An Efficient Management for Map Reduce Using Partition and Aggregation in Software Application

Authors(2) :-P. Ramya, Dr A. Saravanan

In this paper, we study to reduce data traffic and to avoid duplication using a MapReduce technique and data partition scheme. Aggregator problem and large-scale optimization problem of duplication and data traffic were made in online or offline. In these problem we use map reduce technique to clustering the data and use k-nearest algorithm is used to reduce the time and cluster the nearest data to avoid conflict. Then we also use ProMiSH based on random projections and hashing for partition process to avoid data traffic in the search engine. In this, we also using k-nearest algorithm for aggregation to clustering the nearest neighbor data and using ProMiSH based on random projections and hashing for partition process to avoid data traffic in the search engine. Then these we use algorithms to decrease the traffic and conflict while processing the data and improve the speed to access the data faster.

Authors and Affiliations

P. Ramya
Research Scholar,Department of CSC, Sun arts and science college, Thiruvannamalai, Tamil Nadu, India
Dr A. Saravanan
Professor, Department of CSC, Sun arts and science college, Thiruvannamalai, Tamil Nadu, India

MapReduce, NSK, K-nearest, ProMiSH

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Publication Details

Published in : Volume 4 | Issue 3 | January-February 2018
Date of Publication : 2018-03-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 96-98
Manuscript Number : CSEIT184317
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

P. Ramya, Dr A. Saravanan, "An Efficient Management for Map Reduce Using Partition and Aggregation in Software Application", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 3, pp.96-98, January-February.2018
URL : http://ijsrcseit.com/CSEIT184317

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