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Implementation of Aggregation of Map and Reduce Function for Performance Improvisation

Authors(1):

Varsha B.Bobade
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Big Data is term that refers to data sets whose size (volume), complexity (variability), and rate of growth (velocity) make them difficult to capture, manage, process or analyzed. To analyze this enormous amount of data Hadoop can be used. Hadoop is an open source software project that enables the distributed processing of large data sets across clusters of commodity servers.

I proposed a modified MapReduce architecture that allows data to be pipelined between operators. This reduces completion times and improve system utilization for batch jobs as well. I present a modified version of the Hadoop MapReduce framework that supports online aggregation, which allows users to see early returns from a job as it is being computed. The objective of the proposed technique is to signicantly improve the performance of Hadoop MapReduce for efficient Big Data processing.

Varsha B.Bobade

Big Data, Hadoop Framework, Online Aggregation, Combiners.

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Publication Details

Published in : Volume 2 | Issue 5 | September-October - 2016
Date of Publication Print ISSN Online ISSN
2016-10-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
196-201 IJSRSET162537   Technoscience Academy

Cite This Article

Varsha B.Bobade, "Implementation of Aggregation of Map and Reduce Function for Performance Improvisation", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 5, pp.196-201, September-October-2016.
URL : http://ijsrset.com/IJSRSET162537.php