAINED AND THE $"-3 CAN MATCH ITS PARAMETER VALUES TO THE NEEDED STATEMENT PARAMETERS AT RUNTIME 4HIS EXAMPLE FOLLOWS THE USUAL 31, STYLE OF SPECIFYING PARAMETERS BY POSITION BUT THE 8-, DOCUMENT LOSES A LOT OF ITS SELF DESCRIBING QUALITIES AS A RESULT $EPENDING ON THE $"-3 IT MAY BE POSSIBLE TO USE NAMED ELEMENTS WITHIN THE 8-, DOCUMENT AND MATCH THEM TO NAMED STATEMENT PARAMETERS AT RUNTIME
8-,õ$ATAõ%XCHANGE ! $"-3 CAN SUPPORT 8-, DATA EXCHANGE IN A SIMPLE FORM MERELY BY SUPPORTING 8-, OUTPUT FOR QUERY RESULTS AND 8-, INPUT FOR ).3%24 OPERATIONS (OWEVER THIS REQUIRES THE USER OR PROGRAMMER TO CAREFULLY CONSTRUCT THE FORMAT OF THE GENERATED QUERY RESULTS IN THE SOURCE DATABASE TO MATCH THE EXPECTED FORMAT FOR THE ).3%24 OPERATIONS IN THE DESTINATION DATABASE 8-, DATA EXCHANGE IS MORE USEFUL IF THE $"-3 PROVIDES MORE EXPLICIT BUILT IN SUPPORT 3EVERAL COMMERCIAL $"-3 PRODUCTS NOW OFFER THE ABILITY TO PERFORM A BULK EXPORT OF A TABLE OR IN A MORE SOPHISTICATED OPERATION THE RESULTS OF A QUERY INTO AN EXTERNAL FILE FORMATTED AS AN 8-, DOCUMENT !T THE DESTINATION END THESE PRODUCTS OFFER THE SAME ABILITY TO DO A BULK IMPORT FROM THIS SAME TYPE OF FILE INTO A $"-3 TABLE 7ITH THIS SCHEME THE 8-, DOCUMENT FILE BECOMES A STANDARD WAY OF REPRESENTING TABLE CONTENTS FOR THE EXCHANGE .OTE THAT ONCE 8-, BASED TABLE IMPORTEXPORT CAPABILITIES ARE OFFERED THEIR USE IS NOT RESTRICTED TO DATABASE TO DATABASE EXCHANGES 4HE SOURCE OF THE 8-, DOCUMENT IN THE DATA EXCHANGE FILE COULD WELL BE AN ENTERPRISE APPLICATION SUCH AS A 3UPPLY #HAIN -ANAGEMENT 3#- SYSTEM 4HE DESTINATION SIMILARLY COULD BE AN ENTERPRISE APPLICATION )N ADDITION MANY %!) %)) AND %4, SYSTEMS NOW SUPPORT 8-, DOCUMENT FILES 4HESE SYSTEMS PROVIDE FURTHER PROCESSING AND INTEGRATION CAPABILITIES SUCH AS ELIMINATING DUPLICATED DATA AND COMBINING DATA FROM MULTIPLE INPUT FILES
8-,õ3TORAGEõANDõ)NTEGRATION 8-, INPUT OUTPUT AND DATA EXCHANGE CAPABILITIES OFFER A VERY EFFECTIVE WAY TO INTEGRATE EXISTING RELATIONAL DATABASES WITH THE EMERGING WORLD OF 8-, 7ITH THESE APPROACHES 8-, IS USED IN THE EXTERNAL WORLD TO REPRESENT STRUCTURED DATA BUT THE DATA WITHIN THE DATABASE ITSELF RETAINS ITS ROWCOLUMN TABULAR BINARY STRUCTURE !S 8-, DOCUMENTS PROLIFERATE A NATURAL NEXT STEP IS TO CONSIDER STORING 8-, DOCUMENTS THEMSELVES WITHIN A DATABASE
3IMPLEõ8-,õ3TORAGEõWITHõ,ARGEõ/BJECTS !NY 31, BASED $"-3 THAT SUPPORTS LARGE OBJECTS AUTOMATICALLY CONTAINS BASIC SUPPORT FOR 8-, DOCUMENT STORAGE AND RETRIEVAL 4HE SECTION ON LARGE OBJECT SUPPORT IN #HAPTER DESCRIBES HOW SEVERAL COMMERCIAL DATABASES STORE AND RETRIEVE LARGE TEXT DOCUMENTS THROUGH CHARACTER LARGE OBJECT #,/" DATA TYPES -ANY COMMERCIAL PRODUCTS SUPPORT DOCUMENTS OF UP TO GIGABYTES FOR #,/" DATA WHICH IS ADEQUATE FOR THE VAST MAJORITY OF 8-, DOCUMENTS !S ALREADY MENTIONED /RACLE $" 5$" AND 31, 3ERVER ALL SUPPORT AN 8-, TYPE IN PROPRIETARY IMPLEMENTATIONS AS AN ALTERNATIVE TO USING #,/"3 TO STORE 8-, DATA 4O STORE 8-, DOCUMENTS USING #,/"S YOU WOULD TYPICALLY DEFINE A TABLE THAT CONTAINS ONE #,/" COLUMN TO CONTAIN THE DOCUMENT TEXT AND SOME AUXILIARY COLUMNS USING STANDARD DATA TYPES THAT CONTAIN ATTRIBUTES THAT IDENTIFY THE DOCUMENT &OR EXAMPLE IF A TABLE IS TO STORE PURCHASE ORDER DOCUMENTS YOU MIGHT DEFINE AUXILIARY COLUMNS TO HOLD THE CUSTOMER
#HAPTERçç
31,çANDç8-,ç
NUMBER ORDER DATE AND PURCHASE ORDER NUMBER USING ).4%'%2 6!2#(!2 OR $!4% DATA TYPES IN ADDITION TO THE #,/" COLUMN FOR THE 8-, DOCUMENT 9OU CAN SEARCH THE TABLE OF PURCHASE ORDERS BASED ON CUSTOMER NUMBERS ORDER DATES OR 0/ NUMBERS AND USE THE #,/" PROCESSING TECHNIQUES DESCRIBED IN #HAPTER TO RETRIEVE OR STORE THE 8-, DOCUMENT !N ADVANTAGE OF THIS APPROACH IS THAT IT IS RELATIVELY SIMPLE TO IMPLEMENT )T ALSO MAINTAINS A CLEAN SEPARATION BETWEEN THE 31, OPERATIONS SUCH AS QUERY PROCESSING AND THE 8-, OPERATIONS ! DISADVANTAGE IS THAT THE LEVEL OF 8-,$"-3 INTEGRATION IS FAIRLY WEAK )N THE SIMPLEST IMPLEMENTATIONS A STORED 8-, DOCUMENT IS COMPLETELY OPAQUE TO THE $"-3 THE $"-3 KNOWS NOTHING ABOUT ITS CONTENTS 9OU CANNOT EFFICIENTLY SEARCH FOR A DOCUMENT BASED ON ONE OF ITS ATTRIBUTES OR ITS ELEMENT VALUES UNLESS THAT PARTICULAR ATTRIBUTE OR ELEMENT HAS BEEN EXTRACTED FROM THE 8-, DOCUMENT AND IS ALSO REPRESENTED AS A SEPARATE COLUMN IN THE TABLE )F YOU CAN ANTICIPATE IN ADVANCE WHICH TYPES OF SEARCHES ARE LIKELY THIS IS NOT A LARGE RESTRICTION 3OME OBJECT RELATIONAL DATABASES PROVIDE A MORE ADVANCED SEARCH CAPABILITY FOR #,/"S BY EXTENDING THE 31, 7(%2% CLAUSE WITH FULL TEXT SEARCH CAPABILITY 4HESE PRODUCTS ALLOW YOU TO SEARCH #,/" COLUMNS AS TEXT USING THE TYPE OF TEXT SEARCH CAPABILITIES TYPICALLY FOUND IN WORD PROCESSORS 4HIS PROVIDES AN EXPANDED BUT TYPICALLY STILL LIMITED CAPABILITY FOR SEARCHING 8-, DOCUMENTS STORED AS #,/" COLUMNS 5SING FULL TEXT SEARCH YOU COULD FOR EXAMPLE LOCATE EVERY PURCHASE ORDER WHERE THE PHRASE h4YPE 7IDGETSv OCCURRED (OWEVER IT WILL BE DIFFICULT OR IMPOSSIBLE TO SEARCH FOR ONLY THOSE 8-, DOCUMENTS WHERE h4YPE 7IDGETSv APPLIES IN AN ORDER ITEM DESCRIPTION ELEMENT "ECAUSE THE SEARCH SOFTWARE DOESNT EXPLICITLY KNOW ABOUT THE STRUCTURE OF 8-, DOCUMENTS IT WILL PROBABLY ALSO RETURN ROWS WHERE h4YPE 7IDGETSv OCCURS IN A COMMENTS ELEMENT OR SOME OTHER ELEMENT
,ARGEõ/BJECTSõANDõ0ARSERS 7HEN EXCHANGED BETWEEN APPLICATIONS OR STORED IN A FILE OR IN A $"-3 #,/" COLUMN 8-, DOCUMENTS ARE ALWAYS IN TEXT FORM 4HIS MAKES THE CONTENTS VERY PORTABLE BUT UNWIELDY FOR COMPUTER PROGRAMS TO HANDLE !N 8-, PARSER IS A PIECE OF COMPUTER SOFTWARE THAT TRANSLATES 8-, DOCUMENTS FROM THEIR TEXT FORM TO A MORE PROGRAM FRIENDLY INTERNAL REPRESENTATION !NY 31, BASED $"-3 THAT SUPPORTS 8-, WILL HAVE AN 8-, PARSER AS PART OF ITS SOFTWARE FOR ITS OWN USE IN PROCESSING 8-, )F THE $"-3 BRAND SUPPORTS #,/"S IT CAN PROVIDE FURTHER INTEGRATION WITH 8-, BY ALLOWING AN 8-, PARSER TO OPERATE DIRECTLY ON THE #,/" COLUMN CONTENTS 4HERE ARE TWO POPULAR TYPES OF 8-, PARSERS WHICH SUPPORT TWO STYLES OF 8-, PROCESSING s $OCUMENT /BJECT -ODEL $/- $/- PARSERS TRANSFORM AN 8-, DOCUMENT INTO A HIERARCHICAL TREE STRUCTURE WITHIN A COMPUTERS MAIN MEMORY ! PROGRAM CAN THEN MAKE CALLS TO THE $/- !0) TO NAVIGATE THROUGH THE TREE MOVING UP AND DOWN OR SEQUENTIALLY THROUGH THE ELEMENT HIERARCHY 4HE $/- !0) MAKES THE ELEMENT STRUCTURE OF AN 8-, DOCUMENT EASILY ACCESSIBLE TO PROGRAMMERS AND SIMPLIFIES RANDOM ACCESS TO PORTIONS OF THE DOCUMENT
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s 3IMPLE !0) FOR 8-, 3!8 3!8 PARSERS TRANSFORM AN 8-, DOCUMENT INTO A SERIES OF CALLBACKS TO A PROGRAM WHICH INFORM THE PROGRAM OF EACH PART OF THE 8-, DOCUMENT AS IT IS ENCOUNTERED ! PROGRAM CAN BE STRUCTURED TO TAKE CERTAIN ACTIONS WHEN THE BEGINNING OF A DOCUMENT SECTION IS ENCOUNTERED OR WHEN A PARTICULAR ATTRIBUTE IS ENCOUNTERED 4HE 3!8 !0) IMPOSES A MORE SEQUENTIAL STYLE OF PROCESSING ON A PROGRAM USING IT 4HE !0)S CALLBACK STYLE MATCHES WELL WITH AN EVENT DRIVEN PROGRAM STRUCTURE
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%ITHER TYPE OF 8-, PARSER WILL VALIDATE THAT AN 8-, DOCUMENT IS WELL FORMED AND CAN ALSO VALIDATE AN 8-, DOCUMENT AGAINST A SCHEMA AS DESCRIBED IN THE h8-, 3CHEMAv SECTION LATER IN THIS CHAPTER ! $/- PARSER IS PRACTICAL WHEN THE SIZE OF THE STORED 8-, DOCUMENT IS FAIRLY SMALL IT WILL REQUIRE DOUBLE THE MEMORY SPACE OF THE TEXT 8-, DOCUMENT BECAUSE IT GENERATES A SECOND TREE STRUCTURED REPRESENTATION OF THE ENTIRE DOCUMENT &OR VERY LARGE DOCUMENTS A 3!8 PARSER MAKES IT EASY TO PROCESS DOCUMENTS IN SMALL DISCRETE PIECES (OWEVER THE FACT THAT THE ENTIRE DOCUMENT IS NOT AVAILABLE AT ONE TIME MAY REQUIRE A PROGRAM TO MAKE MULTIPLE PASSES THROUGH IT IF THE PROGRAM NEEDS TO PROCESS VARIOUS SECTIONS OF THE DOCUMENT OUT OF SEQUENTIAL ORDER
8-,õ-ARSHALING 3TORING 8-, DOCUMENTS AS LARGE OBJECTS WITHIN A DATABASE IS AN EXCELLENT SOLUTION FOR SOME TYPES OF 31,8-, INTEGRATION )F THE 8-, DOCUMENTS ARE FOR EXAMPLE TEXT ORIENTED BUSINESS DOCUMENTS OR IF THEY ARE TEXT COMPONENTS OF WEB PAGES THEN THERE IS REALLY VERY LITTLE NEED FOR THE $"-3 TO hUNDERSTANDv THE INTERNALS OF THE 8-, DOCUMENTS %ACH DOCUMENT CAN PROBABLY BE IDENTIFIED BY ONE OR MORE KEYWORDS OR ATTRIBUTES WHICH CAN EASILY BE EXTRACTED AND STORED AS CONVENTIONAL COLUMNS FOR SEARCHING )F THE 8-, DOCUMENTS TO BE PROCESSED ARE REALLY DATA PROCESSING RECORDS HOWEVER THE SIMPLE INTEGRATION PROVIDED BY LARGE OBJECTS MAY BE TOO PRIMITIVE 9OU WILL PROBABLY WANT TO PROCESS AND ACCESS INDIVIDUAL ELEMENTS AND SEARCH BASED ON THEIR CONTENTS AND ATTRIBUTES 4HE $"-3 ALREADY PROVIDES THESE CAPABILITIES FOR ITS NATIVE ROWCOLUMN DATA 7HY CANT THE $"-3 AUTOMATICALLY DECOMPOSE AN INCOMING 8-, DOCUMENT TRANSFORMING ITS ELEMENT CONTENTS AND ATTRIBUTE VALUES INTO A CORRESPONDING SET OF INTERNAL ROWCOLUMN DATA FOR PROCESSING /N THE OUTBOUND SIDE WE HAVE ALREADY SEEN HOW THIS APPROACH CAN WORK TO TRANSFORM ROWCOLUMN QUERY RESULTS INTO AN 8-, DOCUMENT 4HE SAME TECHNIQUE COULD BE USED TO RECOMPOSE AN 8-, DOCUMENT IF IT WERE ONCE AGAIN NEEDED IN ITS EXTERNAL TEXT FORM 4HE CHALLENGE OF TRANSFORMING 8-, DOCUMENTS WHICH ARE AN EXCELLENT EXTERNAL DATA REPRESENTATION TO AND FROM INTERNAL DATA REPRESENTATIONS MORE USEFUL FOR PROGRAMS IS NOT UNIQUE TO DATABASE SYSTEMS 4HE SAME PROBLEMS OCCUR FOR EXAMPLE IN *AVA PROCESSING OF 8-, WHERE IT IS VERY DESIRABLE TO TRANSFORM AN 8-, DOCUMENT TO AND FROM A SET OF *AVA CLASS INSTANCES FOR INTERNAL PROCESSING 4HE PROCESS OF DECOMPOSING AN 8-, DOCUMENT INTO ITS COMPONENT ELEMENTS AND ATTRIBUTES IN SOME INTERNAL BINARY REPRESENTATION IS CALLED UNMARSHALING IN THE 8-, LITERATURE #ONVERSELY THE PROCESS OF REASSEMBLING THESE INDIVIDUAL ELEMENT AND ATTRIBUTE REPRESENTATIONS INTO A COMPLETE TEXT 8-, DOCUMENT IS CALLED MARSHALING &OR VERY SIMPLE 8-, DOCUMENTS THE MARSHALING AND UNMARSHALING PROCESS IS STRAIGHTFORWARD AND COMMERCIAL $"-3 PRODUCTS ARE MOVING TO SUPPORT IT #ONSIDER ONCE AGAIN THE SIMPLE PURCHASE ORDER DOCUMENT IN &IGURE )TS ELEMENTS MAP DIRECTLY ONE TO ONE ONTO INDIVIDUAL COLUMNS OF THE /2$%23 TABLE )N THE SIMPLEST CASE THE NAMES OF THE ELEMENTS OR ATTRIBUTES WILL BE IDENTICAL TO THE NAMES OF THE CORRESPONDING COLUMNS 4HE $"-3 CAN RECEIVE AN INBOUND 8-, DOCUMENT LIKE THE ONE IN THE FIGURE AND AUTOMATICALLY TURN ITS ELEMENTS OR ATTRIBUTES DEPENDING ON THE STYLE USED INTO COLUMN VALUES USING THE ELEMENT NAMES OR ATTRIBUTE NAMES TO DRIVE THE PROCESS 2ECONSTITUTING THE 8-, DOCUMENT FROM A ROW OF THE TABLE IS ALSO NO PROBLEM AT ALL 4HE $"-3 MUST DO SLIGHTLY MORE WORK IF THE ELEMENT NAMES IN THE 8-, DOCUMENT DONT PRECISELY MATCH COLUMN NAMES )N THIS CASE SOME KIND OF MAPPING BETWEEN ELEMENT NAMES OR ATTRIBUTE NAMES AND COLUMN NAMES MUST BE SPECIFIED )TS RELATIVELY STRAIGHTFORWARD TO PUT SUCH A MAPPING INTO THE $"-3 SYSTEM CATALOG
#HAPTERçç
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-ANY USEFUL REAL WORLD 8-, DOCUMENTS DO NOT MAP NEATLY INTO SINGLE ROWS OF A TABLE &IGURE SHOWS A SIMPLE EXTENSION OF THE PURCHASE ORDER 8-, DOCUMENT FROM &IGURE WHICH SUPPORTS THE TYPICAL REAL WORLD REQUIREMENT THAT A PURCHASE ORDER MAY CONTAIN MULTIPLE LINE ITEMS (OW SHOULD THIS 8-, DOCUMENT BE UNMARSHALED INTO THE SAMPLE DATABASE /NE SOLUTION IS TO MAKE EACH LINE ITEM FROM THE PURCHASE ORDER INTO A SEPARATE ROW OF THE /2$%23 TABLE )GNORE FOR THE MOMENT THAT EACH ROW IN THE /2$%23 TABLE MUST CONTAIN A UNIQUE ORDER NUMBER BECAUSE THE ORDER NUMBER IS THE PRIMARY KEY 4HIS WOULD RESULT IN SOME DUPLICATION OF DATA SINCE THE SAME ORDER NUMBER ORDER DATE CUSTOMER NUMBER AND SALESPERSON NUMBER WILL APPEAR IN SEVERAL ROWS )T WOULD ALSO MAKE MARSHALING THE DATA TO RECONSTITUTE THE DOCUMENT MORE COMPLEXTHE $"-3 WOULD HAVE TO KNOW THAT ALL OF THE ROWS WITH THE SAME ORDER NUMBER SHOULD BE MARSHALED INTO ONE PURCHASE ORDER 8-, DOCUMENT WITH MULTIPLE LINE ITEMS #LEARLY THE MARSHALINGUNMARSHALING OF EVEN THIS SIMPLE DOCUMENT REQUIRES A MORE COMPLEX MAPPING 4HE MULTILINE PURCHASE ORDER MERELY SCRATCHES THE SURFACE OF MARSHALING AND UNMARSHALING 8-, DOCUMENTS 4HE MORE GENERAL SITUATION IS SHOWN IN &IGURE WHERE THE $"-3 MUST UNMARSHAL AN 8-, DOCUMENT INTO MULTIPLE ROWS OF MULTIPLE INTERRELATED TABLES 4O MARSHAL THE DOCUMENT THE $"-3 MUST EXERCISE THE RELATIONSHIPS BETWEEN THE TABLES TO FIND THE RELATED ROWS AND RECOMPOSE THE 8-, HIERARCHY 4HE UNDERLYING REASON FOR THIS COMPLEXITY IS THE MISMATCH BETWEEN 8-,S NATURAL HIERARCHICAL STRUCTURE AND THE FLAT NORMALIZED ROWCOLUMN STRUCTURE OF A RELATIONAL DATABASE
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-ARSHALING AND UNMARSHALING ARE BOTH SIMPLIFIED AND MADE MORE COMPLEX IF A $"-3 SUPPORTS OBJECT RELATIONAL EXTENSIONS SUCH AS STRUCTURED DATA TYPES 4HE TRANSLATION TO AND FROM 8-, CAN BE SIMPLER BECAUSE INDIVIDUAL COLUMNS OF A TABLE CAN NOW HAVE THEIR OWN HIERARCHICAL STRUCTURE ! HIGHER LEVEL 8-, ELEMENT SUCH AS A BILLING ADDRESS COMPOSED OF STREET CITY STATE COUNTRY AND POSTAL CODE ELEMENTS CAN BE MAPPED INTO A CORRESPONDING COLUMN WITH AN ABSTRACT !$$2%33 DATA TYPE WITH ITS OWN INTERNAL HIERARCHY (OWEVER THE TRANSLATION TO AND FROM 8-, NOW INVOLVES MORE DECISIONS IN THE DATABASE DESIGN TRADING OFF THE MARSHALINGUNMARSHALING SIMPLICITY OF STRUCTURED DATA TYPES AGAINST THE FLEXIBILITY OF A FLATTENED ROWCOLUMN APPROACH 3EVERAL COMMERCIAL PRODUCTS ARE BEGINNING TO OFFER MARSHALINGUNMARSHALING CAPABILITIES OR HAVE ANNOUNCED PLANS TO PROVIDE THIS CAPABILITY IN FUTURE RELEASES 4HE PERFORMANCE OVERHEAD OF THIS TRANSLATION CAN BE VERY SUBSTANTIAL AND IT REMAINS TO BE SEEN HOW POPULAR THESE CAPABILITIES WILL BE IN PRACTICE (OWEVER IF AN APPLICATION IS HANDLING EXTERNAL DATA IN 8-, FORM THE TRANSLATION BETWEEN 8-, AND 31, DATA MUST OCCUR AT SOME POINT AND TRANSLATION WITHIN THE $"-3 ITSELF MAY BE THE MOST EFFICIENT APPROACH
8-,õANDõ-ETADATA /NE OF THE MOST POWERFUL QUALITIES OF THE RELATIONAL MODEL IS ITS VERY RIGID SUPPORT FOR DATA TYPES AND DATA STRUCTURE IMPLEMENTED BY THE DEFINITIONS OF TABLES COLUMNS PRIMARY KEYS FOREIGN KEYS AND CONSTRAINTS )N ADDITION AS SHOWN IN #HAPTER THE SYSTEM CATALOG OF A RELATIONAL DATABASE CONTAINS METADATA OR hDATA ABOUT THE DATAv IN THE DATABASE "Y QUERYING THE SYSTEM CATALOG YOU CAN DISCOVER THE STRUCTURE OF THE DATABASE INCLUDING THE DATA TYPES OF ITS COLUMNS THE COLUMNS THAT COMPOSE ITS TABLES AND INTRATABLE RELATIONSHIPS
#HAPTERçç
31,çANDç8-,ç
)N CONTRAST 8-, DOCUMENTS BY THEMSELVES PROVIDE ONLY VERY LIMITED METADATA 4HEY IMPOSE A HIERARCHICAL ELEMENT STRUCTURE ON THEIR DATA BUT THE ONLY REAL DATA ABOUT THE STRUCTURE IS THE NAMES OF THE ELEMENTS AND ATTRIBUTES !N 8-, DOCUMENT CAN BE WELL FORMED AND STILL HAVE QUITE AN IRREGULAR STRUCTURE &OR EXAMPLE THERE IS NOTHING TO PREVENT A WELL FORMED 8-, DOCUMENT FROM HAVING A NAMED ELEMENT THAT CONTAINS TEXT DATA IN ONE INSTANCE AND SUBELEMENTS IN ANOTHER INSTANCE OR A NAMED ATTRIBUTE THAT HAS AN INTEGER VALUE FOR ONE ELEMENT AND A DATE VALUE FOR ANOTHER #LEARLY A DOCUMENT WITH THIS STRUCTURE WHILE IT MAY BE WELL FORMED DOES NOT REPRESENT DATA THAT IS EASILY TRANSFORMED TO AND FROM A RELATIONAL DATABASE 7HEN USING 8-, FOR DATA PROCESSING DOCUMENTS STRONGER SUPPORT FOR DATA TYPES AND RIGID STRUCTURE IS NEEDED 8-, STANDARDS AND PRODUCTS HAVE ADDRESSED THIS NEED IN MULTIPLE WAYS DURING THE SHORT HISTORY OF 8-, TECHNOLOGIES 4HESE INCLUDE s $OCUMENT 4YPE $EFINITION $4$ ! PART OF THE ORIGINAL 8-, SPECIFICATION $OCUMENT 4YPE $EFINITIONS PROVIDED A WAY TO SPECIFY AND RESTRICT THE STRUCTURE OF A DOCUMENT 8-, PARSERS CAN EXAMINE AN 8-, DOCUMENT IN THE CONTEXT OF A $4$ AND DETERMINE WHETHER IT IS A VALID DOCUMENT IE WHETHER IT CONFORMS TO THE $4$ RESTRICTIONS s 8-, $ATA 3UBMITTED TO THE 7# IN 8-, $ATA WAS AN EARLY ATTEMPT TO ADDRESS SOME OF THE DEFICIENCIES IN THE $4$ SCHEME )T NEVER RECEIVED 7# ENDORSEMENT BUT MANY OF ITS IDEAS HAVE CARRIED FORWARD INTO THE 8-, 3CHEMA SPECIFICATION -ICROSOFT ADAPTED ITS OWN FORM OF 8-, $ATA CALLED 8-, $ATA 2EDUCED 8$2 AND IMPLEMENTED IT AS PART OF ITS "IZ4ALK INTEGRATION SERVER AND )NTERNET %XPLORER BROWSER 4HE ENERGY AROUND THE 8-, $ATA PROPOSAL SHIFTED IN LATE AND TO THE 8-, 3CHEMA PROPOSAL s 8-, 3CHEMA ! STAND ALONE SPECIFICATION THAT BECAME A 7# RECOMMENDATION IN -AY 8-, 3CHEMA BUILT ON AND EXTENDED THE IDEAS IN 8-, $ATA 8-, 3CHEMA PROVIDES MUCH MORE RIGOROUS DATA TYPE SUPPORT AND HAS THE ADVANTAGE THAT THE SCHEMA DEFINITION THE DOCUMENT METADATA IS ITSELF EXPRESSED AS AN 8-, DOCUMENT IN MUCH THE SAME WAY THAT RELATIONAL DATABASE METADATA IS PROVIDED VIA A STANDARD RELATIONAL TABLE STRUCTURE s )NDUSTRY GROUP STANDARDS !S MENTIONED EARLIER VARIOUS INDUSTRY GROUPS HAVE BANDED TOGETHER TO DEFINE 8-, STANDARDS FOR SPECIFIC TYPES OF DOCUMENTS THAT ARE IMPORTANT FOR DATA EXCHANGE WITHIN THEIR INDUSTRY &OR EXAMPLE FINANCIAL SERVICES FIRMS ARE WORKING ON STANDARDS TO DESCRIBE FINANCIAL INSTRUMENTS STOCKS BONDS ETC AND MARKET DATA -ANUFACTURING FIRMS ARE WORKING ON STANDARDS TO DESCRIBE PURCHASE ORDER DOCUMENTS ORDER CONFIRMATIONS AND THE LIKE 4HESE STANDARDS FOR SPECIFIC INDUSTRY ORIENTED DOCUMENTS ARE USUALLY BUILT ON GENERIC STANDARDS SUCH AS $4$ AND 8-, 3CHEMA
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4HE AREA OF 8-, METADATA AND DOCUMENT TYPE STANDARDS IS EVOLVING RAPIDLY 4HE 7# PROVIDES A FREQUENTLY UPDATED WEB SITE AT HTTPWWWWORG WHICH PROVIDES ACCESS TO THE VARIOUS 8-, RELATED STANDARDS AND INFORMATION ABOUT THEIR STATUS 9OU CAN FIND INFORMATION ABOUT INDUSTRY SPECIFIC STANDARDS AT HTTPWWWXMLORG A SITE ORGANIZED AND HOSTED BY THE /RGANIZATION FOR THE !DVANCEMENT OF 3TRUCTURED )NFORMATION 3YSTEMS /!3)3 4HE SITE CONTAINS A REGISTRY OF 8-, BASED STANDARDS CLASSIFIED BY INDUSTRY
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$OCUMENTõ4YPEõ$EFINITIONSõ$4$S 4HE EARLIEST ATTEMPT TO STANDARDIZE 8-, METADATA WAS CONTAINED IN THE $OCUMENT 4YPE $EFINITION $4$ CAPABILITY OF THE ORIGINAL 8-, SPECIFICATION $4$S ARE USED TO SPECIFY THE FORM AND STRUCTURE OF A PARTICULAR TYPE OF DOCUMENT SUCH AS A PURCHASE ORDER DOCUMENT OR A TRANSFER OF FUNDS DOCUMENT &IGURE SHOWS A $4$ THAT MIGHT BE USED FOR A SIMPLE PURCHASE ORDER DOCUMENT IN &IGURE 4HIS $4$ DEMONSTRATES ONLY A FRACTION OF THE FULL CAPABILITIES OF $4$S BUT IT ILLUSTRATES THE KEY COMPONENTS OF A TYPICAL $4$ 4HE %,%-%.4 ENTRIES IN THE $4$ DEFINE THE ELEMENT HIERARCHY THAT GIVES THE DOCUMENT ITS BASIC FORM $4$S PROVIDE FOR THESE DIFFERENT TYPES OF ELEMENTS s 4EXT ONLY ELEMENT 4HE ELEMENT CONTAINS ONLY A TEXT STRING WHICH CAN REPRESENT A DATA VALUE FROM A SINGLE COLUMN OF DATABASE DATA s %LEMENT ONLY ELEMENT 4HE ELEMENTS CONTENTS ARE OTHER ELEMENTS SUBELEMENTS IT IS THE PARENT IN A LOCAL PARENTCHILD HIERARCHY OF ELEMENTS 4HIS TYPE OF ELEMENT CAN BE USED TO REPRESENT A ROW OF A TABLE WITH SUBELEMENTS REPRESENTING THE COLUMNS s -IXED CONTENT ELEMENT 4HE ELEMENT CAN CONTAIN A MIXTURE OF INTERSPERSED TEXT CONTENTS AND SUBELEMENTS 4HIS TYPE IS NOT TYPICALLY USED FOR DATABASE CONTENTS BECAUSE THIS MIX OF SUBELEMENTS AND DATA DOESNT NATURALLY APPEAR IN THE ROW COLUMN STRUCTURE OF TABLES s %MPTY CONTENT ELEMENT 4HE ELEMENT HAS NO CONTENTNEITHER SUBELEMENTS NOR TEXT CONTENTBUT IT MAY HAVE ATTRIBUTES 4HIS TYPE OF ELEMENT CAN REPRESENT A ROW OF A TABLE WHEN ITS ATTRIBUTES ARE USED TO REPRESENT INDIVIDUAL COLUMN VALUES s !NY CONTENT ELEMENT 4HE ELEMENT HAS UNRESTRICTED CONTENT 4HE CONTENT MAY BE EMPTY OR MAY CONTAIN A MIX OF SUBELEMENTS ANDOR TEXT ,IKE THE MIXED CONTENT ELEMENT THIS TYPE IS TYPICALLY NOT USEFUL FOR 8-, DOCUMENTS USED IN DATABASE PROCESSING
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31,çANDç8-,ç
)N THE PURCHASE ORDER $4$ OF &IGURE THE TOP LEVEL PURCHASE/RDER ELEMENT AND THE ORDER)TEM ELEMENT HAVE THE ELEMENT ONLY TYPE 4HEIR DECLARATIONS LIST THE SUBELEMENTS THAT THEY CONTAIN 4HE CUSTOMER.UMBER AND ORDER$ATE ELEMENTS ARE TEXT ONLY ELEMENTS INDICATED BY THE 0#$!4! DEFINITIONS 4HE TERMS ELEMENT IS EMPTY IT ONLY HAS ATTRIBUTES "OTH ATTRIBUTES HAVE VALUES THAT ARE CHARACTER DATA INDICATED BY THE #$!4! TYPE ONE IS REQUIRED AS INDICATED AND THE OTHER IS OPTIONAL .OTE THAT THIS $4$ COMBINES A DATA AS ELEMENTS STYLE FOR THE CUSTOMER INFORMATION AND A DATA AS ATTRIBUTES STYLE FOR THE ORDER TERMS ONLY FOR ILLUSTRATIVE PURPOSES )N PRACTICE YOU WOULD CHOOSE ONE OR THE OTHER STYLE OF DATA REPRESENTATION AND USE IT CONSISTENTLY TO SIMPLIFY PROCESSING $OCUMENT 4YPE $EFINITIONS ARE CRITICAL TO MAKE 8-, ACTUALLY USEFUL IN PRACTICE FOR REPRESENTING STRUCTURED DOCUMENTS FOR DATA EXCHANGE 4HEY ALLOW YOU TO DEFINE THE ESSENTIAL ELEMENTS OF A TRANSACTIONAL DOCUMENT SUCH AS A PURCHASE ORDER OR AN EMPLOYEE PERSONNEL ACTION FORM OR A REQUEST FOR QUOTE FORM 7ITH A $4$ FOR SUCH A DOCUMENT IN PLACE IT IS STRAIGHTFORWARD TO VALIDATE THAT A DOCUMENT THAT ORIGINATES SOMEWHERE ELSE WITHIN A COMPANY OR EVEN OUTSIDE A COMPANY IS A VALID DOCUMENT OF THE SPECIFIC TYPE AND CAN BE PROCESSED !NY 8-, PARSER WHETHER BASED ON THE $/- !0) OR THE 3!8 !0) IS CAPABLE OF VALIDATING AN 8-, DOCUMENT AGAINST A SUPPLIED $4$ )N ADDITION ITS POSSIBLE TO EXPLICITLY DECLARE THE $4$ TO WHICH AN 8-, DOCUMENT SHOULD CONFORM WITHIN THE DOCUMENT ITSELF $OCUMENT 4YPE $EFINITIONS HAVE SOME DRAWBACKS HOWEVER 4HEY LACK THE STRONG DATA TYPING TYPICALLY FOUND IN RELATIONAL DATABASES 4HERE IS NO WAY TO SPECIFY THAT AN ELEMENT MUST CONTAIN AN INTEGER OR A DATE FOR EXAMPLE $4$S ALSO LACK GOOD SUPPORT FOR USER DEFINED OR CORPORATE DEFINED TYPES OR SUBDOCUMENT STRUCTURES &OR EXAMPLE ITS POSSIBLE THAT THE ORDER)TEM ELEMENT IN &IGURE WILL APPEAR NOT ONLY IN A PURCHASE ORDER DOCUMENT BUT ALSO IN A CHANGE ORDER DOCUMENT AN ORDER CANCELLATION DOCUMENT A BACKORDER DOCUMENT AND AN ORDER ACKNOWLEDGEMENT DOCUMENT )T WOULD BE CONVENIENT TO DEFINE THE ORDER)TEM SUBSTRUCTURE ONCE GIVE IT A NAME AND THEN REFER TO IT IN THESE OTHER DOCUMENT DEFINITIONS BUT $4$S DONT PROVIDE THIS CAPABILITY $4$S ARE ALSO SOMEWHAT RESTRICTIVE IN THE TYPES OF CONTENT STRUCTURES THAT THEY ALLOW ALTHOUGH IN PRACTICE THEY ARE USUALLY RICH ENOUGH TO SUPPORT THE KINDS OF TRANSACTIONAL DOCUMENTS NEEDED FOR HYBRID DATABASE8-, APPLICATIONS &INALLY THE EXPRESSIONS USED BY $4$S TO DEFINE DOCUMENT STRUCTURE ARE AN EXTENDED FORM OF "ACKUS .AUR &ORM ".& !N EXAMPLE OF THIS IS THE ASTERISK THAT APPEARS AFTER THE ORDER)TEM DECLARATION WITHIN THE PURCHASE/RDER ELEMENT LIST IN &IGURE WHICH MEANS h4HIS ELEMENT MAY BE REPEATED ZERO OR MORE TIMESv 7HILE FAMILIAR TO COMPUTER SCIENCE STUDENTS WHO DEAL WITH COMPUTER LANGUAGES THIS FORMAT IS UNFAMILIAR TO PEOPLE WHO APPROACH 8-, FROM THE DOCUMENT MARKUP WORLD OF (4-, !LL OF THESE DEFICIENCIES APPEARED SOON AFTER THE ADOPTION OF 8-, AND WORK TO DEFINE A STRONGER METADATA CAPABILITY FOR 8-, DOCUMENTS BEGAN %VENTUALLY THESE EFFORTS RESULTED IN THE 8-, 3CHEMA SPECIFICATION DESCRIBED IN THE NEXT SECTION
8-,õ3CHEMA
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$ATAõ4YPESõINõ8-,õ3CHEMA &ROM A DATABASE POINT OF VIEW 8-, 3CHEMAS STRONG SUPPORT FOR DATA TYPES AND DATA STRUCTURES IS ONE OF ITS MAJOR ADVANTAGES 8-, 3CHEMA DEFINES OVER BUILT IN DATA TYPES WHICH CORRESPOND FAIRLY CLOSELY TO THE DEFINED 31, DATA TYPES 4ABLE LISTS THE MOST IMPORTANT 8-, 3CHEMA BUILT IN DATA TYPES FOR DATABASE PROCESSING
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,IKE THE 31, STANDARD 8-, 3CHEMA SUPPORTS USER DEFINED DATA TYPES THAT ARE DERIVED FROM THESE BUILT IN TYPES OR FROM OTHER USER DEFINED TYPES 9OU CAN SPECIFY A DERIVED DATA TYPE AS A RESTRICTION ON ANOTHER 8-, TYPE &OR EXAMPLE HERE IS A DEFINITION FOR A DERIVED REP.UM4YPE TYPE THAT RESTRICTS LEGAL EMPLOYEE NUMBERS TO A RANGE FROM TO SIMPLE4YPE NAME REP.UM4YPE RESTRICTION BASE INTEGER MIN)NCLUSIVE VALUE MAX%XCLUSIVE VALUE RESTRICTION SIMPLE4YPE
7ITH THIS DATA TYPE DEFINED YOU CAN DECLARE ENTITIES OR ATTRIBUTES IN A SCHEMA AS HAVING A DATA TYPE OF REP.UM4YPE AND THE RESTRICTION IS AUTOMATICALLY IMPLEMENTED 8-, 3CHEMA PROVIDES A RICH SET OF DATA TYPE CHARACTERISTICS CALLED FACETS ON WHICH YOU CAN BUILD RESTRICTIONS 4HESE INCLUDE DATA LENGTH FOR STRINGS AND BINARY DATA INCLUSIVE AND EXCLUSIVE DATA RANGES NUMBER OF DIGITS AND FRACTIONAL DIGITS FOR NUMERIC DATA AND EXPLICIT LISTS OF PERMITTED VALUES 4HERE IS EVEN A BUILT IN PATTERN MATCHING CAPABILITY WHERE DATA VALUES CAN BE RESTRICTED BY USING A REGULAR EXPRESSION SYNTAX LIKE THAT USED IN THE 0ERL SCRIPTING LANGUAGE 8-, 3CHEMA ALSO GIVES YOU THE ABILITY TO DEFINE COMPLEX DATA TYPES WHICH ARE USER DEFINED STRUCTURES &OR EXAMPLE HERE IS A DEFINITION FOR A COMPLEX CUST!DDR4YPE TYPE THAT IS COMPOSED OF FAMILIAR SUBELEMENTS COMPLEX4YPE NAME CUST!DDR4YPE SEQUENCE ELEMENT NAME STREET TYPE STRING ELEMENT NAME CITY TYPE STRING ELEMENT NAME STATE TYPE STRING ELEMENT NAME POST#ODE TYPE INTEGER SEQUENCE COMPLEX4YPE
9OU CAN ALSO CREATE A USER DEFINED DATA TYPE THAT IS A LIST OF DATA ITEMS WITH ANOTHER TYPE &OR EXAMPLE HERE IS A DEFINITION FOR A COMPLEX REP,IST4YPE TYPE WHICH IS A LIST OF SALESPERSON EMPLOYEE NUMBERS SIMPLE4YPE NAME REP,IST4YPE LIST ITEM4YPE REP.UM4YPE SIMPLE4YPE
8-, 3CHEMA ALSO ALLOWS YOU TO OVERLOAD A USER DEFINED DATA TYPE ALLOWING IT TO TAKE ON ONE OF SEVERAL DIFFERENT UNDERLYING DATA TYPES DEPENDING ON THE SPECIFIC NEED &OR EXAMPLE IN THE PRECEDING CUST!DDR4YPE DEFINITION THE POSTAL CODE PORTION OF THE ADDRESS IS DEFINED AS AN INTEGER 4HIS WORKS FOR 53 STYLE FIVE DIGIT :)0 CODES EXCEPT THAT IT DOESNT PRESERVE THE LEADING ZERO BUT NOT FOR #ANADIAN SIX DIGIT POSTAL CODES WHICH INCLUDE LETTERS
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AND DIGITS ! MORE INTERNATIONAL APPROACH IS TO DECLARE THE 53 AND #ANADIAN VERSIONS AND THEN A MORE UNIVERSAL POSTAL CODE WHICH MAY BE ANY OF THE TYPES SIMPLE4YPE NAME US:IP4YPE RESTRICTION BASE INTEGER TOTAL$IGITS VALUE RESTRICTION SIMPLE4YPE SIMPLE4YPE NAME CAN0OST4YPE RESTRICTION BASE STRING LENGTH VALUE RESTRICTION SIMPLE4YPE SIMPLE4YPE NAME INTL0OST4YPE UNION MEMBER4YPES US:IP4YPE CAN0OST4YPE SIMPLE4YPE
7ITH USER DEFINED DATA TYPE DEFINITIONS IN PLACE YOU CAN MORE EASILY DEFINE LARGER MORE COMPLEX STRUCTURES &OR EXAMPLE HERE IS PART OF THE PURCHASE ORDER DOCUMENT IN &IGURE EXPANDED TO INCLUDE A BILL TO AND SHIP TO ADDRESS AND TO PERMIT A LIST OF SALES REPRESENTATIVES COMPLEX4YPE NAME PURCHASE/RDER4YPE x OTHER ELEMENT DECLARATIONS GO HERE x ELEMENT NAME BILL!DDR TYPE CUST!DDR4YPE ELEMENT NAME SHIP!DDR TYPE CUST!DDR4YPE ELEMENT NAME REP.UMS TYPE REP,IST4YPE x OTHER ELEMENT DECLARATIONS CONTINUE x
