Simplified Mapreduce Mechanism for Large Scale Data Processing

dc.contributor.author	Munna, Md Tahsir Ahmed
dc.contributor.author	Allayear, Shaikh Muhammad
dc.contributor.author	Alam, Mirza Mohtashim
dc.contributor.author	Rahman, Sheikh Shah Mohammad Motiur
dc.contributor.author	Rahman, Md Samadur
dc.contributor.author	Sarker, M. Mesbahuddin
dc.date.accessioned	2018-09-22T07:14:57Z
dc.date.accessioned	2019-05-27T09:56:59Z
dc.date.available	2018-09-22T07:14:57Z
dc.date.available	2019-05-27T09:56:59Z
dc.date.issued	2018
dc.identifier.uri	http://hdl.handle.net/20.500.11948/3263
dc.description.abstract	MapReduce 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.	en_US
dc.language.iso	en	en_US
dc.publisher	SPC	en_US
dc.subject	MapReduce	en_US
dc.subject	Large Scale Data	en_US
dc.subject	Hadoop	en_US
dc.subject	Simplified Algorithm	en_US
dc.subject	Performance Analysis	en_US
dc.title	Simplified Mapreduce Mechanism for Large Scale Data Processing	en_US
dc.type	Article	en_US