Simplified Mapreduce Mechanism for Large Scale Data Processing | Zendy

Md Tahsir Ahmed Munna | Zendy; Shaikh Muhammad Allayear | Zendy; Mirza Mohtashim Alam | Zendy; Sheikh Shah Mohammad Motiur Rahman | Zendy; Md Samadur Rahman | Zendy; M Mesbahuddin Sarker | Zendy

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Simplified Mapreduce Mechanism for Large Scale Data Processing

Author(s) -

Md Tahsir Ahmed Munna,

Shaikh Muhammad Allayear,

Mirza Mohtashim Alam,

Sheikh Shah Mohammad Motiur Rahman,

Md Samadur Rahman,

M Mesbahuddin Sarker

Publication year - 2018

Publication title -

international journal of engineering and technology

Language(s) - English

Resource type - Journals

ISSN - 2227-524X

DOI - 10.14419/ijet.v7i3.8.15211

Subject(s) - computer science , big data , data intensive computing , programming paradigm , data processing , scale (ratio) , parallel computing , map reduce , parallel processing , distributed computing , cluster (spacecraft) , distributed database , database , data mining , operating system , grid computing , programming language , physics , geometry , mathematics , quantum mechanics , grid

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.

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