%LEMENTSõANDõ!TTRIBUTESõINõ8-,õ3CHEMA "UILDING ON ITS SUPPORT FOR A RICH DATA TYPE STRUCTURE 8-, 3CHEMA ALSO PROVIDES A RICH VOCABULARY FOR SPECIFYING THE LEGAL STRUCTURE OF A DOCUMENT TYPE AND THE PERMITTED ELEMENTS AND ATTRIBUTES THAT COMPOSE IT 8-, 3CHEMA SUPPORTS THE SAME BASIC ELEMENT TYPES DEFINED IN THE $4$ MODEL s 3IMPLE CONTENT 4HE ELEMENT CONTAINS ONLY TEXT CONTENT ALTHOUGH AS EXPLAINED IN THE PRECEDING SECTION THE TEXT CAN BE RESTRICTED TO DATA OF A SPECIFIC TYPE LIKE A DATE OR A NUMERIC VALUE #ONTENT OF THIS TYPE IS DEFINED USING A SIMPLE#ONTENT ELEMENT s %LEMENT ONLY CONTENT 4HE ELEMENT CONTAINS ONLY SUBELEMENTS #ONTENT OF THIS TYPE IS DEFINED USING A COMPLEX4YPE ELEMENT
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s -IXED CONTENT 4HE ELEMENT CONTAINS A MIX OF SUBELEMENTS AND ITS OWN TEXT CONTENT 5NLIKE THE $4$ MIXED CONTENT MODEL 8-, 3CHEMA REQUIRES THAT THE SEQUENCE OF ELEMENTS AND TEXT CONTENT BE RIGIDLY DEFINED AND VALID DOCUMENTS MUST CONFORM TO THE DEFINED SEQUENCE #ONTENT OF THIS TYPE IS DEFINED USING A MIXED ATTRIBUTE ON A COMPLEX4YPE ELEMENT
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s %MPTY CONTENT 4HE ELEMENT CONTAINS ONLY ATTRIBUTES AND NO TEXT CONTENT OF ITS OWN 8-, 3CHEMA TREATS THIS AS A SPECIAL CASE OF ELEMENT ONLY CONTENT WITH NO DECLARED ELEMENTS s !NY CONTENT 4HE ELEMENT CONTAINS ANY MIX OF CONTENT AND SUBELEMENTS IN ANY ORDER #ONTENT OF THIS TYPE IS DEFINED USING THE 8-, 3CHEMA DATA TYPE ANY4YPE AS THE DATA TYPE OF THE ELEMENT 4HESE BASIC ELEMENT TYPES CAN APPEAR INDIVIDUALLY IN THE DECLARATIONS OF ELEMENTS WITHIN A SCHEMA 9OU CAN ALSO SPECIFY THAT AN ELEMENT MAY OCCUR MULTIPLE TIMES WITHIN A DOCUMENT AND OPTIONALLY SPECIFY A MINIMUM AND A MAXIMUM NUMBER OF OCCURRENCES 8-, 3CHEMA ALSO SUPPORTS 31, STYLE .5,, VALUES FOR ELEMENTS TO INDICATE THAT ELEMENT CONTENTS ARE UNKNOWN 4HE 8-, TERMINOLOGY IS NIL VALUES BUT THE CONCEPT IS THE SAME 4HIS CAPABILITY SIMPLIFIES MAPPING OF DATA BETWEEN 8-, DOCUMENT ELEMENTS AND DATABASE COLUMNS THAT CAN CONTAIN .5,, VALUES 8-, 3CHEMA LETS YOU DEFINE A LOGICAL GROUP OF ELEMENTS THAT ARE TYPICALLY USED TOGETHER AND LETS YOU GIVE THE ELEMENT GROUP A NAME 3UBSEQUENT ELEMENT DECLARATIONS CAN THEN INCLUDE THE ENTIRE NAMED GROUP OF ELEMENTS AS A UNIT 'ROUPED ELEMENTS ALSO PROVIDE ADDITIONAL FLEXIBILITY FOR ELEMENT STRUCTURE 4HE GROUP CAN SPECIFY A SEQUENCE OF ELEMENTS WHICH MUST ALL BE PRESENT IN THE SPECIFIED ORDER !LTERNATIVELY IT CAN SPECIFY A CHOICE OF ELEMENTS INDICATING THAT ONLY ONE OF A SET OF DEFINED ELEMENT TYPES MUST APPEAR 8-, 3CHEMA PROVIDES SIMILAR CONTROL OVER ATTRIBUTES 9OU CAN SPECIFY AN INDIVIDUAL ATTRIBUTE AS OPTIONAL OR REQUIRED 9OU CAN SPECIFY A DEFAULT ATTRIBUTE VALUE TO BE USED IF AN EXPLICIT VALUE IS NOT PROVIDED IN THE DOCUMENT INSTANCE OR A FIXED ATTRIBUTE VALUE WHICH FORCES THE ATTRIBUTE TO ALWAYS HAVE THE SPECIFIED VALUE IN AN INSTANCE DOCUMENT !TTRIBUTE GROUPS ALLOW YOU TO DEFINE AND NAME A GROUP OF ATTRIBUTES THAT ARE TYPICALLY USED TOGETHER 4HE ENTIRE GROUP OF ATTRIBUTES CAN BE DECLARED FOR AN ELEMENT IN A SCHEMA SIMPLY BY NAMING THE ATTRIBUTE GROUP &INALLY 8-, 3CHEMA PROVIDES EXTENSIVE SUPPORT FOR 8-, NAMESPACES WHICH ARE USED TO STORE AND MANAGE DIFFERENT 8-, VOCABULARIESTHAT IS DIFFERENT COLLECTIONS OF DATA TYPE DEFINITIONS AND DATA STRUCTURE DECLARATIONS THAT ARE USED FOR DIFFERENT PURPOSES )N A LARGE ORGANIZATION IT WILL BE USEFUL TO DEFINE STANDARDIZED 8-, REPRESENTATIONS FOR COMMON BASIC BUSINESS OBJECTS SUCH AS AN ADDRESS A PRODUCT NUMBER OR A CUSTOMER ID AND TO COLLECT THESE IN A COMMON REPOSITORY (IGHER LEVEL 8-, DECLARATIONS FOR DOCUMENTS SUCH AS PURCHASE ORDERS VACATION TIME REQUESTS PAYMENT AUTHORIZATION FORMS AND THE LIKE WILL ALSO BE USEFUL BUT SHOULD TYPICALLY BE COLLECTED TOGETHER IN GROUPS BASED ON SHARED USAGE 8-, NAMESPACES SUPPORT THESE CAPABILITIES BY ALLOWING YOU TO COLLECT RELATED 8-, DEFINITIONS AND DECLARATIONS STORE THEM IN A FILE AND IDENTIFY THEM BY NAME !N 8-, SCHEMA FOR A NEW TYPE OF DOCUMENT CAN THEN DRAW ITS BASIC DATA DEFINITIONS AND STRUCTURES FROM ONE OR MORE NAMESPACES BY REFERENCING THE NAMESPACES IN THE SCHEMA HEADER )N FACT THE STANDARD 8-, VOCABULARY AND MANY OF THE BUILT IN DATA TYPES ARE DEFINED IN A NAMESPACE MAINTAINED ON THE 7# ORGANIZATION WEB SITE !N )NTERNET STYLE 52, IDENTIFIES THE SOURCE FILE FOR AN 8-, NAMESPACE )F AN 8-, 3CHEMA DECLARATION INCORPORATES DEFINITIONS FROM MORE THAN ONE 8-, NAMESPACE THE POTENTIAL FOR NAME CONFLICT EXISTS 4HE SAME NAME COULD EASILY HAVE BEEN CHOSEN BY THE DEVELOPERS OF TWO DIFFERENT NAMESPACES TO REPRESENT TWO QUITE DIFFERENT 8-, STRUCTURES OR DATA TYPES 4O REMOVE THE POTENTIAL AMBIGUITY 8-, DATA TYPES AND STRUCTURE DEFINITIONS CAN BE SPECIFIED USING QUALIFIED NAMES BY USING A TECHNIQUE THAT CLOSELY PARALLELS
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THE USE OF QUALIFIED COLUMN NAMES IN 31, %ACH NAMESPACE THAT IS IDENTIFIED IN A SCHEMA HEADER CAN BE ASSIGNED A PREFIX NAME WHICH IS THEN USED TO QUALIFY REFERENCES TO ITEMS WITHIN THAT NAMESPACE &OR CLARITY THE PREFIX NAMES HAVE BEEN OMITTED FROM THE SCHEMA EXAMPLES IN THIS CHAPTER (ERE IS A MORE TYPICAL SCHEMA HEADER AND EXCERPT FROM A SCHEMA BODY THAT USES PREFIX NAMES AND QUALIFICATION TO REFERENCE THE MAIN 8-, 3CHEMA NAMESPACE MAINTAINED BY 7# AND A CORPORATE NAMESPACE SCHEMA XMLNSXSD HTTPWWWWORG8-,3CHEMA XMLNSCORP HTTPWWWMYCOMPANYCOMSCHEMASPURCHASING COMPLEX4YPE NAME PURCHASE/RDER4YPE x OTHER ELEMENT DECLARATIONS GO HERE x ELEMENT NAME ORDER$ATE TYPE XSDDATE ELEMENT NAME BILL!DDR TYPE CORPCUST!DDR4YPE ELEMENT NAME SHIP!DDR TYPE CORPCUST!DDR4YPE ELEMENT NAME REP.UMS TYPE CORPREP,IST4YPE NILLABLE TRUE x OTHER ELEMENT DECLARATIONS CONTINUE x
)N THIS EXAMPLE THE CORPORATE 8-, NAMESPACE IS IDENTIFIED BY THE PREFIX CORP AND THE MAIN 8-, 3CHEMA NAMESPACE BY THE PREFIX XSD !LL OF THE DATA TYPE REFERENCES ARE QUALIFIED BY ONE OF THESE PREFIXES AND AS A RESULT THEY ARE UNAMBIGUOUS "ECAUSE QUALIFIED REFERENCES CAN BECOME QUITE CUMBERSOME ITS ALSO POSSIBLE TO SPECIFY DEFAULT NAMESPACES THAT MINIMIZE THE NEED FOR PREFIXES 4HE COMPLETE 8-, 3CHEMA NAMING SYSTEM IS QUITE A BIT MORE SOPHISTICATED THAN THE CAPABILITIES OUTLINED HERE BUT THE CAPABILITIES ARE CLEARLY DIRECTED TOWARD SUPPORTING THE CREATION OF VERY COMPLEX DOCUMENT TYPE SPECIFICATIONS BY LARGE GROUPS OF PEOPLE !S WITH $4$S THE POWER OF 8-, 3CHEMA IS THAT IT ALLOWS YOU TO SPECIFY WELL DEFINED DOCUMENT TYPES AGAINST WHICH INDIVIDUAL DOCUMENT INSTANCES CAN BE VALIDATED !LL OF THE POPULAR 8-, PARSERS WHETHER THEY IMPLEMENT THE 3!8 !0) OR THE $/- !0) PROVIDE 8-, 3CHEMAnBASED VALIDATION 9OU CAN SPECIFY THE SCHEMA TO WHICH AN 8-, DOCUMENT CLAIMS CONFORMANCE WITHIN THE 8-, DOCUMENT ITSELF BUT YOU CAN ALSO ASK A PARSER TO VALIDATE AN ARBITRARY 8-, DOCUMENT AGAINST AN ARBITRARY SCHEMA
8-,õANDõ1UERIES
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31, PROVIDES A POWERFUL AND VERY USEFUL QUERY FACILITY FOR FINDING TRANSFORMING AND RETRIEVING STRUCTURED DATA FROM RELATIONAL DATABASES SO ITS NATURAL TO SEEK A SIMILAR QUERY CAPABILITY FOR FINDING TRANSFORMING AND RETRIEVING STRUCTURED DATA FROM 8-, DOCUMENTS 4HE EARLIEST EFFORTS TO DEFINE A QUERY AND TRANSFORMATION CAPABILITY WERE EMBODIED IN A PAIR OF SPECIFICATIONS%XTENSIBLE 3TYLESHEET ,ANGUAGE 4RANSFORMATION 83,4 AND 8-, 0ATH ,ANGUAGE 80ATH ,IKE 8-, ITSELF THESE SPECIFICATIONS HAVE THEIR ROOTS IN DOCUMENT PROCESSING 83,4 FOCUSES ON TRANSFORMING AN 8-, DOCUMENT AS SHOWN IN &IGURE ! STYLE SHEET GOVERNS THE TRANSFORMATION SELECTING WHICH ELEMENTS OF THE INPUT 8-, DOCUMENT ARE TO BE TRANSFORMED AND DICTATING HOW THEY ARE MODIFIED AND COMBINED WITH OTHER ELEMENTS TO PRODUCE THE OUTPUT 8-, DOCUMENT /NE POPULAR USE FOR 83,4 IS TO TRANSFORM A SINGLE GENERIC VERSION OF A WEB PAGE INTO VARIOUS FORMS THAT ARE APPROPRIATE FOR RENDERING ON DIFFERENT SCREEN SIZES AND DISPLAY DEVICES
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7ITHIN THE 83,4 LANGUAGE IT IS OFTEN NECESSARY TO SELECT INDIVIDUAL ELEMENTS OR GROUPS OF ELEMENTS TO BE TRANSFORMED OR TO NAVIGATE THROUGH THE ELEMENT HIERARCHY TO SPECIFY DATA TO BE COMBINED FROM PARENT AND CHILD ELEMENTS 80ATH ORIGINALLY EMERGED AS A PART OF THE 83,4 LANGUAGE FOR ELEMENT SELECTION AND NAVIGATION )T QUICKLY BECAME APPARENT THAT 80ATH WAS USEFUL FOR OTHER APPLICATIONS AS WELL AND THE SPECIFICATION WAS SPLIT OUT OF 83,4 TO STAND ON ITS OWN )N THE EARLY DAYS OF 8-, 80ATH WAS THE DE FACTO QUERY CAPABILITY FOR 8-, DOCUMENTS -ORE RECENTLY INDUSTRY ATTENTION HAS FOCUSED ON SOME OF THE DEFICIENCIES OF 80ATH AS A FULL QUERY LANGUAGE ! 7# WORKING GROUP WAS FORMED TO SPECIFY A QUERY FACILITY UNDER THE WORKING NAME 8-, 1UERY OR 81UERY !S THE SPECIFICATION PASSED THROUGH VARIOUS DRAFTS THE 83, WORKING GROUP RESPONSIBLE FOR 83,4 AND 80ATH AND THE 81UERY WORKING GROUPS JOINED FORCES )N *ANUARY BOTH 81UERY AND 80ATH WERE PUBLISHED AS STANDARDS 4HE TWO LANGUAGES ARE TIGHTLY LINKED WITH COMMON SYNTAX AND SEMANTICS WHEREVER POSSIBLE ! FULL DESCRIPTION OF 81UERY AND 80ATH IS BEYOND THE SCOPE OF THIS BOOK (OWEVER A BRIEF REVIEW OF 81UERY CONCEPTS AND A FEW EXAMPLES WILL ILLUSTRATE THE RELATIONSHIP TO 31,
81UERYõ#ONCEPTS 4HE DATA MODEL UNDERLYING THE 31, IS THE ROWCOLUMN TABLE AND THE DATA MODEL UNDERLYING 81UERY IS A TREE STRUCTURED HIERARCHY OF NODES THAT REPRESENT AN 8-, DOCUMENT 81UERY ACTUALLY USES A FINER GRAINED TREE STRUCTURE THAN THE ELEMENT HIERARCHY OF 8-, DOCUMENTS AND 8-, 3CHEMA 4HESE 81UERY NODES ARE RELEVANT FOR DATABASE STYLE QUERIES s %LEMENT NODE 4HIS TYPE OF 81UERY NODE REPRESENTS AN ELEMENT ITSELF s 4EXT NODE 4HIS TYPE OF NODE REPRESENTS ELEMENT CONTENTS )T IS A CHILD OF THE CORRESPONDING ELEMENT NODE s !TTRIBUTE NODE 4HIS TYPE OF NODE REPRESENTS AN ATTRIBUTE AND ATTRIBUTE VALUE FOR AN ELEMENT )T IS A CHILD OF THE CORRESPONDING ELEMENT NODE s $OCUMENT NODE 4HIS IS A SPECIALIZED ELEMENT NODE THAT REPRESENTS THE TOP OR ROOT LEVEL OF A DOCUMENT
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4O NAVIGATE THROUGH AN ITEM TREE AND IDENTIFY ONE OR MORE ITEMS FOR PROCESSING 81UERY USES A PATH EXPRESSION )N MANY WAYS A PATH EXPRESSION PLAYS THE SAME ROLE FOR 81UERY AS THE 31, QUERY EXPRESSION DESCRIBED IN #HAPTER PLAYS FOR 31, ! PATH EXPRESSION IDENTIFIES AN INDIVIDUAL NODE IN THE 81UERY ITEM TREE BY SPECIFYING THE SEQUENCE OF STEPS THROUGH THE TREE HIERARCHY THAT IS NEEDED TO REACH THE NODE 81UERY PATH EXPRESSIONS COME IN TWO TYPES s 2OOTED PATH EXPRESSION ! ROOTED PATH EXPRESSION STARTS AT THE TOP THE ROOT OF THE ITEM TREE AND STEPS DOWN THROUGH THE HIERARCHY TO REACH THE TARGET NODE 7ITHIN THE BOOK DOCUMENT IN &IGURE THE ROOTED PATH EXPRESSION BOOK0ARTCHAPTER SECTIONPARA NAVIGATES DOWN TO AN INDIVIDUAL PARAGRAPH WITHIN A SECTION OF A CHAPTER s 2ELATIVE PATH EXPRESSION ! RELATIVE PATH EXPRESSION STARTS THE CURRENT NODE OF THE ITEM TREE THE NODE WHERE PROCESSING IS CURRENTLY FOCUSED AND STEPS UP ANDOR DOWN THROUGH THE HIERARCHY TO REACH THE TARGET NODE 7ITHIN THE BOOK DOCUMENT IN &IGURE THE RELATIVE PATH EXPRESSION SECTIONPARA NAVIGATES DOWN TO A SPECIFIC PARAGRAPH IF THE CURRENT NODE IS A CHAPTER NODE 4HE STEPS WITHIN A PATH CAN SPECIFY MOTION DOWNWARD WITHIN THE NODE TREE TO CHILD NODES THAT REPRESENT SUBELEMENTS ELEMENT CONTENTS OR ELEMENT ATTRIBUTES 4HE STEPS CAN ALSO SPECIFY UPWARD MOTION TO THE PARENT OF A NODE 7ITH EACH STEP YOU CAN SPECIFY A NODE TEST THAT MUST BE PASSED TO CONTINUE ON THE PATH TO THE TARGET ELEMENT 4ABLE SHOWS SOME TYPICAL PATH EXPRESSIONS AND THE NAVIGATION PATH THAT THEY SPECIFY
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,IKE 31, 81UERY IS A SET ORIENTED LANGUAGE )T IS OPTIMIZED TO WORK ON AN 81UERY SEQUENCE AN ORDERED COLLECTION OF ZERO OR MORE ITEMS 4HE ITEMS THEMSELVES MIGHT BE ELEMENTS ATTRIBUTES OR DATA VALUES 81UERY OPERATIONS TEND TO TAKE SEQUENCES AS THEIR INPUT AND PRODUCE SEQUENCES AS THEIR OUTPUT ! SIMPLE ATOMIC DATA ITEM IS USUALLY TREATED AS IF IT WERE A ONE ITEM SEQUENCE 81UERY ALSO RESEMBLES 31, IN BEING A STRONGLY TYPED LANGUAGE 4HE WORKING DRAFT OF THE 81UERY SPECIFICATION IS EVOLVING TO ALIGN THE 81UERY DATA TYPES WITH THOSE SPECIFIED IN 8-, 3CHEMA WHICH WERE DESCRIBED EARLIER IN THIS CHAPTER IN THE h8-, 3CHEMAv SECTION ,IKE 31, 81UERY PROVIDES CONSTRUCTORS TO BUILD UP MORE COMPLEX DATA VALUES 81UERY DIFFERS SUBSTANTIALLY FROM 31, IN BEING AN EXPRESSION ORIENTED RATHER THAN A STATEMENT ORIENTED LANGUAGE #ASUALLY STATED EVERYTHING IN 81UERY IS AN EXPRESSION WHICH IS EVALUATED TO PRODUCE A VALUE 0ATH EXPRESSIONS ARE ONE TYPE OF 81UERY EXPRESSION AND THEY PRODUCE A SEQUENCE OF NODES AS THEIR RESULT /THER EXPRESSIONS MAY COMBINE LITERAL VALUES FUNCTION CALLS ARITHMETIC AND "OOLEAN EXPRESSIONS AND THE TYPICAL PARENTHESIZED COMBINATIONS OF THESE TO FORM ARBITRARILY COMPLEX EXPRESSIONS %XPRESSIONS CAN ALSO COMBINE SEQUENCES OF NODES USING SET OPERATIONS LIKE THE UNION OR INTERSECTION OF SETS WHICH MATCH THE CORRESPONDING 31, SET OPERATIONS .AMED VARIABLES IN 81UERY ARE DENOTED BY A LEADING DOLLAR SIGN IN THEIR NAMES &OR EXAMPLE ORDER.UM CURRENT/FFICE AND C WOULD BE VALID 81UERY VARIABLE NAMES 6ARIABLES CAN BE USED FREELY IN 81UERY EXPRESSIONS TO COMBINE THEIR VARIABLES WITH LITERALS AND OTHER VARIABLE VALUES AND NODE VALUES 6ARIABLES RECEIVE NEW VALUES THROUGH FUNCTION CALLS AND BY ASSIGNMENT IN FOR OR LET EXPRESSIONS
1UERYõ0ROCESSINGõINõ81UERY 81UERY PATH EXPRESSIONS CAN PROVIDE THE 8-, EQUIVALENT OF THE SIMPLE 31, 3%,%#4 STATEMENT WITH A 7(%2% CLAUSE !SSUME THAT A COLLECTION OF 8-, DOCUMENTS CONTAINS THE 8-, EQUIVALENT OF THE CONTENTS OF THE SAMPLE DATABASE WITH THE TOP LEVEL DOCUMENTS NAMED WITH THE NAMES OF THE TABLES IN THE SAMPLE DATABASE AND THE INDIVIDUAL ROW STRUCTURES NAMED WITH THE SINGULAR EQUIVALENTS OF THOSE NAMES EG THE /&&)#%3 DOCUMENT CONTAINS INDIVIDUAL /&&)#% ELEMENTS TO REPRESENT THE ROWS OF THE /&&)#%3 TABLE ETC (ERE ARE SOME QUERY REQUESTS AND THEIR CORRESPONDING PATH EXPRESSIONS )DENTIFY THE OFlCES MANAGED BY EMPLOYEE NUMBER OFFICESOFFICE;MGR =
&IND ALL OFlCES WITH SALES OVER TARGET OFFICESOFFICE;SALES TARGET=
&IND ALL ORDERS FOR MANUFACTURER !#) WITH AMOUNTS OVER ORDERSORDER;MFR g!#)g AND AMOUNT =
"ECAUSE THE SAMPLE DATABASE IS A SHALLOW ROWCOLUMN STRUCTURE THE 8-, HIERARCHY IS ONLY THREE LEVELS DEEP 4O ILLUSTRATE THE QUERY POSSIBILITIES IN MORE HIERARCHICAL 8-, DOCUMENTS CONSIDER ONCE AGAIN THE BOOK DOCUMENT IN &IGURE (ERE ARE SOME QUERY REQUESTS AND THEIR CORRESPONDING PATH EXPRESSIONS
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&IND ALL COMPONENTS OF CHAPTERS THAT HAVE DRAFT STATUS BOOK0ARTCHAPTER;REV3TATUS DRAFT=
'ET THE THIRD PARAGRAPH OF THE SECOND CHAPTER OF PART BOOK0ART; PART.UM =CHAPTER;=PARA;=
4HESE EXPRESSIONS DONT GIVE YOU THE SAME CONTROL OVER QUERY RESULTS AS THE 3%,%#4 LIST PROVIDES IN 31, QUERIES 4HEY ALSO DONT PROVIDE THE EQUIVALENT OF 31, CURSORS FOR ROW BY ROW PROCESSING 81UERY PROVIDES BOTH OF THESE CAPABILITIES THROUGH &OR,ET7HERE 2ETURNS EXPRESSIONS &,72 EXPRESSIONS PRONOUNCED hFLOWERv !N EXAMPLE IS THE BEST WAY TO ILLUSTRATE THE CAPABILITY /NCE AGAIN ASSUME A SET OF 8-, DOCUMENTS STRUCTURED TO RESEMBLE THE SAMPLE DATABASE AS IN THE PREVIOUS EXAMPLES 4HIS QUERY IMPLEMENTS A TWO TABLE JOIN AND GENERATES THREE SPECIFIC COLUMNS OF QUERY RESULTS ,IST THE SALESPERSONS NAME ORDER DATE AND AMOUNT OF ALL ORDERS UNDER SORTED BY AMOUNT SMALL/RDERS [ FOR O IN DOCUMENTORDERSXML ORDERS;AMOUNT = R IN DOCUMENTSALESREPSXML SALESREPS;EMPL?NUM OREP= RETURN SMALL/RDER [ RNAME OORDER?DATE OAMOUNT ] SMALL/RDER SORTBYAMOUNT ] SMALL/RDERS
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!T THE OUTER LEVEL THE CONTENTS OF THE SMALL/RDERS ELEMENT ARE SPECIFIED BY THE 81UERY EXPRESSION ENCLOSED IN THE OUTER BRACES 4HE FOR EXPRESSION USES TWO VARIABLES TO ITERATE THROUGH TWO DOCUMENTS CORRESPONDING TO THE /2$%23 AND 3!,%32%03 TABLES 4HESE TWO VARIABLES EFFECTIVELY IMPLEMENT A JOIN BETWEEN THE TWO TABLES DOCUMENTS 4HE PREDICATES SEARCH ARGUMENTS AT THE END OF EACH OF THE TWO LINES FOLLOWING THE FOR KEYWORD CORRESPOND TO THE 31, 7(%2% CLAUSE 4HE PREDICATE IN THE FIRST LINE RESTRICTS THE QUERY TO ORDERS WITH AMOUNTS UNDER 4HE PREDICATE IN THE SECOND ROW IMPLEMENTS THE JOIN USING THE O VARIABLE TO LINK ROWS IN THE 3!,%32%03 TABLE DOCUMENT WITH ROWS IN THE /2$%23 TABLE DOCUMENT 4HE RETURN PART OF THE FOR EXPRESSION SPECIFIES WHICH ELEMENTS SHOULD BE RETURNED AS THE RESULTS OF THE EXPRESSION EVALUATION )T CORRESPONDS TO THE SELECT LIST IN A 31, QUERY 4HE RETURNED VALUE WILL BE AN 8-, SEQUENCE OF SMALL/RDER ELEMENTS AND EACH ELEMENT COMES FROM ONE CORRESPONDING ELEMENT IN THE SOURCE TABLES DOCUMENTS /NCE AGAIN THE ITERATION VARIABLES ARE USED TO QUALIFY THE SPECIFIC PATH TO THE ELEMENT WHOSE CONTENTS ARE TO BE RETURNED &INALLY THE SORTBY PART OF THE EXPRESSION FUNCTIONS IN THE SAME WAY AS THE CORRESPONDING /2$%2 "9 CLAUSE OF A 31, QUERY ! FEW ADDITIONAL QUERY PROCESSING CAPABILITIES ARE NOT ILLUSTRATED IN THIS EXAMPLE 9OU CAN USE A LET EXPRESSION WITHIN THE FOR ITERATION TO CAPTURE ADDITIONAL VARIABLE VALUES WITHIN THE FOR LOOP THAT YOU MAY NEED IN PREDICATES OR OTHER EXPRESSIONS !N IFxTHENxELSE EXPRESSION SUPPORTS CONDITIONAL EXECUTION !GGREGATE FUNCTIONS SUPPORT GROUPED
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81UERY QUERIES CORRESPONDING TO THE 31, SUMMARY QUERIES DESCRIBED IN #HAPTER 7ITH THESE CAPABILITIES THE FLEXIBILITY OF 81UERY IS COMPARABLE TO THAT OF 31, QUERY EXPRESSIONS (OWEVER AS YOU CAN SEE FROM THE EXAMPLE THE STYLE OF THE QUERY EXPRESSION IS QUITE DIFFERENT REFLECTING BOTH THE EXPRESSION ORIENTATION AND THE VERY STRONG NAVIGATIONAL ORIENTATION OF 81UERY AND 8-, DOCUMENTS
8-,õ$ATABASES 7ITH THE PROLIFERATION OF 8-, USAGE AND 8-, DOCUMENTS SEVERAL VENTURE BACKED STARTUP COMPANIES HAVE BEEN FORMED TO COMMERCIALIZE NATIVE 8-, DATABASES 4YPICALLY THESE DATABASES STORE AND MODEL THEIR DATA CONTENTS AS 8-, DOCUMENTS 4HE ACTUAL DATABASE CONTENTS MAY BE STORED IN NATIVE FORM AS 8-, TEXT OR IN SOME PARSED FORM SUCH AS THAT MAINTAINED BY A $/- 8-, PARSER -OST OF THE 8-, DATABASE PRODUCTS CURRENTLY SUPPORT 80ATH AS A CORE QUERY CAPABILITY AND MANY OF THEM HAVE ADDED PROPRIETARY EXTENSIONS TO 80ATH TO MAKE IT A MORE COMPLETE QUERY LANGUAGE 4HEY TYPICALLY PLEDGE SUPPORT FOR 81UERY AS A REPLACEMENT FOR 80ATH OR AS A SECOND COMPLEMENTARY QUERY LANGUAGE AS SOON AS THE 81UERY SPECIFICATION IS FINALIZED 4HE VENDORS OF NATIVE 8-, DATABASES TEND TO MAKE THE SAME ARGUMENTS IN FAVOR OF THEIR PRODUCTS THAT THE OBJECT ORIENTED DATABASE VENDORS MADE A DECADE EARLIER 7ITH EXTERNAL DATA INCREASINGLY REPRESENTED AS 8-, THE BEST MATCH IS A DATABASE THAT CARRIES THE SAME UNDERLYING DATA MODEL 4HE CHOICE OF 8-, DOCUMENTS AS A NATIVE FORMAT REDUCES THE OVERHEAD OF 8-, MARSHALING AND UNMARSHALING BUT PROVIDES THE SAME LEVEL OF INDIVIDUAL ELEMENT AND ATTRIBUTE ACCESS AND NAVIGATION &INALLY THEY SAY THAT WITH A GROWING BODY OF USERS TRAINED IN (4-, AND 8-, AN 8-, DATABASE CAN BE MORE ACCESSIBLE TO MORE PEOPLE THAN 31, BASED RELATIONAL DATABASES )T IS STILL TOO SOON TO JUDGE THE EVENTUAL MARKET SUCCESS AND IMPACT OF THE NATIVE 8-, DATABASES )T SEEMS LIKELY THAT A NATIVE 8-, DATABASE MAY BE A GOOD MATCH FOR DATA MANAGEMENT NEEDS WITHIN AN 8-, BASED WEB SITE FOR STORING ACCESSING AND TRANSFORMING 8-, DOCUMENTS (OWEVER THE PREVIOUS HISTORY OF PURE OBJECT ORIENTED DATABASES SUGGESTS THAT RELATIONAL DATABASE VENDORS ARE CAPABLE OF EXTENDING THEIR CORE PRODUCTS TO INCORPORATE THE MOST IMPORTANT FEATURES OF NEW DATA MODELS AT A PACE THAT IS FAST ENOUGH TO RETAIN THEIR DOMINANT MARKET SHARES )T SEEMS VERY LIKELY THAT RELATIONAL DATABASES WILL REMAIN THE DOMINANT NATIVE DATABASE TYPE FOR DATA PROCESSING APPLICATIONS "UT WITHIN THESE PRODUCTS 8-, INTEGRATION WILL GROW TIGHTER OVER TIME AND RELATIONAL PRODUCTS WILL OFFER MORE AND MORE 8-, ORIENTED FEATURES
#HAPTERçç
31,çANDç8-,ç
3UMMARY 4HIS CHAPTER DESCRIBED THE RELATIONSHIPS BETWEEN 8-, AND 31, AND BETWEEN 8-, DOCUMENTS AND RELATIONAL DATABASES s 8-, HAS ITS ORIGINS IN PRINTING AND PUBLISHING IT WAS ORIGINALLY DESIGNED AS A WAY TO INDICATE AND SPECIFY DOCUMENT CONTENTS s 8-,S DOCUMENT ORIENTATION PRODUCES A NATURAL HIERARCHICAL VIEW OF DATA 4HE MISMATCH BETWEEN 8-, HIERARCHIES AND 31, ROWCOLUMN TABLES IS ONE OF THE BIGGEST CHALLENGES WHEN INTEGRATING THE TWO TECHNOLOGIES s 8-, DOCUMENTS COMPRISE A HIERARCHY OF ELEMENTS %LEMENTS CAN CARRY CONTENTS THEY CAN HAVE NAMED ATTRIBUTES AND THEY CAN HAVE OTHER ELEMENTS AS CHILDREN s 8-, INTEGRATION WITH RELATIONAL DATABASES CAN TAKE SEVERAL FORMS INCLUDING 8-, QUERY OUTPUT 8-, INPUT 8-, DATA EXCHANGE AND THE STORAGE AND RETRIEVAL OF 8-, DATA WITHIN THE DATABASE ITSELF s 8-, 3CHEMA AND AN OLDER STANDARD 8-, $4$S DEFINE RIGID STRUCTURES FOR SPECIFIC TYPES OF DOCUMENTS 4HEY ARE USEFUL TO RESTRICT DOCUMENT CONTENTS TO A STANDARD FORM ACCEPTABLE FOR DATA PROCESSING APPLICATIONS s 81UERY IS AN EMERGING QUERY LANGUAGE FOR 8-, DOCUMENTS )T HAS SOME PARALLELS TO 31, BUT ITS FOCUS ON EXPRESSIONS AND PATH NAVIGATION MAKE IT QUITE DIFFERENT IN STYLE FROM 31, s .ATIVE 8-, DATABASES HAVE BEEN INTRODUCED AND ARE MOVING TO ADOPT 81UERY AS A NATIVE QUERY LANGUAGE 4HEY POSE A CHALLENGE TO THE RELATIONAL MODEL BUT MAJOR $"-3 VENDORS ARE MOVING QUICKLY TO PROVIDE 8-, EXTENSIONS TO THEIR RELATIONAL PRODUCTS
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#(!04%2
3PECIALTYç$ATABASES
4
ODAYS DATABASE MARKET IS DOMINATED BY THE MAJOR ENTERPRISE DATABASE MANAGEMENT SYSTEMS 4HE FLAGSHIP PRODUCTS FROM /RACLE )"- -ICROSOFT 3YBASE AND OTHERS ARE LARGE COMPLEX PIECES OF SOFTWARE THAT HAVE EVOLVED TO A hONE SIZE FITS ALLv APPROACH ,ARGE COMPANIES CAN USE THE LATEST VERSION OF THE /RACLE DATABASE OR OF )"-S $" TO PROCESS ONLINE TRANSACTIONS FROM THEIR WEB SITE TO STORE DATA WAREHOUSES AND ANALYZE BUSINESS DATA TO MANAGE DATA FOR THEIR ACCOUNTING AND FINANCE SYSTEMS AND TO SUPPORT DEPARTMENTAL DATABASE USE 4HESE APPLICATIONS REPRESENT DIFFERENT WORKLOADS BUT THE ENTERPRISE DATABASE PRODUCTS ARE BROAD ENOUGH AND FLEXIBLE ENOUGH TO ADDRESS THEM ALL 3OME DATABASE APPLICATIONS HOWEVER HAVE REQUIREMENTS THAT ARE SO SPECIALIZED OR SO STRINGENT THAT THE MAINSTREAM ENTERPRISE DATABASES CANNOT STRETCH FAR ENOUGH TO ADDRESS THEM EFFECTIVELY 4HESE APPLICATIONS REMAIN THE DOMAIN OF SPECIALTY OR NICHE DATABASE PRODUCTS )TS A TESTIMONY TO THE POWER OF 31, THAT EVEN THESE SPECIALIZED NICHE DATABASE PRODUCTS ARE 31, BASED TODAY 4HIS CHAPTER EXAMINES FOUR OF THESE DATABASE NICHES THE SPECIALTY DATABASES THAT ADDRESS THEM AND THE 31, FEATURES THAT HAVE BEEN ADDED TO MEET THEIR REQUIREMENTS
6ERYõ,OWõ,ATENCYõANDõ)N -EMORYõ$ATABASES 3OME IMPORTANT DATABASE APPLICATIONS IN THE TELECOM AND FINANCIAL SERVICES MARKETS REQUIRE VERY FAST RESPONSE FROM THE DATABASE SYSTEM OFTEN MEASURED IN MILLIONTHS OF A SECOND &OR EXAMPLE EVERY MOBILE NETWORK HAS AN UNDERLYING DATABASE THAT TRACKS THE CURRENT LOCATION OF EVERY MOBILE PHONE AND OF THE PARTICULAR CELL TOWER THAT IS SERVICING THE PHONE 4HIS DATABASE MUST ALWAYS BE UP TO DATE SO THE NETWORK CAN DETERMINE AT ALL TIMES WHERE TO ROUTE AN INCOMING CALL FOR ANY MOBILE PHONE THAT IS CONNECTED )F A CALL IS ALREADY UNDER WAY AND THE MOBILE USER IS ON THE MOVE FOR EXAMPLE IF HE OR SHE IS RIDING IN A CAR THE DATABASE DEMANDS ARE EVEN HIGHER BECAUSE THE CALL IN PROCESS MUST BE hHANDED OFFv FROM ONE CELL LOCATION TO ANOTHER &OR A NETWORK OF TENS OF MILLIONS OF MOBILE PHONES EACH INDIVIDUAL DATABASE ACCESS MUST BE VERY SHORT OR THE DATABASE WILL BECOME A BOTTLENECK TO CALL PROCESSING
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4HE DATABASE DEMANDS ARE EVEN HIGHER IF THE MOBILE USER IS ON A PREPAID BILLING PLAN 7HEN SUCH A CUSTOMER TRIES TO USE A MOBILE SERVICETO MAKE A CALL SEND A TEXT MESSAGE OR ACCESS THE )NTERNETTHE NETWORK MUST QUICKLY DETERMINE WHETHER TO ALLOW THE ACTION "EHIND THE SCENES SOFTWARE IN THE NETWORK MUST DETERMINE WHICH CUSTOMER IS TRYING TO ACT FIND THAT CUSTOMERS BILLING PLAN FIGURE OUT THE BILLING CHARGE ASSOCIATED WITH THE ACTION WHICH MAY VARY DEPENDING ON THE TIME OF DAY OR THE LOCATION OR ON WHETHER THE CUSTOMER IS BEING CALLED OR TEXTED OR ON MANY OTHER FACTORS LOOK UP THE CUSTOMERS CURRENT ACCOUNT BALANCE DETERMINE WHETHER THE CUSTOMER HAS SUFFICIENT FUNDS AND DEDUCT THE INITIAL CHARGES FROM THE CUSTOMERS BALANCE 4HIS SEQUENCE CAN REQUIRE DOZENS OF ACCESSES AND UPDATES TO THE OPERATORS BILLING DATABASEALL WHILE THE CUSTOMER AND THE NETWORK ARE WAITING FOR A CALL OR SOME OTHER ACTIVITY TO START )N MANY AREAS OF THE WORLD A MOBILE NETWORK WILL HAVE TENS OF MILLIONS OF SUBSCRIBERS THE VAST MAJORITY OF WHOM ARE PREPAID CUSTOMERS SO AGAIN DATABASE ACCESS MUST BE VERY SWIFT &INANCIAL TRADING APPLICATIONS POSE A SIMILAR DATABASE LATENCY CHALLENGE &EEDS OF MARKET DATA SUCH AS OFFERS TO BUY AND SELL STOCKS CAN EXCEED MESSAGES PER SECOND AND THAT TOTAL IS REVISED UPWARD AT LEAST TWICE A YEAR ! COMPUTERIZED STOCK TRADING APPLICATION THAT TRACKS THE hCURRENT STATE OF THE TOTAL MARKETv MUST BE ABLE TO PROCESS EACH MESSAGE USUALLY REQUIRING AN UPDATE OF A DATABASE ROW IN LESS THAN MILLIONTHS OF A SECOND OR IT WILL FALL BEHIND THE INCOMING MESSAGES )N ADDITION THE ABILITY TO TRADE QUICKLY AS MARKET CONDITIONS CHANGE IS A KEY COMPETITIVE ADVANTAGE IN STOCK TRADING SO SHAVING EVEN A FEW MILLIONTHS OF A SECOND FROM DATABASE DELAYS CAN BE WORTH MILLIONS OF DOLLARS PER YEAR 4HE DEMANDS OF APPLICATIONS LIKE THESE ARE BEYOND THE SCOPE OF MAINSTREAM DATABASE SYSTEMS TODAY )N THE TYPICAL CLIENTSERVER ARCHITECTURE THE DELAY ASSOCIATED WITH THE NETWORK ALONE IS OFTEN MEASURED IN MILLISECONDS THOUSANDTHS OF A SECOND SO EVEN AN INFINITELY FAST DATABASE POSES TOO MUCH DELAY )F THE NETWORK DELAY IS ELIMINATED ACCESS TO THE PHYSICAL DISK WHERE THE DATABASE IS STORED CAN TAKE TENS OF MILLISECONDS SHIFTING THE BOTTLENECK TO THE COMPUTERS STORAGE %VEN IF THIS DELAY IS ELIMINATED THE COMPLEXITY OF THE DATABASE SOFTWARE AND THE NUMBER OF #05 INSTRUCTIONS THAT IT MUST PROCESS FOR EVEN THE SIMPLEST OF DATABASE OPERATIONS CAN ADD UP TO TENTHS OF A MILLISECOND OR MORE 4O MEET THESE EXTREME DEMANDS DEVELOPERS HISTORICALLY BUILT PROPRIETARY hHOMEGROWNv DATABASES CUSTOMIZED TO THE SPECIFIC REQUIREMENTS OF EACH APPLICATION %VERY MAJOR 7ALL 3TREET BROKERAGE FIRM HAD AN )4 DEPARTMENT THAT BUILT ITS OWN TRADING DATABASE SYSTEM AND EVERY MAJOR TELECOM EQUIPMENT VENDOR BUILT ONE OR MORE NETWORK DATABASES TO SUPPORT ITS NETWORK EQUIPMENT )N THE LATE S A NEW BREED OF STANDARD DATABASE SOFTWARE EMERGED TO ADDRESS THESE REQUIREMENTSTHE 31, BASED IN MEMORY DATABASE
