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1、TheEssenceofCachingGregLuck,FounderandCTOEhcache,TerracottaJavaOne2011Session24241Tuesday,4October2011TheProblemTuesday,4October2011ApplicationApplicationApplicationApplication>100msDataStoreAverageResponseTimeSpeedCostScalabilityTuesday,4October2011TypesofScalingUPSc
2、aleCommodityServerApplicationScaleOUTTuesday,4October2011CapacityPlanning-PeakLoadWORKLOADSANDSOFTWAREINFRASTRUCTURE25FIGURE2.2:Exampleofdailytrafficfluctuationforasearchserviceinonedatacenter;Google’s Web Searches (1 Datacenter)x-axisisa24-h5periodandthey-axisistrafficmeas
3、uredinqueriespersecond.Tuesday,4October2011knowntoprovidegood-qualitysimilarityscores.Hereweconsideronesuchtypeofanalysis,calledco-citation.TheunderlyingideaistocounteveryarticlethatcitesarticlesAandBasavoteforthesimilaritybetweenAandB.Afterthatisdoneforallarticlesandapp
4、ropriatelynormalized,weob-tainanumericalscoreforthe(co-citation)similaritybetweenallpairsofarticlesandcreateadatastructurethatforeacharticlereturnsanorderedlist(byco-citationscore)ofsimilararticles.Thisdatastructureisperiodicallyupdated,andeachupdatethenbecomespartofthes
5、ervingstatefortheonlineservice.Thecomputationstartswithacitationgraphthatcreatesamappingfromeacharticleidenti-fiertoasetofarticlescitedbyit.Theinputdataaredividedintohundredsoffilesofapproximatelythesamesize(e.g.,thiscanbedonebytakingafingerprintofthearticleidentifier,dividi
6、ngitbythenumberofinputfiles,andusingtheremainderasthefileID)toenableefficientparallelexecution.WeuseasequenceofMapReducerunstotakeacitationgraphandproduceco-citationsimilarityscorevectorforallarticles.InthefirstMapphase,wetakeeachcitationlist(A1,A2,A3,...,An)andgenerateallpa
7、irsofdocumentsinthecitationlist,feedingthemtotheReducephase,whichcountsalloccurrencesofeachpair.Thisfirststepresultsinastructurethatassociatesallpairsofco-citeddocumentswithaco-citationcount.NotethatthisbecomesmuchlessthanaquadraticThe Elephant Curve6Tuesday,4October2011D
8、esirablePropertiesofaSolutionTuesday,4October20118Tuesday,4October20119Tuesday,4October2011APerformance