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Design and Analysis of Large Data Processing Techniques

by Madhavi Vaidya, Shrinivas Deshpande, Vilas Thakare
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 8
Year of Publication: 2014
Authors: Madhavi Vaidya, Shrinivas Deshpande, Vilas Thakare
10.5120/17546-8139

Madhavi Vaidya, Shrinivas Deshpande, Vilas Thakare . Design and Analysis of Large Data Processing Techniques. International Journal of Computer Applications. 100, 8 ( August 2014), 24-28. DOI=10.5120/17546-8139

@article{ 10.5120/17546-8139,
author = { Madhavi Vaidya, Shrinivas Deshpande, Vilas Thakare },
title = { Design and Analysis of Large Data Processing Techniques },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 8 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number8/17546-8139/ },
doi = { 10.5120/17546-8139 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:26.782371+05:30
%A Madhavi Vaidya
%A Shrinivas Deshpande
%A Vilas Thakare
%T Design and Analysis of Large Data Processing Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 8
%P 24-28
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As massive data acquisition and storage becomes increasingly affordable, a large number of enterprises are employing statisticians to make the sophisticated data analysis. Particularly, information extraction is done when the data is unstructured or semi-structured in nature. There are emerging efforts taken by both academia and industry on pushing information extraction inside parallel DBMSs. This leads to solving an significant and important issue on what can be a better choice for large scale data processing and analytics. To address this issue, we highlight the comparison and analysis of the three techniques which are nothing but the Parallel DBMS, MapReduce and Bulk Synchronous Processing in this paper.

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Index Terms

Computer Science
Information Sciences

Keywords

Parallel MapReduce Hadoop BSP Distributed

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