!NATOMYõOFõANõ)N -EMORYõ$ATABASE )N MEMORY DATABASES TAKE THE TRADITIONAL ARCHITECTURE OF AN ENTERPRISE DATABASE SYSTEM AND RADICALLY CHANGE SOME OF THE CORE ASSUMPTIONS )N A CONVENTIONAL DATABASE THE ACTIVE DATABASE IS STORED ON MASS STORAGE DISKS AND ONLY A SMALL FRACTION OF THE DATA IS HELD IN THE COMPUTER SYSTEMS MEMORY AT ANY ONE TIME )N AN IN MEMORY DATABASE THE ENTIRE ACTIVE DATABASE IS STORED IN MEMORY HENCE THE NAME %VERY DATABASE ACCESS OR UPDATE CAN BE SATISFIED BY MEMORY ACCESS YOU NEVER NEED TO RETRIEVE DATA FROM MASS STORAGE 4HE DATABASE SYSTEM MAY STILL MAINTAIN A LOG OF TRANSACTIONS ON DISK OR STORE A COPY OF THE DATABASE ON DISK FOR ERROR RECOVERY MOST COMMERCIAL SYSTEMS DO BOTH OF THESE THINGS BUT THE DISK ACCESS IS NOT IN THE DIRECT PATH TO COMPLETE THE DATABASE OPERATION
#HAPTERçç
3PECIALTYç$ATABASESç
4HE SIMPLE CHANGE IN ASSUMPTION FROM A DISK CENTRIC TO A MEMORY CENTRIC DESIGN HAS BROAD REACHING IMPLICATIONS FOR THE WAY THE $"-3 OPERATES s )N A CONVENTIONAL DATABASE THE DATA IN MEMORY IS A COPY OF THE hREALv DATA ON DISK AND THE COPY CAN BECOME OUT OF DATE AS OTHER #05S OR SYSTEMS UPDATE THE DATABASE 4HE $"-3 MUST TAKE MEASURES TO ENSURE THAT THE IN MEMORY DATA IS FRESH AND REFRESH IT FROM THE DISK IF IT IS NOT &OR AN IN MEMORY DATABASE THE DATA IN MEMORY IS THE ACTIVE COPY IT IS ALWAYS FRESH s )N A CONVENTIONAL DATABASE THE ARRANGEMENT OF THE DATA ON DISK CAN DRAMATICALLY IMPACT PERFORMANCE 4HE $"! MUST TAKE MEASURES TO ENSURE THAT THE STORAGE SYSTEM 3!. OR .!3 ALONG WITH ASSOCIATED DISK DRIVES IS CONFIGURED AND OPTIMIZED SUCH THAT FREQUENTLY ACCESSED DATA CAN BE RETRIEVED AND UPDATED WITH MINIMAL DISK INPUT ANDOR OUTPUT )/ WHICH IS MUCH SLOWER THAN MEMORY ACCESS )N AN IN MEMORY DATABASE THE PHYSICAL STORAGE CONFIGURATION OF DATA IS IRRELEVANTxTHE SPEED TO ACCESS DIFFERENT RANDOM LOCATIONS IN THE COMPUTERS MEMORY IS FOR MOST PURPOSES THE SAME s "ECAUSE THE PHYSICAL DISK CONFIGURATION IS IMPORTANT A CONVENTIONAL DATABASE IS CONSTANTLY REARRANGING DATA LOCATIONS SPLITTING DATA STORED IN A SINGLE DISK BLOCK INTO MULTIPLE DISK BLOCKS AND UPDATING ITS INTERNAL DATA STRUCTURES TO KEEP TRACK OF THE LOCATIONS !N IN MEMORY DATABASE HAS NO NEED TO MOVE DATA AROUND IN MEMORY s "ECAUSE THE PHYSICAL LOCATION OF A DATABASE ROW ON DISK CAN CHANGE A CONVENTIONAL DATABASE KEEPS TRACK OF THE ROW BASED ON A VIRTUAL ADDRESS OR ROW ID %VERY TIME THE ROW MUST BE PHYSICALLY ACCESSED THE DATABASE PERFORMS AN INTERNAL LOOKUP TO FIND THE ACTUAL CURRENT PHYSICAL LOCATION s )N CONVENTIONAL DATABASES $"!S AND DATABASE USERS CONSIDER FAULT TOLERANCE A GIVEN BECAUSE CONVENTIONAL $"-3S ARE DESIGNED TO WRITE DATA UPDATES TO THE LOG FILE FIRST AND LOGS ARE TYPICALLY MIRRORED TO MORE THAN ONE PHYSICAL DEVICE 4HIS IS NOT AT ALL THE CASE WITH IN MEMORY DATABASES WHERE A SUDDEN POWER FAILURE OR SERVER FAILURE CAN EASILY LOSE CHANGES MADE SINCE THE LAST WRITE TO DISK &AULT TOLERANCE CAN BE ACHIEVED WITH IN MEMORY DATABASES THROUGH TECHNOLOGY SUCH AS REDUNDANT DATABASE COPIES UNINTERRUPTIBLE POWER SYSTEMS AND NONVOLATILE MEMORY BUT IT TAKES CAREFUL PLANNING AND DESIGN TO IMPLEMENT THESE FEATURES
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4HE PRACTICAL IMPACT OF THESE DIFFERENCES IS ILLUSTRATED BY CONSIDERING A SIMPLE DATABASE OPERATIONFINDING THE ROW POINTED TO BY A FOREIGN KEY )N THE SAMPLE DATABASE THIS IS A MOVE FROM A SPECIFIC ROW IN THE /2$%23 TABLE TO THE CORRESPONDING ROW IN THE 02/$5#43 TABLE FOR THE PRODUCT BEING ORDERED FOR EXAMPLE )N AN IN MEMORY DATABASE THIS IS A VERY SIMPLE OPERATION 4HE FOREIGN KEY WILL BE REPRESENTED WITHIN THE DATABASE BY A DIRECT POINTER TO THE MEMORY LOCATION OF THE CORRESPONDING 02/$5#43 ROW &OLLOWING THIS LINK TAKES ONLY A FEW #05 INSTRUCTIONS AND THE TIME REQUIRED IS MEASURED IN MILLIONTHS OR EVEN BILLIONTHS OF A SECOND &OR THE CONVENTIONAL DATABASE THE SITUATION IS FAR MORE COMPLEX 4HE FOREIGN KEY IS PROBABLY REPRESENTED BY THE DATA VALUES OF THE MANUFACTURER AND PRODUCT )$S 4HE DATABASE MUST USE ITS INDEXING SCHEME TO LOCATE THE CORRESPONDING 02/$5#43 ROW &OR A LARGER DATABASE OF TENS OF THOUSANDS OF PRODUCTS THE INDEX MAY BE SEVERAL LAYERS DEEP )F THE DISK BLOCK CONTAINING THE TOP LEVEL OF THE INDEX IS IN MEMORY THE $"-3 CAN START WORKING ITS
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WAY DOWN THROUGH THE INDEX LAYERS )F NOT THE BLOCK OF DATA MUST BE LOCATED ON DISK AND BROUGHT INTO MEMORY 4HE SAME PATTERN REPEATS AT EACH LEVEL OF THE INDEX WITH COMPUTATION REQUIRED TO FIND THE PARTICULAR INDEX ENTRY WITHIN THE BLOCK &INALLY THE INDEX HAS BEEN SEARCHED AND THE VIRTUAL ROW ID OF THE CORRECT ROW HAS BEEN FOUND .OW THE PROCESS REPEATS TO LOCATE THE ACTUAL ROW OF DATA 4HE $"-3 TRANSLATES THE VIRTUAL ROW ID INTO A PHYSICAL LOCATIONAGAIN ITS A COMPUTATIONALLY INTENSIVE PROCESS 4HE CURRENT BLOCKS OF DATA IN THE $"-3 MEMORY BUFFERS ARE SEARCHED TO DETERMINE IF THE REQUIRED DATA IS ALREADY IN MEMORY )F SO THE $"-3 MUST ALSO CHECK TO MAKE SURE THAT THE CONTENTS OF THAT PARTICULAR BLOCK HAVE NOT BEEN INVALIDATED BY ANOTHER PROGRAMS UPDATES )F THE BLOCK IS FRESH PROCESSING CAN PROCEED IF NOT A DISK READ IS REQUIRED TO FETCH IT INTO MEMORY "UT FIRST THE $"-3 MUST CHOOSE WHICH BLOCK OF DATA CURRENTLY IN MEMORY IS TO BE REPLACED BY THIS NEW BLOCK AGAIN COMPUTATION IS REQUIRED TO APPLY THE APPROPRIATE ALGORITHM TO SELECT THE STALE BLOCK )F IT HAS BEEN UPDATED IT MUST BE WRITTEN TO DISK FIRST AND THEN THE NEW BLOCK CAN BE RETRIEVED 4HE $"-3 ISNT QUITE FINISHED YET 4HAT + OR + BLOCK OF DATA LIKELY CONTAINS SEVERAL ROWS OF 02/$5#43 SO THE CORRECT ROWS LOCATION MUST BE CALCULATED 4HEN THE $"-3 CAN RETRIEVE THE ROW COPY IT INTO A DIFFERENT MEMORY LOCATION WHERE THE $"-3 CAN OPERATE ON IT AND THE ACTUAL WORK OF ACCESSING ANDOR MODIFYING THE DATA CAN PROCEED %VEN IF THE TRADITIONAL $"-3 DOESNT HAVE TO PERFORM ANY ACTUAL DISK )/ IN THE PROCESS JUST DESCRIBED THE POSSIBILITY OF DISK )/ DRIVES THE NEED TO EXECUTE HUNDREDS OF THOUSANDS OF #05 INSTRUCTIONS AT BEST TO CARRY OUT THE REQUESTED OPERATION )T IS THIS DIFFERENCE IN COMPLEXITY EVEN WHEN A TRADITIONAL $"-3 IS RUNNING WITH ALL OF ITS DATA IN MEMORY THAT CREATES A DRAMATIC DIFFERENCE IN LATENCY BETWEEN AN IN MEMORY DATABASE AND A TRADITIONAL ENTERPRISE DATABASE
)N -EMORYõ$ATABASEõ)MPLEMENTATIONS 4HE FIRST COMMERCIAL DATABASE PRODUCTS BASED ON IN MEMORY ARCHITECTURE APPEARED IN THE LATE S FOLLOWING UNIVERSITY RESEARCH EARLIER IN THE DECADE /NE OF THE ADVANTAGES OF THESE PRODUCTS WAS THEIR ABILITY TO USE THE SAME INDUSTRY STANDARD 31, AS THEIR COMPLEX ENTERPRISE COUSINS ! PROGRAMMER WHO WAS ALREADY FAMILIAR WITH $" OR /RACLE DEVELOPMENT COULD SHIFT TO AN IN MEMORY DATABASE DEVELOPMENT PROJECT AND FIND A COMFORTABLE FAMILIAR DATABASE LANGUAGE 4HIS ADVANTAGE AND THE FLEXIBILITY OF A 31, BASED RELATIONAL DATABASE COMPARED WITH THE RIGIDITY OF THE EARLIER PROPRIETARY IN MEMORY DATABASES MADE THE NEW GENERATION OF IN MEMORY DATABASES THE POPULAR CHOICE FOR NEW TELECOM AND FINANCIAL TRADING APPLICATIONS AT THE BEGINNING OF THE NEXT DECADE "Y MID DECADE THE POPULARITY OF IN MEMORY DATABASES HAD CAUGHT THE ATTENTION OF THE MAJOR ENTERPRISE DATABASE VENDORS /NE OF THE MARKET LEADERS 4IMES4EN WAS ACQUIRED BY /RACLE IN )N RESPONSE )"-S DATABASE DIVISION ACQUIRED ANOTHER IN MEMORY DATABASE PLAYER 3OLID $ATA 3YSTEMS ABOUT A YEAR AND A HALF LATER !LTHOUGH THE LEADING IN MEMORY DATABASES NOW ARE OFFERED BY MAJOR ENTERPRISE DATABASE VENDORS THE IN MEMORY PRODUCTS REMAIN A SEPARATE OFFERING FIRMLY TARGETED AT THEIR MARKET NICHE
#ACHINGõWITHõ)N -EMORYõ$ATABASES )N MANY APPLICATIONS THAT DEMAND THE LOW LATENCY OF IN MEMORY DATABASES THE DATA BEING ACCESSED IS RELATED TO THE DATA IN A MUCH LARGER CONVENTIONAL ENTERPRISE DATABASE )N MOBILE PHONE APPLICATIONS FOR EXAMPLE THE REAL TIME NETWORK INFORMATION ABOUT MOBILE PHONES
#HAPTERçç
3PECIALTYç$ATABASESç
THEIR LOCATIONS AND CURRENT CALLING OR TEXTING OPERATIONS IS RELATED TO DATA ABOUT CUSTOMERS THEIR BILLING PLANS AND HISTORICAL USAGE PATTERNS 4O GET A COMPLETE REAL TIME VIEW OF THE CUSTOMER THE INFORMATION IN THE IN MEMORY AND ENTERPRISE DATABASES MUST BE RELATED )N RECENT YEARS IN MEMORY DATABASES HAVE EVOLVED TO MEET THIS NEED BY BEING REPURPOSED AS A HIGH PERFORMANCE DATABASE CACHE FRONT ENDING A CONVENTIONAL ENTERPRISE DATABASE 4HIS CACHING ARCHITECTURE IS SHOWN IN &IGURE 2EAL TIME DATABASE REQUESTS ARE SATISFIED BY THE IN MEMORY CACHE WHILE MORE TRADITIONAL DATABASE PROCESSING USES THE CONVENTIONAL DISK BASED BACK END DATABASE "OTH /RACLE AND )"- HAVE MOVED TO OFFER THESE CACHING CONFIGURATIONS AFTER THEIR RESPECTIVE ACQUISITIONS OF IN MEMORY DATABASE VENDORS 4HE IN MEMORY DATABASE CACHING CURRENTLY OFFERED PROVIDES CONSISTENT 31, ACCESS TO FRONT END AND BACK END DATA 4HE CACHE ALSO OFFERS SOME LEVEL OF TRANSPARENCY TO THE 31, PROGRAMMER WHO DOES NOT NEED TO KNOW WHETHER THE DATA BEING REQUESTED RESIDES IN THE FRONT END OR BACK END SYSTEM (OWEVER TODAYS IN MEMORY CACHES ARE NOT TRANSPARENT TO THE DATABASE ADMINISTRATOR 4HE ADMINISTRATOR MUST CAREFULLY CHOOSE WHICH TABLES OR VIEWS ARE TO BE hPULLED FORWARDv INTO THE IN MEMORY FRONT END SO THAT REAL TIME QUERIES CAN BE SATISFIED WITHOUT PASSING THE REQUEST TO THE BACK END 4HOSE DECISIONS REQUIRE A CAREFUL BALANCE BETWEEN THE PERFORMANCE ADVANTAGES OF CACHING AND THE OVERHEAD OF KEEPING THE FRONT END AND BACK END SYSTEMS SYNCHRONIZED TO ENSURE DATA INTEGRITY )TS LIKELY THAT THESE TWO TIER CACHING ARCHITECTURES WILL GAIN IN POPULARITY TO SUPPORT HIGH VOLUME WEB SITES AND OTHER )NTERNET DATABASE PROCESSING !S THEY DO AN INCREASED LEVEL OF TRANSPARENCY AND MORE hAUTOMATIC INTELLIGENCEv IN THE CACHE WILL BE IMPORTANT
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#OMPLEXõ%VENT 0ROCESSINGõANDõ3TREAMõ$ATABASES 3OME IMPORTANT APPLICATIONS IN FINANCIAL SERVICES AND REAL TIME SYSTEMS INVOLVE PROCESSING A STREAM OF DATA COMING FROM A DATA FEED &OR EXAMPLE IN STOCK TRADING APPLICATIONS THE VARIOUS STOCK EXCHANGES TRANSMIT A CONTINUOUS STREAM OF QUOTES OFFERS TO BUY OR SELL SECURITIES AND COMPLETED TRANSACTIONS THAT MUST BE CAPTURED AND ANALYZED FOR AUTOMATED TRADING /R IN A REAL TIME BATTLEFIELD APPLICATION VARIOUS RADAR AND SENSOR SYSTEMS MAY GENERATE A CONTINUOUS STREAM OF DATA ABOUT TROOP MOVEMENTS AND THREATS THAT MUST BE CAPTURED AND ANALYZED TO DETERMINE THE APPROPRIATE RESPONSE )N THESE EXAMPLES AND OTHERS LIKE THEM THE INDIVIDUAL MESSAGES IN THE DATA STREAM REPRESENT REAL WORLD EVENTS SUCH AS A STOCK TRADE OR A TROOP MOVEMENT &OR THIS REASON THE APPLICATIONS ARE OFTEN REFERRED TO AS STREAM PROCESSING OR EVENT PROCESSING APPLICATIONS ! CONVENTIONAL ENTERPRISE DATABASE ARCHITECTURE ADDRESSES EVENT PROCESSING APPLICATIONS BY FIRST CAPTURING THE STREAM OF EVENTS AND PERSISTING IT TO DISK AS A SEQUENCE OF ROWS IN A DATABASE TABLE OR TABLES AS SHOWN IN &IGURE /NCE THE DATA IS STORED IN THE DATABASE ONE OR MORE QUERIES CAN BE RUN AGAINST IT TO PRODUCE THE REQUIRED ANALYSIS )F THE APPLICATION DEMANDS A CONTINUOUS REAL TIME ANALYSIS OF THE DATA AS IT EVOLVES IT WILL RERUN THE QUERY OVER AND OVER PERHAPS ONCE EVERY FEW SECONDS %ACH SUBSEQUENT QUERY WILL CAPTURE THE ADDITIONAL DATA ADDED TO THE TABLE IN THE MOST RECENT INTERVAL AND REFLECT THAT DATA IN THE QUERY RESULTS )F THE APPLICATION NEEDS TO REPORT ON ONLY THE MOST RECENT DATA ANOTHER PROCESS MAY BE INTRODUCED THAT DELETES STALE DATA FROM THE TABLE !S THE FIGURE ILLUSTRATES CONVENTIONAL DATABASE SYSTEMS ARE DESIGNED TO QUERY hDATA AT RESTvTHE DATA AS IT EXISTS ON THE COMPUTER SYSTEMS STORAGE &OR EVENT PROCESSING APPLICATIONS THE ACTUAL GOAL IS OFTEN TO ANALYZE AND SUMMARIZE hDATA IN MOTIONvTHE STREAM OF DATA AS IT FLOWS BY ON A NETWORK /FTEN THE APPLICATION HAS NO INTEREST IN THE INDIVIDUAL EVENTS IN THE STREAM EXCEPT FOR HOW THEY CONTRIBUTE TO A REAL TIME AVERAGE OR RUNNING TOTAL OR WHEN THEY DEVIATE FROM SOME NORMAL OR EXPECTED RESULT 4HE PROCESS OF PERSISTING THE DATA TO DISK IS A WASTED STEP FOR SUCH APPLICATIONS )N EXTREME CASES THE DISK STORAGE MAY PROVE TO BE A BOTTLENECK IN THE SYSTEM LIMITING THE RATE AT WHICH ARRIVING EVENTS CAN BE PROCESSED %VENTS MAY BE SKIPPED IN THE PROCESS RESULTING IN MISSED OPPORTUNITIES FOR SECURITIES TRADES OR INCOMPLETE BATTLEFIELD INFORMATION FOR DECISION MAKING
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)N THE LATE S AND EARLY S UNIVERSITY RESEARCHERS BEGAN TO FOCUS ON THE PROBLEMS OF EVENT PROCESSING AND BUILT PROTOTYPES OF A DIFFERENT TYPE OF DATABASE ENGINE DESIGNED TO DIRECTLY PROCESS DATA IN MOTION 4HESE STREAM DATABASES EXAMINE EVENT DATA AS IT ARRIVES AND CALCULATE AND SUMMARIZE IT ON THE FLY WITHOUT PERSISTING IT TO DISK AS SHOWN IN &IGURE 1UERIES OPERATE CONTINUOUSLY PRODUCING A STEADY STREAM OF REAL TIME MOVING AVERAGES OR TOTALS OR FLAGGING INDIVIDUAL EVENTS THAT ARE ABNORMAL AND REQUIRE FURTHER EXAMINATION )N SOME OF THESE SYSTEMS THE STREAM DATA CAN BE COMBINED WITH DATA IN CONVENTIONAL DATABASE TABLES WHICH MAY CONTAIN REFERENCE DATA THAT IS LOOKED UP TO INTERPRET THE DATA STREAM OR NORMAL VALUES AGAINST WHICH THE DATA STREAM IS TO BE COMPARED 4HIS PRODUCES A HYBRID DATABASE THAT COMBINES EVENT PROCESSING AND CONVENTIONAL DATABASE ANALYTICS
#ONTINUOUSõ1UERIESõINõ3TREAMõ$ATABASES
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4HE CONCEPT OF A CONTINUOUS QUERY IS FUNDAMENTAL TO THE OPERATION OF STREAM DATABASES 5NLIKE A TRADITIONAL DATABASE QUERY WHICH RETRIEVES AND CALCULATES THE SPECIFIED DATA FROM DATA STORED ON DISK AS OF A PARTICULAR TIME A CONTINUOUS QUERY IS EXECUTED REPEATEDLY AGAINST THE DATA ARRIVING IN A DATA STREAM -OST PRODUCTS OFFER THE ABILITY TO SPECIFY EITHER TIME BASED OR RECORD BASED WINDOWS 4HEY MAY ALSO OFFER THE CHOICE OF A SLIDING WINDOW OR A JUMPING WINDOW 4HE OPERATION OF CONTINUOUS QUERIES AND WINDOWS IS ILLUSTRATED IN &IGURE 5SING A TIME BASED WINDOW FOR EXAMPLE A STREAMING DATABASE CAN BE INSTRUCTED TO CALCULATE THE AVERAGE PRICE AND TOTAL SHARE VOLUME FOR EACH STOCK TRADED DURING A FIVE MINUTE INTERVAL 4HE SEQUENCE OF QUERY VALUES OVER TIME REPRESENTS THE STATE OF THE STOCK MARKET DURING A TRADING SESSION !LTERNATIVELY USING A RECORD BASED WINDOW THE DATABASE CAN BE INSTRUCTED TO CALCULATE THE AVERAGE PRICE AND TOTAL SHARE VOLUME FOR EACH GROUP OF TRADES THAT OCCURS !GAIN THE SEQUENCE OF QUERY VALUES OVER TIME WILL SHOW THE EVOLVING STATE OF THE STOCK MARKET THIS TIME PACED BY THE RATE OF TRADING INSTEAD OF THE PASSAGE OF TIME )N ALL CASES THE QUERY RESULTS OFTEN REPRESENT STATISTICAL CALCULATIONS OF NUMERICAL DATA TOTALS AVERAGES MAXIMUM MINIMUM STANDARD DEVIATION ETC DURING A WINDOW OF TIME POSSIBLY GROUPED AS IN THIS EXAMPLE BY TICKER SYMBOL OF THE STOCK )T IS OFTEN USEFUL TO COMBINE THIS DYNAMICALLY CALCULATED INFORMATION WITH STATIC INFORMATION THAT IS LOOKED UP IN A TRADITIONAL ENTERPRISE DATABASE
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3TREAMõ$ATABASEõ)MPLEMENTATIONS 3OME OF THE EARLIEST WORK ON STREAM DATABASES WAS CONDUCTED BY UNIVERSITY RESEARCHERS FROM -)4 "ROWN AND "RANDEIS 5NIVERSITY LED BY $R -ICHAEL 3TONEBREAKER WHO HAD PIONEERED EARLIER GENERATIONS OF RELATIONAL DATABASE TECHNOLOGY )N $R 3TONEBREAKER AND SOME OF HIS RESEARCH COLLEAGUES FORMED A COMPANY NAMED 3TREAM"ASE 3YSTEMS /N THE OPPOSITE COAST RESEARCHERS AT THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEY WERE ALSO WORKING ON STREAM DATABASES AS THEY HAD WORKED ON EARLIER GENERATIONS OF DATABASE TECHNOLOGY ,ED BY $R -ICHAEL &RANKLIN THIS RESEARCH WAS BASED ON THE 0OSTGRES OPEN SOURCE DATABASE ENGINE WHICH IRONICALLY HAD BEEN INITIALLY DEVELOPED BY ONE OF $R 3TONEBREAKERS EARLIER TEAMS )N THE "ERKELEY RESEARCH BECAME THE FOUNDATION OF A VENTURE BACKED COMPANY NAMED 4RUVISO FOCUSED ON THE STREAM DATABASE OPPORTUNITY )N THE 5NITED +INGDOM A DECADE OF DATABASE RESEARCH AT #AMBRIDGE 5NIVERSITY PRODUCED !PAMA A COMPANY FOUNDED IN !PAMA FOCUSED AT THE APPLICATIONS LEVEL DEVELOPING AND DELIVERING AN ALGORITHMIC TRADING PLATFORM THAT IT SOLD TO THE SECURITIES INDUSTRY 4HE UNDERLYING EVENT PROCESSING FOUNDATION IS EXPOSED IN TWO OTHER PRODUCTS FOCUSED ON GENERIC #OMPLEX %VENT 0ROCESSING #%0 AND ON "USINESS !CTIVITY -ONITORING "!- )N 0ROGRESS 3OFTWARE ACQUIRED !PAMA AS A COMPLEMENT TO ITS /BJECT3TORE OBJECT DATABASE 4WO OTHER EARLIER MARKET PLAYERS WERE #ORAL FOUNDED IN IN -OUNTAIN 6IEW #ALIFORNIA AND !LERI WHICH HAD DEVELOPED EVENT PROCESSING TECHNOLOGY DURING ITS YEAR HISTORY AND HAD ADDED PACKAGED APPLICATIONS FOR 7ALL 3TREET TRADING THROUGH ACQUISITION 4HE COMPANIES MERGED IN AND JETTISONED THE TRADING APPLICATION TO FOCUS ON COMBINING THEIR #%0 OFFERINGS UNDER THE BANNER OF CONTINUOUS INTELLIGENCE !LL OF THE MARKET PARTICIPANTS FOCUS PRIMARILY ON 7ALL 3TREET SECURITIES TRADING APPLICATIONS BECAUSE THAT MARKET SEGMENT HAS THE CLEAREST REQUIREMENTS FOR THE CAPABILITIES THAT STREAMING DATABASES UNIQUELY PROVIDE AND ALSO HAS THE LARGEST OPPORTUNITIES FOR
#HAPTERçç
3PECIALTYç$ATABASESç
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#%0 APPLICATIONS TO SIGNIFICANTLY INCREASE REVENUE &EDERAL GOVERNMENT APPLICATIONS ESPECIALLY IN THE INTELLIGENCE COMMUNITY FOR ANALYSIS OF GATHERED INTELLIGENCE STREAMS ALSO FIGURE PROMINENTLY FOR SEVERAL OF THE VENDORS !LL OF THE VENDORS CITE SOME SUCCESSES IN WEB BASED BUSINESSES OR IN TELECOM AS EVIDENCE OF THE POTENTIAL FOR BROADER MARKET APPEAL BUT THE DEPLOYMENTS OUTSIDE THE 7ALL 3TREET AND GOVERNMENT SECTORS HAVE BEEN LIMITED TO DATE
3TREAMõ$ATABASEõ#OMPONENTS 4HE MARKET FOR STREAM DATABASES HAS MATURED TO THE POINT WHERE ALL OF THE VENDORS OFFER A SIMILAR SUITE OF FACILITIES 4HE MAJOR ELEMENTS ILLUSTRATED IN &IGURE USUALLY INCLUDE MOST OF THE FOLLOWING s !N EVENT PROCESSING ENGINE ACCEPTS INCOMING MESSAGES FROM A DATA FEED OR NETWORK AND CARRIES OUT CONTINUOUS QUERIES AGAINST THE DATA 4HE ENGINE MAY ALSO INCLUDE THE ABILITY TO COMBINE DATA FROM THE STREAM WITH DATA FROM ITS OWN STATIC TABLES OR FROM STATIC DATA MANAGED BY A TRADITIONAL ENTERPRISE $"-3 s ! SUITE OF INPUT ADAPTERS ACCEPTS INCOMING MESSAGES FROM COMMON DATA FEEDS AND PASSES THEM TO THE EVENT PROCESSING ENGINE IN A STANDARD FORMAT 4HE ADAPTERS TYPICALLY SUPPORT THE *AVA -ESSAGING 3ERVICE *-3 !0) 4IBCOS POPULAR 2ENDEZVOUS MESSAGING SERVICE VARIOUS FEEDS FROM THE FINANCIAL MARKETS AND OTHER ENTERPRISE MESSAGING SYSTEMS
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s ! SUITE OF OUTPUT ADAPTERS ACCEPTS MESSAGES PASSED THROUGH BY THE EVENT PROCESSING ENGINE OR GENERATED BY IT AND TRANSLATES THEM FOR TRANSMISSION ON COMMON MESSAGING SYSTEMS SUCH AS *-3 COMPATIBLE SYSTEMS OR 2ENDEZVOUS
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s %NTERPRISE $"-3 LINKS ALLOW THE EVENT PROCESSING ENGINE TO MERGE DATA FROM THE DATA FEED WITH DATA RETRIEVED FROM TRADITIONAL ENTERPRISE DATABASES !LL OF THE MAJOR PRODUCTS SUPPORT DATABASE ACCESS VIA *$"# AND SOME PROVIDE SUPPORT FOR PROPRIETARY ENTERPRISE DATABASE !0)S s ! DEVELOPMENT ENVIRONMENT ALLOWS PROGRAMMERS TO BUILD CONTINUOUS QUERIES AND TO TEST AND DEPLOY THEM AS PRODUCTION SYSTEMS 3OME VENDORS OFFER GRAPHICAL DEVELOPMENT ENVIRONMENTS TO SPECIFY DATA FILTERING MERGING JOINING AND GROUPING /THERS PROVIDE SUPPORT FOR A TEXT BASED 31, BASED LANGUAGE THAT IS USED TO SPECIFY THE QUERIES 4HE DEVELOPMENT ENVIRONMENT MAY ALSO SUPPORT A MODELING LANGUAGE TO DEFINE THE FORMATS OF THE VARIOUS DATA STREAMS AND HOW THE DATA IS TO BE MANIPULATED BY THE ENGINE s ! DASHBOARD OR PORTAL PROVIDES A GRAPHICAL VIEW OF THE QUERY RESULTS VISUALLY DISPLAYING AVERAGES TOTALS EXCEPTIONS AND THE LIKE IN REAL TIME AS THE EVENT PROCESSING ENGINE CARRIES OUT ITS WORK ON THE STREAMING DATA
%MBEDDEDõ$ATABASES 3OME DATABASES ARE COMPLETELY INVISIBLE TO END USERS BECAUSE THEY ARE DEEPLY EMBEDDED WITHIN MACHINES OR DEVICES AND USED TO SUPPORT OR CONTROL THEIR OPERATION 4HE MACHINERY THAT CONTROLS A MANUFACTURING PROCESS OR AN AUTOMATED LOADING DOCK FOR EXAMPLE MIGHT CONTAIN A DATABASE THAT HELPS TO CONTROL THE ASSEMBLY LINE OR LOADING EQUIPMENT ! NETWORK ELEMENT SUCH AS A ROUTER A SWITCH OR AN AUTOMATED VOICE RESPONSE UNIT MAY CONTAIN A DATABASE THAT STORES CONFIGURATION PARAMETERS OR GATHERS PERFORMANCE STATISTICS OR THAT DETERMINES THE VALID RESPONSES TO A USERS SPOKEN COMMANDS 4HE ENTERTAINMENT AND ENGINE CONTROL SYSTEMS IN YOUR CAR MAY WELL CONTAIN EMBEDDED DATABASES THAT STORE INFORMATION ABOUT YOUR FAVORITE SATELLITE RADIO STATIONS OR THAT COLLECT ENGINE PERFORMANCE INFORMATION TO ANTICIPATE MAINTENANCE REQUIREMENTS )N EACH OF THESE CASES THE OPERATION OF THE DATABASE IS FUNDAMENTAL TO THE OPERATION OF THE DEVICE BUT NO DATABASE QUERIES ARE VISIBLE AND NO DATABASE ADMINISTRATOR IS MANAGING THE DATABASES OPERATION 5NTIL ABOUT TEN YEARS AGO EMBEDDED DATABASES TO SUPPORT APPLICATIONS LIKE THESE WERE ALWAYS CUSTOM BUILT TO MEET THE SPECIFIC NEEDS OF THE APPLICATION %MBEDDED DATABASES ALMOST ALWAYS OPERATE IN A VERY RESOURCE CONSTRAINED ENVIRONMENT WITH LIMITED MEMORY AND LITTLE OR NO DISK STORAGE 4HERE WAS SIMPLY NO WAY THAT A DATABASE SYSTEM BASED ON STANDARD 31, COULD SQUEEZE INTO THE REQUIRED VERY SMALL MEMORY FOOTPRINT AND THE GENERALITY OF A 31, BASED DATABASE WAS OVERKILL FOR THE NEEDS OF THE APPLICATION /VER TIME HOWEVER THE COST OF MEMORY DISK STORAGE AND COMPUTING POWER HAS STEADILY PLUMMETED PROVIDING VASTLY MORE PROCESSING POWER AND STORAGE AT LOW PRICE POINTS )N PARALLEL THE SOPHISTICATION AND INTELLIGENCE OF FACTORY AUTOMATION NETWORK EQUIPMENT ENTERTAINMENT SYSTEMS AND CONTROL SYSTEMS HAS GROWN DRAMATICALLY !T THE INTERSECTION OF THOSE TWO TRENDS COMMERCIAL 31, BASED EMBEDDED DATABASE PRODUCTS HAVE EMERGED TO FILL THE NEED
#HAPTERçç
3PECIALTYç$ATABASESç
%MBEDDEDõ$ATABASEõ#HARACTERISTICS #OMMERCIAL EMBEDDED 31, DATABASE PRODUCTS TEND TO HAVE THE SAME BASIC CHARACTERISTICS DRIVEN BY THE REQUIREMENTS OF THE TYPES OF APPLICATIONS THAT THEY SERVE 4HESE INCLUDE s 6ERY SMALL MEMORY FOOTPRINT 7HILE ENTERPRISE DATABASES TYPICALLY REQUIRE TENS OF GIGABYTES OR MORE OF MEMORY TO OPERATE EMBEDDED DATABASES MAY SQUEEZE INTO AS LITTLE AS A FEW HUNDRED KILOBYTES OF MEMORY s :ERO OR VERY LITTLE ADMINISTRATION 7HILE ENTERPRISE DATABASES TYPICALLY HAVE DEDICATED $"!S WHO CONFIGURE MANAGE AND TUNE THEM EMBEDDED DATABASES ARE COMPLETELY MANAGED BY THE APPLICATION THAT USES THEM 4HERE IS NO DATABASE ADMINISTRATION AND USUALLY LITTLE OR NO CONFIGURATION WHEN THE PRODUCT CONTAINING THE DATABASE IS PLACED INTO SERVICE s 3UPPORT FOR UNCONVENTIONAL STORAGE 4HE DATA MANAGED BY AN EMBEDDED DATABASE MAY BE STORED ENTIRELY IN MEMORY IN NONVOLATILE hFLASHv MEMORY ON A SOLID STATE 53" DRIVE OR ON A STORAGE MEDIUM OTHER THAN THE DISK DRIVES USUALLY FOUND ON DATABASE SERVERS s ,IMITED 31, SUPPORT 7ITH MUCH LESS MEMORY TO WORK IN THE RANGE OF 31, LANGUAGE SUPPORT IS USUALLY LIMITED TO BASIC DATA MANIPULATION AND QUERIES 4HE APPLICATION PROBABLY HAS NO NEED OF DATA WAREHOUSING EXTENSIONS EXOTIC DATA TYPES INTEGRATION WITH 8-, OR DATABASE AUDITING s 3TATIC DATABASE SCHEMA 4HE STRUCTURE OF THE DATABASE IS DESIGNED TO SERVE A SPECIFIC APPLICATION AND IT CAN BE DETERMINED AT THE TIME THE PRODUCT IS DESIGNED 4HERE IS LITTLE NEED FOR THE ABILITY TO DYNAMICALLY ADD DELETE OR CHANGE COLUMN OR TABLE DEFINITIONS s 3INGLE USER OPERATION ! SINGLE APPLICATION OR A SMALL GROUP OF APPLICATIONS TYPICALLY USES THE DATABASE OFTEN ELIMINATING THE NEED FOR SOPHISTICATED MULTIUSER CONCURRENCY CONTROL
%MBEDDEDõ$ATABASEõ)MPLEMENTATIONS
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4HE S SAW A PROLIFERATION OF EMBEDDED DATABASE PRODUCTS DRIVEN BY A PROLIFERATION OF PRODUCTS THAT REQUIRED EMBEDDED DATA MANAGEMENT AND DRAMATIC IMPROVEMENTS IN THEIR PROCESSING POWER AND MEMORY CAPACITY 3OME OF THESE PRODUCTS CAME OUT OF UNIVERSITY RESEARCH SUCH AS THE 3LEEPY#AT EMBEDDED DATABASE BASED ON "ERKELEY$" )N #ANADA %MPRESS 3OFTWARE WAS AN EARLY EMBEDDED DATABASE PIONEER 4HE 2AIMA DATABASE PRODUCTS WERE ANOTHER EARLY ENTRY SUBSEQUENTLY ACQUIRED BY "IRDSTEP 0ROGRESS 3OFTWARES RANGE OF DATABASE PRODUCTS INCLUDES /PEN%DGE AS ITS EMBEDDED DATABASE MEMBER %NCIRQS PRODUCT OFFERS ONE OF THE SMALLEST MEMORY FOOTPRINTS AVAILABLE THROUGH A UNIQUE COMPILED CODE ARCHITECTURE 4HE OPEN SOURCE DATABASE MOVEMENT ALSO EXTENDED TO EMBEDDED DATABASES 31,ITE WHICH REMAINS ONE OF THE MORE POPULAR PRODUCTS IS IMPLEMENTED AND DISTRIBUTED AS AN OPEN SOURCE PRODUCT !LTHOUGH IT HAS A LARGER FOOTPRINT THAN MOST EMBEDDED DATABASES OPEN SOURCE -Y31, PLAYS A ROLE IN THE HIGH END OF THE EMBEDDED MARKET /NE OF THE APPEALS OF OPEN SOURCE DATABASES FOR EMBEDDED APPLICATIONS IS THAT THE DEVELOPER CAN IF WILLING TO INVEST THE TIME AND EFFORT CUSTOMIZE THE DATABASE ENGINE STRIPPING OUT PARTS THAT ARENT NEEDED TO SQUEEZE INTO AN EVEN SMALLER FOOTPRINT
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4HE MARKET FOR EMBEDDED DATABASES HAS REMAINED RELATIVELY SMALL DUE IN PART TO EXTREME PRICING PRESSURE "ECAUSE THESE DATABASES ARE EMBEDDED INTO OTHER PRODUCTS THE PER UNIT COST OF THE DATABASE SYSTEM TO THE PRODUCT VENDOR BECOMES A PART OF THE PRODUCT COST JUST AS IF IT WERE A PLASTIC OR ELECTRONIC PART 0RODUCT VENDORS NEGOTIATE THESE COSTS AGGRESSIVELY AND ITS NOT UNUSUAL FOR AN EMBEDDED DATABASE FOR A VOLUME PRODUCT TO GENERATE ONLY A FEW DOLLARS PER UNIT FOR ITS VENDOR &OR THIS REASON MOST EMBEDDED DATABASES STILL COME FROM SMALLER OFTEN VENTURE BACKED VENDORS 4HERE ARE SOME EXCEPTIONS MOST NOTABLY THE "ERKELEY$" OFFERING FROM /RACLE WHICH ACQUIRED THE PRODUCT AND THE COMPANY THAT PRODUCED IT
