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Survey on Improved Scheduling in Hadoop MapReduce in Cloud Environments

by B.Thirumala Rao, Dr. L.S.S.Reddy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 34 - Number 9
Year of Publication: 2011
Authors: B.Thirumala Rao, Dr. L.S.S.Reddy
10.5120/4128-5964

B.Thirumala Rao, Dr. L.S.S.Reddy . Survey on Improved Scheduling in Hadoop MapReduce in Cloud Environments. International Journal of Computer Applications. 34, 9 ( November 2011), 29-33. DOI=10.5120/4128-5964

@article{ 10.5120/4128-5964,
author = { B.Thirumala Rao, Dr. L.S.S.Reddy },
title = { Survey on Improved Scheduling in Hadoop MapReduce in Cloud Environments },
journal = { International Journal of Computer Applications },
issue_date = { November 2011 },
volume = { 34 },
number = { 9 },
month = { November },
year = { 2011 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume34/number9/4128-5964/ },
doi = { 10.5120/4128-5964 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:20:37.605448+05:30
%A B.Thirumala Rao
%A Dr. L.S.S.Reddy
%T Survey on Improved Scheduling in Hadoop MapReduce in Cloud Environments
%J International Journal of Computer Applications
%@ 0975-8887
%V 34
%N 9
%P 29-33
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing is emerging as a new computational paradigm shift. Hadoop-MapReduce has become a powerful Computation Model for processing large data on distributed commodity hardware clusters such as Clouds. In all Hadoop implementations, the default FIFO scheduler is available where jobs are scheduled in FIFO order with support for other priority based schedulers also. In this paper we study various scheduler improvements possible with Hadoop and also provided some guidelines on how to improve the scheduling in Hadoop in Cloud Environments.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Hadoop HDFS MapReduce

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