Towards Extract-Transform-Load Operations in a Big Data context
Hana Mallek, Faïza Ghozzi, F. Gargouri
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引用次数: 10
Abstract
BigDataemergedafterabigexplosionofdatafromtheWeb2.0,digitalsensors,andsocialmedia applications such as Facebook, Twitter, etc. In this constant growth of data, many domains are influenced, especially thedecisional support systemdomain,where the integrationof processes shouldbeadaptedtosupportthishugeamountofdatatoimproveanalysisgoals.Thebasicpurpose ofthisresearcharticleistoadaptextract-transform-loadprocesseswithBigDatatechnologies,in order tosupportnotonlythisevolutionofdatabutalsotheknowledgediscovery.Inthisarticle, anewapproachcalledBigDimensionalETL(BigDimETL)issuggestedtodealwithETLbasic operationsandtakeintoaccountthemultidimensionalstructure.Inordertoacceleratedatahandling, theMapReduceparadigmisusedtoenhancedatawarehousingcapabilitiesandHBaseasadistributed storagemechanism.ExperimentalresultsconfirmthattheETLoperationperformswellespecially withadaptedoperations. KEywORDS Big Data, ETL, Hbase, Map Reduce, Multidimensional Structure
面向大数据环境下的提取-转换-加载操作
BigDataemergedafterabigexplosionofdatafromtheWeb2.0,digitalsensors,andsocialmedia应用程序,如Facebook, Twitter等,在数据的不断增长中,许多领域都受到了影响,特别是thedecisional supportsystemdomain,where theintegrationof processesshouldbeadaptedtosupportthishugeamountofdatatoimproveanalysisgoals。Thebasicpurpose ofthisresearcharticleistoadaptextract-transform-loadprocesseswithBigDatatechnologies,in order_ tosupportnotonlythisevolutionofdatabutalsotheknowledgediscovery。Inthisarticle, anewapproachcalledBigDimensionalETL(BigDimETL)issuggestedtodealwithETLbasic operationsandtakeintoaccountthemultidimensionalstructure。Inordertoacceleratedatahandling, theMapReduceparadigmisusedtoenhancedatawarehousingcapabilitiesandHBaseasadistributed storagemechanism。ExperimentalresultsconfirmthattheETLoperationperformswellespecially withadaptedoperations。关键词:大数据,ETL, Hbase, Map Reduce,多维结构
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