-OBILEõ$ATABASES ! FOURTH TYPE OF SPECIALTY DATABASE IS ESPECIALLY TUNED TO SUPPORT THE DATA MANAGEMENT NEEDS OF HANDHELD DEVICES SUCH AS PERSONAL DIGITAL ASSISTANTS 0$!S HANDHELD COMPUTERS SMARTPHONES AND MOBILE LAPTOP COMPUTERS "ECAUSE THESE DEVICES ARE BATTERY POWERED THEY TYPICALLY HAVE VERY LIMITED RESOURCES COMPARED WITH THE DATABASE SERVERS THAT HOST ENTERPRISE DATABASES 4HEY USUALLY HAVE MUCH LESS POWERFUL AND SLOWER PROCESSORS MUCH MORE LIMITED MEMORY AND MUCH SMALLER DISK STORAGE OR NO DISK STORAGE AT ALL USING FLASH MEMORY AS ALTERNATIVE NONVOLATILE STORAGE /VER THE LAST DECADE THE RISING POPULARITY OF LAPTOP AND NOTEBOOK COMPUTERS AND THE EMERGENCE OF ENTIRE NEW CATEGORIES OF INTELLIGENT HANDHELD DEVICES HAVE SPARKED THE DEVELOPMENT OF 31, BASED MOBILE DATABASES TO SUPPORT THESE DEVICES AND THEIR APPLICATIONS
-OBILEõ$ATABASEõ2OLES -OBILE DATABASES TYPICALLY PLAY ONE OR MORE WELL DEFINED ROLES ON THE DEVICES THAT THEY SUPPORT s 3UPPORT FOR DEVICE OPERATION 4HE DATABASE MAY STORE CONFIGURATION DATA OR THE CURRENT USER SELECTIONS FOR OPTIONAL CAPABILITIES THAT CAN BE CONFIGURED OR SWITCHED ON AND OFF 4HIS ROLE IS GENERALLY HIDDEN FROM THE USER AND USES THE MOBILE DATABASE AS AN EMBEDDED DATABASE s 3UPPORT FOR EMBEDDED APPLICATIONS /N A HANDHELD COMPUTER THE PERSONAL APPOINTMENT CALENDAR MAY BE STORED IN A LOCAL DATABASE TO MAKE IT EASILY SEARCHABLE /N A SMARTPHONE THE LIST OF CONTACTS AND THEIR ADDRESSES E MAIL ADDRESSES VARIOUS PHONE NUMBERS AND THE LIKE MAY BE STORED IN A DATABASE 4HE DATABASE MAY BE HIDDEN FROM USER VIEW BUT THE APPLICATION IS READILY VISIBLE s 3UPPORT FOR MOBILE PACKAGED APPLICATIONS %NTERPRISE APPLICATIONS MAY USE A HANDHELD COMPUTER OR A LAPTOP AS A DATA COLLECTION OR DATA ANALYSIS DEVICE WHERE A USER ENTERS DATA VIA A FORM OR GRAPHS THE DATA s ,OCAL DATABASE PROCESSING /CCASIONALLY THE USERS OF A LAPTOP OR HANDHELD COMPUTER MAY REQUIRE A PERSONAL DATABASE FOR STORING INFORMATION THAT THEY GENERATE OR ANALYZE s !CCESS TO ENTERPRISE DATABASES 4HE MOBILE DEVICE MAY BE A PORTAL THROUGH WHICH THE USER ACCESSES DATA STORED IN AN ENTERPRISE DATABASE 4HE LOCAL DATABASE SOFTWARE ACCEPTS DATA ACCESS OR DATA MANIPULATION REQUESTS PASSES THEM ON TO THE ENTERPRISE DATABASE RECEIVES THE RESULTS AND PASSES THEM BACK TO LOCAL SOFTWARE ON THE MOBILE DEVICE THROUGH A LOCAL !0)
#HAPTERçç
3PECIALTYç$ATABASESç
3YNCHRONIZATION WITH AN ENTERPRISE DATABASE IS A SIGNATURE CHARACTERISTIC OF THE LEADING MOBILE DATABASE PRODUCTS 7HEN NO NETWORK CONNECTION IS AVAILABLE THE MOBILE DATABASE SUPPORTS STAND ALONE OPERATION FOR MOBILE APPLICATIONS RUNNING ON THE MOBILE DEVICE 7HEN A NETWORK CONNECTION BECOMES AVAILABLE THE MOBILE DATABASE PROVIDES INTELLIGENT RESYNCHRONIZATION UPLOADING CHANGES MADE TO THE LOCAL DATABASE RECEIVING CHANGES MADE TO THE ENTERPRISE DATABASE AND RESOLVING ANY CONFLICTS BETWEEN THEM )N ADDITION WHEN A NETWORK CONNECTION IS AVAILABLE THE MOBILE DATABASE MAY ACT AS AN INTELLIGENT CACHE STORING A LOCAL COPY OF FREQUENTLY ACCESSED DATA TO AVOID THE NETWORK OVERHEAD OF REPEATED ACCESS
-OBILEõ$ATABASEõ)MPLEMENTATIONS 3YBASES 31,!NYWHERE PRODUCT ENJOYS THE LARGEST MARKET SHARE IN THE MOBILE DATABASE MARKET PRIMARILY DUE TO ITS POPULARITY ON LAPTOP COMPUTERS 4HE PRODUCT OFFERS A GOOD BALANCE BETWEEN FAIRLY COMPREHENSIVE 31, SUPPORT AND RELATIVELY MODEST RESOURCE REQUIREMENTS )T PROVIDES DATA SYNCHRONIZATION WITH ENTERPRISE DATABASES THROUGH INDUSTRY STANDARD !0)S /$"# AND *$"# SO THAT INTEGRATION WITH ALMOST ANY COMMERCIAL ENTERPRISE DATABASE PRODUCT IS POSSIBLE 4HE PRODUCT ALSO PROVIDES GOOD MANAGEABILITY FOR ENVIRONMENTS WHERE IT IS BROADLY DEPLOYED SUCH AS DEPLOYMENT TO A FIELD SALES ORGANIZATION OR A MOBILE MAINTENANCE FORCE 3YBASE HAS AGGRESSIVELY MARKETED 31,!NYWHERE TO MOBILE AND ENTERPRISE APPLICATION DEVELOPERS AS A MOBILE DATABASE THAT CAN EASILY BE EMBEDDED INTO THE MOBILE EDITIONS OF THEIR PRODUCTS OR DELIVERED IN CONJUNCTION WITH THOSE PRODUCTS %VEN WHEN NOT EMBEDDED MOBILE APPLICATIONS TEND TO PROVIDE 31,!NYWHERE SUPPORT BECAUSE OF ITS POPULARITY 4HE PRODUCT IS PART OF AN OVERALL FOCUS ON MOBILE APPLICATIONS AT 3YBASE AND BECAUSE OF THIS EMPHASIS HAS MAINTAINED OR GROWN ITS MARKET SHARE /RACLES MOBILE DATABASE OFFERING IS /RACLE ,ITE WHICH IT MARKETS AS A COMPLEMENT TO ITS FLAGSHIP ENTERPRISE DATABASE /RACLE ,ITE RUNS ON LAPTOP COMPUTERS AND SELECTED OTHER MOBILE DEVICES !N /RACLE SUPPLIED SYNCHRONIZATION SERVER PROVIDES THE BACK END ANCHOR FOR /RACLE ,ITE AND LINKS IT TO /RACLE DATABASES AND OTHER ENTERPRISE DATABASES VIA /$"#*$"# &OR MANY YEARS /RACLE DID NOT FOCUS ON /RACLE ,ITE SALES AND THE PRODUCT LOST MARKET SHARE TO 31,!NYWHERE -ORE RECENTLY /RACLE HAS BEGUN TO EVANGELIZE /RACLE ,ITE TO APPLICATION DEVELOPERS AND ENTERPRISE CUSTOMERS NEEDING A MOBILE SOLUTION 4HE PRODUCT ALSO SERVES AS AN EMBEDDED DATABASE SUPPORTING DEVICES AS DIVERSE AS INDUSTRIAL EQUIPMENT AND VENDING MACHINES
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3UMMARY !LTHOUGH ENTERPRISE CLASS DATABASE PRODUCTS DOMINATE THE MARKET SPECIALTY DATABASES SERVE IMPORTANT MARKET NICHES s )N MEMORY DATABASES SERVE APPLICATIONS THAT DEMAND VERY LOW LATENCY SUCH AS THOSE THAT SUPPORT THE OPERATION OF TELECOM NETWORKS OR FINANCIAL TRADING s %MBEDDED DATABASES SERVE APPLICATIONS WHERE HARDWARE RESOURCES ARE EXTREMELY CONSTRAINED SUCH AS AUTOMOTIVE SYSTEMS MASS MARKET CONSUMER DEVICES OR LOW COST NETWORK EQUIPMENT s 3TREAM DATABASES SERVE APPLICATIONS WHERE A VERY HIGH VOLUME STREAM OF DATA MUST BE CONTINUOUSLY PROCESSED AND ANALYZED SUCH AS THE FLOW OF INFORMATION FROM A SENSOR NETWORK OR A FINANCIAL MARKET DATA FEED s -OBILE DATABASES SUPPORT THE DATABASE REQUIREMENTS OF PERSONAL DIGITAL ASSISTANTS HANDHELD COMPUTERS SMARTPHONES AND LAPTOP COMPUTERS PROVIDING BOTH LOCAL DATABASE CAPABILITY AND SYNCHRONIZATION WITH ENTERPRISE DATABASES s /THER NEW NICHES ARE LIKELY TO EMERGE AS NEW FIELDS EMERGE WITH THEIR OWN DATA MANAGEMENT REQUIREMENTS AND 31, HAS SHOWN REMARKABLE RESILIENCY TO ADAPT TO THESE NEW SPECIALIZED REQUIREMENTS WHILE STILL PROVIDING A STANDARDIZED DATABASE LANGUAGE
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1, AND 31, BASED RELATIONAL DATABASES ARE AMONG THE CORE FOUNDATION TECHNOLOGIES OF TODAYS INFORMATION TECHNOLOGY INDUSTRY &ROM ITS FIRST COMMERCIAL IMPLEMENTATION THREE DECADES AGO 31, HAS GROWN TO BECOME THE STANDARD DATABASE LANGUAGE )N ITS FIRST DECADE THE BACKING OF )"- THE BLESSING OF STANDARDS BODIES AND THE FERVOR OF EARLY $"-3 VENDORS MOVED 31, FROM ACADEMIA INTO THE ENTERPRISE ARENA )N ITS SECOND DECADE THE IMPACT OF 31, EXTENDED TO PERSONAL COMPUTERS AND WORKGROUPS AND TO NEW APPLICATIONS LIKE DATA WAREHOUSING 4HE THIRD DECADE ESTABLISHED 31, AS THE DATA MANAGEMENT FOUNDATION FOR )NTERNET BASED COMPUTING AND SPAWNED MULTI BILLION DOLLAR SUBMARKETS SUCH AS BUSINESS INTELLIGENCE 4HE MARKET EVIDENCE CLEARLY SHOWS THE IMPORTANCE OF 31, s 4HE WORLDS SECOND LARGEST SOFTWARE COMPANY /RACLE HAS BEEN BUILT ON THE SUCCESS OF 31, BASED RELATIONAL DATA MANAGEMENT THROUGH BOTH ITS FLAGSHIP DATABASE SERVERS AND TOOLS AND ITS 31, BASED ENTERPRISE APPLICATIONS s )"- THE WORLDS LARGEST COMPUTER COMPANY OFFERS ITS 31, BASED $" SOFTWARE ACROSS ALL OF ITS PRODUCT LINES AND HAS ACQUIRED OTHER 31, BASED DATABASES AND APPLICATIONS s -ICROSOFT THE WORLDS LARGEST SOFTWARE COMPANY HAS BET ON ITS 31, 3ERVER DATABASE AS A KEY WEAPON IN ITS QUEST TO PENETRATE ENTERPRISE )4 AND AS THE DATA MANAGEMENT FOUNDATION FOR ALL OF ITS SERVICES AND APPLICATIONS s 3UN -ICROSYSTEMS A &ORTUNE TECHNOLOGY COMPANY SAW ENOUGH VALUE IN 31, TO BUY -Y31, !' THEREBY ACQUIRING -Y31, WHICH IS THE WORLDS LARGEST OPEN SOURCE 31, BASED 2$"-3 -Y31, POWERS MANY OF THE WEB SITES ON THE )NTERNET s 8-, A POTENTIAL CHALLENGER TO 31, AND THE RELATIONAL MODEL HAS INSTEAD BEEN ABSORBED INTO 31, BASED DATA MANAGEMENT HELPING TO EXTEND ITS DOMINANCE s !LL OF THE MAJOR PACKAGED ENTERPRISE APPLICATIONSFROM FINANCE TO SUPPLY CHAIN TO SALES FORCE AUTOMATION AND CUSTOMER RELATIONSHIP MANAGEMENTARE BUILT ON 31, BASED DATABASES
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s 31, IS THE STANDARD FOR SPECIALIZED DATABASES ON MOBILE DEVICES AND LAPTOPS AND FOR EMBEDDED APPLICATIONS IN TELECOMM NETWORKS AND MANUFACTURING SYSTEMS s 31, BASED ACCESS TO DATABASES IS A REQUIRED PART OF )NTERNET APPLICATION SERVERS AND 31, DATABASES UNDERLIE ALL MAJOR E COMMERCE SITES FROM !MAZON TO E"AY 4HIS CHAPTER DESCRIBES SOME OF THE MOST IMPORTANT CURRENT TRENDS AND DEVELOPMENTS IN THE DATABASE MARKET AND EXAMINES THE MAJOR FORCES THAT WILL ACT ON 31, AND DATABASE MANAGEMENT OVER THE NEXT SEVERAL YEARS
$ATABASEõ-ARKETõ4RENDS 4ODAYS MARKET FOR DATABASE MANAGEMENT PRODUCTS AND SERVICES IS MEASURED IN TENS OF BILLIONS OF DOLLARS )N MANY WAYS IT IS A MATURE MARKET WITH /RACLE )"- AND -ICROSOFT FIRMLY ESTABLISHED AS THE DOMINANT VENDORS AND WITH GROWTH RATES MEASURED IN SINGLE DIGIT OR LOW DOUBLE DIGIT PERCENTAGES FROM YEAR TO YEAR "UT DATABASE INNOVATION CONTINUES ACROSS A BROAD SPECTRUM 6ENTURE CAPITALISTS STILL POUR MONEY INTO DOZENS OF DATABASE STARTUPS 3OME OF THOSE STARTUPS HAVE GROWN TO EXCEED MILLION ANNUAL REVENUE IN THE LAST FEW YEARS AND OTHERS HAVE BEEN SWALLOWED UP BY THE MAJOR PLAYERS WHILE ON THEIR WAY TO THAT MARK -EANWHILE THE MAJOR VENDORS EACH EMPLOY THOUSANDS OF DEVELOPERS TO EXTEND AND ENHANCE THEIR PRODUCTS 3PECIALIZED CATEGORIES SUCH AS EMBEDDED DATABASES CLOUD BASED DATABASES OPEN SOURCE DATABASES AND STREAM ORIENTED DATABASES HAVE GENERATED SIGNIFICANT GROWTH 4HE TRENDS SHAPING THE MARKET BODE WELL FOR ITS CONTINUED HEALTH AND POINT TO A CONTINUING TENSION BETWEEN MARKET MATURITY AND CONSOLIDATION ON THE ONE HAND AND EXCITING NEW DATABASE CAPABILITIES AND APPLICATIONS ON THE OTHER
%NTERPRISEõ$ATABASEõ-ARKETõ-ATURITY 2ELATIONAL DATABASE TECHNOLOGY HAS BECOME ACCEPTED AS A CORE ENTERPRISE DATA PROCESSING TECHNOLOGY AND RELATIONAL DATABASES HAVE BEEN DEPLOYED BY ALL LARGE CORPORATIONS "ECAUSE OF THE IMPORTANCE OF CORPORATE DATABASES AND YEARS OF EXPERIENCE IN USING RELATIONAL TECHNOLOGY MANY LARGE CORPORATE )4 DEPARTMENTS HAVE SELECTED A SINGLE $"-3 BRAND AS AN ENTERPRISEWIDE DATABASE STANDARD /NCE SUCH A STANDARD HAS BEEN ESTABLISHED AND WIDELY DEPLOYED WITHIN A COMPANY USERS STRONGLY RESIST SWITCHING BRANDS %VEN THOUGH AN ALTERNATIVE $"-3 PRODUCT MAY OFFER ADVANTAGES FOR A PARTICULAR APPLICATION OR MAY PIONEER A NEW USEFUL FEATURE AN ANNOUNCEMENT BY THE CURRENT VENDOR THAT SUCH FEATURES ARE PLANNED FOR A FUTURE RELEASE WILL OFTEN FORESTALL THE LOSS OF A CUSTOMER BY THE ESTABLISHED VENDOR 4HE TREND TOWARD CORPORATE DATABASE STANDARDS HAS TENDED TO REINFORCE AND STRENGTHEN THE MARKET POSITIONS OF THE ESTABLISHED MAJOR $"-3 VENDORS )N THE CORPORATE )4 ORGANIZATION ESTABLISHED SALES AND CUSTOMER SUPPORT RELATIONSHIPS DEEP IN HOUSE FAMILIARITY WITH THE SELECTED STANDARD PRODUCT AND MULTIYEAR ENTERPRISEWIDE PURCHASE AGREEMENTS HAVE BECOME MORE IMPORTANT FACTORS THAN DATABASE TECHNOLOGY ADVANTAGE 7ITH THIS MARKET DYNAMIC THE LARGE ESTABLISHED PLAYERS TEND TO CONCENTRATE ON GROWING THEIR BUSINESS WITHIN THEIR EXISTING INSTALLED BASE INSTEAD OF ATTEMPTING TO TAKE CUSTOMERS AWAY FROM COMPETITORS
#HAPTERçç
4HEç&UTUREçOFç31,ç
/NE IMPORTANT IMPACT OF THE TREND TO CORPORATE $"-3 VENDOR STANDARDIZATION HAS BEEN A CONSOLIDATION IN THE DATABASE INDUSTRY .EW STARTUP DATABASE VENDORS TEND TO PIONEER NEW DATABASE TECHNOLOGY AND TO GROW BY SELLING IT TO EARLY ADOPTERS 4HESE EARLY ADOPTERS HAVE HELPED TO SHAPE THE TECHNOLOGY AND HAVE IDENTIFIED THE SOLUTION AREAS WHERE THE TECHNOLOGY CAN DELIVER REAL BENEFITS !FTER A FEW YEARS WHEN THE ADVANTAGES OF THE NEW TECHNOLOGY HAVE BEEN DEMONSTRATED THE STARTUP VENDORS ARE ACQUIRED BY LARGE ESTABLISHED PLAYERS 4HESE VENDORS CAN BRING THE NEW TECHNOLOGY INTO THEIR INSTALLED BASE AND CAN BRING THEIR MARKETING AND SALES MUSCLE TO BEAR IN AN ATTEMPT TO WIN BUSINESS IN THEIR COMPETITORS ACCOUNTS 4HE EARLY S SAW THIS CYCLE PLAY OUT WITH DATABASE VENDOR ACQUISITIONS OF DATABASE TOOLS VENDORS )N THE LATE S THE CYCLE REPEATED WITH ACQUISITIONS OF SPECIALIZED DATA WAREHOUSING VENDORS AND OBJECT RELATIONAL DATABASES /RACLE AND )"- BOTH ACQUIRED IN MEMORY DATABASE VENDORS IN THE MIDDLE OF THE S AND 3UN ACQUIRED -Y31, !' THE LARGEST OPEN SOURCE DATABASE VENDOR 3PECIALIZED DATA WAREHOUSING STARTUPS APPEAR POISED TO BE THE NEXT TARGETS
-ARKETõ$IVERSITYõANDõ3EGMENTATION $ESPITE THE MATURING OF SOME PARTS OF THE DATABASE MARKET ESPECIALLY THE MARKET FOR CORPORATE ENTERPRISE CLASS DATABASE SYSTEMS NEW SEGMENTS AND NICHES CONTINUE TO APPEAR 4HE TRADITIONAL SEGMENTATION OF MAINFRAME DATABASES DOMINATED BY )"- DATA CENTER DATABASES DOMINATED BY /RACLE AND WORKGROUP DATABASES DOMINATED BY -ICROSOFT HAS GIVEN WAY TO A MUCH MORE DIVERSE AND DYNAMIC SEGMENTATION -ARKET SEGMENTS THAT HAVE EMERGED OVER THE LAST FEW YEARS AND THAT HAVE EXPERIENCED HIGH GROWTH INCLUDE s $ATA WAREHOUSING DATABASES FOCUSED ON MANAGING HUNDREDS OF TERABYTES OF DATA OR MORE SUCH AS HISTORICAL RETAIL PURCHASE DATA s "USINESS INTELLIGENCE AND ONLINE ANALYTIC PROCESSING /,!0 DATABASES FOCUSED ON CARRYING OUT COMPLEX ANALYSES OF DATA TO DISCOVER UNDERLYING TRENDS DATA MINING ALLOWING ORGANIZATIONS TO MAKE BETTER BUSINESS DECISIONS s -OBILE DATABASES IN SUPPORT OF MOBILE WORKERS SUCH AS SALESPEOPLE SUPPORT PERSONNEL FIELD SERVICE PEOPLE CONSULTANTS AND MOBILE PROFESSIONALS /FTEN THESE MOBILE DATABASES ARE TIED BACK TO A CENTRALIZED DATABASE FOR SYNCHRONIZATION s %MBEDDED DATABASES WHICH OPERATE INSIDE A CLOSED hBLACK BOXv SYSTEM SUCH AS A PIECE OF MANUFACTURING EQUIPMENT OR AN AUTOMOBILES CONTROL AND ENTERTAINMENT SYSTEM OR A PIECE OF NETWORKING EQUIPMENT 4HESE DATABASES USUALLY HAVE VERY SMALL FOOTPRINTS AND REQUIRE LITTLE OR NO ADMINISTRATION s )N MEMORY DATABASES AND DATABASE CACHES DESIGNED FOR ULTRAHIGH PERFORMANCE /,40 APPLICATIONS SUCH AS SECURITIES TRADING OR HIGH VOLUME E COMMERCE SITES s #LICKSTREAM DATABASES RECORDING THE ONLINE ACTIVITY OF MILLIONS OF USERS CLICK BY CLICK SO THAT A WEB SITE CAN BE OPTIMIZED BASED ON ACTUAL USER BEHAVIOR
s 3TREAMING DATABASES THAT OPERATE ON hDATA IN MOTION v SUCH AS DATA ABOUT SECURITIES TRADES NETWORK TRAFFIC OR BANKING TRANSACTIONS AS IT PASSES BY ON A NETWORK
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s #LUSTERED DATABASES DESIGNED TO TAKE ADVANTAGE OF POWERFUL LOW COST SERVERS USED IN PARALLEL TO PERFORM DATABASE MANAGEMENT TASKS WITH HIGH SCALABILITY AND RELIABILITY
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31,ç4ODAYçANDç4OMORROW
0ACKAGEDõ%NTERPRISEõ!PPLICATIONS )N THE EARLY DAYS OF 31, BASED DATABASES MOST ENTERPRISE APPLICATIONS THAT RAN THE DAY TO DAY OPERATIONS OF MAJOR CORPORATIONS WERE DEVELOPED IN HOUSE BY THE CORPORATE )4 DEPARTMENT 4ODAY COMPANIES OF ALL SIZES HAVE SHIFTED FROM MAKE TO BUY STRATEGIES FOR MAJOR ENTERPRISE APPLICATIONS INCLUDING %20 SUPPLY CHAIN HUMAN RESOURCES PROCUREMENT SALES FORCE AUTOMATION CUSTOMER RELATIONSHIP MANAGEMENT AND DOZENS OF OTHERS 6ARIOUS ENTERPRISE APPLICATION VENDORS NOW SUPPLY THESE APPLICATIONS AS ENTERPRISE CLASS PACKAGED APPLICATIONS ALONG WITH CONSULTING CUSTOMIZATION AND INSTALLATION SERVICES !LL OF THESE PACKAGES ARE BUILT ON A FOUNDATION OF 31, BASED RELATIONAL DATABASES 4HE EMERGENCE OF DOMINANT PURCHASED ENTERPRISE APPLICATIONS HELPED TO ACCELERATE THE CONSOLIDATION OF THE DATABASE MARKET 4HE MAJOR ENTERPRISE SOFTWARE PACKAGE VENDORS TENDED TO SUPPORT $"-3 PRODUCTS FROM ONLY TWO OR THREE OF THE MAJOR $"-3 VENDORS &OR EXAMPLE IF A CUSTOMER CHOOSES TO DEPLOY 3!0 AS ITS COMPANYWIDE %20 APPLICATION THE UNDERLYING DATABASE IS RESTRICTED TO THOSE SUPPORTED BY THE 3!0 PACKAGES 4HIS TENDED TO REINFORCE THE DOMINANT POSITION OF THE CURRENT TOP TIER ENTERPRISE DATABASE PLAYERS AND TO MAKE IT MORE DIFFICULT FOR NEWER DATABASE VENDORS TO GAIN MARKET SHARE 4HE DYNAMICS TENDED TO FAVOR )"- AND /RACLE AS THE ESTABLISHED ENTERPRISE CLASS VENDORS AND TO HOLD BACK THE ADOPTION OF 31, 3ERVER 3YBASE AND -Y31, IN THE CORPORATE DATA CENTER )T ALSO THREATENED TO DEPRESS DATABASE PRICES AS THE $"-3 WAS VIEWED MORE AS A COMPONENT PART OF AN APPLICATION DRIVEN DECISION RATHER THAN A STRATEGIC DECISION IN ITS OWN RIGHT 2ESPONDING TO THIS TREND AND THE MATURING OF THE ENTERPRISE SOFTWARE MARKET /RACLE HAS EMBARKED ON A MAJOR DRIVE TO BECOME NOT ONLY THE DOMINANT DATABASE SOFTWARE VENDOR BUT ALSO A MAJOR VENDOR OF ENTERPRISE APPLICATIONS )NITIALLY /RACLE DEVELOPED ITS OWN ENTERPRISE APPLICATIONS WHICH MET LIMITED SUCCESS IN THE MARKET 3WITCHING STRATEGIES /RACLE HAS OVER THE LAST DECADE BUILT ITS APPLICATIONS SOFTWARE BUSINESS BY SPENDING TENS OF BILLIONS OF DOLLARS TO ACQUIRE SOFTWARE COMPANIES AND THEIR CUSTOMER BASES )"- HAS ALSO BEEN AN ACTIVE ACQUIRER OF TOOLS AND INFRASTRUCTURE SOFTWARE BUT HAS SHIED AWAY FROM MAJOR APPLICATIONS CATEGORIES 4HE RELATIONSHIP BETWEEN ENTERPRISE APPLICATIONS AND ENTERPRISE DATABASES IS STILL PLAYING OUT IN THE MARKETPLACE /RACLE PUSHES THE ADVANTAGE OF hONE STOP SHOPPINGv ACROSS ALL TYPES OF SOFTWARE WITH THE FUTURE PROMISE STILL LARGELY UNREALIZED OF TIGHTER INTEGRATION ACROSS THE FULL RANGE OF ENTERPRISE SOFTWARE !PPLICATIONS AND OTHER SOFTWARE ACQUIRED BY /RACLE TEND TO SUPPORT ONLY THE /RACLE DATABASE OVER TIME REDUCING THE DATA MANAGEMENT CHOICES AVAILABLE TO ITS APPLICATION CUSTOMERS )N CONTRAST )"- TAKES A CONSULTING AND SERVICES LED APPROACH TELLING CUSTOMERS THAT IT WILL HELP THEM SELECT THE BEST PRODUCTS AVAILABLE IN THE INDUSTRY #OMPETITORS AND CRITICS POINT OUT THAT )"- TENDS TO RECOMMEND ITS OWN HARDWARE AND CORE SOFTWARE INCLUDING ITS $" DATABASE 3!0 STILL ENJOYS A DOMINANT POSITION IN THE INSTALLED BASE OF ENTERPRISE APPLICATIONS AND HAS FILLED OUT ITS SUITE OF APPLICATIONS APPLICATION SERVERS AND OTHER INFRASTRUCTURE SOFTWARE WITH SELECTED SMALLER ACQUISITIONS "UT 3!0 LACKS AN ENTERPRISE CLASS DATABASE AND ITS APPLICATIONS BUSINESS GENERATES HUNDREDS OF MILLIONS OF DOLLARS OF DATABASE REVENUE FOR /RACLE AND )"- 4HE SHAPE OF THE ENTERPRISE APPLICATIONS MARKET OVER THE NEXT TEN YEARS REMAINS UNCLEAR BUT IT WILL SHAPE THE MARKET SHARES OF THE MAJOR DATABASE PLAYERS
#HAPTERçç
4HEç&UTUREçOFç31,ç
3OFTWARE AS A 3ERVICEõ3AA3 !GAINST THE ESTABLISHED BACKDROP OF MAJOR PACKAGED ENTERPRISE SOFTWARE A NEW TREND HAS BEGUN TO EMERGETHE DELIVERY OF ENTERPRISE APPLICATIONS OVER THE )NTERNET ACCESSED VIA A WEB BROWSER 5NDER THIS 3OFTWARE AS A 3ERVICE 3AA3 MODEL THE CORPORATE )4 DEPARTMENT DOESNT INSTALL OR OPERATE THE ENTERPRISE APPLICATIONS IN ITS OWN DATA CENTER )NSTEAD THE ENTERPRISE APPLICATIONS RUN ON SERVERS OPERATED BY THE APPLICATIONS VENDOR OR OPERATED ON THAT VENDORS BEHALF 4HE POTENTIAL BENEFIT TO THE ENTERPRISE IS A REDUCED AMOUNT OF CORPORATE )4 WORKLOAD REDUCED OPERATING COSTS AND FASTER ACCESS TO NEW IMPROVED VERSIONS OF THE APPLICATION AS SOFTWARE UPGRADES ARE TRANSPARENTLY INSTALLED AND DELIVERED OVER THE )NTERNET 3ALESFORCECOM PIONEERED THE 3AA3 MODEL FOR SALES FORCE AUTOMATION APPLICATIONS AND HAS GROWN TO WELL OVER A BILLION DOLLARS IN ANNUAL REVENUE IN THE PROCESS FORCING THE ESTABLISHED LEADER IN THE SPACE 3IEBEL 3YSTEMS INTO AN ACQUISITION BY /RACLE /THER VENDORS HAVE DEMONSTRATED THE ABILITY TO DELIVER %20 #2- (2 AND OFFICE APPLICATIONS VIA THE 3AA3 MODEL 4HE 3AA3 MODEL HAS THE POTENTIAL TO SERIOUSLY IMPACT THE ENTERPRISE DATABASE MARKET 7ITH A HOSTED 3AA3 DELIVERED APPLICATION THE PARTICULAR DATABASE SYSTEM UNDERLYING AN ENTERPRISE APPLICATION IS INVISIBLE TO THE CUSTOMER )T MAY BE /RACLE )"-S $" 31, 3ERVER -Y31, OR SOME OTHER TECHNOLOGY BUT AS LONG AS THE APPLICATION WORKS PROPERLY THE CUSTOMER DOESNT CARE )N THIS WAY THE 3AA3 MODEL THREATENS TO TAKE DATABASE BUYING DECISIONS AWAY FROM CORPORATE )4 AND CONCENTRATE THEM IN THE HANDS OF THE 3AA3 BASED APPLICATION VENDORS !T THIS WRITING 3AA3 REMAINS A MINOR PART OF THE OVERALL ENTERPRISE )4 LANDSCAPE )T HAS MADE INROADS INTO SPECIFIC DEPARTMENTAL APPLICATIONS SUCH AS SALES FORCE AUTOMATION AND HAS PROVEN VERY POPULAR WITH SMALL AND MEDIUM SIZED BUSINESSES THAT LACK LARGE CORPORATE )4 STAFFS "UT THE ECONOMIC BENEFITS OF THE 3AA3 MODEL CAN BE COMPELLING AND 3ALESFORCECOM HAS BOLDLY PROCLAIMED THAT ITS STRATEGY IS TO BRING ABOUT hTHE END OF ENTERPRISE SOFTWAREv )F 3AA3 CONTINUES TO GAIN TRACTION AND STARTS TO PENETRATE MAINSTREAM FINANCE AND %20 SYSTEMS EXPECT THE MAJOR DATABASE VENDORS TO TRY TO PROTECT THEIR INSTALLED BASES AND MARKET POWER
(ARDWAREõ0ERFORMANCEõ'AINS
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/NE OF THE MOST IMPORTANT CONTRIBUTORS TO THE RISE OF 31, HAS BEEN A DRAMATIC INCREASE IN THE PERFORMANCE OF RELATIONAL DATABASES 0ART OF THIS PERFORMANCE INCREASE WAS DUE TO ADVANCES IN DATABASE TECHNOLOGY AND QUERY OPTIMIZATION (OWEVER MOST OF THE $"-3 PERFORMANCE IMPROVEMENT CAME FROM GAINS IN THE RAW PROCESSING POWER OF THE UNDERLYING COMPUTER SYSTEMS AND FROM CHANGES IN THE $"-3 SOFTWARE DESIGNED TO CAPITALIZE ON THOSE GAINS 7HILE THE PERFORMANCE OF MAINFRAME SYSTEMS STEADILY INCREASED THE MOST STRIKING PERFORMANCE GAINS HAVE BEEN IN THE 5.)8 BASED AND 7INDOWS BASED SERVER MARKETS WHERE PROCESSING POWER HAS DOUBLED OR MORE YEAR BY YEAR 3OME OF THE MOST SIGNIFICANT ADVANCES IN SERVER PERFORMANCE COME FROM THE GROWTH OF SYMMETRIC MULTIPROCESSING 3-0 SYSTEMS WHERE TWO FOUR EIGHT OR EVEN DOZENS OF PROCESSORS OPERATE IN PARALLEL SHARING THE PROCESSING WORKLOAD ! MULTIPROCESSOR ARCHITECTURE CAN BE APPLIED TO /,40 APPLICATIONS WHERE THE WORKLOAD CONSISTS OF MANY SMALL PARALLEL DATABASE TRANSACTIONS 4RADITIONAL /,40 VENDORS SUCH AS 4ANDEM HAVE ALWAYS USED A MULTIPROCESSOR ARCHITECTURE AND THE LARGEST MAINFRAME SYSTEMS HAVE USED MULTIPROCESSOR DESIGNS FOR MORE THAN A DECADE )N THE S MULTIPROCESSOR SYSTEMS BECAME A MAINSTREAM PART OF THE 5.)8 BASED SERVER MARKET AND IN THE NEXT DECADE MULTIPROCESSOR SERVERS BECAME THE NORM AT THE MIDRANGE AND HIGH END OF THE 0# SERVER MARKET
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31,ç4ODAYçANDç4OMORROW
4ODAY EVEN DESKTOP SYSTEMS BASED ON )NTEL AND !-$ MICROPROCESSORS FEATURE TWO WAY AND FOUR WAY #05 CORES WHERE A SINGLE PROCESSOR CHIP OPERATES WITH NEARLY THE SAME POWER AS TWO OR FOUR SEPARATE PROCESSORS "LADE SERVER SYSTEMS EXPAND THIS CAPABILITY FURTHER MAKING SERVERS WITH DOZENS OF PROCESSORS HIGHLY ECONOMICAL 4HE MAINSTREAM ADOPTION OF BIT HARDWARE ARCHITECTURE AND OPERATING SYSTEMS HAS EXPANDED THE MEMORY ON THESE SYSTEMS TO TENS OR EVEN HUNDREDS OF GIGABYTES 3ERVERS THAT RIVAL THE COMPUTING POWER OF TRADITIONAL MAINFRAMES NOW CARRY PRICE TAGS OF UP TO -ULTICORE AND MULTIPROCESSOR SYSTEMS ALSO PROVIDED PERFORMANCE BENEFITS IN DECISION SUPPORT AND DATA ANALYSIS APPLICATIONS $"-3 VENDORS HAVE INVESTED HEAVILY TO PARALLELIZE THEIR QUERY OPERATIONS TAKING THE WORK OF A SINGLE COMPLEX 31, QUERY AND SPLITTING IT INTO MULTIPLE PARALLEL PATHS OF EXECUTION 7ITH THESE TECHNIQUES A QUERY THAT MIGHT HAVE TAKEN TWO HOURS ON A SINGLE PROCESSOR SYSTEM CAN BE COMPLETED IN JUST A FEW MINUTES #OMPANIES ARE TAKING ADVANTAGE OF THIS HARDWARE BASED PERFORMANCE BOOST TO OBTAIN BUSINESS ANALYSIS RESULTS IN A FRACTION OF THE TIME PREVIOUSLY REQUIRED "UT MORE OFTEN THEY ARE USING THE INCREASED PROCESSING POWER TO CARRY OUT MUCH MORE COMPLEX AND SOPHISTICATED ANALYSIS TO OPTIMIZE THEIR OPERATIONS 4ODAY THE QUEST FOR FASTER DATABASE PERFORMANCE CERTAINLY SHOWS NO SIGNS OF STOPPING FUELED BY $"-3 OPTIMIZATION FOR MULTIPROCESSOR AND MULTICORE HARDWARE )N THE PAST THE DATABASE PERFORMANCE QUEST HAS FUELED THE TOP END OF THE HARDWARE MARKET DRIVING DEMAND FOR ADDITIONAL MAINFRAME CAPACITY AND HIGH END 5.)8 SERVERS FROM 3UN (EWLETT 0ACKARD AND OTHERS )N THE FUTURE IT APPEARS THAT THE DATABASE PERFORMANCE QUEST WILL HAVE AN EVEN MORE PROFOUND IMPACT ON MIDRANGE AND COMMODITY SERVERS AND THE MICROPROCESSORS THAT POWER THEM
$ATABASEõ3ERVERõ!PPLIANCES 4HE HISTORY OF 31, AND RELATIONAL DATABASES HAS BEEN A RECURRING CYCLE OF INTEREST IN AND THEN DISSATISFACTION WITH DEDICATED DATABASE SERVER APPLIANCES 4O BUILD THESE SYSTEMS A VENDOR COMBINED HIGH PERFORMANCE MICROPROCESSORS FAST DISK DRIVES AND PREINTEGRATED SOFTWARE TO DELIVER A hBLACK BOXv DATABASE SERVER THAT COULD SIMPLY BE ATTACHED TO THE NETWORK AND POWERED ON $ATABASE SERVER VENDORS TYPICALLY ARGUED THAT THEY COULD DELIVER MUCH BETTER DATABASE PERFORMANCE WITH A SPECIALLY DESIGNED DATABASE ENGINE THAN WITH A GENERAL PURPOSE COMPUTER SYSTEM )N SOME CASES THEIR SYSTEMS INCLUDED APPLICATION SPECIFIC INTEGRATED CIRCUITS !3)#S THAT IMPLEMENT SOME OF THE $"-3 LOGIC IN HARDWARE FOR MAXIMUM SPEED $EDICATED DATABASE SYSTEMS FROM COMPANIES SUCH AS 4ERADATA 3HAREBASE FORMERLY "RITTON ,EE AND .ETEZZA FOUND SOME ACCEPTANCE IN APPLICATIONS THAT INVOLVE COMPLEX QUERIES AGAINST VERY LARGE DATABASES 7HILE 4ERADATA SUCCEEDED AND REMAINS A POWERFUL FORCE IN THE HIGH END OF THE DATA WAREHOUSING MARKET THE OTHER PACKAGED DATABASE SERVERS OF THE S AND S FAILED TO MAKE AN IMPACT 4HE NOTION OF A PACKAGED ALL IN ONE DATABASE SERVER APPLIANCE WAS BRIEFLY REKINDLED AT THE END OF THE S BY /RACLE #ORPORATION AND ITS #%/ ,ARRY %LLISON %LLISON ARGUED THAT THE )NTERNET ERA HAD SEEN THE SUCCESS OF OTHER ALL IN ONE PRODUCTS SUCH AS NETWORKING EQUIPMENT AND WEB CACHE SERVERS /RACLE ANNOUNCED PARTNERSHIPS WITH SEVERAL SERVER HARDWARE VENDORS TO BUILD /RACLE BASED DATABASE APPLIANCES /VER TIME HOWEVER THESE EFFORTS HAD LITTLE MARKET IMPACT AND /RACLES ENTHUSIASM FOR DATABASE APPLIANCES SEEMED TO FADE
#HAPTERçç
4HEç&UTUREçOFç31,ç
3EVERAL VENTURE BACKED STARTUPS HAVE RECENTLY EMBRACED THE IDEA OF DATABASE SERVER APPLIANCES ONCE AGAIN SOMETIMES IN THE FORM OF DATABASE CACHING SERVERS THAT RESIDE IN A NETWORK BETWEEN THE APPLICATION AND AN ENTERPRISE DATABASE )N SUCH A CONFIGURATION THE ABSOLUTE TRANSPARENCY OF THE CACHE IS CRITICAL AND THE EMERGENCE OF -Y31, AS AN EXTREMELY POPULAR OPEN SOURCE DATABASE HAS HELPED TO ENABLE THAT TRANSPARENCY -ANY OF THE DATABASE APPLIANCES RUN -Y31, SOFTWARE SO THE APPLICATION ACCESSING THE DATABASE CANT TELL WHETHER IT IS COMMUNICATING WITH THE APPLIANCE OR WITH -Y31, RUNNING ON A CONVENTIONAL SERVER /RACLE HAS ALSO REENERGIZED THE DATABASE APPLIANCE CONCEPT ANNOUNCING A HIGH END /RACLE DATABASE APPLIANCE WHOSE HARDWARE COMES FROM (EWLETT 0ACKARD
