Volume 8 Number 4 (Apr. 2013)
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JCP 2013 Vol.8(4): 929-936 ISSN: 1796-203X
doi: 10.4304/jcp.8.4.929-936

A Task Scheduling Algorithm for Hadoop Platform

Jilan Chen, Dan Wang, and Wenbing Zhao
College of Computer Science, Beijing University of Technology, Beijing, China

Abstract—MapReduce is a kind of software framework for easily writing applications which process vast amounts of data on large clusters of commodity hardware. In order to get better allocation of tasks and load balancing, the MapReduce work mode and task scheduling algorithm of Hadoop platform is analyzed in this paper. According to this situation that the number of tasks of the smaller weight job is more, while that of the larger weight job is less, this paper introduces the idea of weighted round-robin scheduling algorithm into the task scheduling of Hadoop and puts forward the weight update rules through analyzing all the situations of weight update. Experimental result indicates that it is effective in making task allocation and achieving good balance when it is applied into the Hadoop platform which uses only JobTracker scheduling.

Index Terms—Cloud computing, Hadoop, MapReduce, Task scheduling

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Cite: Jilan Chen, Dan Wang, and Wenbing Zhao, " A Task Scheduling Algorithm for Hadoop Platform," Journal of Computers vol. 8, no. 4, pp. 929-936, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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