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1、MLDMWORKSHOP,JANUARY20131DataStreamAnalisysandDataMiningWithStormGregorMajcen,MihaZidarAbstract—TwitterStormisapowerfuldistributedreal-timeonStormthenwewilltakethatknowledgetohypothesiseadataprocessingsolutionwithawiderangeofusage.Inthissolutionforthestockmarketprediction.paperwear
2、egoingtotakealookathowwecanutilizeTwitterStorm’spowerfordataminingonstreamsofdata.Themainfocusofthispaperisreal-timedataprocessingandonlinedataII.TWITTERSTORMmining.Stormisanopensourcedistributedandfault-tolerantIndexTerms—onlinelearning,continuousdata,datamining,real-timecomputati
3、onsystemthatiswriteninclojureanddistributedsystems,horizontalscaling,batchprocessingrunsonJVM.Itprovidesahighabstractionlayerwithwhichwecanruncomplexcomputationsonaclusterofcomputers.StormprovidesuserswithageneralframeworkI.INTRODUCTIONforperformingcomputataionsondatastreamsinreal-
4、time,ODAYwearegeneratingmoredatapersecondthansimilartohowHadoopprovidesuserswithaframeworkforTeverbeforeandtheamountofdataproducedisonlyperformingbatchprocessingoperations.Becauseitrunsonincreasingovertime.DataonitsownisnotthatusefulfortopofZookeeperandhasagoodmessagingsystemusingu
5、sunlesswecanextractinformationfromitandthespeedtupplesofdataitprovidesagoodalternativetomanagingofgatheringthatinformationisbecommingmoreandmoreyourownclusterwithqueuesandworkes.valuable.Thisiswherethereal-timedataprocessingcomesin.BigcompanieslikeTwitter,Groupon,spider.ioandothers
6、Stormcanbeusedforstreamprocessing,processingmes-areusingTwitterStormtoprovideabetteruserexperience.sages,updatingdatabases,updatingonlinemachinelearn-ingmodelsinreal-time.OtherusesalsoincludecontinuousInthelastfewyearsdataprocessinghascomealongwaycomputation,doingacontinuousqueryon
7、datastreamsandwithserviceslikeMapReduce,AmazonEMR,Hadoop,andstreamingouttheresultstousersastheyarecomputed,andrelatedtechologies.AlloftheseweremadetohandlemassivefordistributedRPC.amountsofdata,andtheydothatveryaffectively.Butlatelytheirweaknessisshowingintheirlackofreal-timeproces
8、sing.A.StormstructureNowsp