31,õ3TANDARDIZATION
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4HE ADOPTION OF AN OFFICIAL !.3))3/ 31, STANDARD WAS ONE OF THE MAJOR FACTORS THAT SECURED 31,S PLACE AS THE STANDARD RELATIONAL DATABASE LANGUAGE IN THE S #OMPLIANCE WITH THE !.3))3/ STANDARD HAS BECOME A CHECK OFF ITEM FOR EVALUATING $"-3 PRODUCTS SO EACH $"-3 VENDOR CLAIMS THAT ITS PRODUCT IS COMPATIBLE WITH OR BASED ON THE !.3))3/ STANDARD 4HROUGH THE NEXT YEARS ALL OF THE POPULAR $"-3 PRODUCTS EVOLVED TO CONFORM TO THE PARTS OF THE STANDARD THAT REPRESENTED COMMON USAGE /THER PARTS SUCH AS THE MODULE LANGUAGE WERE EFFECTIVELY IGNORED 4HIS PRODUCED SLOW CONVERGENCE AROUND A CORE 31, LANGUAGE IN POPULAR $"-3 PRODUCTS !S DISCUSSED IN #HAPTER THE ORIGINAL 31, STANDARD WAS RELATIVELY WEAK WITH MANY OMISSIONS AND AREAS THAT ARE LEFT AS IMPLEMENTATION CHOICES &OR SEVERAL YEARS THE STANDARDS COMMITTEE WORKED ON AN EXPANDED 31, STANDARD THAT REMEDIED THOSE WEAKNESSES AND THAT SIGNIFICANTLY EXTENDED THE 31, LANGUAGE 5NLIKE THE FIRST 31, STANDARD WHICH SPECIFIED FEATURES THAT WERE ALREADY AVAILABLE IN MOST 31, PRODUCTS THE 31, STANDARD WHEN IT WAS PUBLISHED IN WAS AN ATTEMPT TO LEAD RATHER THAN FOLLOW THE MARKET )T SPECIFIED FEATURES AND FUNCTIONS THAT WERE NOT YET WIDELY IMPLEMENTED IN CURRENT $"-3 PRODUCTS 3OME OF THESE FEATURES SUCH AS ITS ENHANCED JOIN CAPABILITIES AND BROADER USE OF SUBQUERIES ARE EFFECTIVELY MAINSTREAM CAPABILITIES TODAY WHILE OTHERS EVEN IF WIDELY IMPLEMENTED HAVE NOT BEEN WIDELY ADOPTED 4HE SAME PATTERN HAS CONTINUED WITH SUBSEQUENT REVISIONS OF THE 31, STANDARD PUBLISHED IN IN AND OVER THE LAST FEW YEARS 4HE SIZE OF THE STANDARD HAS GROWN SUBSTANTIALLY MORE THAN TRIPLING IN THE PROGRESSION FROM 31, TO TODAYS FULL STANDARD WHICH IS DIVIDED INTO ALMOST A DOZEN DIFFERENT SUBPARTS )N NEWER AREAS SUCH AS THE INCORPORATION OF 8-, THE RACE CONTINUES BETWEEN PROPRIETARY INNOVATION BY THE $"-3 VENDORS SEEKING COMPETITIVE ADVANTAGE AND THE EVOLUTION OF THE STANDARD TO ENSURE 31, PORTABILITY 4HE LIKELY FUTURE PATH OF 31, STANDARDIZATION APPEARS TO BE A CONTINUATION OF THE TRAJECTORY FOLLOWED IN RECENT YEARS 4HE CORE OF THE 31, LANGUAGE WILL CONTINUE TO BE HIGHLY STANDARD -ORE FEATURES WILL SLOWLY BECOME A PART OF THE CORE AND WILL BE DEFINED AS ADD ON PACKAGES OR NEW STANDARDS IN THEIR OWN RIGHT $ATABASE VENDORS WILL CONTINUE TO ADD NEW PROPRIETARY FEATURES IN AN ONGOING EFFORT TO DIFFERENTIATE THEIR PRODUCTS AND RESPOND TO EMERGING MARKET REQUIREMENTS /VER TIME THE PROPRIETARY FEATURES THAT BECOME THE MOST POPULAR WILL BECOME THE FEATURES WHERE CUSTOMERS DEMAND STANDARDIZATION AND THE VENDORS AND STANDARDS COMMITTEES WILL RESPOND
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31,ç4ODAYçANDç4OMORROW
31,õINõTHEõ.EXTõ$ECADE 0REDICTING THE PATH OF THE DATABASE MARKET AND 31, OVER THE NEXT FIVE TO TEN YEARS IS A RISKY PROPOSITION %ACH MAJOR TECHNOLOGY WAVE OVER THE PAST THREE DECADES HAS HAD A SIGNIFICANT IMPACT ON DATA MANAGEMENT AND 31, 4HE EMERGENCE OF THE 0# AND ITS CREATION OF THE CLIENTSERVER ERA OF THE S AND S IS AN EARLY EXAMPLE -ORE RECENTLY THE EMERGENCE OF THE )NTERNET AND ITS BROWSER BASED ARCHITECTURE HAS PRODUCED A NEW WAVE OF )NTERNET BASED DATA MANAGEMENT DELIVERED AS 7EB 3ERVICES 'OING FORWARD THE )NTERNET APPEARS POISED TO BECOME TRULY UBIQUITOUS WITH BROADBAND OR WIRELESS NETWORKS INTERCONNECTING EVERY TYPE OF ELECTRONIC DEVICE )TS LIKELY THAT THIS NEXT STAGE OF THE )NTERNET REVOLUTION COULD HAVE AN EVEN MORE DISRUPTIVE IMPACT ON THE DATA MANAGEMENT ARCHITECTURES OF THE FUTURE THAN THE FIRST WAVE OF )NTERNET DEPLOYMENT HAD OVER THE LAST DECADE .ONETHELESS SEVERAL TRENDS APPEAR TO BE SAFE PREDICTIONS FOR THE FUTURE EVOLUTION OF DATABASE MANAGEMENT 4HEY ARE DISCUSSED IN THE FINAL SECTIONS OF THIS CHAPTER
$ISTRIBUTEDõ$ATABASES !S MORE AND MORE APPLICATIONS ARE USED ON AN ENTERPRISEWIDE BASIS OR BEYOND THE ABILITY OF A SINGLE CENTRALIZED DATABASE TO SUPPORT DOZENS OF MAJOR APPLICATIONS AND THOUSANDS OF CONCURRENT USERS WILL CONTINUE TO ERODE )NSTEAD MAJOR CORPORATE DATABASES WILL BECOME MORE AND MORE DISTRIBUTED WITH DEDICATED DATABASES SUPPORTING THE MAJOR APPLICATIONS AND FUNCTIONAL AREAS OF THE CORPORATION 4O MEET THE HIGHER SERVICE LEVELS REQUIRED OF ENTERPRISEWIDE OR )NTERNET BASED APPLICATIONS DATA MUST BE DISTRIBUTED BUT TO ENSURE THE INTEGRITY OF BUSINESS DECISIONS AND OPERATIONS THE OPERATION OF THESE DISTRIBUTED DATABASES MUST BE TIGHTLY COORDINATED !NOTHER STRAIN ON CENTRALIZED DATABASE ARCHITECTURES WILL BE THE CONTINUING GROWTH OF MOBILE PERSONAL COMPUTERS AND OTHER MOBILE INFORMATION APPLIANCE DEVICES 4HESE DEVICES ARE BY THEIR NATURE MORE USEFUL IF THEY CAN BECOME AN INTEGRAL PART OF A DISTRIBUTED NETWORK (OWEVER BY THEIR NATURE THEY ARE ALSO OCCASIONALLY CONNECTEDTHEY WORK IN A SOMETIMES DISCONNECTED SOMETIMES CONNECTED MODE USING EITHER WIRED OR WIRELESS NETWORKS 4HE DATABASES AT THE HEART OF MOBILE APPLICATIONS MUST BE ABLE TO OPERATE IN THIS OCCASIONALLY CONNECTED ENVIRONMENT 4HESE TRENDS WILL DRIVE HEAVY DEMAND FOR DATA DISTRIBUTION DATABASE INTEGRATION DATA SYNCHRONIZATION DATA CACHING DATA STAGING AND DISTRIBUTED DATABASE TECHNOLOGY ! ONE SIZE FITS ALL MODEL OF DISTRIBUTED DATA AND TRANSACTIONS IS INADEQUATE FOR THE HIGHLY DISTRIBUTED ANYWHEREANYTIME ENVIRONMENT THAT WILL EMERGE )NSTEAD SOME TRANSACTIONS WILL REQUIRE ABSOLUTE SYNCHRONIZATION WITH A CENTRALIZED MASTER DATABASE WHILE OTHERS WILL DEMAND SUPPORT FOR LONG DURATION TRANSACTIONS WHERE SYNCHRONIZATION MAY TAKE HOURS OR DAYS $EVELOPING WAYS TO CREATE AND OPERATE THESE DISTRIBUTED ENVIRONMENTS WITHOUT HAVING THEM BECOME A DATABASE ADMINISTRATORS NIGHTMARE WILL BE A MAJOR CHALLENGE FOR $"-3 VENDORS IN THE NEXT DECADE AND A MAJOR SOURCE OF REVENUES FOR THE VENDORS THAT PROVIDE PRACTICAL RELATIVELY EASY TO USE SOLUTIONS
-ASSIVEõ$ATAõ7AREHOUSINGõFORõ"USINESSõ/PTIMIZATION 4HE LAST FEW YEARS HAVE DEMONSTRATED THAT COMPANIES THAT USE DATABASE TECHNOLOGY AGGRESSIVELY AND TREAT THEIR DATA AS A VALUABLE CORPORATE ASSET CAN GAIN TREMENDOUS COMPETITIVE ADVANTAGE 4HE COMPETITIVE SUCCESS OF 7AL -ART FOR EXAMPLE WAS WIDELY
#HAPTERçç
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ATTRIBUTED TO ITS USE OF INFORMATION TECHNOLOGY LED BY DATABASE TECHNOLOGY TO TRACK ITS INVENTORY AND SALES DAILY BASED ON CASH REGISTER TRANSACTION DATA 4HIS ALLOWS THE COMPANY TO MINIMIZE ITS INVENTORY LEVELS AND CLOSELY MANAGE ITS SUPPLIER RELATIONSHIPS $ATA MINING TECHNIQUES HAVE ALLOWED COMPANIES TO DISCOVER UNEXPECTED TRENDS AND RELATIONSHIPS BASED ON THEIR ACCUMULATED DATAINCLUDING THE LEGENDARY DISCOVERY BY ONE RETAILER THAT LATE NIGHT SALES OF DIAPERS WERE HIGHLY CORRELATED WITH SALES OF BEER )T SEEMS CLEAR THAT COMPANIES WILL CONTINUE TO ACCUMULATE AS MUCH INFORMATION AS THEY CAN ON THEIR CUSTOMERS SALES INVENTORIES PRICES AND OTHER BUSINESS FACTORS 4HE )NTERNET CREATES ENORMOUS NEW OPPORTUNITIES FOR THIS KIND OF INFORMATION GATHERING %VERY CUSTOMER OR PROSPECTIVE CUSTOMERS INTERACTION WITH A COMPANYS WEB SITE CLICK BY CLICK PROVIDES POTENTIAL CLUES TO THE CUSTOMERS WANTS NEEDS AND BEHAVIOR 4HAT TYPE OF CLICK BY CLICK INFORMATION NOW GENERATES HUNDREDS OF GIGABYTES OF DATA OR MORE EACH DAY ON A BUSY WEB SITE 4HE DATABASES TO MANAGE THESE MASSIVE QUANTITIES OF DATA WILL NEED TO RAPIDLY IMPORT VAST QUANTITIES OF NEW DATA AND TO RAPIDLY PEEL OFF LARGE DATA SUBSETS FOR ANALYSIS 4HEY WILL NEED TO BE ABLE TO SCALE TO ACCOMMODATE A BODY OF DATA THAT COULD EASILY GROW TWO OR THREE ORDERS OF MAGNITUDE IN A YEAR ! TREND TO STORE THESE DATABASES hIN THE )NTERNET CLOUD v USING STORAGE AND PROCESSING POWER PROVIDED BY COMPANIES LIKE !MAZON OR 'OOGLE IS ALREADY EMERGING 4O COPE WITH THE MASSIVE VOLUMES OF DATA AND MAINTAIN REASONABLE ECONOMICS THE DATA WAREHOUSING SOLUTIONS WILL NEED TO BE BASED ON MASSIVE DEPLOYMENT OF LOW COST COMMODITY HARDWARE
5LTRAHIGH 0ERFORMANCEõ$ATABASES
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4HE EMERGENCE OF AN )NTERNET CENTRIC ARCHITECTURE IS EXPOSING ENTERPRISE DATA PROCESSING INFRASTRUCTURES TO NEW PEAK LOAD DEMANDS THAT DWARF THE WORKLOADS OF JUST A FEW YEARS AGO 7HEN DATABASES PRIMARILY SUPPORTED IN HOUSE APPLICATIONS USED BY A FEW DOZEN EMPLOYEES AT A TIME DATABASE PERFORMANCE ISSUES MAY HAVE PRODUCED EMPLOYEE FRUSTRATION BUT THEY DID NOT REALLY IMPACT CUSTOMERS 4HE ADVENT OF CALL CENTERS AND OTHER CUSTOMER SUPPORT APPLICATIONS PRODUCED A CLOSER COUPLING BETWEEN DATA MANAGEMENT AND CUSTOMER SATISFACTION BUT APPLICATIONS WERE STILL LIMITED TO AT MOST HUNDREDS OF CONCURRENT USERS THE PEOPLE MANNING THE PHONES IN THE CALL CENTER 7ITH THE )NTERNET THE CONNECTION BETWEEN A CUSTOMER AND THE COMPANYS DATABASES BECOMES A DIRECT ONE $ATABASE PERFORMANCE PROBLEMS TRANSLATE DIRECTLY INTO SLOW CUSTOMER RESPONSE TIMES $ATABASE UNAVAILABILITY TRANSLATES DIRECTLY INTO LOST SALES &URTHERMORE DATABASES AND OTHER PARTS OF THE DATA PROCESSING INFRASTRUCTURE ARE NO LONGER BUFFERED FROM PEAK LOAD TRANSACTION RATES )F A FINANCIAL SERVICES FIRM OFFERS ONLINE TRADING OR PORTFOLIO MANAGEMENT IT WILL NEED TO PREPARE FOR PEAK LOAD VOLUMES ON DAYS OF HEAVY STOCK PRICE MOVEMENT THAT MAY BE OR TIMES THE AVERAGE DAILY VOLUME 3IMILARLY AN ONLINE RETAILER MUST GEAR UP TO SUPPORT hCYBER -ONDAY v THE HEAVIEST DAY OF THE YEAR END SELLING SEASON NOT JUST MID -ARCH TRANSACTION RATES 4HE DEMANDS OF E COMMERCE AND REAL TIME )NTERNET INFORMATION ACCESS ARE ALREADY PRODUCING PEAK LOAD TRANSACTION RATES FROM THE MOST POPULAR )NTERNET SERVICES THAT ARE ONE OR TWO ORDERS OF MAGNITUDE HIGHER THAN THE FASTEST CONVENTIONAL DISK BASED 2$"-3 SYSTEMS 4O COPE WITH THESE DEMANDS COMPANIES WILL INCREASINGLY TURN TO DISTRIBUTED AND REPLICATED DATABASES 4HEY WILL PULL HOT DATA FORWARD AND CACHE IT CLOSER TO THE CUSTOMER INTERACTION WITHIN THE NETWORK 4O MEET PEAK LOAD DEMANDS THEY WILL USE IN MEMORY DATABASES 4HIS WILL IN TURN REQUIRE NEW DATABASE SUPPORT FOR DECIDING WHICH DATA TO
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CACHE AND WHICH LEVELS OF SYNCHRONIZATION AND REPLICATION ARE APPROPRIATE !T FIRST THESE ISSUES WILL APPLY ONLY TO THE LARGEST AND HIGHEST VOLUME SITES BUT JUST AS WEB PAGE CACHING HAS BECOME AN ACCEPTED AND THEN AN ESSENTIAL TECHNIQUE FOR MAINTAINING ADEQUATE WEB BROWSER PERFORMANCE HOT DATA CACHING WILL BECOME A MAINSTREAM )NTERNET DATA MANAGEMENT ARCHITECTURE AS VOLUMES GROW /NE OF THE TECHNOLOGIES WITH POTENTIAL TO COPE WITH THESE RESPONSE TIME DEMANDS IS SOLID STATE STORAGE WHERE LOW COST 2!- OR FLASH MEMORY REPLACES DISKS AS THE PRIMARY DATABASE STORAGE MEDIUM 7HILE THE ECONOMICS OF DISK STORAGE HAVE STEADILY IMPROVED YEAR AFTER YEAR THE PERFORMANCE OF DISKS REMAINS LARGELY UNCHANGED SINCE IT DEPENDS ON ELECTROMECHANICAL FACTORS -EANWHILE SOLID STATE MEMORY IS SUBJECT TO THE SAME ECONOMICS OF SCALE THAT HAVE RAPIDLY INCREASED THE DENSITY AND DRIVEN DOWN THE COST OF OTHER MICROELECTRONIC DEVICES AS PRODUCTION VOLUMES HAVE RISEN 4HE EXPLODING PRODUCTION OF SOLID STATE MEMORY TO POWER CONSUMER DEVICES SUCH AS -0 PLAYERS SMARTPHONES AND SIMILAR DEVICES IS DRIVING DOWN THE COST OF SOLID STATE MEMORY FOR BUSINESS APPLICATIONS AS WELL 7E MAY WELL SEE THE ADVENT OF FULLY SOLID STATE DATABASE APPLIANCES WITH NO MOVING PARTS WITHIN THE NEXT THREE TO FIVE YEARS
)NTERNETõANDõ.ETWORKõ3ERVICESõ)NTEGRATION )N THE )NTERNET ERA DATABASE MANAGEMENT WILL INCREASINGLY BECOME JUST ONE MORE NETWORK SERVICE AND ONE THAT MUST BE TIGHTLY INTEGRATED WITH OTHER SERVICES SUCH AS MESSAGING TRANSACTION SERVICES AND NETWORK MANAGEMENT )N SOME OF THESE AREAS STANDARDS HAVE BEEN LONG ESTABLISHED SUCH AS THE 8! STANDARD FOR DISTRIBUTED TRANSACTION MANAGEMENT )N OTHERS STANDARDS HAVE RAPIDLY SOLIDIFIED SUCH AS THE 3/!0 STANDARD FOR SENDING 8-, DATA OVER THE )NTERNETS (440 PROTOCOL AND THE 5$$) 5NIVERSAL $ESCRIPTION $ISCOVERY AND )NTEGRATION STANDARDS FOR FINDING SERVICES IN A DISTRIBUTED NETWORK ENVIRONMENT #HALLENGES REMAIN IN CREATING EFFECTIVE STANDARDS FOR MANAGING DISTRIBUTED NETWORKS OF SERVICES AND FOR DEFINING AND MAINTAINING SERVICE LEVELS ACROSS THEM 4HE MULTITIER ARCHITECTURE THAT IS DOMINATING )NTERNET CENTRIC APPLICATIONS ALSO POSES NEW QUESTIONS ABOUT WHICH ROLES SHOULD BE PLAYED BY THE DATABASE MANAGER AND BY OTHER COMPONENTS OF THE OVERALL INFORMATION SYSTEM &OR EXAMPLE WHEN NETWORK TRANSACTIONS ARE VIEWED FROM THE POINT OF DISTRIBUTED DATABASES A TWO PHASE COMMIT PROTOCOL IMPLEMENTED IN A PROPRIETARY WAY BY A $"-3 VENDOR MAY PROVIDE A SOLUTION 7HEN NETWORK TRANSACTIONS INVOLVE A COMBINATION OF LEGACY APPLICATIONS EG MAINFRAME #)#3 #USTOMER )NFORMATION #ONTROL 3YSTEM TRANSACTIONS RELATIONAL DATABASE UPDATES AND INTERAPPLICATION MESSAGES THE TRANSACTION MANAGEMENT PROBLEM MOVES OUTSIDE THE DATABASE AND EXTERNAL MECHANISMS ARE REQUIRED ! SIMILAR TRADE OFF SURROUNDS THE EMERGENCE OF *AVA BASED APPLICATION SERVERS AS A MIDDLE TIER PLATFORM FOR EXECUTING BUSINESS LOGIC "EFORE THE )NTERNET ERA STORED PROCEDURES BECAME KNOWN AS THE ACCEPTED $"-3 TECHNIQUE FOR EMBEDDING BUSINESS LOGIC WITHIN THE DATABASE ITSELF -ORE RECENTLY *AVA HAS EMERGED AS A VIABLE STORED PROCEDURE LANGUAGE AN ALTERNATIVE TO EARLIER VENDOR PROPRIETARY LANGUAGES .OW APPLICATION SERVERS CREATE AN ALTERNATIVE PLATFORM FOR BUSINESS LOGIC WRITTEN IN *AVA IN THIS CASE EXTERNAL TO THE DATABASE )TS LIKELY THAT THESE TWO TRENDS WONT BE RATIONALIZED BUT THAT INSTEAD BUSINESS LOGIC WILL LIVE IN THE DATABASE OR ON THE APPLICATION SERVER BASED ON ORGANIZATIONAL CONSIDERATIONS 4HE DATA MANAGEMENT GROUP WILL USE STORED PROCEDURES AND LOGIC WITHIN THE DATABASE TO PROVIDE HIGHLY STRUCTURED ACCESS TO THE MANAGED DATA SOLELY VIA STORED PROCEDURES OR
#HAPTERçç
4HEç&UTUREçOFç31,ç
CORRESPONDING WEB SERVICES 4HE APPLICATIONS INTEGRATION GROUP WILL USE *AVA CODE RUNNING ON THE APPLICATION SERVER TO IMPLEMENT WORKFLOWS AND TO INTEGRATE INFORMATION FROM THE DATABASE WITH DATA COMING FROM OTHER PRODUCTIONS SYSTEMS 7ITH /RACLES ACQUISITION OF "%! ALL OF THE MAJOR DATABASE VENDORS NOW PRODUCE THEIR OWN APPLICATION SERVERS SO THE DATABASE AND APPLICATION SERVER ENVIRONMENTS MAY BECOME MORE TIGHTLY INTEGRATED OVER TIME ! PARALLEL TREND CAN BE SEEN IN THE GROWTH OF ,!-0 ,INUX !PACHE -Y31, AND 0(00YTHON0ERL AS AN OPEN SOURCE WEB PLATFORM
%MBEDDEDõ$ATABASES 2ELATIONAL DATABASE TECHNOLOGY HAS REACHED INTO MANY PARTS OF THE COMPUTER INDUSTRY FROM SMALL HANDHELD DEVICES TO LARGE MAINFRAMES $ATABASES UNDERLIE NEARLY ALL ENTERPRISE CLASS APPLICATIONS AS THE FOUNDATION FOR STORING AND MANAGING THEIR INFORMATION ,IGHTWEIGHT DATABASE TECHNOLOGY UNDERLIES AN EVEN BROADER RANGE OF APPLICATIONS $IRECTORY SERVICES A FOUNDATION TECHNOLOGY FOR THE NEW ERA OF VALUE ADDED DATA COMMUNICATIONS NETWORK SERVICES ARE A SPECIALIZED FORM OF DATABASE TECHNOLOGY ,IGHTWEIGHT HIGH PERFORMANCE DATABASES ALSO FORM AN INTEGRAL PART OF TELECOMMUNICATIONS NETWORKS ENABLING CELLULAR NETWORKS ADVANCED BILLING SCHEMES SMART MESSAGING SERVICES AND SIMILAR CAPABILITIES 4HESE EMBEDDED DATABASE APPLICATIONS HAVE TRADITIONALLY BEEN IMPLEMENTED USING PROPRIETARY CUSTOM WRITTEN DATA MANAGEMENT CODE TIGHTLY INTEGRATED WITH THE APPLICATION 4HIS APPLICATION SPECIFIC APPROACH PRODUCED THE HIGHEST POSSIBLE PERFORMANCE BUT AT THE EXPENSE OF AN INFLEXIBLE HARD TO MAINTAIN DATA MANAGEMENT SOLUTION 7ITH DECLINING MEMORY PRICES AND HIGHER PERFORMANCE PROCESSORS LIGHTWEIGHT 31, BASED RELATIONAL DATABASES ARE NOW ABLE TO ECONOMICALLY SUPPORT THESE APPLICATIONS 4HE ADVANTAGES OF A STANDARDS BASED EMBEDDED DATABASE ARE SUBSTANTIAL 7ITHOUT A SERIOUS COMPROMISE IN PERFORMANCE AN APPLICATION CAN BE DEVELOPED IN A MORE MODULAR FASHION CHANGES IN DATABASE STRUCTURE CAN BE HANDLED TRANSPARENTLY AND NEW SERVICES AND APPLICATIONS CAN BE RAPIDLY DEPLOYED ATOP EXISTING DATABASES 7ITH THESE ADVANTAGES EMBEDDED DATABASE APPLICATIONS APPEAR DESTINED TO BE A NEW AREA OF GROWTH POTENTIAL FOR 31, AND RELATIONAL DATABASE TECHNOLOGY !S IN SO MANY OTHER AREAS OF INFORMATION TECHNOLOGY THE ULTIMATE TRIUMPH OF 31, BASED DATABASES MAY BE THAT THEY DISAPPEAR INTO THE FABRIC OF OTHER PRODUCTS AND SERVICESINVISIBLE AS A STAND ALONE COMPONENT BUT VITAL TO THE PRODUCT OR SERVICE THAT CONTAINS THEM
/BJECTõ)NTEGRATION
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4HE MOST SIGNIFICANT UNKNOWN IN THE FUTURE EVOLUTION OF 31, IS HOW IT WILL INTEGRATE WITH OBJECT ORIENTED TECHNOLOGIES -ODERN APPLICATION DEVELOPMENT TOOLS AND METHODOLOGIES ARE ALL BASED ON OBJECT ORIENTED TECHNIQUES 4WO OBJECT ORIENTED LANGUAGES # AND *AVA DOMINATE SERIOUS SOFTWARE DEVELOPMENT FOR BOTH CLIENT SIDE AND SERVER SIDE SOFTWARE /BJECT ORIENTED SCRIPTING LANGUAGES SUCH AS 0(0 AND 0ERL DOMINATE WEB DEVELOPMENT 4HE CORE ROWCOLUMN PRINCIPLES OF THE RELATIONAL DATA MODEL AND 31, HOWEVER ARE ROOTED IN A MUCH EARLIER #/"/, ERA OF RECORDS AND FIELDS NOT OBJECTS AND METHODS 4HE OBJECT DATABASE VENDORS DEALT WITH THE OBJECTRELATIONAL MISMATCH BY DISCARDING THE RELATIONAL MODEL WHOLESALE IN FAVOR OF PURE OBJECT DATABASE STRUCTURES "UT THE LACK OF STANDARDS STEEP LEARNING CURVE LACK OF SIMPLE QUERY FACILITIES AND OTHER DISADVANTAGES PREVENTED PURE OBJECT DATABASES FROM HAVING ANY SIGNIFICANT MARKET SUCCESS )NSTEAD THE RELATIONAL DATABASE VENDORS WORKED TO INTEGRATE OBJECT ORIENTED FEATURES AND ESPECIALLY
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8-, SUPPORT INTO THE RELATIONAL MODEL -UCH WORK HAS ALREADY BEEN DONE BUT IT SEEMS A SAFE BET THAT RELATIONAL AND OBJECT TECHNOLOGIES WILL BE EVEN MORE TIGHTLY INTEGRATED GOING FORWARD INCLUDING THESE TRENDS s *AVA BASED INTERFACES TO 2$"-3S SUCH AS *$"# AND EMBEDDED 31, FOR *AVA WILL CONTINUE TO GROW RAPIDLY IN POPULARITY AS WILL INTERFACES FROM OBJECT ORIENTED SCRIPTING LANGUAGES s *AVA WILL BECOME A MORE IMPORTANT STORED PROCEDURE LANGUAGE FOR IMPLEMENTING BUSINESS LOGIC WITHIN AN 2$"-3 3LOWLY *AVA MAY REPLACE PROPRIETARY STORED PROCEDURE LANGUAGES LIKE /RACLES 0,31, FOR NEW APPLICATIONS s $"-3 PRODUCTS WILL EXPAND SUPPORT FOR ABSTRACT COMPLEX DATA TYPES THAT EXHIBIT OBJECT ORIENTED CAPABILITIES SUCH AS ENCAPSULATION AND INHERITANCE 8-, WILL PROVIDE THE VEHICLE FOR STORING STRUCTURED NONRELATIONAL DATA BUT IT WILL BE COMPLEMENTED BY THE ABILITY TO STORE STREAMING MEDIA SUCH AS MUSIC AND VIDEO s -ESSAGE ORIENTED INTERFACES INCLUDING DATABASE TRIGGERS THAT PRODUCE MESSAGES EXTERNAL TO THE $"-3 FOR INTEGRATION WITH OTHER APPLICATIONS WILL GROW IN IMPORTANCE AS THE DATABASE BECOMES A MORE ACTIVE COMPONENT FOR INTEGRATING SYSTEMS TOGETHER s 4HE LINES BETWEEN CONTENT MANAGEMENT SYSTEMS USED TO MANAGE DOCUMENTS AND RELATIONAL DATABASE MANAGEMENT SYSTEMS WILL BLUR AS 8-, BLURS THE DISTINCTION BETWEEN A hDOCUMENTv AND A hSTRUCTURED DATA RECORDv 4HE PATTERN OF RELATIONAL $"-3 EVOLUTION TO SUPPORT NEW TECHNOLOGIES AND REQUIREMENTS HAS BEEN CLEARLY EXHIBITED AND REPEATED OVER THE PAST TWO DECADES 4HE NEW TECHNOLOGY SUCH AS OBJECTS OR 8-, OR DATA WAREHOUSING COMES ON THE SCENE GENERATES A LOT OF ENTHUSIASM AND SPAWNS A WAVE OF STARTUPS &OR A FEW YEARS THESE NEWCOMERS RIDE THE NEW TECHNOLOGY WAVE AND SERVE THOSE WHO DERIVE STRONG BENEFITS FROM IT "UT AT THE SAME TIME THE RELATIONAL $"-3 VENDORS ADAPT TO THE NEW TECHNOLOGY AND FIND WAYS TO INTEGRATE ITAT FIRST AT A VERY BASIC LEVELINTO THEIR EXISTING PRODUCTS %VENTUALLY THOSE PRODUCTS BECOME hGOOD ENOUGHv FOR THE MAINSTREAM USE OF THE NEW TECHNOLOGY AND THE EXISTING PRODUCTS HAVE EVOLVED TO MEET THE CHALLENGE )T SEEMS LIKELY THAT PATTERN WILL REPEAT ITSELF WITH NEW TECHNOLOGIES LIKE FURTHER INTEGRATION OF OBJECTS INTO THE FUTURE
#LOUD "ASEDõANDõ(ORIZONTALLYõ3CALABLEõ$ATABASES !S THE )NTERNET HAS DEVELOPED MANY STANDARD ELEMENTS OF THE )NTERNET ARCHITECTURE HAVE BEEN FACED WITH THE NEED TO MASSIVELY SCALE IN THEIR ABILITY TO PROCESS VERY LARGE VOLUMES OF hTRANSACTIONSv 7EB SERVERS MUST SCALE TO HANDLE MILLIONS OF CLICKS PER HOUR !PPLICATION SERVERS MUST SCALE TO EXECUTE BUSINESS LOGIC ON BEHALF OF TENS OF THOUSANDS OF TRANSACTIONS .ETWORK ELEMENTS LIKE ROUTERS SWITCHES AND LOAD BALANCERS MUST SIMILARLY SCALE
#HAPTERçç
4HEç&UTUREçOFç31,ç
)N EACH OF THESE CASES THE APPROACH TO SCALING HAS BEEN HORIZONTALA SINGLE WEB SERVER GROWS INTO TWO THEN THREE THEN A DOZEN AND POTENTIALLY HUNDREDS OF SERVERS SHARING THE WORKLOAD IN THE WEB SERVER TIER 4HE SERVERS OPERATE FROM SHARED OR REPLICATED STORAGE WITH EACH SERVER ABLE TO SERVE UP ANY GIVEN PAGE ON DEMAND 4O MAKE THE SCHEME WORK THE SERVER IS IMPLANTED AS A STATELESS SYSTEM 7HENEVER POSSIBLE ANY INFORMATION THAT MUST BE RETAINED ACROSS INDIVIDUAL INTERACTIONS IS PASSED BACK TO THE CLIENT TO BE PASSED BACK INTO THE NETWORK WITH THE NEXT REQUEST !NY STATE INFORMATION THAT CANNOT BE HANDLED IN THIS WAY IS hPUSHEDv IN THE OTHER DIRECTIONBACK INTO THE DATABASE SERVER THAT UNDERLIES THE ARCHITECTURE &OR MANY HIGH VOLUME WEB SITES OR WEB SERVICES THE UNDERLYING DATABASE IS NOW BEGINNING TO EMERGE AS A BOTTLENECK 5NFORTUNATELY THE HORIZONTAL SCALING SOLUTION THAT WORKED SO WELL FOR WEB SERVERS AND APPLICATION SERVERS RUNS INTO PROBLEMS FOR THE DATABASE SERVER "Y ITS VERY NATURE THE DATABASE IS STATEFUL NOT STATELESS 4HE !#)$ !TOMICITY #ONSISTENCY )SOLATION AND $URABILITY PROPERTIES DEMAND THAT EITHER ALL THE INDIVIDUAL ELEMENTS OF A TRANSACTION ARE COMMITTED OR NONE ARE COMMITTED AND THAT CONCURRENT TRANSACTIONS SHOULD NOT INTERFERE WITH ONE ANOTHER 4HERE IS NO hBACK END LAYERv INTO WHICH STATE INFORMATION CAN BE PUSHED THE DATABASE MUST MAINTAIN THE STATE INFORMATION 4HESE CHALLENGES REPRESENT AN IMPORTANT NEW FRONTIER IN DATABASE ARCHITECTURE DESIGNING DATABASE SYSTEMS THAT CAN SCALE HORIZONTALLY WITH EFFICIENCY 3IGNIFICANT ADVANCES HAVE BEEN MADE IN RECENT YEARS AS VENDORS DEPLOYED DATABASES WITH CLUSTERING OR GRID CAPABILITY 4HESE NEW DATABASE ARCHITECTURES MUST CLEARLY SPREAD OUT THE DATABASE PROCESSING ACROSS DOZENS OF SERVERS OR MORE BUT THE INFORMATION ON THOSE SERVERS MUST BE KEPT CONSISTENT IN ALL THE WAYS DESCRIBED IN #HAPTER 0ART OF THE SOLUTION WILL COME FROM INTELLIGENTLY DIVIDING DIFFERENT TYPES OF DATA IN THE DATABASE 2EFERENCE OR LOOKUP DATA THAT DOES NOT CHANGE OR DATA THAT CHANGES ONLY INFREQUENTLY SUCH AS CUSTOMER CONTACT INFORMATION CAN BE HORIZONTALLY REPLICATED BECAUSE MAINTAINING CONSISTENCY ACROSS DOZENS OF SERVERS DOES NOT REQUIRE MUCH EFFORT 4RANSITIVE DATA SUCH AS THE DATA MAINTAINED DURING THE COURSE OF A TRANSACTION WILL PROBABLY NEED TO BE MAINTAINED ON A SINGLE hSYSTEM OF RECORDv WITHIN THE CLUSTER OF SYSTEMS WITH REQUESTS FOR THAT DATA BEING AUTOMATICALLY ROUTED TO THE CORRECT SYSTEM (OW TO DELIVER THIS ARCHITECTURE IN AN EFFICIENT SCALABLE MANNER REMAINS A NEW FRONTIER FOR COMMERCIAL PRODUCTS "UT THE DEMAND FOR DATABASES THAT CAN RESIDE hIN THE CLOUDv AND DELIVER MASSIVE SCALABILITY USING HORIZONTAL SCALING TECHNIQUES IS SUBSTANTIAL AND GROWING 3TARTUP VENDORS THAT PRESENT A PLAUSIBLE WAY OF BUILDING SUCH SYSTEMS WILL ATTRACT VENTURE FUNDING AND THE TECHNIQUES THAT EMERGE TO SUCCESSFULLY ADDRESS THE PROBLEM WILL EVENTUALLY FIND THEIR WAY INTO MAINSTREAM PRODUCTS AS OTHERS HAVE BEFORE THEM 7HEN THAT HAPPENS DATABASE PROCESSING POWER DELIVERED IN THE CLOUD THE WAY MASSIVE COMPUTING POWER AND STORAGE ARE BEING DELIVERED TODAY CAN BECOME A REALITY
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3UMMARY 31, CONTINUES TO PLAY A MAJOR ROLE IN THE COMPUTER INDUSTRY AND APPEARS POISED TO CONTINUE AS AN IMPORTANT CORE TECHNOLOGY s 31, BASED DATABASES ARE FLAGSHIP SOFTWARE PRODUCTS FOR THE THREE LARGEST SOFTWARE VENDORS IN THE WORLD -ICROSOFT /RACLE AND )"- s 31, BASED DATABASES OPERATE ON ALL CLASSES OF COMPUTER SYSTEMS FROM MAINFRAMES AND DATABASE SERVERS TO DESKTOP COMPUTER CLIENTS NOTEBOOK COMPUTERS AND HANDHELD 0$!S s !LL OF THE MAJOR ENTERPRISE APPLICATIONS USED IN LARGE ORGANIZATIONS RELY ON ENTERPRISE CLASS 31, DATABASES TO STORE AND STRUCTURE THEIR DATA s 31, BASED DATABASES HAVE RESPONDED SUCCESSFULLY TO THE CHALLENGES OF THE OBJECT MODEL WITH 31, EXTENSIONS IN OBJECTRELATIONAL DATABASES s 31, BASED DATABASES ARE RESPONDING TO THE NEEDS OF )NTERNET BASED ARCHITECTURES BY INCORPORATING 8-, AND INTEGRATING TIGHTLY WITH APPLICATION SERVERS s 0ROVIDING MASSIVE DATABASE SCALABILITY FOR CLOUD COMPUTING IS A MAJOR CHALLENGE CONFRONTING THE DATABASE MARKET TODAY
7**
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!PPENDIXES
!00%.$)8õ! 4HE 3AMPLE $ATABASE !00%.$)8õ" $"-3 6ENDOR 0ROlLES !00%.$)8õ# 31, 3YNTAX 2EFERENCE
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OST OF THE EXAMPLES IN THIS BOOK ARE BASED ON THE SAMPLE DATABASE DESCRIBED IN THIS APPENDIX 4HE SAMPLE DATABASE CONTAINS DATA THAT SUPPORTS A SIMPLE ORDER PROCESSING APPLICATION FOR A SMALL DISTRIBUTION COMPANY )T CONSISTS OF FIVE TABLES
s 02/$5#43 #ONTAINS ONE ROW FOR EACH TYPE OF PRODUCT THAT IS AVAILABLE FOR SALE s /&&)#%3 #ONTAINS ONE ROW FOR EACH OF THE COMPANYS FIVE SALES OFFICES WHERE THE SALESPEOPLE WORK s 3!,%32%03 #ONTAINS ONE ROW FOR EACH OF THE COMPANYS TEN SALESPEOPLE s #534/-%23 #ONTAINS ONE ROW FOR EACH OF THE COMPANYS CUSTOMERS s /2$%23 #ONTAINS ONE ROW FOR EACH ORDER PLACED BY A CUSTOMER &OR SIMPLICITY EACH ORDER IS ASSUMED TO BE FOR A SINGLE PRODUCT &IGURE ! GRAPHICALLY SHOWS THE FIVE TABLES THE COLUMNS THAT THEY CONTAIN AND THE PARENTCHILD RELATIONSHIPS AMONG THEM 4HE PRIMARY KEY OF EACH TABLE IS SHADED 4HE FIVE TABLES IN THE SAMPLE DATABASE CAN BE CREATED USING THE FOLLOWING #2%!4% 4!",% AND !,4%2 STATEMENTS 3IGNIFICANT VARIATIONS EXIST IN THE SUPPORT FOR DATA TYPES AND SYNTAX ACROSS AVAILABLE 31, PRODUCTS 9OU WILL THEREFORE FIND THAT THE 31, STATEMENTS SHOWN HERE MAY REQUIRE MODIFICATION TO RUN ON THE 31, BASED DATABASE THAT YOU ARE USING 4O HELP YOU SORT OUT THOSE DIFFERENCES SCRIPTS CONTAINING STATEMENTS TAILORED FOR $" -Y31, /RACLE AND 31, 3ERVER ARE AVAILABLE FOR DOWNLOAD FROM THE -C'RAW (ILL WEB SITE 3CRIPTS CONTAINING THE ).3%24 STATEMENTS REQUIRED TO LOAD SAMPLE DATA ROWS INTO THE TABLES THAT MATCH THE EXAMPLES USED THROUGHOUT THIS BOOK ARE ALSO AVAILABLE 4O ACCESS THE DOWNLOADS PAGE FOLLOW THESE STEPS
/PEN YOUR WEB BROWSER AND GO TO WWWMHPROFESSIONALCOM COMPUTINGDOWNLOAD
/N THE BANNER ACROSS THE TOP OF THE PAGE CLICK #/-054).'
