ROUTE: run-time robust reducer workload estimation for MapReduce-Reference-Cited by-同舟云学术

ROUTE: run-time robust reducer workload estimation for MapReduce

Published:2016-03-29 Issue:3 Volume:26 Page:224-244
ISSN:1055-7148
Container-title:International Journal of Network Management
language:en
Short-container-title:Int. J. Network Mgmt

Author:

Liu Zhihong¹²,Zhang Qi³²,Boutaba Raouf²,Liu Yaping¹,Gong Zhenghu¹

Affiliation:

1. College of Computer; National University of Defense Technology; Changsha Hunan China

2. David R. Cheriton School of Computer Science; University of Waterloo; Waterloo ON Canada

3. Department of Electrical and Computer Engineering; University of Toronto; Toronto ON Canada

Funder

National Natural Science Foundation of China

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Computer Networks and Communications,Computer Science Applications

Reference32 articles.

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4. Gufler B Augsten N Reiser A Kemper A Load balancing in MapReduce based on scalable cardinality estimates ICDE, 2012 IEEE 28th Intl. Conf. on Washington DC, USA 2012 522 533

5. Yan W Xue Y Malin B Scalable and robust key group size estimation for reducer load balancing in MapReduce Big Data, 2013 IEEE Intl. Conf. on Santa Clara Marriott, USA 2013 156 162

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1. Estimating runtime of a job in Hadoop MapReduce;Journal of Big Data;2020-07-06

2. MapReduce Data Skewness Handling: A Systematic Literature Review;International Journal of Parallel Programming;2019-01-23

3. MAPSkew: Metaheuristic Approaches for Partitioning Skew in MapReduce;Algorithms;2018-12-24

4. RMHC-MR: Instance selection by random mutation hill climbing algorithm with MapReduce in big data;Procedia Computer Science;2017