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1、WorkloadDrivenIndexDefragmentationVivekNarasayya,ManojSyamalaMicrosoftResearchOneMicrosoftWay,Redmond,WA,USA.viveknar@microsoft.commanojsy@microsoft.comAbstract—Decisionsupportqueriesthatscanlargeindexescanincludingmeasuresofinternalandexternalfragmentation.Wesuffersigni
2、ficantdegradationinI/Operformanceduetoindexrefertotechniquesthatrelyonlyonthefragmentationfragmentation.DBAsrelyonrulesofthumbthatuseindexsizeinformationfordecidingwhichindexestodefragmentasdata-andfragmentationinformationtoaccomplishthetaskofdrivenapproaches.Sinceitisus
3、uallynotpossibletodecidingwhichindexestodefragment.However,therearetwodefragmentallindexeswithinatypicalbatchwindow(e.g.afundamentallimitationsthatmakethistaskchallenging.First,fewhoursatnight),DBAstodayuserulesofthumbtoselectdatabaseenginesofferlittlesupporttohelpestima
4、tetheimpactofdefragmentinganindexontheI/Operformanceofaquery.whichindexestodefragment,e.g.selectindexesthataremostSecond,defragmentationissupportedonlyatthegranularityoffragmented.anentireB+-Tree,whichcanbetoorestrictivesinceWeobservetwokeylimitationswiththestate-of-the-
5、artindefragmentationisanexpensiveoperation.Thispaperdescribesindexdefragmentation.First,thegranularityatwhichindextechniquesforaddressingtheabovelimitations.WealsostudydefragmentationissupportedisthefullB+-Tree,whichcantheproblemofselectingtheappropriateindexestodefragme
6、ntveryexpensiveforlargeindexes.Inmanycases,theforagivenworkload.WehaveimplementedourtechniquesinfragmentationmaynotbeuniformlydistributedacrosstheMicrosoftSQLServeranddevelopedatoolthatcanprovideB+Tree.Forexample,consideraclusteredindexontheappropriateindexdefragmentatio
7、nrecommendationstoDBAs.OrderDatecolumnofalargefacttablethatstoresorderWeevaluatetheeffectivenessoftheproposedtechniquesonseveralrealandsyntheticdatabases.information.Asnewdataisinsertedintothefacttable,theB+-Treegetsfragmented.However,itisoftenthecasethatI.INTRODUCTIONma
8、nyofthequeriesreferencingonlyrecentdata(e.g.lastDecisionsupportqueriesoftenrequirescansoflargemonthorla