!LONG THE LEFT MARGIN ABOUT HALFWAY DOWN THE PAGE CLICK THE LINK $OWNLOADS 3ECTION
3CROLL DOWN THE PAGE TO THE LINES FOR THIS BOOKS TITLE
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! REAL WORLD ORDER PROCESSING DATABASE WOULD PROBABLY CONTAIN SEVERAL DOZEN TABLES 4HE TABLES WOULD TYPICALLY CONTAIN MANY COLUMNS OF ADDITIONAL INFORMATION SUCH AS BILLING AND SHIP TO ADDRESSES AND TRANSACTIONS SUCH AS PRODUCT RETURNS AND SALES TAX CALCULATIONS 4HE TABLES FOR A REAL WORLD COMPANY WOULD ALSO CONTAIN MANY MORE ROWS THAN IN THIS SAMPLE DATABASE (OWEVER THE DATA AND TABLES IN THE SAMPLE DATABASE ARE RICH ENOUGH IN THEIR STRUCTURE TO ILLUSTRATE ALL OF THE MAJOR CAPABILITIES OF 31, AND THE SMALL NUMBER OF ROWS MAKES IT EASIER TO TRACE THE PATH FROM THE SOURCE DATA ALL THE WAY THROUGH THE QUERIES TO THE FINAL QUERY RESULTS
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HE VENDORS AND OPEN SOURCE PROJECTS PROFILED IN THIS APPENDIX INCLUDE THE MARKET SHARE LEADERS IN THE ENTERPRISE DATABASE MARKET EMERGING LEADERS IN OTHER MAJOR MARKET SEGMENTS OR PIONEERS IN EMERGING SEGMENTS #OLLECTIVELY THEY ARE RESPONSIBLE FOR THE VAST MAJORITY OF 31, RELATED REVENUES 4HE VENDORS AND THEIR PRODUCTS ARE s !STER $ATA N#LUSTER s #ODE'EAR )NTERBASE s DATA"ASED )NTELLIGENCE D"!3% 0LUS s %NCIRQ $EVICE 31, s %NTERPRISE$" 0OSTGRES 0LUS s &IREBIRD &IREBIRD s 'REENPLUM 'REENPLUM s (EWLETT 0ACKARD .ON3TOP 31, (0 /RACLE $ATABASE -ACHINE s (31,$" (31,$" s )"- $" EDITIONS )NFORMIX 3OLID$" s )NGRES #ORPORATION )NGRES s )NTERSYSTEMS #ACH£ s -ATISSE 3OFTWARE )NC -ATISSE s -ICROSOFT 31, 3ERVER s -IMER )NFORMATION 4ECHNOLOGY -IMER s .ETEZZA .ETEZZA s /RACLE #ORPORATION /RACLE EDITIONS 2DB 4IMES4EN 3LEEPY#AT s 0AR!CCEL )NC 0AR!CCEL s 0OSTGRES 0OSTGRE31, s 3TREAMBASE 3YSTEMS 3TREAMBASE s 3UN -ICROSYSTEMS -Y31,
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s 3YBASE !DAPTIVE 3ERVER %NTERPRISE 31, !NYWHERE s 4ERADATA #ORPORATION 4ERADATA s 4RUVISO )NC 4RUVISO s 5NIFY #ORPORATION 31,"ASE s 6ERTICA 3YSTEMS 6ERTICA s 8EROUND 8EROUND )NTELLIGENT $ATA 'RID
!STERõ$ATAõN#LUSTER !STER $ATA IS A VENTURE BACKED STARTUP FOCUSED ON hFRONTLINE DATA WAREHOUSINGv 4HE COMPANY TARGETS A NEW GENERATION OF DATA ANALYSIS APPLICATIONS SUCH AS ANALYZING CLICKSTREAM DATA FROM VERY LARGE WEB SITES RECOGNIZING FRAUD AND SPAM PATTERNS IN REAL TIME AND PERFORMING SOPHISTICATED FINANCIAL ANALYSIS &OR THESE APPLICATIONS IT ARGUES THAT TRADITIONAL BACK OFFICE DATA WAREHOUSES BASED ON DATA EXTRACTED AND LOADED FROM PRODUCTION DATABASES ARE INADEQUATE )NSTEAD THE COMPANY OFFERS THE N#LUSTER DATABASE AN ANALYTIC 31, DATABASE BASED ON A MULTITIERED CLUSTERED ARCHITECTURE THAT IS DESIGNED FOR FRONT OFFICE DEPLOYMENT AND CLAIMS VERY HIGH AVAILABILITY AND SCALABILITY ! COMPANION N#LUSTER #LOUD %DITION PLACES THE DATABASE hIN THE CLOUDv AND OFFERS ON DEMAND ANALYTIC DATABASE PROCESSING
#ODE'EARõ)NTERBASE #ODE'EAR IS A DIVISION OF %MBARCADERO 4ECHNOLOGIES AND IS THE COMPANY CURRENTLY RESPONSIBLE FOR THE )NTERBASE $"-3 )NTERBASE IS WELL SUITED FOR EMBEDDED DATABASE APPLICATIONS WITH THE ENTIRE SYSTEM FITTING IN ONLY A FEW TENS OF MEGABYTES OF DISK SPACE 4HE SYSTEM IS DESIGNED TO OPERATE WITHOUT A DATABASE ADMINISTRATOR AND WAS ONE OF THE FIRST TO IMPLEMENT MULTIVERSION CONCURRENCY CONTROL 4HE PRODUCT HAS HAD A LONG AND CIRCUITOUS HISTORY )T WAS ORIGINALLY DEVELOPED AS A DATABASE FOR THE !POLLO ENGINEERING WORKSTATION IN THE MID S RIGHTS TO )NTERBASE WERE SOLD TO !SHTON 4ATE WHICH WAS THE LEADING 0# DATABASE VENDOR OF THE ERA "ORLAND A PROMINENT VENDOR OF SOFTWARE DEVELOPMENT TOOLS PURCHASED !SHTON 4ATE IN AND )NTERBASE BECAME A "ORLAND PRODUCT .EARLY A DECADE LATER IN THE S "ORLAND DECIDED TO CHANGE THE LICENSING FOR )NTERBASE AND TO MAKE IT AVAILABLE AS AN OPEN SOURCE PRODUCT 4HE OPEN SOURCE VERSION OF THE PRODUCT REMAINS ACTIVE AS THE &IREBIRD PROJECT BUT THE COMMERCIALLY LICENSED PROPRIETARY VERSION OF THE PRODUCT IS NOW AVAILABLE THROUGH #ODE'EAR%MBARCADERO WHERE ITS DEVELOPMENT CONTINUES
õDATA"ASEDõ)NTELLIGENCEõD"!3%õ0LUS 4HE DATA"ASED )NTELLIGENCE D") COMPANY IS THE CURRENT HOME OF D"!3% A PIONEERING DATABASE FROM THE EARLIEST DAYS OF THE PERSONAL COMPUTER OVER YEARS AGO &OR YEARS THE D"!3% PRODUCTS ORIGINALLY DEVELOPED BY !SHTON 4ATE WERE THE RUNAWAY VOLUME LEADERS IN THE 0# DATABASE CATEGORY WITH MILLIONS OF COPIES DELIVERED AND A PEAK MARKET SHARE OF OVER PERCENT !S PERSONAL COMPUTERS GREW MUCH MORE POWERFUL ADVANCED MINICOMPUTER DATABASES INVADED THE 0# DATABASE SEGMENT EXERTING CONSIDERABLE COMPETITIVE PRESSURE ON D"!3% 4HE MOST NOTABLE OF THESE WAS -ICROSOFTS 31, 3ERVER DERIVED FROM 3YBASES MINICOMPUTER DATABASE !T THE SAME TIME COMPETITIVE hCLONESv OF D"!3% BEGAN TO APPEAR INCLUDING &OXBASE WHICH APPEARED IN !LTHOUGH THE D"!3% DATABASE AND ITS CLONES OFFERED LIMITED FUNCTIONALITY THE D"!3% PROGRAMMING LANGUAGE WAS USED TO DEVELOP A WIDE RANGE OF BUSINESS APPLICATIONS ON 0#S AND DEVELOPED A STRONG PROGRAMMER FOLLOWING
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%NCIRQõ$EVICE31, %NCIRQS $EVICE31, IS A 31, BASED DATABASE TARGETED FOR EMBEDDED DEVICE APPLICATIONS 7ITH ITS SMALL FOOTPRINT $EVICE31, PROVIDES A DATA MANAGEMENT FOUNDATION FOR SET TOP BOXES ALL IN ONE PRINTERFAXSCANNERCOPIER PRODUCTS AUTOMOTIVE ENTERTAINMENT AND CONTROL SYSTEMS THAT NEED THE FLEXIBILITY OF 31, BUT ARE HIGHLY MEMORY CONSTRAINED 4HE COMPANY CLAIMS THE SMALLEST FOOTPRINT OF ANY EMBEDDED 31, IMPLEMENTATION REQUIRING ONLY A FEW TENS OF KILOBYTES OF MEMORY IN ITS MINIMUM CONFIGURATION -ORE RECENTLY THE COMPANY HAS USED ITS CORE TECHNOLOGY TO ADDRESS THE EMERGING MARKET FOR #OMPLEX %VENT 0ROCESSING #%0 4HESE APPLICATIONS MUST PROCESS HIGH VOLUMES OF STREAMING DATA GENERATED BY DATA AND TELECOMMUNICATIONS NETWORKS SECURITIES TRADING AND NETWORK DEVICES )N THIS MARKET THE COMPANY COMPETES WITH STARTUP STREAMING DATABASE VENDORS
%NTERPRISE$"õ0OSTGRESõ0LUS %NTERPRISE$" OFFERS A COMMERCIAL VERSION OF THE 0OSTGRES OPEN SOURCE DATABASE OPTIMIZED FOR TRANSACTION INTENSIVE WORKLOADS AND HIGH SCALABILITY 4HE COMPANYS 0OSTGRES 0LUS PRODUCT AUGMENTS THE 0OSTGRES OPEN SOURCE CORE WITH TUNING MANAGEMENT AND MONITORING TOOLS AND FEATURES SUCH AS AN IN MEMORY CACHING LAYER AND ENCRYPTION ! SECOND PRODUCT 0OSTGRES 0LUS !DVANCED 3ERVER FURTHER EXTENDS 0OSTGRES WITH /RACLE COMPATIBILITY FEATURES WHICH PROVIDE /RACLE STYLE 31, SYNTAX /RACLE COMPATIBLE DATA TYPES SUPPORT FOR /RACLES 0,31, LANGUAGE AND SUPPORT FOR /RACLES PROPRIETARY /RACLE #ALL )NTERFACE /#) &OUNDED IN THE COMPANY IS VENTURE BACKED AND BASED IN .EW *ERSEY
&IREBIRDõ&IREBIRD &IREBIRD IS AN OPEN SOURCE 31, DATABASE TARGETED FOR EMBEDDED APPLICATIONS )T FEATURES A RELATIVELY RICH 31, IMPLEMENTATION INCLUDING !#)$ TRANSACTIONS REFERENTIAL INTEGRITY BIT SUPPORT VERSIONING STORED PROCEDURES AND TRIGGERS IN A VERY SMALL FOOTPRINT 4HE &IREBIRD PROJECT WAS ORIGINALLY ESTABLISHED IN AND BEGAN WITH THE OPEN SOURCE VERSION OF "ORLANDS )NTERBASE DATABASE PRODUCT )T HAS SINCE BEEN SIGNIFICANTLY REWRITTEN AND DEVELOPMENT CONTINUES USING THE OPEN SOURCE MODEL UNDER THE COORDINATION OF THE &IREBIRD PROJECT
'REENPLUM 'REENPLUM IS A VENTURE BACKED DATABASE STARTUP FOCUSED ON THE DATA WAREHOUSING MARKET )TS 'REENPLUM DATABASE IS BASED ON THE OPEN SOURCE 0OSTGRES TECHNOLOGY WHICH THE COMPANY HAS TUNED AND OPTIMIZED TO SUPPORT LARGE DATA WAREHOUSE DATABASES ON CLUSTERS OF COMMODITY SERVERS 7ITH A hSHARED NOTHINGv ARCHITECTURE THE 'REEENPLUM SOFTWARE
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&OR A WHILE !SHTON 4ATE RESPONDED TO THE COMPETITIVE CHALLENGE WITH A MULTIPRONGED STRATEGY AS IT SIMULTANEOUSLY UNDERTOOK A MAJOR REWRITE OF D"!3% ACQUIRED OTHER DATABASE PRODUCTS AND ENTERED INTO A MARKETING AGREEMENT WITH -ICROSOFT TO SELL 31, 3ERVER IN THE RETAIL MARKET .ONE OF THESE INITIATIVES PROVED SUCCESSFUL AND IN "ORLAND ACQUIRED !SHTON 4ATE PRIMARILY BECAUSE OF THE LARGE D"!3% INSTALLED BASE 2ESPONSIBILITY FOR D"!3% DEVELOPMENT PASSED TO D") IN AND IT HAS LAUNCHED A SUCCESSOR PRODUCT CALLED D"!3% 0LUS 4ODAY D"!3% PLAYS A ROLE AS A DEVELOPMENT ENVIRONMENT AND FRONT END FOR OTHER RELATIONAL DATABASES AND IS COMPLEMENTED BY D1UERY FOR BUSINESS INTELLIGENCE APPLICATIONS 0ROGRAMMERS CAN STILL TAKE ADVANTAGE OF THE ENHANCED D"!3% PROGRAMMING LANGUAGE AND VIA /$"# CONNECTORS USE IT TO ACCESS DATA STORED IN /RACLE 31, 3ERVER 3YBASE $" AND A HALF DOZEN OTHER $"-3S
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DISTRIBUTES WAREHOUSE CONTENTS OVER MANY LOW COST SERVER SYSTEMS TO EFFICIENTLY SUPPORT WHAT IT CLAIMS ARE hPETABYTE SCALEv DATABASES )T THEN PARALLELIZES QUERIES ACROSS THE SERVERS TO PROVIDE BUSINESS INTELLIGENCE ANSWERS QUICKLY DESPITE LARGE DATABASE SIZES 5NLIKE SOME VENTURE BACKED RIVALS OFFERING DATABASE APPLIANCES TUNED FOR DATA WAREHOUSING 'REENPLUM PRIDES ITSELF ON A SOFTWARE ONLY APPROACH AND HAS ESTABLISHED PARTNERSHIPS WITH 3UN -ICROSYSTEMS AND OTHERS TO TAKE ADVANTAGE OF HIGH DENSITY LOW COST BLADE SERVERS
(EWLETT 0ACKARDõ#OMPANY (EWLETT 0ACKARD (0 IS ONE OF THE LARGEST COMPUTER SYSTEMS VENDORS AND DATABASE MANAGEMENT HAS HISTORICALLY PLAYED AN IMPORTANT ROLE IN (0S PRODUCT LINE )N THE S THE COMPANY PIONEERED DATABASE MANAGEMENT ON MINICOMPUTERS WITH ITS )MAGE $"-3 WHICH RAN ON (0 MINICOMPUTERS IN ENGINEERING AND TECHNICAL APPLICATIONS AND ITS )MAGE $"-3 WHICH RAN ON (0 MINICOMPUTERS IN COMMERCIAL APPLICATIONS 4HE )MAGE $"-3 WAS BASED ON THE NETWORK DATA MODEL )N THE MID S (0 INTRODUCED AN UPGRADED $"-3 NAMED !LLBASE WHICH PROVIDED BOTH BACKWARD COMPATIBILITY WITH THE )MAGE DATABASE AND A 31, BASED RELATIONAL INTERFACE (0S SIGNIFICANT MARKET SHARE IN MINICOMPUTERS AND LATER IN 5.)8 BASED SERVERS ALSO MADE IT AN IMPORTANT PLATFORM FOR THE INDEPENDENT $"-3 VENDORS INCLUDING )NGRES )NFORMIX /RACLE AND 3YBASE 4HE COMPANY EVENTUALLY ABANDONED !LLBASE IN FAVOR OF STRONG PARTNERSHIPS WITH THE INDEPENDENT VENDORS (0 REENTERED THE DATABASE MARKET hTHROUGH THE BACK DOORv WHEN IT ACQUIRED #OMPAQ IN #OMPAQ HAD EARLIER ACQUIRED 4ANDEM #OMPUTERS THE LEADING MANUFACTURER OF FAULT TOLERANT COMPUTER SYSTEMS AND SERVERS OPTIMIZED FOR EXTREMELY HIGH AVAILABILITY $ATABASE MANAGEMENT FOR 4ANDEMS .ON3TOP SYSTEMS IS PROVIDED BY A 31, BASED RELATIONAL $"-3 CALLED .ON3TOP 31, WHICH DELIVERS A HIGH LEVEL OF AVAILABILITY AND FAULT TOLERANCE AS A DATABASE SERVER .ON3TOP SYSTEMS AND DATABASES ARE STILL WIDELY INSTALLED AS THE SERVER INFRASTRUCTURE FOR BANK !4- NETWORKS AND IN STOCK TRADING AND OTHER FINANCIAL SERVICES APPLICATIONS -ORE RECENTLY (0 HAS ENTERED THE DATA WAREHOUSING MARKET THROUGH A PARTNERSHIP WITH /RACLE #ORPORATION 4HE TWO COMPANIES HAVE JOINTLY DEVELOPED THE (0 /RACLE %XADATA $ATABASE -ACHINE WHICH TIGHTLY INTEGRATES /RACLES DATABASE SOFTWARE WITH (0 HARDWARE AND STORAGE 4HE $ATABASE -ACHINE IS OPTIMIZED FOR DATA WAREHOUSING APPLICATIONS AND WAS DESIGNED TO COMPETE WITH SIMILAR SYSTEMS FROM 4ERADATA AND .ETEZZA )T IS SOLD AS A DATA WAREHOUSING APPLIANCE BY /RACLES DATABASE SALES TEAM
(31,$"õ(31,$" 4HE (31, $ATABASE %NGINE (31,$" IS AN OPEN SOURCE RELATIONAL DATABASE WRITTEN IN *AVA )T FEATURES A SMALL FOOTPRINT UNDER +" WHEN EMBEDDED IN APPLETS WITH A FAIRLY RICH 31, SYNTAX AND A CHOICE OF EMBEDDED OR SERVER ARCHITECTURE (31,$" SUPPORTS BOTH DISK BASED AND IN MEMORY TABLES 4HE PRODUCT HAS ITS ORIGINS IN THE PROPRIETARY *AVA BASED (YPERSONIC DATABASE FROM THE EARLY S BUT DEVELOPMENT SINCE HAS BEEN COORDINATED AS AN OPEN SOURCE PROJECT )N ADDITION TO ITS ROLE AS AN EMBEDDABLE LIGHTWEIGHT *AVA DATABASE (31,$" IS THE DATABASE COMPONENT OF THE /PEN/FFICEORG SUITE OF OPEN SOURCE OFFICE PRODUCTIVITY SOFTWARE
)"-õ#ORPORATIONõ$" õ)NFORMIX )"- IS THE LARGEST COMPUTER TECHNOLOGY VENDOR IN THE WORLD AND SOFTWARE COMPOSES A LARGE AND GROWING SHARE OF ITS TOTAL REVENUES $ATABASES HAVE BEEN A MAJOR SOURCE OF SOFTWARE
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s $" FOR Z/3 IS )"-S FLAGSHIP RELATIONAL $"-3 PRODUCT )T IS A LARGE COMPLEX SOFTWARE PRODUCT THAT RUNS ON )"- MAINFRAME SYSTEMS UNDER THE Z OPERATING SYSTEM SUCCESSOR TO /3 AND ITS ANCESTOR -63 4HIS PRODUCT SUPPORTS SOME OF THE LARGEST TRANSACTION PROCESSING DATABASES IN THE WORLD AND OFFERS THE BROADEST FEATURE SET OF )"-S DATABASE PRODUCTS SPANNING VERY HIGH PERFORMANCE TRANSACTION PROCESSING DATA WAREHOUSING AND TIGHTLY INTEGRATED 8-, SUPPORT s $" FOR ,INUX 5.)8 AND 7INDOWS IS A DATABASE MANAGEMENT SYSTEM FOR SERVER SYSTEMS FROM DEPARTMENTAL SCALE UP TO THE LARGEST 5.)8 BASED SERVER CLUSTERS THAT POWER LARGE CORPORATE DATA CENTERS ,IKE ITS MAINFRAME COUNTERPART IT INTEGRATES RELATIONAL AND 8-, DATA &OR A TIME THE PRODUCT WAS NAMED $" 5NIVERSAL $ATABASE 5$" TO DISTINGUISH IT FROM THE MAINFRAME VERSION OF $" WHICH WAS BUILT ON A DIFFERENT CODE BASE 4HE SOFTWARE COMES IN SEVERAL EDITIONS !N ENTRY LEVEL %XPRESS %DITION IS AVAILABLE AT NO CHARGE TO COMPETE WITH OPEN SOURCE DATABASES ! MIDRANGE 7ORKGROUP %DITION HAS FEATURES TAILORED FOR DEPARTMENTAL SYSTEMS 4HE %NTERPRISE %DITION PROVIDES FULL FUNCTIONALITY APPROACHING THAT OF MAINFRAME $" s $" %VERYWHERE EXTENDS THE $" FAMILY TO SUPPORT MOBILE DEVICES AND EMBEDDED DATABASE APPLICATIONS )N ADDITION TO ITS DATA MANAGEMENT CAPABILITIES THIS EDITION OF $" PROVIDES SUPPORT FOR hOCCASIONALLY CONNECTEDv ENVIRONMENTS WITH ITS DATA SYNCHRONIZATION FEATURES $" %VERYWHERE COMPETES WITH 3YBASES 31, !NYWHERE WHICH DOMINATES THE MOBILE MARKET SEGMENT s )NFORMIX WAS ACQUIRED BY )"- IN AFTER TWO DECADES OF ESTABLISHING ITSELF AS ONE OF THE MOST INNOVATIVE DATABASES ON 5.)8 BASED SYSTEMS /NE OF THE EARLIEST 5.)8 BASED DATABASES THE )NFORMIX PRODUCT WAS REWRITTEN TO SUPPORT 31, IN AND WAS AMONG THE FIRST TO FULLY TAKE ADVANTAGE OF THE 3-0 5.)8 SERVERS THAT DOMINATED THE S )N )NFORMIX ACQUIRED )LLUSTRA A PIONEERING OBJECT RELATIONAL DATABASE VENDOR MAKING IT THE FIRST MAJOR 31, DATABASE VENDOR TO EMBRACE THE OBJECTRELATIONAL TREND #HALLENGES WITH THE )LLUSTRA ACQUISITION AND INTERNAL MANAGEMENT PROBLEMS STALLED THE COMPANYS GROWTH IN THE LATE S AND )"- ACQUIRED IT PRIMARILY FOR ITS USER BASE OF OVER CUSTOMERS )"- CONTINUES TO SUPPORT AND ENHANCE THE )NFORMIX PRODUCT AS A 5.)8 BASED /,40 DATABASE s 3OLID$" IS AN IN MEMORY RELATIONAL DATABASE THAT )"- ACQUIRED IN EARLY !T THIS WRITING )"- OFFERS THE PRODUCT IN TWO EDITIONS )"- 3OLID$" IS A PERSISTENT IN MEMORY STAND ALONE DATABASE THAT PROVIDES EXTREMELY LOW LATENCY DATABASE ACCESS FOR REAL TIME TRANSACTION PROCESSING APPLICATIONS )"- 3OLID$" 5NIVERSAL #ACHE USES THE SOLID TECHNOLOGY AS AN IN MEMORY CACHE THAT ACCELERATES THE PERFORMANCE OF A RANGE OF DISK BASED 2$"-3S )"-S ANNOUNCED DIRECTION IS TO MORE TIGHTLY INTEGRATE THE 3OLID$" INTO ITS MAINSTREAM DATABASE PRODUCT FAMILY 4HESE )"- DATABASE PRODUCTS ARE PART OF A MUCH BROADER )"- FAMILY OF INFRASTRUCTURE SOFTWARE PRODUCTS THAT HAS BEEN BUILT THROUGH A COMBINATION OF )"- DEVELOPMENT AND ACQUISITION 4HE 7EB3PHERE FAMILY ENJOYS A LARGE MARKET SHARE IN THE APPLICATION SERVER
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REVENUE AT )"- FOR SEVERAL DECADES AND STILL MAKE UP THE LIONS SHARE OF ITS SOFTWARE BUSINESS 4WO OLDER NONRELATIONAL MAINFRAME DATABASE PRODUCTS)-3 A HIERARCHICAL $"-3 AND $, $ATA ,ANGUAGE A HIERARCHICAL DATABASE ACCESS METHODSTILL CONTRIBUTE TO )"-S SALES BUT 31, BASED RELATIONAL PRODUCTS DOMINATE
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MARKET AND #OGNOS ACQUIRED IN LATE HOLDS A SIMILAR POSITION IN THE BUSINESS INTELLIGENCE MARKET !LONG WITH HUNDREDS OF OTHER PRODUCTS THESE COMPOSE A PRODUCT FAMILY THAT ALLOWS )"- TO OFFER hONE STOP SHOPPINGv FOR KEY SOFTWARE PRODUCTS TO THE LARGEST )4 SHOPS IN THE WORLD
)NGRESõ#ORPORATIONõ)NGRES 4HE )NGRES DATABASE TRACES ITS ORIGINS TO ONE OF THE EARLIEST RELATIONAL DATABASE PROTOTYPES BUILT AT THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEY 4HE ORIGINAL "ERKELEY )NGRES CODE WAS READILY AVAILABLE AT LOW COST AND SEVERAL "ERKELEY STUDENTS AND PROFESSORS FORMED A COMPANY 2ELATIONAL 4ECHNOLOGY )NC LATER RENAMED )NGRES #ORPORATION TO PRODUCE A COMMERCIAL VERSION $URING THE EARLY AND MIDDLE S THE )NGRES $"-3 AND ITS 15%, DATABASE LANGUAGE WAS A MAJOR RIVAL TO 31, AND THERE WAS A PARTICULARLY STRONG COMPETITIVE RIVALRY BETWEEN )NGRES AND /RACLE IN THE MIDRANGE $"-3 MARKET 7HEN 31, EMERGED AS THE STANDARD DATABASE LANGUAGE 2ELATIONAL 4ECHNOLOGY ADAPTED )NGRES TO SUPPORT BOTH 15%, AND 31, )NGRES WAS FIRST IMPLEMENTED ON $IGITAL MINICOMPUTERS AND ENJOYED EARLY SUCCESS IN THE ACADEMIC COMMUNITY BUT THE CENTER OF GRAVITY MOVED TO 5.)8 BASED AND LATER ,INUX BASED PLATFORMS WHERE IT REMAINS TODAY 5LTIMATELY )NGRES CREATED A SUBSTANTIAL AND LOYAL INSTALLED BASE BUT LOST THE DATABASE WARS TO /RACLE 4HE COMPANY WAS ACQUIRED BY !3+ A MAKER OF MANUFACTURING APPLICATIONS SOFTWARE IN THE EARLY S &OUR YEARS LATER THE COMBINED !3+)NGRES WAS ACQUIRED BY #OMPUTER !SSOCIATES #! WHICH HAD PERFECTED A BUSINESS MODEL OF ACQUIRING OUT OF FAVOR SOFTWARE PRODUCTS WITH LARGE INSTALLED BASES #! CONTINUED TO ENHANCE THE PRODUCT FOR THE NEXT DECADE BUT ULTIMATELY DECIDED TO RELEASE IT AS AN OPEN SOURCE DATABASE PRODUCT IN 4HIS GAVE THE PRODUCT A NEW LEASE ON LIFE AS IT NOW PRESENTED A POWERFUL VERY MATURE DATABASE PRODUCT AVAILABLE AT VERY LOW COST #! PARTNERED WITH A PRIVATE EQUITY FIRM TO FORM A NEW COMPANY )NGRES #ORPORATION TO PROVIDE SUPPORT AND SERVICES FOR THE OPEN SOURCE )NGRES )NGRES #ORPORATION TOUTS THE ADVANTAGES OF TODAYS )NGRES AS HIGH SECURITY HIGH AVAILABILITY HIGH SCALABILITY AND HIGH PERFORMANCE )N ADDITION TO THE )NGRES DATABASE THE COMPANY OFFERS AN INTEGRATED )NGRES ,INUX SOFTWARE PACKAGE A hSOFTWARE APPLIANCEv A SET OF DEVELOPMENT ENVIRONMENTS AND A DATABASE MIDDLEWARE PRODUCT THAT INTEGRATES ACROSS UNDERLYING /RACLE 31, 3ERVER $" AND )NGRES DATABASES
)NTERSYSTEMSõ#ACH£ )NTERSYSTEMS TOUTS ITS #ACH£ DATABASE AS THE hWORLDS FASTEST OBJECT DATABASEv 4HE ORIGINS OF BOTH THE COMPANY AND THE PRODUCT GO ALL THE WAY BACK TO THE S BEFORE THE ADVENT OF THE RELATIONAL DATABASE TO A COMPUTER OPERATING SYSTEM AND PROGRAMMING LANGUAGE NAMED -5-03 -ASSACHUSETTS 'ENERAL (OSPITAL 5TILITY -ULTI 0ROGRAMMING 3YSTEM DEVELOPED AT -ASSACHUSETTS 'ENERAL (OSPITAL 4HE SYSTEM WAS DESIGNED FOR DATABASE ORIENTED APPLICATIONS AND ACHIEVED CONSIDERABLE POPULARITY IN THE NEXT TWO DECADES FOR HEALTH CARE MEDICAL AND FINANCIAL INFORMATION SYSTEMS 4HE -5-03 SYSTEM ACTUALLY ACHIEVED THE STATUS OF AN !.3) STANDARD IN AND )NTERSYSTEMS WAS FOUNDED AS ONE OF THE LEADING SUPPLIERS OF -5-03 SOFTWARE 4HE COMPANY EVENTUALLY ACQUIRED MANY OF ITS RIVALS AND CONSOLIDATED THE ACQUIRED PRODUCTS UNDER THE #ACH£ BRAND IN THE LATE S 4HE CODE HAS OF COURSE UNDERGONE SUBSTANTIAL ENHANCEMENT AND MODIFICATION OVER THE YEARS 4HE #ACH£ PRODUCT IS DOUBLY POSITIONED AS AN OBJECT ORIENTED DATABASE AND A hMULTIDIMENSIONAL DATA ENGINE v AND UNLIKE MOST 31, BASED PRODUCTS IT DOES NOT HAVE A RELATIONAL ARCHITECTURE AT ITS FOUNDATION (OWEVER 31, ACCESS TO DATA PLAYS A MAJOR ROLE IN
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-ATISSEõ3OFTWARE õ)NCõ-ATISSE -ATISSE IS DESCRIBED AS A hPOST OBJECT RELATIONALv DATABASE EXTENDING THE EVOLUTION OF DATABASE TECHNOLOGY PAST THE RELATIONAL OBJECT ORIENTED AND OBJECT RELATIONAL PHASES 4HE DATABASE SUPPORTS AN EXTENDED 31, LANGUAGE DESIGNED TO EXTEND THE DATA MODEL BEYOND TABLES TO INCLUDE hSEMANTIC NETWORKSv OF DATA 4HE PRODUCT ALSO OFFERS DISTRIBUTED DATABASE CAPABILITIES TUNED FOR BLADE SERVER CONFIGURATIONS 4HE COMPANYS CUSTOMER BASE INCLUDES COMPANIES IN THE BANKINGFINANCIAL SERVICES AND TELECOM MARKETS
-ICROSOFTõ#ORPORATION -ICROSOFT IS THE LARGEST VENDOR OF PERSONAL COMPUTER SOFTWARE IN THE WORLD )T DOMINATES SEVERAL SECTORS OF 0# AND WORKGROUP SOFTWARE INCLUDING OFFICE APPLICATIONS -3 /FFICE AND ITS SPREADSHEET WORD PROCESSING PRESENTATION E MAIL CLIENT AND OTHER COMPONENTS E MAIL -ICROSOFT %XCHANGE SERVER DIRECTORY SERVICES -ICROSOFT !CTIVE $IRECTORY AND WORKGROUP SOFTWARE -ICROSOFT 3HARE0OINT AS WELL AS THE VARIOUS 7INDOWS OPERATING SYSTEM EDITIONS ON WHICH THAT SOFTWARE RUNS -ICROSOFT 31, 3ERVER IS A MAJOR COMPONENT OF THE COMPANYS WORKGROUP SOFTWARE PRODUCT LINE )T SERVES BOTH AS A STAND ALONE RELATIONAL DATABASE SYSTEM AND AS AN EMBEDDED DATABASE COMPONENT OF OTHER SERVER SIDE SYSTEMS 5NTIL -ICROSOFTS PRODUCT LINEUP DID NOT INCLUDE A DATABASE MANAGEMENT SYSTEM 7ITH THE ANNOUNCEMENT OF ITS /3 %XTENDED %DITION IN )"- PROVIDED A PERSONAL COMPUTER OPERATING SYSTEM WITH AN INTEGRATED $"-3 AND DATA COMMUNICATIONS )N -ICROSOFT RESPONDED WITH 31, 3ERVER A VERSION OF THE 3YBASE $"-3 PORTED TO /3 -ICROSOFT SOON ABANDONED /3 IN FAVOR OF ITS OWN 7INDOWS OPERATING SYSTEM BUT -ICROSOFT RETAINED ITS COMMITMENT TO 31, 3ERVER PORTING IT TO SERVER VERSIONS OF 7INDOWS !T THE TIME THE 0# DATABASE MARKET WAS STILL DOMINATED BY !SHTON 4ATES D"!3% DATABASE AND -ICROSOFT HEDGED ITS BET ON 31, 3ERVER BY ACQUIRING &OXBASE WHICH OFFERED A D"!3% CLONE IN THE EARLY S 4HE &OXBASE PRODUCT WAS DISPLACED FAIRLY QUICKLY BY -ICROSOFT !CCESS AN INTERNALLY DEVELOPED PRODUCT WHICH PROVIDED A GRAPHICAL USER INTERFACE AN EASY TO USE 0# DATABASE AND /$"# CONNECTIVITY TO hREALv RELATIONAL DATABASES INCLUDING 31, 3ERVER -ICROSOFTS COMMITMENT TO 31, 3ERVER HAS GROWN OVER THE YEARS AND TODAY IT IS ONE OF THE DOZEN MOST IMPORTANT -ICROSOFT PRODUCTS $ESPITE COMPETITION FROM /RACLE )"- AND OTHERS -ICROSOFTS 31, 3ERVER ENJOYS THE ADVANTAGE THAT DERIVES FROM -ICROSOFTS OWNERSHIP OF 7INDOWS AND IT IS THE MOST POPULAR DATABASE FOR THE 7INDOWS SERVER PLATFORM !S A RESULT IT HOLDS A LARGE SHARE OF THE WORKGROUP AND DEPARTMENTAL DATABASE MARKETS -ICROSOFT HAS DRAMATICALLY EXPANDED THE SCOPE OF 31, 3ERVER OVER THE YEARS )TS FEATURE SET HAS EXPANDED BEYOND THOSE EXPECTED OF A DEPARTMENTAL DATABASE TO EMBRACE MANY DIFFERENT ASPECTS OF DATABASE PROCESSING 31, 3ERVER IS WELL SUITED TO DEPARTMENTAL OR DIVISION LEVEL /,40 AND IT HAS EXTENSIVE FEATURES TO SUPPORT DATA WAREHOUSING ,IKE THE FLAGSHIP OFFERINGS FROM /RACLE AND )"- 31, 3ERVER HAS INTEGRATED OBJECT DATABASE CAPABILITIES AND EXTENSIVE SUPPORT FOR 8-, -ICROSOFTS AMBITION FOR 31, 3ERVER AND THE UNDERLYING 7INDOWS SERVER OPERATING SYSTEMS IS TO STEADILY DRIVE INTO LARGER AND MORE COMPLEX DATA CENTER ENVIRONMENTS )N 31, 3ERVER -ICROSOFT ADDED DATA ENCRYPTION AUDITING AND MANAGEMENT CAPABILITIES TO SUPPORT THAT EFFORT 4HAT REVISION ALSO ADDED SUPPORT FOR SPATIAL DATA EXPANDED 8-,
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MOST #ACH£ IMPLEMENTATIONS AND THE #ACH£ DATABASE SUPPORTS BOTH /$"# AND *$"# !0)S )N ADDITION TO THE DATABASE THE #ACH£ SUITE INCLUDES AN INTEGRATED APPLICATION SERVER AND WEB SERVER
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SUPPORT AND USER DEFINED DATA TYPES TO ADDRESS A BROADER RANGE OF APPLICATIONS AND THEIR DATA &INALLY 31, 3ERVER ENHANCED THE BUSINESS INTELLIGENCE CAPABILITIES OF 31, 3ERVER AND OFFERED A MAJOR EXPANSION OF ITS ENTERPRISE REPORTING CAPABILITY 7ITH THESE CAPABILITIES THE POPULARITY OF 31, 3ERVER SHOULD CONTINUE TO INCREASE LIMITED MOSTLY BY ITS BEING RESTRICTED TO THE 7INDOWS SERVER PLATFORM
-IMERõ)NFORMATIONõ4ECHNOLOGYõ-IMER 4HE -IMER DATABASE NAMED AFTER THE .ORSE GOD OF WISDOM HAD ITS ORIGINS OVER YEARS AGO AT THE 5NIVERSITY OF 5PPSALA IN 3WEDEN 4HE UNIVERSITY PROJECT SPAWNED A COMPANY OF THE SAME NAME WHICH HAS FOUND A NICHE SUPPLYING 31, BASED DATABASES FOR EMBEDDED AND MOBILE APPLICATIONS 4HE PRODUCT IS AVAILABLE IN THREE EDITIONS -IMER 31, %MBEDDED IS OPTIMIZED FOR SMALL FOOTPRINT SEVERAL HUNDRED KILOBYTES AND ZERO MAINTENANCE -IMER 31, -OBILE IS OPTIMIZED FOR MOBILE PHONES AND OTHER HANDHELD DEVICES THAT REQUIRE LOCAL DATABASE OPERATION AND CONNECTION TO THE ENTERPRISE -IMER 31, %NTERPRISE OPERATES AS A CENTRAL hHOME BASE v BACKING THE %MBEDDED OR -OBILE PRODUCTS OR ACTING AS A STAND ALONE ENTERPRISE DATABASE 4HE COMPANY PRIDES ITSELF ON ITS STANDARDS COMPLIANCE WITH AN EMPLOYEE SERVING ON THE )3/ 31, STANDARDS COMMITTEE
.ETEZZAõ#ORPORATIONõ.ETEZZA .ETEZZA OFFERS A DATABASE APPLIANCE FOCUSED ON DATA WAREHOUSING AND BUSINESS INTELLIGENCE APPLICATIONS 4HE COMPANY CLAIMS TO SIMPLIFY DATA WAREHOUSING BY DEPLOYING PURPOSE BUILT APPLIANCES WITH A TIGHTLY INTEGRATED AND TUNED COMBINATION OF HARDWARE AND SOFTWARE )TS APPLIANCES USE A MASSIVELY PARALLEL PROCESSING -00 APPROACH SPREADING THE DATA IN THE WAREHOUSE OVER MANY INDIVIDUAL PROCESSING ELEMENTS %ACH ELEMENT INCLUDES A DISK DRIVE A MICROPROCESSOR AND A CUSTOM .ETEZZA LOGIC CHIP DESIGNED TO OPTIMIZE AND OFFLOAD QUERY PROCESSING AS DATA STREAMS OFF THE DISK 3INCE MANY BUSINESS INTELLIGENCE AND ANALYTICS QUERIES REQUIRE A SEQUENTIAL SCAN OF ENTIRE TABLES THE COMPANY ARGUES THAT THIS APPROACH CAN FAR OUTPERFORM CONVENTIONAL DATABASE SOFTWARE RUNNING ON STANDARD COMPUTER SERVERS WHERE THE DATA MUST BE MOVED FROM THE DISK TO THE #05 MEMORY FOR PROCESSING .ETEZZA DEFIED A HISTORY OF FAILED DATABASE APPLIANCE STARTUPS THE COMPANY GREW RAPIDLY FROM A VENTURE BACKED STARTUP TO A COMPANY WITH MORE THAN MILLION IN REVENUE AND HAD ITS INITIAL PUBLIC OFFERING IN )T COUNTS LARGE RETAILERS INSURANCE COMPANIES AND TELECOM OPERATORS AMONG ITS CUSTOMERS
/RACLEõ#ORPORATION /RACLE #ORPORATION WAS THE FIRST $"-3 VENDOR TO OFFER A COMMERCIAL 31, PRODUCT PRECEDING )"-gS OWN ANNOUNCEMENT BY ALMOST TWO YEARS $URING THE S /RACLE GREW TO BECOME THE LARGEST INDEPENDENT $"-3 VENDOR 4HE COMPANY SUBSEQUENTLY EXPANDED INTO ENTERPRISE APPLICATIONS SOFTWARE AND MIDDLEWARE AND BECAME A MAJOR CONSOLIDATOR OF ENTERPRISE SOFTWARE COMPANIES IN THE EARLY S THROUGH AN ACQUISITION SPREE ,ED BY ITS HIGH PROFILE FOUNDER AND #%/ ,ARRY %LLISON THE COMPANY IS ONE OF THE MOST SUCCESSFUL AND LARGEST SOFTWARE COMPANIES IN THE WORLD SECOND ONLY TO -ICROSOFT IN REVENUES 4HE /RACLE $"-3 WAS ORIGINALLY IMPLEMENTED ON $IGITAL MINICOMPUTERS BUT SALES OF /RACLE DRAMATICALLY ACCELERATED WITH THE POPULARITY OF 5.)8 BASED AND LATER ,INUX BASED SYSTEMS WHICH GENERATE THE MAJORITY OF /RACLES MULTI BILLION DOLLAR DATABASE REVENUES 4HE /RACLE $"-3 WAS ORIGINALLY BASED ON )"-S 3YSTEM2 PROTOTYPE AND REMAINED GENERALLY COMPATIBLE WITH )"-gS 31, BASED PRODUCTS IN THE EARLY YEARS !S ITS MARKET SHARE GREW
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/RACLE STRUCK OUT ON ITS OWN CREATING PROPRIETARY EXTENSIONS LIKE ITS 0,31, PROGRAMMING LANGUAGE $URING THE hDATABASE WARSv OF THE S /RACLE AGGRESSIVELY MARKETED THE /,40 PERFORMANCE OF ITS $"-3 USING BENCHMARK RESULTS FROM MULTIPROCESSOR SYSTEMS TO SUBSTANTIATE ITS CLAIM AS THE /,40 PERFORMANCE LEADER 4HE COMPANY SUCCESSIVELY FOCUSED ITS SIGHTS ON )NGRES ITS EARLY ARCHRIVAL AND LATER ON 3YBASE WHICH CHALLENGED FOR A ROLE AS /,40 LEADER FOR A FEW YEARS 4HE COMPANYS CULTURE HAS ALWAYS COMBINED GOOD TECHNOLOGY WITH A VERY AGGRESSIVE SALES FORCE AND HIGH PROFILE MARKETING CAMPAIGNS /RACLES PRODUCT LINE HAS EXPANDED WELL BEYOND ITS DATABASE ORIGINS AND NOW INCLUDES ENTERPRISE SOFTWARE PRODUCTS AS DIVERSE AS APPLICATION SERVERS AND MIDDLEWARE FINANCIAL AND ACCOUNTING APPLICATIONS RETAIL AND TELECOM INDUSTRY SOFTWARE AND APPLICATIONS FOR MANAGING CUSTOMER RELATIONSHIPS AND (2 (OWEVER DATABASE TECHNOLOGY REMAINS THE CORE OF THE COMPANY AND IT HAS A DOMINANT MARKET SHARE IN THE ENTERPRISE DATABASE MARKET CHALLENGED ONLY BY )"- 4HE COMPANY IS ALSO A LEADER IN DATA WAREHOUSING EMBEDDED DATABASES 8-, INTEGRATION AND MANY OTHER NICHES AND HAS EVEN VENTURED INTO HARDWARE SELLING A DATA WAREHOUSING APPLIANCE BASED ON HARDWARE SUPPLIED BY (EWLETT 0ACKARD 4HE FLAGSHIP /RACLE DATABASE HAS BEEN THROUGH MANY MAJOR REVISIONS NUMBERED AS /RACLE /RACLEI AND I I FOR h)NTERNETv AND /RACLE G AND G G FOR hGRIDv )T IS AN EXTREMELY CAPABLE LARGE AND COMPLEX PIECE OF SOFTWARE AND AN ENTIRE SUBINDUSTRY HAS GROWN UP AROUND /RACLE DATABASE ADMINISTRATION /RACLE PERFORMANCE TUNING AND /RACLE TRAINING AND CONSULTING 4HE MAJORITY OF THE /RACLE DATABASE TECHNOLOGY HAS BEEN DEVELOPED INTERNALLY UNLIKE THE /RACLE APPLICATIONS AND MIDDLEWARE BUSINESS WHERE THE COMPANY HAS ACQUIRED LARGE SUCCESSFUL COMPANIES SUCH AS 0EOPLE3OFT 3IEBEL (YPERION AND "%! 3YSTEMS (OWEVER THE COMPANY HAS MADE A FEW NOTABLE DATABASE ACQUISITIONS 4HEY INCLUDE 2DB 6-3 A PIONEERING MINICOMPUTER DATABASE PRODUCT 4IMES4EN A STARTUP THAT PIONEERED THE IN MEMORY DATABASE SEGMENT AND 3LEEPY#AT A LEADING OPEN SYSTEMS EMBEDDED DATABASE 2DB6-3 ACQUIRED BY /RACLE IN WAS A PIONEERING DATABASE ORIGINALLY DEVELOPED BY $IGITAL %QUIPMENT #ORPORATION FOR ITS INDUSTRY LEADING 6!86-3 BIT MINICOMPUTER 4HE PRODUCT WAS EVENTUALLY PORTED TO THE /PEN6-3 OPERATING SYSTEM A 5.)86-3 HYBRID AND RAN ON $IGITALS VERY HIGH PERFORMANCE !LPHA FAMILY OF PROCESSORS 2DB6-3 PIONEERED SEVERAL DATABASE INNOVATIONS INCLUDING A COST BASED OPTIMIZER !LL OF THE MINICOMPUTER VENDORS EVENTUALLY DECIDED NOT TO COMPETE IN DATABASE SOFTWARE WITH THE INDEPENDENT DATABASE VENDORS AND EITHER SHUT DOWN OR SOLD OFF THEIR DATABASE OPERATIONS $IGITAL WAS NO EXCEPTION AND /RACLE WAS EAGER TO ACQUIRE BOTH THE 2DB CUSTOMER BASE AND THE 2DB DEVELOPMENT TEAM 4IMES4EN ACQUIRED BY /RACLE IN WAS A VENTURE BACKED STARTUP THAT COMMERCIALIZED THE IN MEMORY DATABASE TECHNOLOGY INITIALLY DEVELOPED AT (0 ,ABS IN THE EARLY S 5NLIKE CONVENTIONAL ENTERPRISE DATABASES WHICH RELY ON DISKS FOR DATA STORAGE AN IN MEMORY DATABASE IS OPTIMIZED FOR DATABASES THAT CAN FIT ENTIRELY IN MAIN MEMORY AND THAT REQUIRE LIGHTNING FAST PERFORMANCE 4IMES4EN FOCUSED ON HIGH PERFORMANCE APPLICATIONS IN THE TELECOM AND FINANCIAL SERVICES INDUSTRIES AND ALSO INTRODUCED A VERSION OF ITS SOFTWARE THAT OPERATED AS A FRONT END CACHE ACCELERATOR FOR /RACLE 7ITH THE ACQUISITION /RACLE HAS CONTINUED TO OFFER /RACLE 4IMES4EN AS A STAND ALONE IN MEMORY DATABASE AND HAS BEGUN TO MORE TIGHTLY INTEGRATE IT AS A CACHE FOR ITS FLAGSHIP /RACLE $"-3 /RACLE ACQUIRED 3LEEPY#AT 3OFTWARE AND ITS COMMERCIAL VERSION OF THE OPEN SOURCE "ERKELEY$" DATABASE IN "ERKELEY$" ENJOYED A POSITION AS A POPULAR OPEN SOURCE DATABASE DUE IN PART TO THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEYS HISTORICAL ROLE AS A CENTER FOR DATABASE INNOVATION /RACLE CONTINUES TO OFFER THE PRODUCT UNDER AN OPEN SOURCE LICENSE AND IT IS A KEY PART OF /RACLES RECENT INITIATIVES IN THE EMBEDDED DATABASE MARKET
