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云计算平台中分布式Hadoop数据挖掘关键技术研究（英文）.docx

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云计算平台中分布式Hadoop数据挖掘关键技术研究（英文） ResearchonKeyTechnologiesofDistributedHadoopDataMininginCloudComputingPlatforms Abstract: Withtherapiddevelopmentoftechnology,cloudcomputinghasbecomethemainstreamtrendinthefieldofinformationtechnology.Asoneofthecoretechnologiesincloudcomputing,Hadoopprovidesadistributedcomputingplatformforlarge-scaledatastorageandprocessing.Datamining,asanimportantaspectofbigdataanalysis,playsacrucialroleinextractingvaluableinformationfrommassivedata.ThispaperfocusesonthekeytechnologiesofdistributedHadoopdataminingincloudcomputingplatforms,includingdatapreprocessing,distributedcomputing,parallelalgorithms,anddatavisualization.Throughcomprehensiveresearchandanalysis,thispaperaimstoprovideinsightsintothechallengesandpotentialsolutionsinordertoachieveefficientandeffectivedataminingincloudcomputingplatforms. 1.Introduction: 1.1BackgroundandSignificance Cloudcomputingplatformshavegainedsignificantpopularityduetotheirscalability,cost-effectiveness,andflexibilityinhandlinglarge-scaledata.Hadoop,asanopen-sourceframework,hasbecomeapopularchoiceforbigdataprocessingincloudcomputingenvironments.However,dataminingindistributedHadoopsystemsposesseveralchallenges,suchasdatapreprocessing,efficientparallelalgorithms,andvisualizinginsightsfrommassivedata.Therefore,itisnecessarytoconductresearchonthekeytechnologiesthatenableeffectivedataminingincloudcomputingplatforms. 2.KeyTechnologiesofDistributedHadoopDataMining: 2.1DataPreprocessing Datapreprocessingisanessentialstepindataminingasitinvolvescleaning,transforming,andintegratingdataforfurtheranalysis.IndistributedHadoopsystems,datapreprocessingshouldconsiderthedistributednatureofdataandworkloadpartitioning.Keytechniquesfordistributeddatapreprocessingincludedatapartitioning,datareplication,andfeatureselection.Thesetechniquesoptimizedatadistribution,reducedatatransferoverhead,andimprovetheefficiencyofsubsequentdataminingtasks. 2.2DistributedComputing DistributedcomputingplaysacrucialroleinHadoopdatamining,asitenablesparall