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Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data

P. Dadheech1 , D. Goyal2 , S. Srivastava3

  1. Dept. of CSE, Suresh Gyan Vihar University, Jaipur, India.
  2. Principal, Suresh Gyan Vihar University, Jaipur, India.
  3. Dept. of ICT, Manipal University, Jaipur, India.

Correspondence should be addressed to: pankajdadheech777@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-8 , Page no. 211-214, Aug-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i8.211214

Online published on Aug 30, 2017

Copyright © P. Dadheech, D. Goyal, S. Srivastava . 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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IEEE Style Citation: P. Dadheech, D. Goyal, S. Srivastava, “Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.211-214, 2017.

MLA Style Citation: P. Dadheech, D. Goyal, S. Srivastava "Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data." International Journal of Computer Sciences and Engineering 5.8 (2017): 211-214.

APA Style Citation: P. Dadheech, D. Goyal, S. Srivastava, (2017). Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data. International Journal of Computer Sciences and Engineering, 5(8), 211-214.

BibTex Style Citation:
@article{Dadheech_2017,
author = {P. Dadheech, D. Goyal, S. Srivastava},
title = {Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2017},
volume = {5},
Issue = {8},
month = {8},
year = {2017},
issn = {2347-2693},
pages = {211-214},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1418},
doi = {https://doi.org/10.26438/ijcse/v5i8.211214}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i8.211214}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1418
TI - Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data
T2 - International Journal of Computer Sciences and Engineering
AU - P. Dadheech, D. Goyal, S. Srivastava
PY - 2017
DA - 2017/08/30
PB - IJCSE, Indore, INDIA
SP - 211-214
IS - 8
VL - 5
SN - 2347-2693
ER -

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Abstract

The problem that has occurred as a result of the increased connection between the device and the system is creating information at an exponential rate that it is becoming increasingly difficult for a possible solution for processing. Therefore, creating a platform for such advanced level data processing, which increase the level of hardware and software with bright data. In order to improve the efficiency of the Hadoop Cluster in large data collection and analysis, we have proposed an algorithm system that meets the needs of protected discrimination data in Hadoop Clusters and improves performance and efficiency. The proposed paper aims to find out the effectiveness of the new algorithm, compare, consultation, and find out the best solution for improving the big data scenario is a competitive approach. The map reduction techniques from Hadoop will help maintain a close watch on the underlying or discriminatory Hadoop clusters with insights of results as expected from the luminosity.

Key-Words / Index Term

Big data, hadoop, heterogeneous clusters, map reduce, throughput, latency

References

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