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0AR!CCELõ)NCõ0AR!CCEL 0AR!CCEL IS A VENTURE BACKED STARTUP FOCUSED ON THE DATA WAREHOUSING AND BUSINESS INTELLIGENCE MARKET 4HE COMPANYS CHIEF TECHNOLOGY OFFICER "ARRY :ANE PREVIOUSLY SERVED AS CHIEF TECHNOLOGY OFFICER AT .ETEZZA A VERY SUCCESSFUL VENDOR OF DATABASE APPLIANCES FOR DATA WAREHOUSING 5NLIKE .ETEZZA 0AR!CCEL IS TAKING A SOFTWARE ONLY APPROACH APPLYING ITS MASSIVELY PARALLEL PROCESSING -00 ARCHITECTURE TO CLUSTERS OF OFF THE SHELF HIGH PERFORMANCE LOW COST SERVERS 4HE COMPANY ARGUES THAT THE RELENTLESS PRICEPERFORMANCE IMPROVEMENT OF STANDARD #05S AS THEY OBEY -OORES LAW AND RIDE VOLUME MANUFACTURING COST DECLINES OUTWEIGHS ANY TEMPORARY PERFORMANCE ADVANTAGES FROM CUSTOM QUERY PROCESSING HARDWARE 0AR!CCELS 60 OF ENGINEERING "RUCE 3COTT ALSO HAS ENJOYED A PROMINENT CAREER IN THE DATABASE FIELD OVER SEVERAL DECADES BEGINNING AS ONE OF THE FOUR COFOUNDERS OF /RACLE #ORPORATION WHERE HE WAS THE ARCHITECT OF THE FIRST SEVERAL VERSIONS OF THE /RACLE DATABASE 0AR!CCEL STRESSES A COMBINATION OF ARCHITECTURAL APPROACHES AS THE KEY TO DELIVERING MASSIVE DATA WAREHOUSING SCALABILITY 3TORING THE DATABASE IN A COLUMN ORIENTED RATHER THAN ROW ORIENTED SEQUENCE MINIMIZES THE AMOUNT OF DATA THAT MUST BE SCANNED TO CALCULATE AVERAGES TOTALS AND STATISTICAL FUNCTIONS #OMPRESSION FURTHER MINIMIZES THE AMOUNT OF DATA THAT MUST BE TRANSFERRED FROM DISK 0ARALLEL OPERATION WITH A SHARED NOTHING ARCHITECTURE SPREADS THE DATA ACROSS PROCESSING UNITS AND ALLOWS BUSINESS INTELLIGENCE QUERIES TO BE SPREAD OUT AND TO PERFORM PARALLEL RATHER THAN SERIAL SCANNING OF DATA &INALLY SUPPORT FOR IN MEMORY OPERATION ALLOWS VERY HIGH PERFORMANCE FOR SMALLER DATASETS
0OSTGRE31,õ0OSTGRE31, 0OSTGRE31, IS ONE OF THE MOST POPULAR OPEN SOURCE 31, DATABASE IMPLEMENTATIONS AND HAS SERVED AS THE FOUNDATION OF SEVERAL COMMERCIAL PRODUCTS OVER THE YEARS 4HE ORIGINAL 0OSTGRES IMPLEMENTATION WAS DONE AT THE 5NIVERSITY OF #ALIFORNIA AT "ERKELEY AND WAS CONCEIVED AS A SUCCESSOR TO THE EARLIER "ERKELEY )NGRES PROJECT /NE OF THE MAJOR GOALS WAS TO SUPPORT A BROADER VARIETY OF DATA TYPES AND RELATIONSHIPS 4HE "ERKELEY PROJECT PRODUCED A SERIES OF RELEASES IN THE EARLY S WHICH WERE DISTRIBUTED UNDER THE LIBERAL "3$ "ERKELEY 3OFTWARE $ISTRIBUTION OPEN SOURCE LICENSE 31, SUPPORT WAS ADDED IN THE MID S AND THE 0OSTGRES NAME WAS CHANGED TO 0OSTGRE31, TO REFLECT THE NEW STANDARDS COMPLIANCE 0OSTGRES DEVELOPMENT SOON MOVED OUTSIDE OF "ERKELEY TO AN OPEN SOURCE 0OSTGRE31, COMMUNITY WHICH REMAINS ACTIVE TODAY /NE OF THE EARLIEST COMMERCIALIZATIONS OF 0OSTGRE31, WAS AT )LLUSTRA )NFORMATION 4ECHNOLOGIES AN OBJECT RELATIONAL DATABASE PIONEER FOUNDED BY TWO "ERKELEY ALUMNI )LLUSTRA WAS ACQUIRED BY )NFORMIX ONE OF THE EARLIEST 2$"-3 VENDORS IN AND ITS FEATURES WERE INTEGRATED INTO THE MAINSTREAM )NFORMIX PRODUCT 0OSTGRE31, WAS ALSO PICKED UP BY 3UN -ICROSYSTEMS AND BEGAN SHIPPING AS PART OF ITS 3OLARIS OPERATING SYSTEM DISTRIBUTION -ORE RECENTLY %NTERPRISE$" WAS FOUNDED TO COMMERCIALIZE EXTEND AND SUPPORT 0OSTGRE31, FOR TRANSACTION PROCESSING APPLICATIONS 'REENPLUM SIMILARLY EXTENDS 0OSTGRE31, FOR DATA WAREHOUSING APPLICATIONS AS DOES 4RUVISO FOR STREAMING DATABASE MANAGEMENT 4HE 0OSTGRE31, CODE BASE REMAINS A POPULAR FOUNDATION FOR DATABASE MANAGEMENT IN A VARIETY OF SYSTEMS AND APPLICATIONS
3TREAMBASEõ3YSTEMSõ3TREAMBASE 3TREAMBASE IS A STARTUP COMPANY FOUNDED BY -ICHAEL 3TONEBREAKER THE FORMER "ERKELEY PROFESSOR WHO WAS ALSO THE TECHNOLOGY FOUNDER OF RELATIONAL DATABASE PIONEER )NGRES AND
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3UNõ-ICROSYSTEMSõ-Y31, -Y31, CLAIMS TO BE THE MOST POPULAR 31, DATABASE WITH WELL OVER MILLION INSTALLATIONS )TS POPULARITY EXPLODED WITH THE )NTERNET AND IT BECAME AN EARLY CHOICE FOR )NTERNET SITES THAT NEEDED DATABASE MANAGEMENT 4HIS ROLE WAS CEMENTED IN THE PRODUCTS ROLE IN THE SO CALLED h,!-0v STACK A COMBINATION OF THE ,INUX OPERATING SYSTEM BASE !PACHE WEB SERVER THE -Y31, DATABASE AND THE 0(00YTHON0ERL PROGRAMMING LANGUAGE -Y31, IS ESPECIALLY STRONGLY ASSOCIATED WITH 0(0 AS A TOOL BASE FOR BUILDING DATABASE CENTRIC APPLICATIONS FOR WEB SITES 3OME OF THE HIGHEST VOLUME WEB SITES ON THE )NTERNET USE IT INCLUDING &ACEBOOK 7IKIPEDIA 9OU4UBE AND PARTS OF THE 'OOGLE SYSTEM -Y31, WAS ORIGINALLY DEVELOPED AND DISTRIBUTED BY A COMPANY OF THE SAME NAME -Y31, !" BASED IN 3WEDEN ! BASIC VERSION OF THE SOFTWARE IS AVAILABLE FREE OF CHARGE FOR RESEARCH AND PERSONAL USE UNDER THE OPEN SOURCE '.5 0UBLIC ,ICENSE '0, #OMMERCIAL USE OF -Y31, REQUIRES PAYMENT OF A LICENSE FEE BUT THE COST IS FAIRLY LOW ENCOURAGING WIDESPREAD DISTRIBUTION -Y31, ALSO PROVIDES FEE BASED SUPPORT AND MAINTENANCE FOR THE PRODUCT /NE OF THE UNIQUE FEATURES OF -Y31, IS A CLEAN SEPARATION BETWEEN THE HIGHER LEVEL DATABASE FUNCTIONS INCLUDING THE 31, LANGUAGE PROCESSING AND THE LOWER LEVEL STORAGE ENGINE THAT MANAGES THE PHYSICAL STORAGE AND RETRIEVAL OF DATA /VER TIME SEVERAL DIFFERENT STORAGE ENGINES HAVE BEEN DEVELOPED AND USED TUNED FOR DIFFERENT PURPOSES ! LARGER AND MORE COMPLEX STORAGE ENGINE PROVIDED DISK BASED STORAGE AND FULL !#)$ TRANSACTION SUPPORT FOR MULTIUSER APPLICATIONS !N ALTERNATIVE STORAGE ENGINE WITH A SMALLER FOOTPRINT PROVIDED PERSISTENT DISK STORAGE BUT INCOMPLETE TRANSACTION SUPPORT WELL SUITED FOR SINGLE USER APPLICATIONS AND FOR SOFTWARE DEVELOPMENT 4HIS ARRANGEMENT PROVIDED FLEXIBILITY TO ADDRESS A BROAD RANGE OF APPLICATIONS BUT ALSO LEFT -Y31, AS A VULNERABLE COMPANY /NE OF THE MOST POPULAR EARLY STORAGE ENGINES PRODUCED BY A 3WEDISH COMPANY NAMED )NNO$" WAS ACQUIRED BY /RACLE IN AND THERE WAS BROAD SPECULATION AT THE TIME THAT /RACLE WOULD USE ITS POWER TO STYMIE THE SUCCESS OF -Y31, (OWEVER /RACLE HAS CONTINUED TO RELEASE )NNO$" VERSIONS TO SUPPORT -Y31, AND ALTERNATIVE TRANSACTIONAL STORAGE MANAGERS HAVE EMERGED $ESPITE THE POPULARITY OF -Y31, THE COMPANY HAD A DIFFICULT TIME GROWING ITS REVENUES TO THE SIZE THAT WOULD SUPPORT AN INDEPENDENT ENTERPRISE DATABASE COMPANY BECAUSE OF THE LOW UNIT PRICES ASSOCIATED WITH THE OPEN SOURCE MODEL )N EARLY 3UN -ICROSYSTEMS ANNOUNCED THAT IT WAS ACQUIRING -Y31, AND WOULD USE IT TOGETHER WITH
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OBJECT RELATIONAL PIONEER )LLUSTRA !S THE NAME IMPLIES 3TREAMBASE IS FOCUSED ON APPLYING 31, BASED DATA MANAGEMENT TO VERY LARGE hSTREAMSv OF DATA USUALLY DATA FLOWING OVER A COMPUTER NETWORK 4HE APPLICATIONS ADDRESSED BY STREAM DATABASES ARE SOMETIMES CALLED #OMPLEX %VENT 0ROCESSING #%0 BECAUSE THE INDIVIDUAL PIECES OF DATA STREAMING ACROSS THE NETWORK ARE OFTEN RELATED TO REAL WORLD hEVENTS v SUCH AS PROVIDING A STOCK QUOTE OR CLICKING A BUTTON ON A WEB PAGE #%0 APPLICATIONS USUALLY FILTER CORRELATE AND AGGREGATE DATA FROM THESE EVENTS TO PRODUCE ANALYSIS AND CALCULATIONS IN REAL TIME ,IKE MOST STARTUPS IN THIS SEGMENT 3TREAMBASE FOCUSES ON SPECIFIC VERTICAL MARKETS WHERE #OMPLEX %VENT 0ROCESSING IS IMPORTANT 4ARGET APPLICATIONS IN THE FINANCIAL SERVICES INDUSTRY INCLUDE REAL TIME RISK MANAGEMENT AGGREGATION AND ANALYSIS OF MARKET DATA QUOTES AND TRANSACTIONS AND TRADE ORDER PROCESSING #OMPLEX %VENT 0ROCESSING IS ALSO VERY IMPORTANT IN GOVERNMENT INTELLIGENCE APPLICATIONS WHERE HUGE VOLUMES OF NETWORK INFORMATION MUST BE ANALYZED AS THEY ARE TRANSMITTED TO DETECT PATTERNS AND IRREGULARITIES
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3UNS *AVA PROGRAMMING LANGUAGE TO ADVANCE THE OPEN SOURCE SOFTWARE MOVEMENT 4HIS MOVE MADE -Y31, A PART OF A MUCH LARGER ORGANIZATION WITH GREATER RESOURCES BUT ALSO TIED -Y31, TO 3UNS OWN CHALLENGES AS A HIGH END 5.)8 SYSTEMS VENDOR 4WO OF THE -Y31, FOUNDERS LEFT A YEAR LATER IN EARLY BUT THE PRODUCT APPEARS TO BE FIRMLY ESTABLISHED AS PART OF 3UNS SOFTWARE PRODUCT LINE
3YBASE õ)NC 3YBASE BEGAN AS A MID S $"-3 STARTUP COMPANY ABOUT A DECADE AFTER THE EARLY RELATIONAL DATABASE PIONEERS 4HE COMPANYS FOUNDING TEAM AND MANY OF ITS EARLY EMPLOYEES WERE ALUMNI OF OTHER $"-3 VENDORS AND FOR MOST OF THEM 3YBASE REPRESENTED THE SECOND OR THIRD RELATIONAL $"-3 THAT THEY HAD BUILT 3YBASE POSITIONED ITS PRODUCT AS hTHE RELATIONAL $"-3 FOR ONLINE APPLICATIONSv AND STRESSED THE TECHNICAL AND ARCHITECTURAL FEATURES THAT DISTINGUISHED IT FROM OTHER 31, BASED $"-3 PRODUCTS 4HESE FEATURES INCLUDED s ! CLIENTSERVER ARCHITECTURE WITH CLIENT SOFTWARE RUNNING ON 3UN AND 6!8 WORKSTATIONS AND )"- 0#S AND THE SERVER RUNNING ON 6!86-3 OR 3UN SYSTEMS s ! MULTITHREADED SERVER THAT HANDLED ITS OWN TASK MANAGEMENT AND INPUTOUTPUT FOR MAXIMUM EFFICIENCY s ! PROGRAMMATIC !0) INSTEAD OF THE EMBEDDED 31, INTERFACE USED BY MOST OTHER $"-3 VENDORS s 3TORED PROCEDURES TRIGGERS AND A 4RANSACT 31, DIALECT THAT EXTENDED 31, INTO A COMPLETE SERVER PROGRAMMING LANGUAGE 4HESE INNOVATIONS MADE 3YBASE THE MOST TECHNICALLY hFLASHYv $"-3 AT THE TIME AND THE COMPANYS LATE START ACTUALLY GAVE IT A TECHNICAL COMPETITIVE EDGE 4ECHNOLOGY LEADERSHIP AGGRESSIVE MARKETING AND A FIRST CLASS ROSTER OF VENTURE CAPITAL BACKERS GAINED 3YBASE THE ATTENTION OF INDUSTRY ANALYSTS BUT IT WAS A SUBSEQUENT /%- DEAL WITH -ICROSOFT AND !SHTON 4ATE THAT POSITIONED THE COMPANY AS AN UP AND COMING $"-3 VENDOR 2ENAMED 31, 3ERVER THE 3YBASE $"-3 WAS PORTED TO /3 AND MARKETED BY -ICROSOFT TO COMPUTER SYSTEMS VENDORS ALONG WITH /3 AND BY !SHTON 4ATE THROUGH RETAIL COMPUTER CHANNELS !LTHOUGH SALES FROM THE ALLIANCE WERE MINIMAL THE PUBLICITY PROPELLED 3YBASE INTO THE $"-3 MARKET AS A SERIOUS PLAYER -ICROSOFT TOOK OVER DEVELOPMENT RESPONSIBILITY FOR 31, 3ERVER AND THAT PRODUCT HAS DIVERGED SIGNIFICANTLY FROM 3YBASES $"-3 4HE 3YBASE PRODUCT HAS BEEN THROUGH MANY MAJOR REVISIONS OVER THE YEARS AND 3YBASE AUGMENTED THE FLAGSHIP $"-3 THROUGH ACQUISITIONS OF DEVELOPMENT TOOLS AND OTHER SOFTWARE PRODUCTS OVER THE YEARS "ETWEEN THE THIRD AND FOURTH EDITIONS THE 3YBASE $"-3 BECAME RECOGNIZED AS AN ENTERPRISE CLASS PRODUCT 4ODAY THE FLAGSHIP 3YBASE $"-3 RENAMED !DAPTIVE 3ERVER %NTERPRISE IS A FULL FEATURED ENTERPRISE DATABASE PRODUCT FOR 5.)8 BASED SERVERS )T HAS A SIGNIFICANT INSTALLED BASE ESPECIALLY AMONG FINANCIAL SERVICES AND TECHNOLOGY COMPANIES BUT HOLDS A DISTANT THIRD PLACE OVERALL MARKET SHARE POSITION BEHIND /RACLE AND )"- 4WO COMPLEMENTARY PRODUCTS PROVIDE ADVANCED REPLICATION CAPABILITIES 2EPLICATION 3ERVER FOR LINKING DISTRIBUTED DATABASES AND A DATABASE INTEGRATION CAPABILITY /PEN 3ERVER FOR BRIDGING DISPARATE DATABASE ENVIRONMENTS 3YBASE HAS BEEN PARTICULARLY SUCCESSFUL IN THE MOBILE AND EMBEDDED DATABASE MARKETS WHERE ITS 31, !NYWHERE PRODUCT IS THE MARKET LEADER 31, !NYWHERE PROVIDES BOTH DATA MANAGEMENT ON THE MOBILE SYSTEM OR DEVICE AND DATA EXCHANGE CAPABILITIES THAT LINK TO AND SYNCHRONIZE WITH ENTERPRISE DATABASES
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4ERADATAõ#ORPORATIONõ4ERADATA
4RUVISO õ)NCõ4RUVISO 4RUVISO IS A VENTURE BACKED 3ILICON 6ALLEY STARTUP FOCUSED ON THE STREAMING DATABASE MARKET SEGMENT ,IKE MANY DATABASE STARTUPS IT WAS COFOUNDED BY A "ERKELEY PROFESSOR -ICHAEL &RANKLIN BASED ON THE "ERKELEY 4ELEGRAPH STREAMING DATABASE PROTOTYPE WHICH WAS BUILT BY EXTENDING "ERKELEYS EARLIER WORK ON 0OSTGRES 4HE COMPANY FOCUSES ON BUSINESS INTELLIGENCE AND DATA ANALYTICS APPLICATIONS USING AN APPROACH THAT IT TERMS hCONTINUOUS ANALYTICSv 5NLIKE CONVENTIONAL ANALYTICS WHERE DATA IS FIRST ACCUMULATED INTO A DATA WAREHOUSE AND THEN QUERIED THE CONTINUOUS ANALYTICS APPROACH USES hALWAYS ONv QUERIES WHICH ANALYZE DATA AS IT ARRIVES 4HE 4RUVISO PRODUCTS CAN ALSO PERFORM QUERIES THAT COMBINE STREAMING DATA WITH CONVENTIONAL hDATA AT RESTv &OR SOME TYPES OF IMPORTANT QUERIES THE COMPANY CLAIMS THE CONTINUOUS ANALYTICS APPROACH CAN YIELD PERFORMANCE IMPROVEMENTS OF TWO TO THREE ORDERS OF MAGNITUDE OVER CONVENTIONAL APPROACHES 4RUVISOS CORE DATA MANAGEMENT PRODUCT 4RU#1 IS 31, BASED AND IS COMPLEMENTED BY 4RU,INK WHICH INTEGRATES IT WITH POPULAR DATA FEEDS AND DATA DELIVERY PRODUCTS AND 4RU6IEW WHICH PROVIDES DATA VISUALIZATION
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4ERADATA IS A MAJOR PLAYER IN THE DATA WAREHOUSING MARKET AND IS KNOWN FOR SUPPORTING SOME OF THE LARGEST DATA WAREHOUSES IN THE WORLD 4HE COMPANYS CUSTOMERS INCLUDE SOME OF THE LARGEST RETAILERS TELECOM COMPANIES BANKS AND AIRLINES AND THE COMPANYS REPUTATION WAS SIGNIFICANTLY ENHANCED WHEN IT WAS CHOSEN TO MANAGE 7AL -ARTS MASSIVE DATA WAREHOUSE OF RETAIL PRODUCT BUYING PATTERNS 4HE 4ERADATA DATA WAREHOUSING APPLIANCES COMBINE CUSTOM BUILT HARDWARE WITH PROPRIETARY DATABASE SOFTWARE IN A MASSIVELY PARALLEL ARCHITECTURE WITH A SHARED NOTHING ARCHITECTURE TO PRODUCE EXTREME SCALABILITY ALBEIT AT A SIGNIFICANT COST 4ERADATA GREW OUT OF RESEARCH AT THE #ALIFORNIA )NSTITUTE OF 4ECHNOLOGY #AL4ECH IN 3OUTHERN #ALIFORNIA IN THE LATE S FOCUSED ON MASSIVELY PARALLEL ARCHITECTURES AND THEIR APPLICATION IN DATA MANAGEMENT 4HE COMPANY WAS FOUNDED TO COMMERCIALIZE THE RESEARCH PROTOTYPE AND EARLY CUSTOMERS CAME FROM THE BANKING INDUSTRY "Y THE LATE S THE COMPANY WAS BRAGGING ABOUT TERABYTE SCALE DATA WAREHOUSES AND BEGAN TO DEFINE DATA WAREHOUSING AS A DISTINCT SEGMENT WITHIN THE DATABASE MARKET )N LATE 4ERADATA WAS ACQUIRED BY .#2 #ORPORATION WHICH AT THE TIME WAS A SUBSIDIARY OF TELECOM GIANT !44 RESPONSIBLE FOR !44S COMPUTER SYSTEMS PRODUCTS .#2 HAD A MAJOR POSITION IN THE RETAIL MARKET THROUGH ITS CASH REGISTERS AND SUPPORTING COMPUTER SYSTEMS AND IN BANKING THROUGH ITS !4- TERMINALS AND ASSOCIATED COMPUTERS AND BOTH OF THESE MARKETS WERE HEAVY USERS OF DATA WAREHOUSING PROVIDING THE RATIONALE FOR THE ACQUISITION ! DECADE AND A HALF LATER 4ERADATA HAD BECOME A DOMINANT PLAYER IN DATA WAREHOUSING ACROSS MANY DIFFERENT INDUSTRIES WHILE .#2 HAD FOCUSED EVEN MORE STRONGLY IN ITS INDUSTRY NICHES AND HAD SEPARATED FROM !44 4ERADATA WAS SPUN BACK OUT OF .#2 IN LATE AND NOW COMPETES AS A STAND ALONE PUBLICLY TRADED COMPANY FOCUSED EXCLUSIVELY ON DATA WAREHOUSING )T DOMINATES THE HIGH END OF THE DATA WAREHOUSING MARKET WITH ITS APPLIANCES AND ASSOCIATED SOFTWARE AND FACES COMPETITION PRIMARILY FROM .ETEZZA /RACLE AND )"- -ANY CUSTOMERS RUN 4ERADATA WAREHOUSES WITH HUNDREDS OF TERABYTES OF DATA AND THE COMPANY IS PUSHING UP INTO PETABYTE TERABYTES SCALE 4ERADATA HAS BEEN LESS SUCCESSFUL IN EXTENDING ITS LEADERSHIP DOWN INTO THE LOW END AND MIDRANGE DATA WAREHOUSING MARKET WHERE VENTURE BACKED STARTUPS AND /RACLE AND )"- ALL ENJOY SIGNIFICANT MARKET SHARE
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5NIFYõ#ORPORATIONõ31,"ASE 5NIFY #ORPORATION WAS ONE OF THE EARLIEST 5.)8 BASED DATABASE STARTUPS FOUNDED IN )N THE MID S 5NIFY )NFORMIX )NGRES AND /RACLE WERE THE FOUR MAJOR 5.)8 BASED $"-3 COMPETITORS WITH /RACLE AND )NGRES BATTLING FOR DOMINANCE AS THE hHIGH ENDv $"-3 WHILE )NFORMIX AND 5NIFY COMPETED AT THE LOW END OF THE MARKET 4HE 5NIFY $"-3 WAS BASED ON THE NETWORK DATA MODEL WITH A 31, VENEER FOR RELATIONAL ACCESS AN APPROACH WHICH PROVIDED AN EARLY PERFORMANCE ADVANTAGE BUT WHICH RESTRICTED THE ABILITY TO RAPIDLY EVOLVE THE PRODUCTS 31, SUPPORT /VER TIME THE NAMESAKE DATABASE BECAME A DECLINING PART OF THE BUSINESS 4HE COMPANYS !CCELL FOURTH GENERATION LANGUAGE WAS ONE OF THE FIRST ', PRODUCTS AND EXPANDED OVER TIME TO BECOME A CROSS PLATFORM APPLICATION DEVELOPMENT ENVIRONMENT FOR ANY 31, BASED DATABASE $EVELOPMENT TOOLS REMAIN AN IMPORTANT PART OF THE COMPANYS PRODUCT LINE TODAY )N 5NIFY ACQUIRED 'UPTA 4ECHNOLOGIES WHICH HAD BEEN FOUNDED MORE THAN A DECADE EARLIER BY EX /RACLE EXECUTIVE 5MANG 'UPTA ,IKE 5NIFY 'UPTAS PRODUCT LINE INCLUDED A DATABASE PRODUCT 31,"ASE AND DATABASE DEVELOPMENT TOOLS 31,"ASE REMAINS AN IMPORTANT PART OF THE COMPANYS PRODUCT LINE TODAY )T HAS EVOLVED INTO A HIGH PERFORMANCE 31, BASED EMBEDDED DATABASE THAT COMBINES SOPHISTICATED CAPABILITIES LIKE ADVANCED LOCKING AND 5NICODE SUPPORT WITH A SMALL FOOTPRINT 5NIFY POSITIONS 31,"ASE AS AN h%MBED )T AND &ORGET )Tv DATABASE THAT REQUIRES NO DATABASE ADMINISTRATION 4HE COMPANY TARGETS INDEPENDENT SOFTWARE VENDORS )36S AND VALUE ADDED RESELLERS 6!2S WHO EMBED 31,"ASE TRANSPARENTLY INTO THEIR APPLICATION SOFTWARE AND SYSTEMS
6ERTICAõ3YSTEMSõ6ERTICA 6ERTICA IS AN ANALYTIC DATABASE STARTUP FOCUSED ON DATA WAREHOUSING APPLICATIONS COFOUNDED BY FORMER "ERKELEY PROFESSOR $R -ICHAEL 3TONEBREAKER WHO HAS BEEN INVOLVED IN SEVERAL OTHER PIONEERING DATABASE STARTUPS OVER THE PAST YEARS AND IS NOW AN ADJUNCT PROFESSOR AT -)4 4HE COMPANYS 6ERTICA DATABASE USES AN ARCHITECTURE THAT HAS RAPIDLY BECOME POPULAR FOR THESE APPLICATIONS COMBINING A COLUMN ORIENTED ORGANIZATION AND DATA COMPRESSION IN A SHARED NOTHING ARCHITECTURE THAT SCALES HORIZONTALLY 4HE PRODUCT USES INDUSTRY STANDARD /$"# AND *$"# INTERFACES AND TARGETS DATABASES FROM HUNDREDS OF GIGABYTES TO HUNDREDS OF TERABYTES IN SIZE 5NIQUELY 6ERTICA OFFERS ITS DATABASE IN THREE DIFFERENT FORMS 4HE 6ERTICA $ATABASE IS A SOFTWARE PRODUCT THAT RUNS ON A GRID OF ,INUX BASED SERVERS 4HE 6ERTICA !NALYTIC $ATABASE !PPLIANCE COMBINES THE 6ERTICA DATABASE SOFTWARE WITH 2ED (AT ,INUX AND (0 BLADE SERVER HARDWARE FOR A PREPACKAGED hOUT OF THE BOXv DATA MART SOLUTION &INALLY 6ERTICA !NALYTIC $ATABASE FOR THE #LOUD RUNS THE COMPANYS DATABASE SOFTWARE ON !MAZONS %# %LASTIC #OMPUTE #LOUD TO PROVIDE A 3OFTWARE AS A 3ERVICE 3AA3 APPROACH
8EROUNDõ8EROUNDõ)NTELLIGENTõ$ATAõ'RID 8EROUND IS A DATABASE STARTUP FOUNDED BY AN )SRAELI TEAM THAT BRINGS ITS NETWORKING EXPERTISE TO BEAR ON DISTRIBUTED DATABASE DESIGN 4HE COMPANYS 8EROUND )NTELLIGENT $ATA 'RID )$' IS TARGETED FOR ONLINE TRANSACTION PROCESSING APPLICATIONS THAT DEMAND REAL TIME RESPONSE FOR DATA CAPTURE UPDATE AND RETRIEVAL OPERATIONS )T DISTRIBUTES DATA HORIZONTALLY ACROSS A GRID OF PROCESSORS BASED ON A RAPID TRANSLATION OF DATABASE PRIMARY KEYS INTO SERVER NETWORK ADDRESSES 4HIS ALLOWS VERY LOW LATENCY DATA ACCESS FOR KEY BASED 31, OPERATIONS AND A HIGH DEGREE OF SCALABILITY )N ADDITION TO THE 31, !0) )$' OFFERS ,$!0 81UERY AND PROPRIETARY !0)S 2EPLICATION ACROSS THE GRID IS USED TO PROVIDE REDUNDANCY AND HIGH AVAILABILITY
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8EROUND ORIGINALLY TARGETED ITS DATABASE FOR TELECOM APPLICATIONS THAT PROCESS SUBSCRIBER DATA SUCH AS THE DATABASES THAT TRACK THE LOCATIONS AND CAPABILITIES OF MOBILE TELEPHONES IN A NETWORK -ORE RECENTLY THE COMPANY HAS REPACKAGED ITS DATABASE AS )$' #ORE AND SUPPLEMENTED IT WITH TWO ADDITIONAL PRODUCTS)$' 5NIFY WHICH FEDERATES DATA ACROSS EXISTING DATABASES FOR ACCESS VIA )$' AND )$' 3YNC WHICH SYNCHRONIZES DATA ACROSS DATABASES 7ITH THESE ADDITIONS THE COMPANY NOW POSITIONS )$' AS A DATABASE VIRTUALIZATION SOLUTION PROVIDING A SINGLE VIEW ACROSS DISPARATE DATABASES AND NETWORKS
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HE !.3))3/ 31, STANDARD SPECIFIES THE SYNTAX OF THE 31, LANGUAGE USING A FORMAL "ACKUS .AUR &ORM ".& NOTATION 5NFORTUNATELY THE STANDARD IS DIFFICULT TO READ AND UNDERSTAND FOR SEVERAL REASONS &IRST THE STANDARD SPECIFIES THE LANGUAGE BOTTOM UP RATHER THAN TOP DOWN MAKING IT DIFFICULT TO GET THE hBIG PICTUREv OF A 31, STATEMENT 3ECOND THE STANDARD USES UNFAMILIAR TERMS SUCH AS TABLE EXPRESSION AND PREDICATE &INALLY THE ".& IN THE STANDARD IS MANY LAYERS DEEP PROVIDING A VERY PRECISE SPECIFICATION BUT MASKING THE RELATIVELY SIMPLE STRUCTURE OF THE 31, LANGUAGE 4HIS APPENDIX PRESENTS A COMPLETE SIMPLIFIED ".& FOR hSTANDARDv 31, AS IT IS COMMONLY IMPLEMENTED IN THE PRODUCTS OF MOST $"-3 VENDORS 3PECIFICALLY s 4HE LANGUAGE DESCRIBED GENERALLY CONFORMS TO THAT REQUIRED FOR ENTRY LEVEL CONFORMANCE TO THE 31, STANDARD PLUS THOSE INTERMEDIATE LEVEL AND FULL LEVEL CONFORMANCE FEATURES THAT ARE COMMONLY FOUND IN THE MAJOR $"-3 PRODUCTS s 4HE MODULE LANGUAGE IS OMITTED BECAUSE IT IS REPLACED IN VIRTUALLY ALL 31, IMPLEMENTATIONS BY EMBEDDED 31, OR BY A 31, !0) s #OMPONENTS OF THE LANGUAGE ARE REFERRED TO BY THE COMMON NAMES GENERALLY USED IN $"-3 VENDOR DOCUMENTATION RATHER THAN BY THE TECHNICAL NAMES USED IN THE STANDARD 4HE ".& IN THIS APPENDIX USES THE FOLLOWING CONVENTIONS s 31, KEYWORDS APPEAR IN ALL 500%2#!3% -/./30!#% CHARACTERS s 3YNTAX ELEMENTS ARE SPECIFIED IN ITALICS s 4HE NOTATION ELEMENT LIST INDICATES AN ELEMENT OR A LIST OF ELEMENTS SEPARATED BY COMMAS s 6ERTICAL BARS \ INDICATE A CHOICE BETWEEN TWO OR MORE ALTERNATIVE SYNTAX ELEMENTS s 3QUARE BRACKETS ; = INDICATE AN OPTIONAL SYNTAX ELEMENT ENCLOSED WITHIN THEM s "RACES [ ] INDICATE A CHOICE AMONG REQUIRED SYNTAX ELEMENTS ENCLOSED WITHIN THEM
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$ATAõ$EFINITIONõ3TATEMENTS 4HESE STATEMENTS DEFINE THE STRUCTURE OF A DATABASE INCLUDING ITS TABLES AND VIEWS AND THE $"-3 SPECIFIC hOBJECTSv THAT IT CONTAINS #2%!4% 4!",% TABLE TABLE DEF ITEM LIST $2/0 4!",% TABLE ; DROP OPTIONS = #2%!4% 6)%7 VIEW ; COLUMN LIST = !3 QUERY SPEC ; 7)4( #(%#+ /04)/. = $2/0 6)%7 VIEW ; DROP OPTIONS = #2%!4% DB OBJECT TYPE DB OBJECT NAME ; DB OBJECT SPEC = $2/0 DB OBJECT TYPE DB OBJECT NAME ; DROP OPTIONS = !,4%2 DB OBJECT TYPE DB OBJECT NAME ALTER ACTION
4HE KEYWORDS USED TO SPECIFY DATABASE OBJECTS DB OBJECT TYPE DEPEND ON THE SPECIFIC $"-3 4YPICAL hDATABASE OBJECTSv WITH ASSOCIATED PRIVILEGES INCLUDE 4!",% 6)%7 3#(%-! 02/#%$52% &5.#4)/. 42)''%2 $/-!). ).$%8 AND THE NAMED STORAGE AREAS MAINTAINED BY THE $"-3 4HE 31, SYNTAX USED TO SPECIFY THESE OBJECTS IS SPECIFIC TO THE $"-3 THAT SUPPORTS THEM 4HE SPECIFIC ALTER ACTIONS SUPPORTED ARE ALSO $"-3 SPECIFIC AND OBJECT TYPEnSPECIFIC 4HE LANGUAGE ELEMENTS USED IN THE #2%!4% $2/0 AND !,4%2 STATEMENTS ARE >}Õ>}iÊ iiÌ
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TABLE DEF ITEM
COLUMN DEFINITIONÊNÊTABLE CONSTRAINTÊ
COLUMN DEFINITION
COLUMNäDATA TYPEä ÊÊÊÊÊÊQÊ$%&!5,4ÊOÊLITERALÊNÊ53%2ÊNÊ.5,,ÊPÊRÊ ÊÊÊÊÊÊQÊCOLUMN CONSTRAINT LISTÊR
COLUMN CONSTRAINT
QÊ#/.342!).4ÊCONSTRAINT NAMEÊRÊ ÊÊOÊ./4 .5,,ÊNÊUNIQUENESSÊNÊFOREIGN KEY REFÊNÊCHECK CONSTRÊPÊ ÊÊQÊCONSTRAINT TIMINGÊR
TABLE CONSTRAINT
QÊ#/.342!).4ÊCONSTRAINT NAMEÊRÊ ÊÊOÊUNIQUENESSÊNÊFOREIGN KEY CONSTRÊNÊCHECK CONSTRÊPÊ ÊÊQÊCONSTRAINT TIMINGÊR
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!CCESSõ#ONTROLõ3TATEMENTS '2!.4 [ !,, 02)6),%'%3 \ PRIVILEGE LIST ] /. [ TABLE \ DB OBJECT TYPE DB OBJECT NAME ] 4/ [ 05",)# \ USER LIST ] ; 7)4( '2!.4 /04)/. = 2%6/+% [ !,, 02)6),%'%3 \ PRIVILEGE LIST ] /. [TABLE \ DB OBJECT TYPE DB OBJECT NAME ] &2/- [ 05",)# \ USER LIST ] ; 7)4( '2!.4 /04)/. =
4HE KEYWORDS USED TO SPECIFY DATABASE OBJECTS DB OBJECT TYPE DEPEND ON THE SPECIFIC $"-3 4YPICAL hDATABASE OBJECTSv WITH ASSOCIATED PRIVILEGES INCLUDE 4!",% 6)%7 3#(%-! 02/#%$52% &5.#4)/. 42)''%2 $/-!). ).$%8 AND THE NAMED STORAGE AREAS MAINTAINED BY THE $"-3 4HE 31, SYNTAX USED TO SPECIFY THESE OBJECTS IS SPECIFIC TO THE $"-3 THAT SUPPORTS THEM 4HE SPECIFIC PRIVILEGES THAT ARE SUPPORTED ARE ALSO $"-3 SPECIFIC AND OBJECT TYPEnSPECIFIC 4HE LANGUAGE ELEMENT AND SYNTAX USED IN THE '2!.4 AND 2%6/+% STATEMENTS ARE >}Õ>}iÊ iiÌ
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3%,%#4ÊNÊ ÊÊÊÊ$%,%4%ÊNÊ ÊÊÊÊ50$!4%ÊQÊÊCOLUMN LISTÊ®ÊRÊNÊ ÊÊÊÊ).3%24ÊQÊÊCOLUMN LISTÊ®ÊRÊNÊ ÊÊÊÊ%8%#54%
"ASICõ$ATAõ-ANIPULATIONõ3TATEMENTS 4HE hSINGLETON 3%,%#4v STATEMENT RETRIEVES A SINGLE ROW OF DATA INTO A SET OF HOST VARIABLES EMBEDDED 31, OR STORED PROCEDURE VARIABLES 3%,%#4 ; !,, \ $)34).#4 = [ SELECT ITEM LIST \ ] ).4/ VARIABLE LIST &2/- TABLE REF LIST ; 7(%2% SEARCH CONDITION =
4HE hINTERACTIVE 3%,%#4v STATEMENT RETRIEVES ANY NUMBER OF ROWS OF DATA IN AN INTERACTIVE 31, SESSION MULTIROW RETRIEVAL FROM EMBEDDED 31, OR STORED PROCEDURES REQUIRES CURSOR BASED STATEMENTS 3%,%#4 ; !,, \ $)34).#4 = [ SELECT ITEM LIST \ ] ).4/ HOST VARIABLE LIST &2/- TABLE REF LIST ; 7(%2% SEARCH CONDITION = ; '2/50 "9 COLUMN REF LIST = ; (!6).' SEARCH CONDITION = ; /2$%2 "9 SORT ITEM LIST =
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4HESE STATEMENTS CONTROL ACCESS TO DATABASE OBJECTS AND SERVICES
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4HESE STATEMENTS MODIFY THE DATA IN THE DATABASE ).3%24 ).4/ TABLE ; COLUMN LIST = [ 6!,5%3 INSERT ITEM LIST \ QUERY EXPR ] $%,%4% &2/- TABLE ; 7(%2% SEARCH CONDITION = 50$!4% TABLE 3%4 SET ASSIGNMENT LIST ; 7(%2% SEARCH CONDITION =
4RANSACTION 0ROCESSINGõ3TATEMENTS 4HESE STATEMENTS SIGNAL THE END OF A 31, TRANSACTION #/--)4 ; 7/2+ = 2/,,"!#+ ; 7/2+ =
#URSOR "ASEDõ3TATEMENTS 4HESE PROGRAMMATIC 31, STATEMENTS SUPPORT DATA RETRIEVAL AND POSITIONED UPDATE OF DATA $%#,!2% CURSOR ; 3#2/,, = #523/2 &/2 QUERY EXPR ; /2$%2 "9 SORT ITEM LIST = ; &/2 [ 2%!$ /.,9 \ 50$!4% ; /& COLUMN LIST = ] = /0%. CURSOR #,/3% CURSOR &%4#( ; ; FETCH DIR = &2/- = CURSOR ).4/ VARIABLE LIST $%,%4% &2/- TABLE 7(%2% #522%.4 /& CURSOR 50$!4% TABLE 3%4 SET ASSIGNMENT LIST 7(%2% #522%.4 /& CURSOR
4HE OPTIONAL FETCH DIRECTION FETCH DIR IS SPECIFIED AS THE FOLLOWING AND ROW NR CAN BE SPECIFIED AS A NUMERIC VARIABLE OR A NUMERIC LITERAL .%84 \ 02)/2 \ &)234 \ ,!34 \ !"3/,54% ROW NR \ 2%,!4)6% ROW NR
1UERYõ%XPRESSIONS 4HE 31, STANDARD PROVIDES A RICH SET OF EXPRESSIONS FOR SPECIFYING QUERIES FROM SIMPLE QUERIES TO MORE COMPLEX QUERY EXPRESSIONS THAT USE RELATIONAL DATABASE OPERATIONS TO COMBINE THE RESULTS OF SIMPLER QUERIES
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4HE BASIC QUERY SPECIFICATION HAS THE FORM
4HE TABLE REFERENCES TBL REF IN THE &2/- CLAUSE CAN BE s ! SIMPLE TABLE REFERENCE CONSISTING OF A POSSIBLY QUALIFIED TABLE NAME s ! DERIVED TABLE REFERENCE CONSISTING OF A SUBQUERY SEE THE TEXT THAT FOLLOWS THAT PRODUCES A TABLE VALUED RESULT .OT ALL $"-3 BRANDS ALLOW TABLE VALUED SUBQUERIES TO APPEAR IN THE &2/- CLAUSE s ! JOINED TABLE REFERENCE SEE THE TEXT THAT FOLLOWS THAT COMBINES DATA FROM TWO OR MORE TABLES USING RELATIONAL /54%2 */). )..%2 */). OR OTHER JOIN OPERATORS .OT ALL $"-3 BRANDS ALLOW JOIN SPECIFICATIONS TO APPEAR IN THE &2/- CLAUSE *OINED TABLES ARE SPECIFIED ACCORDING TO THE 31, STANDARD AS FOLLOWS IN PRACTICE THERE IS WIDE VARIATION IN THE SPECIFIC TYPES OF JOINS SUPPORTED BY INDIVIDUAL $"-3 BRANDS AND THE SYNTAX USED TO SPECIFY VARIOUS JOIN TYPES Ê/Þ«i
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TABLE REFÊQÊ.!452!,ÊRÊQÊ,%&4ÊNÊ2)'(4ÊNÊ&5,,ÊRÊ ÊÊÊÊ/54%2 */).ÊTABLE REFÊNÊÊ TABLE REFÊQÊ,%&4ÊNÊ2)'(4ÊNÊ&5,,ÊRÊ/54%2 */). ÊÊÊÊTABLE REFÊQÊJOIN SPECÊR
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4HE 31, STANDARD ALLOWS BASIC QUERY SPECIFICATIONS TO BE COMBINED WITH ONE ANOTHER USING THE SET ORIENTED RELATIONAL OPERATIONS 5.)/. %8#%04 AND ).4%23%#4 4HE RESULTING QUERY EXPRESSION PROVIDES THE FULL RELATIONAL SET PROCESSING POWER OF THE STANDARD %NCLOSED IN PARENTHESES A QUERY EXPRESSION BECOMES A SUBQUERY THAT CAN APPEAR IN VARIOUS POSITIONS WITHIN 31, STATEMENTS FOR EXAMPLE WITHIN CERTAIN SEARCH CONDITIONS IN THE 7(%2% CLAUSE
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3%,%#4 ; !,, \ $)34).#4 = [ SELECT ITEM LIST \ ] &2/- TABLE REF LIST ; 7(%2% SEARCH CONDITION = ; '2/50 "9 COLUMN REF LIST = ; (!6).' SEARCH CONDITION =
