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基于Hadoop分布式系统的重复数据检测技术研究与应用的中期报告.docx

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基于Hadoop分布式系统的重复数据检测技术研究与应用的中期报告 （该报告是英文版翻译，可能存在翻译错误） 1.Introduction Duplicatedataindatastoragesystemscancausevariousproblemssuchasincreasedstoragespaceusage,slowerdataprocessingspeed,andinconsistentdataresults.Toaddressthisissue,manyduplicatedatadetectiontechniqueshavebeendeveloped,includinghash-based,content-based,andhybridmethods.However,thesemethodsareoftencomputationallyexpensiveanddifficulttoscaletolargedatasets. Toaddressthesechallenges,thisprojectproposesaMapReduce-basedduplicatedatadetectiontechnique,whichleveragesthepowerofHadoopdistributedsystemforefficientdataprocessing.Specifically,thistechniqueinvolvesdividingthedataintosmallerdatablocksandusingMapReducetoperformsimilarityassessmentsbetweenthedatablocks.Thesimilarityscoresarethenusedtoidentifyandremoveduplicatedatablocks. Inthismid-termreport,wewillbrieflyintroducetheproposedtechniqueandtheprogressmadeintheprojectsofar. 2.Methodology Theproposedtechniqueinvolvesthefollowingsteps: -Dividingtheinputdataintosmallerdatablocks,eachofwhichisofthesamesize. -Computingthesimilarityscorebetweeneachpairofdatablocksusingasimilaritymeasure,suchasJaccardsimilarityorcosinesimilarity. -Identifyingandremovingtheduplicatedatablocksbasedontheirsimilarityscores. Toimplementthisapproach,weareusingtheHadoopdistributedsystem,whichprovidesascalableandfault-tolerantenvironmentforprocessinglargedatasets.Specifically,weareusingtheMapReduceprogrammingmodel,inwhichthedataisdividedintosmallerchunksandprocessedinparallelondifferentnodesinthecluster. 3.Progress Inthefirstphaseoftheproject,wehavesetupaHadoopclusterconsistingoffournodes,eachwith16GBRAMand500GBdiskspace.WehavealsoimplementedaprototypeoftheduplicatedatadetectiontechniqueusingHadoopMapReduce,whichcanprocesssmalldatasetsonthecluster. Inthesecondphaseoftheproject,weplantoscaleupthetechniquetohandlelargerdatasetsbyoptimizingtheperformanceoftheMapReducealgorithmandincreasingthenumberofnodesinthecluster.Wealsoplantoevaluatetheaccuracyandefficiencyofthetechniqueusingsynthetican