Simplified Mapreduce Mechanism for Large Scale Data Processing

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dc.contributor.authorMunna, Md Tahsir Ahmed
dc.contributor.authorAllayear, Shaikh Muhammad
dc.contributor.authorAlam, Mirza Mohtashim
dc.contributor.authorRahman, Sheikh Shah Mohammad Motiur
dc.contributor.authorRahman, Md Samadur
dc.contributor.authorSarker, M. Mesbahuddin
dc.date.accessioned2018-09-22T07:14:57Z
dc.date.accessioned2019-05-27T09:56:59Z
dc.date.available2018-09-22T07:14:57Z
dc.date.available2019-05-27T09:56:59Z
dc.date.issued2018
dc.description.abstractMapReduce has become a popular programming model for processing and running large-scale data sets with a parallel, distributed paradigm on a cluster. Hadoop MapReduce is needed especially for large scale data like big data processing. In this paper, we work to modify the Hadoop MapReduce Algorithm and implement it to reduce processing time.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/20.500.11948/3263
dc.identifier.urihttp://hdl.handle.net/20.500.11948/3263
dc.language.isoen
dc.publisherSPC
dc.sourceDIU Institutional Repository
dc.subjectMapReduce
dc.subjectLarge Scale Data
dc.subjectHadoop
dc.subjectSimplified Algorithm
dc.subjectPerformance Analysis
dc.titleSimplified Mapreduce Mechanism for Large Scale Data Processing
dc.typeArticle

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