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Performance Analysis of Hadoop with Pseudo-Distributed Mode on Different Machines

Ruchi Mittal1 , Ruhi Bagga2

Section:Research Paper, Product Type: Journal Paper
Volume-3 , Issue-6 , Page no. 113-117, Jun-2015

Online published on Jun 29, 2015

Copyright © Ruchi Mittal , Ruhi Bagga . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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How to Cite this Paper

IEEE Style Citation: Ruchi Mittal , Ruhi Bagga, “Performance Analysis of Hadoop with Pseudo-Distributed Mode on Different Machines,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.6, pp.113-117, 2015.

MLA Style Citation: Ruchi Mittal , Ruhi Bagga "Performance Analysis of Hadoop with Pseudo-Distributed Mode on Different Machines." International Journal of Computer Sciences and Engineering 3.6 (2015): 113-117.

APA Style Citation: Ruchi Mittal , Ruhi Bagga, (2015). Performance Analysis of Hadoop with Pseudo-Distributed Mode on Different Machines. International Journal of Computer Sciences and Engineering, 3(6), 113-117.

BibTex Style Citation:
@article{Mittal_2015,
author = {Ruchi Mittal , Ruhi Bagga},
title = {Performance Analysis of Hadoop with Pseudo-Distributed Mode on Different Machines},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2015},
volume = {3},
Issue = {6},
month = {6},
year = {2015},
issn = {2347-2693},
pages = {113-117},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=561},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=561
TI - Performance Analysis of Hadoop with Pseudo-Distributed Mode on Different Machines
T2 - International Journal of Computer Sciences and Engineering
AU - Ruchi Mittal , Ruhi Bagga
PY - 2015
DA - 2015/06/29
PB - IJCSE, Indore, INDIA
SP - 113-117
IS - 6
VL - 3
SN - 2347-2693
ER -

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Abstract

Data cannot be managed by the traditional database management systems when it comes in a large amount. So there comes the Big Data. Hadoop and MapReduce are the solution to handle, manage and analyze Big Data. Hadoop is an open source implementation of MapReduce programming paradigm which is a parallel distributed programming model for handling large data intensive applications. In this paper, we present our experimental work done on Hadoop with pseudo-distributed mode on different machines and analyze the time taken by Hadoop to perform the same operations on different machines.

Key-Words / Index Term

Big Data; Hadoop; MapReduce; Pseudo-distributed Mode; Distributed Programming

References

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