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.OT ALL $"-3 BRANDS SUPPORT ALL OF THESE OPERATIONS ! SIMPLIFIED FORM OF THE 31, SYNTAX FOR THE OPERATIONS WITHOUT THE DETAILS OF OPERATOR PRECEDENCE IS GIVEN BY
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)NDEX ! ABSTRACT DATA TYPES n DEFINING n MANIPULATING n ACCESS CONTROL STATEMENTS ACCESSOR METHODS !#)$ TEST ADDING DATA TO THE DATABASE 3EE ALSO ).3%24 STATEMENTS ADVANCED QUERIES n #!3% EXPRESSION n #!34 EXPRESSION n #/!,%3#% EXPRESSION n .5,,)& EXPRESSION n QUERY EXPRESSIONS n QUERY SPECIFICATION n ROW VALUE CONSTRUCTOR EXPRESSION n ROW VALUED COMPARISONS ROW VALUED EXPRESSIONS n ROW VALUED SUBQUERIES n SCALAR VALUED EXPRESSIONS n TABLE VALUE CONSTRUCTOR EXPRESSION n TABLE VALUED EXPRESSIONS n TABLE VALUED SUBQUERIES n !LERI ALIASES n ALL COLUMN SELECTIONS n
!,4%2 4!",% STATEMENTS n CHANGING PRIMARY AND FOREIGN KEYS n !.$ KEYWORD n !.3) n !.3))3/ 31, TRANSACTION MODEL n !PAMA !0)S BASIC OPERATION DEFINED OVERVIEW WHEN TO USE 3EE ALSO DBLIB !0) *$"# /#) /$"# 31,#,) STANDARD APPLICATION PROGRAMMING INTERFACES 3EE !0)S APPLICATION SERVERS CACHING n DATABASE ACCESS FROM n EARLY WEB SITE IMPLEMENTATIONS n OPEN SOURCE APPLICATION DEVELOPMENT SESSION BEAN DATABASE ACCESS n AND THREE TIER WEB SITE ARCHITECTURE n APPROXIMATE NUMERIC LITERALS ARRAYS VARYING ARRAYS ASSERTIONS n !STER $ATA ASYNCHRONOUS EXECUTION
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ATTRIBUTES #,) IN 8-, 3CHEMA n AUTHORIZATION IDS !6'
" "ACKUS .AUR &ORM 3EE ".& NOTATION BACKWARD COMPATIBILITY BEAN CACHING BEAN MANAGED PERSISTENCE "%47%%. TEST 3EE RANGE TEST BINDING COLUMNS BINDING OFFSET BITMAP INDEXES ",/" BLOCK STRUCTURE ".& NOTATION BOOKMARKS " TREE INDEXES BUILT IN FUNCTIONS n BULK LOAD UTILITIES BUSINESS INTELLIGENCE n BUSINESS RULES n
# #ACH£ n CACHING APPLICATION SERVERS n BEAN CACHING WITH IN MEMORY DATABASES n CALCULATED COLUMNS n CALLABLE STATEMENTS *$"# n CALL LEVEL INTERFACES 3EE #,) #ARTESIAN PRODUCT #!3#!$% DELETE RULE #!3#!$% UPDATE RULE #!3% EXPRESSION n #!34 EXPRESSION n CATALOGS CENTRALIZED ARCHITECTURE n CHANGING A TABLE DEFINITION n CHECK CONSTRAINTS n
#,) n ATTRIBUTES DEFERRED PARAMETER PASSING DESCRIPTORS DYNAMIC QUERY PROCESSING n ERRORS AND DIAGNOSTIC INFORMATION n HANDLES INFORMATION CALLS n NAMED CURSORS PROCESSING QUERY RESULTS n SCROLLING CURSORS STATEMENT EXECUTION WITH PARAMETERS n STATEMENT PROCESSING STRUCTURES n TRANSACTION MANAGEMENT n 3EE ALSO 31,#,) STANDARD CLIENTSERVER APPLICATIONS AND DATABASE ARCHITECTURE WITH STORED PROCEDURES n CLIENTSERVER ARCHITECTURE n CLIENTSERVER LANGUAGE 31, AS A #,/" #,/3% STATEMENT n DYNAMIC #,/3% STATEMENT CLOUD BASED DATABASES n #/!,%3#% EXPRESSION n #ODD %& h4EDv RULES FOR RELATIONAL DATABASES n #ODE'EAR COLLATING SEQUENCE COLLECTIONS DEFINING n MANIPULATING COLLECTION DATA n QUERYING COLLECTION DATA n AND STORED PROCEDURES n COLUMN CONSTRAINTS COLUMN FUNCTIONS n COMPUTING A COLUMN AVERAGE COMPUTING A COLUMN TOTAL n COUNTING DATA VALUES n DUPLICATE ROW ELIMINATION
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FINDING EXTREME VALUES n .5,, VALUES AND n IN THE SELECT LIST n COLUMN NAMES QUALIFIED COLUMN NAMES n COLUMN PRIVILEGES COLUMNS ADDING n CALCULATED n DROPPING n INSERTING COMMERCIAL ACCEPTANCE OF 31, n #/--)4 #/--)4 STATEMENT n #OMMON !PPLICATION %NVIRONMENT #!% COMPARISON TEST n COMPLETE DATABASE LANGUAGE 31, AS A CONDITIONAL EXECUTION n CONNECTION BROWSING CONNECTION POOLING CONSISTENCY CONSTANTS DATE AND TIME CONSTANTS n NUMERIC CONSTANTS STRING CONSTANTS SYMBOLIC CONSTANTS CONSTRAINT NAMES CONSTRUCTOR METHOD CONTAINER MANAGED PERSISTENCE CONTAINERS CONTINUOUS INTELLIGENCE CONTINUOUS QUERIES IN STREAM DATABASES n #ORAL CORRELATED REFERENCES CORRELATED SUBQUERIES n CORRELATION NAMES n 3EE ALSO TABLE ALIASES #/5.4 n #2%!4% !,)!3 STATEMENTS n #2%!4% ).$%8 STATEMENTS n
#2%!4% 02/#%$52% STATEMENT n #2%!4% 4!",% STATEMENTS n n CHECK CONSTRAINTS n COLUMN DEFINITIONS n MISSING AND DEFAULT VALUES n PHYSICAL STORAGE DEFINITION n PRIMARY AND FOREIGN KEY DEFINITIONS n UNIQUENESS CONSTRAINTS n #2%!4% 6)%7 STATEMENTS n CREATING A DATABASE n n 3EE ALSO #2%!4% 4!",% STATEMENTS CROSS JOINS IN STANDARD 31, n CROSS PRODUCT CURSOR BASED REPETITION n CURSOR BASED STATEMENTS n CURSORS EMBEDDED 31, NAMED SCROLLABLE AND UPDATEABLE CURSORS IN *$"# n SCROLLING n AND TRANSACTION PROCESSING
$ DASHBOARDS DATA CLEANSING DATA COMPATIBILITY DATA CROSS CHECKING DATA DEFINITION STATEMENTS 3EE ALSO DYNAMIC DATA DEFINITION $ATA $EFINITION ,ANGUAGE 3EE $$, DATA EXTRACTION DATA INSERTIONUPDATE DATA INTEGRITY ADVANCED CONSTRAINT CAPABILITIES n ASSERTIONS BUSINESS RULES n COLUMN CHECK CONSTRAINTS COLUMN CONSTRAINTS
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DATA INTEGRITY #ONTINUED CONSISTENCY DEFERRED CONSTRAINT CHECKING n DEFINED n DOMAINS n ENTITY INTEGRITY n OTHER DATA RELATIONSHIPS REFERENTIAL INTEGRITY n REQUIRED DATA 31, CONSTRAINT TYPES n TABLE CONSTRAINTS VALIDITY CHECKING n DATA MANIPULATION STATEMENTS n $ATA -ANIPULATION ,ANGUAGE 3EE $-, DATA MINING DATA MIRRORING DATA MODELS #/$!3, MODEL FILE MANAGEMENT SYSTEMS n HIERARCHICAL DATABASES n NETWORK DATABASES n RELATIONAL DATA MODELS n DATA REFORMATTING DATA RETRIEVAL DATA SHARING DATA TYPES n ABSTRACT n !.3))3/ 31, DATA TYPES COLLECTION DATA TYPES AND HOST VARIABLES n USER DEFINED DATA TYPES n IN 8-, 3CHEMA n DATA WAREHOUSING n ARCHITECTURE n FOR BUSINESS OPTIMIZATION n COMPONENTS n CONCEPTS n EVOLUTION OF n EXTRACT TRANSFORM AND LOAD %4, FACT CUBES n LOAD PERFORMANCE n
MULTILEVEL DIMENSIONS n VS /,40 QUERY PERFORMANCE n 31, EXTENSIONS FOR n STAR SCHEMAS n DATABASE ADMINISTRATION LANGUAGE 31, AS A DATABASE CONSTRAINTS ASSERTIONS n DOMAINS DATABASE ENGINES DATABASE GATEWAY LANGUAGE 31, AS A DATABASE INTEROPERABILITY DATABASE LIBRARY !0) 3EE DBLIB !0) DATABASE MANAGEMENT EVOLUTION OF n DATABASE MANAGEMENT SYSTEMS $"-3 STATEMENT PROCESSING n DATABASE PROGRAMMING LANGUAGE 31, AS A DATABASE REQUEST MODULE $"2- DATABASE SERVER APPLIANCES n DATABASE STRUCTURE n AND THE !.3))3/ STANDARD n DATABASES ON MULTIPLE SERVERS MULTIDATABASE ARCHITECTURE n MULTILOCATION ARCHITECTURE n SINGLE DATABASE ARCHITECTURE n DATA"ASED )NTELLIGENCE n $" n D"!3% 0LUS n DBBIND DBGETROW n DBLIB !0) BINDING COLUMNS DYNAMIC QUERIES n VS EMBEDDED 31, n n n ERROR HANDLING n FUNCTIONS OVERVIEW POSITIONED UPDATES n RANDOM ROW RETRIEVAL n
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RETRIEVAL USING POINTERS RETRIEVING .5,, VALUES n 31, 3ERVER QUERIES n STATEMENT BATCHES n $"-3 3EE DATABASE MANAGEMENT SYSTEMS $"-3 DBNEXTROW $$, n STATEMENTS IN POPULAR 31, BASED PRODUCTS n DEADLOCKS n DECIMAL CONSTANTS $%#,!2% #523/2 STATEMENT n $%#,!2% 4!",% STATEMENTS n $%&%22!",% CONSTRAINTS DEFERRED CONSTRAINT CHECKING n DEFERRED PARAMETER PASSING DELETE AND UPDATE RULES n DELETE RULES $%,%4% STATEMENTS n DELETING ALL ROWS WITH SUBQUERIES n DELETING DATA n 3EE ALSO $%,%4% STATEMENTS DERIVED TABLE REFERENCE $%3#2)"% STATEMENT n DESCRIPTORS #,) /#) DESKTOP PERSONAL COMPUTERS DEVELOPMENT ENVIRONMENT $EVICE31, DIALECT TRANSLATION n $)34).#4 KEYWORD n DISTRIBUTED DATA MANAGEMENT n DISTRIBUTED DATABASE ACCESS n DISTRIBUTED REQUESTS n DISTRIBUTED TRANSACTIONS REMOTE REQUESTS REMOTE TRANSACTIONS DISTRIBUTED DATABASE LANGUAGE 31, AS A DISTRIBUTED DATABASES
) N D E X ç DISTRIBUTED DEADLOCKS DISTRIBUTED QUERIES DISTRIBUTED REQUESTS n DISTRIBUTED TRANSACTIONS DISTRIBUTED UPDATES DISTRIBUTING DATA REMOTE DATA TRANSPARENCY n REMOTE DATABASE ACCESS n REPLICATION TRADE OFFS TABLE EXTRACTS n TABLE REPLICATION n TYPICAL REPLICATION ARCHITECTURES n UPDATEABLE REPLICAS n $-, $OCUMENT /BJECT -ODEL $/- $OCUMENT 4YPE $EFINITIONS $4$S n $/- DOMAINS n DRIVERS $2/0 !,)!3 STATEMENTS n DROP BEHAVIOR $2/0 ).$%8 STATEMENTS n $2/0 02/#%$52% STATEMENT DROP RULES $2/0 4!",% STATEMENTS n $2/0 6)%7 STATEMENTS $4$S 3EE $OCUMENT 4YPE $EFINITIONS $4$S DUPLICATE ROWS n ELIMINATION OF AND 5./. OPERATIONS n DYNAMIC DATA DEFINITION DYNAMIC QUERIES n n $%#,!2% #523/2 STATEMENT $%3#2)"% STATEMENT n DYNAMIC #,/3% STATEMENT DYNAMIC &%4#( STATEMENT DYNAMIC /0%. STATEMENT n AND THE 31, STANDARD n DYNAMIC QUERY PROCESSING USING #,) n
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DYNAMIC 31, BASIC STATEMENTS n CONCEPTS n DIALECTS n DYNAMIC STATEMENT EXECUTION n %8%#54% STATEMENT n 02%0!2% STATEMENT n AND THE 31, STANDARD n STANDARD 31,$! n TWO STEP DYNAMIC EXECUTION n 3EE ALSO STATIC 31, DYNAMIC 31, IN /RACLE n
% %*"S 3EE %NTERPRISE *AVA "EANS %*"S ELEMENTS IN 8-, 3CHEMA n EMBEDDED DATABASES CHARACTERISTICS IMPLEMENTATIONS n EMBEDDED 31, AUTOMATIC REBINDING n #,/3% STATEMENT n CONCEPTS n CURSOR BASED DELETES AND UPDATES n CURSORS CURSORS AND TRANSACTION PROCESSING DATA RETRIEVAL IN n VS DBLIB !0) n n n $%#,!2% #523/2 STATEMENT n DECLARING TABLES n DEVELOPING AN EMBEDDED 31, PROGRAM n ERROR HANDLING n &%4#( STATEMENT HOST VARIABLES n INPUT AND OUTPUT HOST VARIABLES n MULTIROW QUERIES n ./4 &/5.$ CONDITION /0%. STATEMENT n
RETRIEVAL USING DATA STRUCTURES RETRIEVING .5,, VALUES n RUNNING AN EMBEDDED 31, PROGRAM n RUNTIME SECURITY SCROLL CURSORS n SIMPLE STATEMENTS n SINGLE ROW QUERIES n EMPTY TABLES %NCIRQ ENTERPRISE APPLICATION SUPPORT ENTERPRISE APPLICATIONS AND DATA CACHING n ENTERPRISE DATABASE MARKET MATURITY n ENTERPRISE $"-3 LINKS %NTERPRISE *AVA "EANS %*"S ACCESSOR METHODS CORRESPONDING DATABASE AND %*" ACTIVITIES DEPLOYMENT DESCRIPTORS FINDER METHODS INTERCEPTOR METHODS SELECT METHODS TYPES n VERSION ENHANCEMENTS n VERSION ENHANCEMENTS n %NTERPRISE$" ENTITY BEANS BEAN MANAGED PERSISTENCE CONTAINER MANAGED PERSISTENCE DATABASE ACCESS FROM n ENTITY INTEGRITY n EQUI JOINS n 3EE ALSO NON EQUI JOINS ERROR CODES ERROR HANDLING n CONDITIONS n *$"# /#) WITH 31,#/$% n WITH 31,34!4% n
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USING #,) n 7(%.%6%2 STATEMENT n ESCAPE CHARACTERS n %UROPEAN 8/0%. CONSORTIUM EVENT PROCESSING APPLICATIONS n EVENT PROCESSING ENGINES EXACT NUMERIC LITERALS %8#%04 OPERATION n EXCLUSIVE LOCKS %8%#54% )--%$)!4% STATEMENT n %8%#54% STATEMENT WITH HOST VARIABLES n WITH 31,$! n EXISTENCE TEST n EXPRESSIONS EXTENSIBILITY %XTENSIBLE 3TYLESHEET ,ANGUAGE 4RANSFORMATION 3EE 83,4 EXTENSIONS FOR DATA WAREHOUSING n EXTERNAL STORED PROCEDURES n 3EE ALSO STORED PROCEDURES
& FACETS FACT CUBES n &%4#( STATEMENT DYNAMIC &%4#( STATEMENT FIELDS FILE DESCRIPTIONS &$S FILE MANAGEMENT SYSTEMS n FILE SERVER ARCHITECTURE FINDER METHODS &)03 &IREBIRD FLOATING POINT CONSTANTS FOREIGN KEYS n AND .5,, VALUES n &2/- CLAUSE QUERY EXPRESSIONS IN n FUNCTIONS n 3EE ALSO BUILT IN FUNCTIONS FUTURE OF 31, CLOUD BASED AND HORIZONTALLY SCALABLE DATABASES n
DATA WAREHOUSING FOR BUSINESS OPTIMIZATION n DISTRIBUTED DATABASES EMBEDDED DATABASES )NTERNET AND NETWORK SERVICES INTEGRATION n OBJECT INTEGRATION n ULTRAHIGH PERFORMANCE DATABASES n
' '2!.4 /04)/. STATEMENTS n 2%6/+% AND n '2!.4 STATEMENTS n n 'REENPLUM n '2/50 "9 CLAUSE n GROUP SEARCH CONDITIONS n .5,, VALUES AND RESTRICTIONS GROUPED QUERIES n MULTIPLE GROUPING COLUMNS n .5,, VALUES IN GROUPING COLUMNS n RESTRICTIONS n GROUPED VIEWS n GROUPING COLUMNS MULTIPLE GROUPING COLUMNS n .5,, VALUES IN n
( HANDHELD DEVICES HANDLES #,) /#) HARDWARE PERFORMANCE GAINS n HASH INDEXES (!6).' CLAUSE n SUBQUERIES IN n HETEROGENEOUS SYSTEMS (EWLETT 0ACKARD #OMPANY HIERARCHICAL DATABASES n HIGH VOLUME )NTERNET DATA MANAGEMENT n
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HISTORY OF 31, n HORIZONTAL VIEWS n HORIZONTALLY SCALABLE DATABASES n HOST VARIABLES n AND DATA TYPES n DECLARING n %8%#54% STATEMENT WITH n INPUT AND OUTPUT n AND .5,, VALUES n (31,$" (4-,
) )"- EARLY COMMITMENT TO 31, )"- #ORPORATION n EARLY RELATIONAL PRODUCTS IMPORTANCE OF 31, n INDEX CREATIONUPDATE INDEXES n INDEX ORGANIZED TABLES INDUSTRY INFRASTRUCTURE INFORMATION CALLS #,) n )NFORMIX n )NGRES #ORPORATION INHERITANCE n SUBTYPES SUPERTYPES TABLE INHERITANCE n ).)4)!,,9 $%&%22%$ CONSTRAINTS ).)4)!,,9 )--%$)!4% CONSTRAINTS IN MEMORY DATABASES n ANATOMY OF n CACHING n IMPLEMENTATIONS n INNER JOINS IN STANDARD 31, n INPUT ADAPTERS ).3%24 STATEMENTS ADDING DATA TO THE DATABASE n BULK LOAD INSERTING .5,, VALUES MULTIROW ).3%24 n SINGLE ROW ).3%24 n INTEGER CONSTANTS
INTEGRITY INTERACTIVE AD HOC QUERIES INTERACTIVE QUERY LANGUAGE 31, AS AN )NTERBASE INTERCEPTOR METHODS )NTERNET AND NETWORK SERVICES INTEGRATION n )NTERNET APPLICATIONS 31, AND )NTERNET CONNECTIONS )NTERNET DATA ACCESS LANGUAGE 31, AS AN )NTERNET DATABASE ACCESS n ).4%23%#4 OPERATION n )NTERSYSTEMS n )3 ./4 .5,, n )3 .5,, n )3/ n
* *%% n JAVA BEANS *AVA $ATABASE #ONNECTIVITY 3EE *$"# *AVA INTEGRATION *$"# !0) n BASIC STATEMENT PROCESSING n CALLABLE STATEMENTS n #ONNECTION OBJECT METHODS DATA SOURCES $RIVER-ANAGER OBJECT METHODS ERROR HANDLING HISTORY AND VERSIONS n IMPLEMENTATIONS AND DRIVER TYPES n OVERVIEW PREPARED STATEMENTS n 2ESULT3ET OBJECT METHODS RETRIEVING METADATA n ROWSETS n SCROLLABLE AND UPDATEABLE CURSORS n SIMPLE QUERY PROCESSING n 3TATEMENT OBJECT METHODS
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4YPE DRIVER *$"#/$"# BRIDGE n 4YPE DRIVER .ATIVE !0) DRIVER n 4YPE DRIVER .ETWORK .EUTRAL DRIVER n 4YPE DRIVER .ETWORK 0ROPRIETARY DRIVER n */). KEYWORD JOINED TABLE REFERENCE JOINED VIEWS n JOINS ALTERNATIVE WAY TO SPECIFY JOINS n CROSS JOINS IN STANDARD 31, n EQUI JOINS n INNER JOINS IN STANDARD 31, n MULTIPLE MATCHING COLUMNS MULTITABLE JOINS IN STANDARD 31, n NATURAL JOINS NON EQUI JOINS OUTER JOINS n n QUERIES WITH THREE OR MORE TABLES n WITH ROW SELECTION CRITERIA n SELF JOINS n STRUCTURE OF n AND SUBQUERIES n SUMMARY OF n UNION JOINS JUMPING WINDOWS
, ,!-0 STACK ,!. SERVERS LARGE DATA OBJECTS LARGE OBJECT SUPPORT IN THE RELATIONAL MODEL n SPECIALIZED ,/" PROCESSING n LATENCY VERY LOW LATENCY AND IN MEMORY DATABASES n ,INUX BASED SERVERS LISTS
LITERALS ,/" LOCATORS n ,/" PROCESSING FUNCTIONS n ,/"S 3EE LARGE DATA OBJECTS LOCATION TRANSPARENCY LOCKING n DEADLOCKS n EXPLICIT LOCKING n ISOLATION LEVELS n LEVELS n PARAMETERS SHARED AND EXCLUSIVE LOCKS LOGICAL DATABASE DEVICES LOGICAL SEGMENTS LOOPING
MAINFRAMES 31, ON MARKET DIVERSITY AND SEGMENTATION MARSHALING n MATCHING COLUMNS MULTIPLE MATCHING COLUMNS MATERIALIZED VIEWS n n -ATISSE 3OFTWARE )NC -!8 n MEMBER FUNCTIONS n MESSAGE HANDLING 3EE ERROR HANDLING MESSAGE DRIVEN BEANS METADATA AND 8-, n METHODS AND STORED PROCEDURES n -ICROSOFT SUPPORT FOR 31, -ICROSOFT #ORPORATION n MILESTONES IN 31, DEVELOPMENT -IMER )NFORMATION 4ECHNOLOGY -). n MINICOMPUTERS 31, ON n MISSING DATA n MIXED VENDOR ENVIRONMENT MOBILE DATABASES n MOBILE LAPTOP 0#S MODIFYING DATA IN THE DATABASE n 3EE ALSO 50$!4% STATEMENTS
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MULTISETS MULTITABLE JOINS IN STANDARD 31, n MULTITABLE QUERIES ALL COLUMN SELECTIONS n PARENTCHILD QUERIES n PERFORMANCE QUALIFIED COLUMN NAMES n RULES FOR MULTITABLE QUERY PROCESSING n SELF JOINS n 31, CONSIDERATIONS FOR n TABLE ALIASES n THREE TABLE JOINS n TWO TABLE QUERY EXAMPLE n 3EE ALSO JOINS MULTITIER ARCHITECTURE n -Y31, n
. NAMED CURSORS NAMED PROCEDURES NAMED ROW TYPES NAMED VARIABLES NAMES COLUMN NAMES TABLE NAMES n NATURAL JOINS .#,/" N#LUSTER . CUBES NESTED SUBQUERIES n NESTED TABLES .ETEZZA #ORPORATION NETWORK APPLICATIONS AND DATABASE ARCHITECTURE n NETWORK DATABASES n NETWORK TRANSPARENCY NETWORKING CENTRALIZED ARCHITECTURE n CLIENTSERVER ARCHITECTURE n FILE SERVER ARCHITECTURE MULTITIER ARCHITECTURE n NODEGROUPS
NON EQUI JOINS NONRESERVED KEYWORDS n 3EE ALSO RESERVED KEYWORDS ./4 $%&%22!",% CONSTRAINTS ./4 &/5.$ CONDITION ./4 KEYWORD n ./4 .5,, CONSTRAINT NULL VALUE TEST n .5,, VALUES n COLUMN FUNCTIONS AND n IN COMPARISON TESTS n AND FOREIGN KEYS n GROUP SEARCH CONDITIONS AND IN GROUPING COLUMNS n AND HOST VARIABLES n INSERTING RETRIEVING n AND UNIQUENESS .5,,)& EXPRESSION n
/ /!3)3 OBJECT INTEGRATION n OBJECT SUPPORT n OBJECT TECHNOLOGY OBJECT ORIENTED DATABASES n ATTRIBUTES CLASSES ENCAPSULATION INHERITANCE MESSAGES AND METHODS OBJECT IDENTITY OBJECTS OBJECTS AND THE DATABASE MARKET n PROS AND CONS OF n OBJECT RELATIONAL DATABASES HANDLES AND OBJECT IDS LARGE DATA OBJECTS SEQUENCES SETS AND ARRAYS STORED PROCEDURES STRUCTUREDABSTRACT DATA TYPES TABLES WITHIN TABLES USER DEFINED DATA TYPES
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/#) CATALOG INFORMATION DESCRIPTORS ERROR HANDLING HANDLES INITIALIZATION AND CONNECTION MANAGEMENT ROUTINES LARGE OBJECT MANIPULATION n OLD /#) FUNCTIONS OVERVIEW QUERY RESULTS PROCESSING STATEMENT EXECUTION TRANSACTION MANAGEMENT n /#)!TTR'ET /#)"INDBY.AME /#)"INDBY0OS /#)$EFINE"Y0OS /#)$ESCRIBE!NY /#))NITIALIZE /#),OGOFF /#),OGON /#)3TMT%XECUTE /#)3TMT0REPARE /$"# ASYNCHRONOUS EXECUTION BINDING OFFSET BLOCK CURSOR BOOKMARKS CATALOG FUNCTIONS n CONNECTION BROWSING CONNECTION POOLING CURRENT ROWSET AND $"-3 INDEPENDENCE EXTENDED CAPABILITIES n OVERVIEW PARAMETER ARRAYS QUERY PROCESSING EFFICIENCY AND THE 31, !CCESS 'ROUP n 31, DIALECT TRANSLATION n STATEMENT BATCHES STATEMENT PROCESSING EFFICIENCY n STRUCTURE OF n 3EE ALSO #,)
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/,!0 /,40 VS DATA WAREHOUSING /NLINE !NALYTICAL 0ROCESSING 3EE /,!0 ONLINE TRANSACTION PROCESSING 3EE /,40 /PEN $ATABASE #ONNECTIVITY 3EE /$"# OPEN SOURCE APPLICATION DEVELOPMENT OPEN SOURCE SUPPORT /0%. STATEMENT n DYNAMIC /0%. STATEMENT n OPTIMIZATION /2 KEYWORD n /RACLE #ALL )NTERFACE 3EE /#) /RACLE #ORPORATION n /RACLE ,ITE /RACLE 31,$! n /3 n OUTER JOINS n LEFT AND RIGHT OUTER JOINS n OLDER OUTER JOIN NOTATION n IN STANDARD 31, n OUTER REFERENCES n OUTPUT ADAPTERS OUTPUT PARAMETERS n OVERLOADING PROCEDURE DEFINITIONS OVERVIEW OF 31, n
0 PACKAGED ENTERPRISE APPLICATIONS 0AR!CCEL )NC PARAMETER ARRAYS PARAMETER MARKERS PARENTCHILD QUERIES n PARTITIONS TABLE AND INDEX PARTITIONING PASSING PRIVILEGES n PATTERN MATCHING TEST n PERFORMANCE PERSISTENCE BEAN MANAGED PERSISTENCE CONTAINER MANAGED PERSISTENCE PERSONAL COMPUTERS 31, ON n PLACEHOLDERS POLYMORPHISM
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31,ç4HEç#OMPLETEç2EFERENCE
PORTABILITY n ACROSS COMPUTER SYSTEMS PORTALS POSITIONED UPDATES n 0OSTGRES 0LUS 0OSTGRE31, PREDICATES 02%0!2% STATEMENT n PREPARED STATEMENTS *$"# n 02)-!29 +%9 CONSTRAINT PRIMARY KEYS n PRIVILEGES n GRANTING n OTHER PRIVILEGES OWNERSHIP PRIVILEGES REVOKING n 31, EXTENDED PRIVILEGES n PROCEDURAL 31, CONCEPTS n PROGRAMMATIC DATABASE ACCESS PROGRAMMATIC INTERFACE PROGRAMMATIC 31, TECHNIQUES n PROLIFERATION OF 31, n PROTECTING DATA n
1 QUALIFIED COLUMN NAMES n QUANTIFIED COMPARISON TEST !,, TEST n !.9 TEST n QUERIES ADVANCED n QUERIES AND 8-, n QUERIES SIMPLE n QUERY EXPRESSIONS n n QUERY RESULTS n COMBINING n PROCESSING RULES SORTING n QUERY SPECIFICATION n
2 RANGE TEST n 2$"-3 RECORD BASED WINDOWS
RECOVERY 2ED "RICK )NTELLIGENT 31, 2)31, REFERENTIAL &/2%)'. +%9 CONSTRAINT REFERENTIAL INTEGRITY n CASCADED DELETES AND UPDATES DELETE AND UPDATE RULES n FOREIGN KEYS AND .5,, VALUES n PROBLEMS n REFERENTIAL CYCLES n AND TRIGGERS RELATIONAL DATA MODELS n FOREIGN KEYS n PRIMARY KEYS n RELATIONSHIPS SAMPLE DATABASE n TABLES n RELATIONAL DATABASE MANAGEMENT SYSTEMS 3EE 2$"-3 RELATIONAL DATABASES RULES FOR RELATIONAL DATABASES n EARLY RELATIONAL PRODUCTS n 31, AS A LANGUAGE FOR TABLE STRUCTURE n 2ELATIONAL /NLINE !NALYTICAL 0ROCESSING 3EE 2/,!0 RELATIONSHIPS 2%,%!3% 3!6%0/).4 STATEMENT REMARKS REMOTE DATA TRANSPARENCY n REMOTE DATABASE ACCESS n REMOTE REQUESTS REMOTE TRANSACTIONS REMOVING A TABLE n REPEATED EXECUTION n REPLICATION REPLICATION ARCHITECTURES HORIZONTAL TABLE SUBSETS MIRRORED TABLES n VERTICAL TABLE SUBSETS n REQUIRED DATA RESERVED KEYWORDS n 3EE ALSO NONRESERVED KEYWORDS
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2%342)#4 DELETE RULE 2%342)#4 UPDATE RULE RESULT SET 3EE ALSO QUERY RESULTS RETRIEVING DATA n SINGLE ROW RETRIEVAL 2%6/+% STATEMENTS n AND THE !.3))3/ STANDARD n 2/,!0 ROLE OF 31, n ROLE BASED SECURITY n 2/,,"!#+ 2/,,"!#+ STATEMENT n ROW DATA TYPES ROW SELECTION n JOINS WITH ROW SELECTION CRITERIA n ROWS ROW VALUE CONSTRUCTOR EXPRESSION n ROW VALUED COMPARISONS ROW VALUED EXPRESSIONS n ROW VALUED SUBQUERIES n
3 3AA3 SAMPLE DATABASE n #534/-%23 TABLE DOWNLOADING SCRIPTS FOR n /&&)#%3 TABLE /2$%23 TABLE 02/$5#43 TABLE 3!,%32%03 TABLE SIMPLE RELATIONAL DATABASE n STRUCTURE OF 3!6%0/).4 STATEMENT 3!8 SCALAR VALUED EXPRESSIONS n SCHEMAS n SCRIPTS n SCROLLING CURSORS n SEARCH CONDITIONS COMPOUND SEARCH CONDITIONS n GROUP SEARCH CONDITIONS n SUBQUERIES n
SECURITY CONCEPTS OBJECTS PRIVILEGES n n ROLE BASED n USER AUTHENTICATION n USER GROUPS n USER IDS n AND VIEWS n SELECT METHODS 3%,%#4 STATEMENTS n n n &2/- CLAUSE DUPLICATE ROWS n n '2/50 "9 CLAUSE n (!6).' CLAUSE n n /2$%2 "9 CLAUSE n 3%,%#4 CLAUSE SELECTING ALL COLUMNS n SINGLE ROW RETRIEVAL VS SUBQUERIES n 7(%2% CLAUSE n n SELF JOINS n SEMANTIC DIFFERENCES 3%15%, SESSION BEANS DATABASE ACCESS FROM n USING *$"# FROM A STATEFUL SESSION BEAN n USING *$"# FROM A STATELESS SESSION BEAN 3%4 $%&!5,4 DELETE RULE 3%4 $%&!5,4 UPDATE RULE SET MEMBERSHIP TEST n n 3%4 .5,, DELETE RULE 3%4 .5,, UPDATE RULE 3%4 42!.3!#4/. STATEMENTS n SETS 3'-, n SHARED LOCKS 3IMPLE !0) FOR 8-, 3!8 SIMPLE ELEMENTS SIMPLE JOINS 3EE EQUI JOINS
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31,ç4HEç#OMPLETEç2EFERENCE
3IMPLE /BJECT !CCESS 0ROTOCOL 3EE 3/!0 SIMPLE QUERIES n SIMPLE TABLE REFERENCE SINGLE ROW QUERIES n SINGLE TABLE QUERIES n COMBINING QUERY RESULTS n SLIDING WINDOWS SLOWLY CHANGING DIMENSIONS SNOWFLAKE SCHEMAS 3/!0 3OFTWARE AS A 3ERVICE 3EE 3AA3 3OLID$" SORTING QUERY RESULTS n AND 5./. OPERATIONS SPECIALTY DATABASES EMBEDDED DATABASES n IN MEMORY DATABASES n MOBILE DATABASES n STREAM DATABASES n 31, !CCESS 'ROUP n 31, CONSTRAINT TYPES n 31, $ATA !REA 31,$! 31, $ESCRIPTOR !REA SQL INJECTION 31, 3ERVER !0)S BASIC TECHNIQUES n DYNAMIC QUERIES n ERROR HANDLING n POSITIONED UPDATES n QUERIES n STATEMENT BATCHES n 31, STANDARDIZATION !.3))3/ STANDARDS n EARLY 31, STANDARDS *$"# AND APPLICATION SERVERS /$"# AND THE 31, !CCESS 'ROUP n PORTABILITY n 31,!LLOC(ANDLE 31,!NYWHERE 31,"ASE
31,"IND#OL n 31,"IND0ARAM 31,"ULK/PERATIONS 31,#ANCEL n 31,#,) STANDARD !0) FUNCTIONS n SCROLLING CURSORS 3EE ALSO #,) 31,#ONNECT 31, CONNECTION n 31,$! STANDARD 31,$! n 31,$ATA3OURCES 31,$ISCONNECT 31,%ND4RAN 31, ENVIRONMENT 31,%RROR n 31,%XEC$IRECT n 31,%XECUTE n 31,&ETCH n 31,&ETCH3CROLL 31,&REE(ANDLE 31,'ET$ATA n 31,'ET$ESC&IELD 31,'ET$ESC2EC 31,0ARAM$ATA 31,0ERSISTENT 3TORED -ODULES 3EE 31,0331,0REPARE 31,03- n STORED PROCEDURES STANDARD n TRIGGERS STANDARD n 31,0UT$ATA 31,2OW#OUNT n 31,3ET#URSOR.AME 31, STATEMENT 3TANDARD 'ENERALIZED -ARKUP ,ANGUAGE 3EE 3'-, STANDARDS STAR SCHEMAS n 34!24 42!.3!#4)/. STATEMENTS n STATEFUL SESSION BEANS
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STATELESS SESSION BEANS STATEMENT BATCHES n STATEMENT BLOCKS n STATEMENT ELEMENTS STATEMENTS n MAJOR 31, STATEMENTS n NONRESERVED KEYWORDS n RESERVED KEYWORDS n STRUCTURE OF A 31, STATEMENT VARIABLES STATIC 31, LIMITATIONS OF n 3EE ALSO DYNAMIC 31, STORED PROCEDURES ADVANTAGES OF n BASIC EXAMPLE n CALLING n CLIENTSERVER APPLICATIONS WITH n AND COLLECTIONS n CONDITIONAL EXECUTION n CREATING n CURSOR BASED REPETITION n EXTERNAL n FLOW OF CONTROL CONSTRUCTS n AND METHODS n OVERLOADING PROCEDURE DEFINITIONS PERFORMANCE REPEATED EXECUTION n RETURNING VALUES VIA PARAMETERS n 31,03- STORED PROCEDURES STANDARD n STATEMENT BLOCKS n SYSTEM DEFINED VARIABLES n STREAM DATABASES n COMPONENTS n IMPLEMENTATIONS n 3TREAMBASE 3YSTEMS n STRUCTURE OF 31, STRUCTURED DATA
) N D E X ç 3TRUCTURED %NGLISH 1UERY ,ANGUAGE 3EE 3%15%, 3TRUCTURED 1UERY ,ANGUAGE 31, SUBQUERIES CORRELATED n DEFINED n IN THE (!6).' CLAUSE n AND JOINS n NESTED n OUTER REFERENCES n ROW VALUED SUBQUERIES n SEARCH CONDITIONS n VS 3%,%#4 STATEMENTS n TABLE VALUED SUBQUERIES n IN THE 7(%2% CLAUSE n SUBQUERY COMPARISON TEST n SUBQUERY SET MEMBERSHIP TEST SUBSTITUTABILITY FEATURE SUCCESS OF 31, n 35- n SUMMARIZING DATA n SUMMARY QUERIES IN OPERATION 3EE ALSO COLUMN FUNCTIONS 3UN -ICROSYSTEMS n 3YBASE )NC SYMMETRIC MULTIPROCESSING 3-0 SYNONYMS n SYNTAX ACCESS CONTROL STATEMENTS BASIC DATA MANIPULATION STATEMENTS n ".& NOTATION CURSOR BASED STATEMENTS DATA DEFINITION STATEMENTS EXPRESSIONS QUERY EXPRESSIONS n SEARCH CONDITIONS SIMPLE ELEMENTS STATEMENT ELEMENTS TRANSACTION PROCESSING STATEMENTS
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SYSTEM CATALOG AND THE !.3))3/ STANDARD CATALOG VIEWS MANDATED BY THE 31, STANDARD n COLUMN INFORMATION n CONTENTS n DEFINED n DOMAINS DESCRIBED IN THE 31, STANDARD PRIVILEGES INFORMATION n AND QUERY TOOLS n RELATIONSHIP INFORMATION n REMARKS 31, INFORMATION SCHEMA n 393#!44!",%3 VIEW n TABLE INFORMATION n TABLES UNIQUE TO THE $"-3 USER INFORMATION n VIEW INFORMATION n SYSTEM TABLES 3YSTEM2 3YSTEMS !PPLICATION !RCHITECTURE 3!!
4 TABLE ALIASES n TABLE CONSTRAINTS TABLE EXTRACTS n TABLE INHERITANCE n 3EE ALSO INHERITANCE TABLE MULTIPLICATION n TABLE NAMES n TABLE REFERENCES TABLES n TABLESPACES TABLE VALUE CONSTRUCTOR EXPRESSION n TABLE VALUED EXPRESSIONS n TABLE VALUED SUBQUERIES n 4ERADATA #ORPORATION TIME BASED WINDOWS TOUR OF 31, n TRANSACTION LOGGING n
TRANSACTION PROCESSING AND CURSORS 31, AND n STATEMENTS TRANSACTIONS !.3))3/ 31, TRANSACTION MODEL n #/--)4 AND 2/,,"!#+ STATEMENTS n CONCURRENT TRANSACTIONS n DEFINED n INCONSISTENT DATA PROBLEM n LOCKING n LOST UPDATE PROBLEM n AND MULTIUSER PROCESSING n PHANTOM INSERT PROBLEM n 3!6%0/).4 AND 2%,%!3% 3!6%0/).4 STATEMENTS 3%4 42!.3!#4/. STATEMENTS n 34!24 42!.3!#4)/. STATEMENTS n TRANSACTION LOGS n UNCOMMITTED DATA PROBLEM n TRENDS DATABASE SERVER APPLIANCES n ENTERPRISE DATABASE MARKET MATURITY n HARDWARE PERFORMANCE GAINS n MARKET DIVERSITY AND SEGMENTATION PACKAGED ENTERPRISE APPLICATIONS 3OFTWARE AS A 3ERVICE 31, STANDARDIZATION TRIGGERS ADVANTAGES AND DISADVANTAGES n DEFINED n IN )NFORMIX 30, n IN /RACLE 0,31, n OTHER CONSIDERATIONS AND REFERENTIAL INTEGRITY AND THE 31, STANDARD 31,03- TRIGGERS STANDARD n IN 4RANSACT 31, n
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4RUVISO )NC 4 TREE INDEXES TWO PHASE COMMIT PROTOCOL n TWO TABLE QUERY EXAMPLE n
5 ULTRAHIGH PERFORMANCE DATABASES n 5NIFY #ORPORATION UNION JOINS 5.)/. OPERATION n n AND DUPLICATE ROWS n MULTIPLE 5.)/. OPERATIONS n AND SORTING 5.)15% CONSTRAINT UNIQUENESS AND .5,, VALUES UNIQUENESS CONSTRAINTS n UNIVERSAL ACCESS 5.)8 BASED SERVERS 5.)8 BASED SYSTEMS 31, ON UNMARSHALING n 50$!4% STATEMENTS n WITH SUBQUERIES n UPDATING ALL ROWS UPDATEABLE REPLICAS n UPDATING THE DATABASE USER DEFINED DATA TYPES n USER DEFINED FUNCTIONS USER IDS n
6 VALIDATION PROCEDURE VALIDITY CHECKING n VARIABLES VARYING ARRAYS VENDOR INDEPENDENCE VENDORS n !STER $ATA N#LUSTER #ODE'EAR )NTERBASE DATA"ASED )NTELLIGENCE D"!3% 0LUS n %NCIRQ $EVICE31, %NTERPRISE$" 0OSTGRES 0LUS &IREBIRD
'REENPLUM n (EWLETT 0ACKARD #OMPANY (31,$" )"- #ORPORATION )"- #ORPORATION $" )NFORMIX n )NGRES #ORPORATION )NGRES )NTERSYSTEMS #ACH£ n -ATISSE 3OFTWARE )NC -ATISSE -ICROSOFT #ORPORATION n -IMER )NFORMATION 4ECHNOLOGY -IMER .ETEZZA #ORPORATION /RACLE #ORPORATION n 0AR!CCEL )NC 0OSTGRE31, 3TREAMBASE 3YSTEMS n 3UN -ICROSYSTEMS -Y31, n 3YBASE )NC 4ERADATA #ORPORATION 4RUVISO )NC 5NIFY #ORPORATION 31,"ASE 6ERTICA 3YSTEMS 8EROUND 8EROUND )NTELLIGENT $ATA 'RID n VERSIONING n ADVANTAGES AND DISADVANTAGES IN OPERATION n 6ERTICA 3YSTEMS VERTICAL VIEWS VIEWS ADVANTAGES OF n CHECKING VIEW UPDATES n CREATING VIEWS n DEFINED n DISADVANTAGES OF DROPPING VIEWS GROUPED VIEWS n HORIZONTAL VIEWS n HOW THE $"-3 HANDLES VIEWS
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31,ç4HEç#OMPLETEç2EFERENCE
VIEWS #ONTINUED JOINED VIEWS n MATERIALIZED VIEWS n n ROWCOLUMN SUBSET VIEWS n AND SECURITY n SOURCE TABLES UPDATES IN COMMERCIAL 31, PRODUCTS UPDATING n VERTICAL VIEWS VIEW UPDATES AND THE !.3))3/ STANDARD
7 WEB SITES EARLY IMPLEMENTATIONS n 7(%.%6%2 STATEMENT n 7(%2% CLAUSE SUBQUERIES IN n WILDCARD CHARACTERS n WORKGROUP DATABASES 31, AND n WORKSTATIONS
8 8EROUND )NTELLIGENT $ATA 'RID n 8-, BASIC CONCEPTS n FOR DATA n DATA EXCHANGE DATA INTEGRATION
DATABASES $OCUMENT 4YPE $EFINITIONS $4$S n ELEMENTS VS ATTRIBUTES n INDUSTRY GROUP STANDARDS INPUT n MARSHALING AND UNMARSHALING n AND METADATA n OUTPUT n OVERVIEW n PARSERS n AND QUERIES n SIMPLE STORAGE WITH LARGE OBJECTS n AND 31, n 31,8-, FUNCTIONS STORAGE n 8-, 3CHEMA n 8-, $ATA 8-, 0ATH ,ANGUAGE 3EE 80!4( 8-, $ATA 8/0%. 80!4( n 81UERY OVERVIEW n PATH EXPRESSIONS n QUERY PROCESSING IN n 83,4 n
