Breaking the MapReduce stage barrier

Abhishek Verma, Nicolas Zea, Brian Cho, Indranil Gupta, Roy H. Campbell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The MapReduce model uses a barrier between the Map and Reduce stages. This provides simplicity in both programming and implementation. However, in many situations, this barrier hurts performance because it is overly restrictive. Hence, we develop a method to break the barrier in MapReduce in a way that improves efficiency. Careful design of our barrier- less MapReduce framework results in equivalent generality and retains ease of programming. We motivate our case with, and experimentally study our barrier-less techniques in, a wide variety of MapReduce applications divided into seven classes. Our experiments show that our approach can achieve better performance times than a traditional MapReduce framework. We achieve a reduction in job completion times that is 25% on average and 87% in the best case.

Original languageEnglish (US)
Title of host publicationProceedings - 2010 IEEE International Conference on Cluster Computing, Cluster 2010
Pages235-244
Number of pages10
DOIs
StatePublished - Dec 2 2010

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
ISSN (Print)1552-5244

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Signal Processing

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  • Cite this

    Verma, A., Zea, N., Cho, B., Gupta, I., & Campbell, R. H. (2010). Breaking the MapReduce stage barrier. In Proceedings - 2010 IEEE International Conference on Cluster Computing, Cluster 2010 (pp. 235-244). [5600302] (Proceedings - IEEE International Conference on Cluster Computing, ICCC). https://doi.org/10.1109/CLUSTER.2010.29