Dynamic profiling and feedback framework for reduce-side join

Makoto Nakayama, Kenichi Yamazaki, Satoshi Tanaka, Hironori Kasahara

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

    Abstract

    MapReduce has become popular and Reduce-side join is one of the most important application of MapReduce. Data skew, in which the data load assigned to each Reduce task fluctuates task by task, increases the MapReduce job completion time. This paper proposes a dynamic profiling and feedback framework that works on a MapReduce cluster. The framework allows programmers to build their own algorithm to address data skew on Reduce-side join based on their specific knowledge and/or requirements. This paper also proposes an estimation method which makes our framework adapt to a wide range of MapReduce cluster sizes. This paper presents two example algorithms to address data skew using the estimation method, and the experimental results shows up to 2.59 times speed-up of join completion time on a cluster with 50 servers and highly skewed input data.

    Original languageEnglish
    Title of host publicationProceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013
    Pages1255-1262
    Number of pages8
    DOIs
    Publication statusPublished - 2013
    Event2013 16th IEEE International Conference on Computational Science and Engineering, CSE 2013 - Sydney, NSW
    Duration: 2013 Dec 32013 Dec 5

    Other

    Other2013 16th IEEE International Conference on Computational Science and Engineering, CSE 2013
    CitySydney, NSW
    Period13/12/313/12/5

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    Keywords

    • Data skew
    • Feedback
    • Framework
    • Profiling
    • Reduce-side Join

    ASJC Scopus subject areas

    • Computer Science (miscellaneous)

    Cite this

    Nakayama, M., Yamazaki, K., Tanaka, S., & Kasahara, H. (2013). Dynamic profiling and feedback framework for reduce-side join. In Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013 (pp. 1255-1262). [6755369] https://doi.org/10.1109/CSE.2013.187

    Dynamic profiling and feedback framework for reduce-side join. / Nakayama, Makoto; Yamazaki, Kenichi; Tanaka, Satoshi; Kasahara, Hironori.

    Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013. 2013. p. 1255-1262 6755369.

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

    Nakayama, M, Yamazaki, K, Tanaka, S & Kasahara, H 2013, Dynamic profiling and feedback framework for reduce-side join. in Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013., 6755369, pp. 1255-1262, 2013 16th IEEE International Conference on Computational Science and Engineering, CSE 2013, Sydney, NSW, 13/12/3. https://doi.org/10.1109/CSE.2013.187
    Nakayama M, Yamazaki K, Tanaka S, Kasahara H. Dynamic profiling and feedback framework for reduce-side join. In Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013. 2013. p. 1255-1262. 6755369 https://doi.org/10.1109/CSE.2013.187
    Nakayama, Makoto ; Yamazaki, Kenichi ; Tanaka, Satoshi ; Kasahara, Hironori. / Dynamic profiling and feedback framework for reduce-side join. Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013. 2013. pp. 1255-1262
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