We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Survey of Task Scheduling Method for Mapreduce Framework in Hadoop

Published on November 2013 by Nilam Kadale, U. A. Mande
2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
Foundation of Computer Science USA
NCIPET - Number 2
November 2013
Authors: Nilam Kadale, U. A. Mande
f2da32bf-2deb-4ff8-9027-30e2fabd582c

Nilam Kadale, U. A. Mande . Survey of Task Scheduling Method for Mapreduce Framework in Hadoop. 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013). NCIPET, 2 (November 2013), 8-10.

@article{
author = { Nilam Kadale, U. A. Mande },
title = { Survey of Task Scheduling Method for Mapreduce Framework in Hadoop },
journal = { 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013) },
issue_date = { November 2013 },
volume = { NCIPET },
number = { 2 },
month = { November },
year = { 2013 },
issn = 0975-8887,
pages = { 8-10 },
numpages = 3,
url = { /proceedings/ncipet/number2/556-1343/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%A Nilam Kadale
%A U. A. Mande
%T Survey of Task Scheduling Method for Mapreduce Framework in Hadoop
%J 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%@ 0975-8887
%V NCIPET
%N 2
%P 8-10
%D 2013
%I International Journal of Computer Applications
Abstract

Nowadays cloud computing widely used for parallel and distributed data processing. Such as hadoop is recently mostly used for parallel and large data processing. In hadoop, mapreduce framework is programming model is allowed to process terabytes of data in very less time. Mapreduce framework uses a task scheduling method to schedule task. There are various method available for scheduling task in mapreduce framework. Survey of various task scheduling method of mapreduce framework is discussed in following sections.

References
  1. Dynamic Priority Scheduler for Hadoop. http://issues. apache. org/jira/browse/HADOOP-476
  2. J. Dean and S. Ghemawat. Mapreduce: simplified data processing on large clusters. In Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6, pages 10–10,Berkeley, CA, USA, 2004. USENIX Association.
  3. M. Zaharia, A. Konwinski, A. D. Joseph, R. H. Katz,and I. Stoica. Improving mapreduce performance in heterogeneous environments. Technical Report UCB/EECS-2008-99, EECS Department, Universityof California, Berkeley, Aug 2008.
  4. M. Zaharia, A. Konwinski, A. D. Joseph, R. Katz, and I. Stoica, "Improving MapReduce performance in heterogeneous environments," in Proc. of OSDI'08. Berkeley, CA, USA:pp. 29-42,2012.
  5. M. Zaharia, D. Borthakur, J. S. Sen, K. Elmeleegy, S. Shenker, and I. Stoica. Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling. In Proceedings of the 5th European conference on Computer systems, EuroSys '10, pages 265–278, New York, NY, USA, 2010. ACM.
  6. M. Zaharia, D. Borthakur, J. S. Sen, K. Elmeleegy, S. Shenker, and I. Stoica. Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling. In Proceedings of the 5th European conference on Computer systems, EuroSys '10, pages 265{278, New York, NY, USA, 2010. ACM.
  7. Thomas Sandholm and Kevin Lai. Dynamic proportional share scheduling in hadoop. In JSSPP '10: 15th Workshop on Job Scheduling Strategies for Parallel Processing, April,2010.
  8. X. Zhang, Y. Feng, S. Feng, J. Fan and M. Zhong. An Effective Data Locality Aware Task Scheduling Method for MapReduce Framework in Heterogeneous Environments. In Proceedings of the International Conference on Cloud and Service Computing, pp. 206-2055, 2011.
  9. X. Zhang, Z. Zhong, B. Tu, S. Feng, and J. Fan. Improving data locality of mapreduce by scheduling in homogeneous computing environments. In Proceedings of IEEE 9th International Symposium on Parallel and Distributed Processing with Applications, pages 120–126, Busan, Korea, 2011. IEEE.
  10. X. Zhang, G. Wang, Z. Yang,Y. Ding "A Two-phase Execution Engine of Reduce Tasks In Hadoop MapReduce"2012.
  11. Yahoo. Hadoop at yahoo, 2010.
  12. Zhenhua Guo, Geoffrey Fox, Mo Zhou "Investigation of Data Locality in MapReduce" 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Scheduler task scheduling mapreduce performance.