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Special Issue Paper

Hadoop framework: impact of data organization on performance

  1. Yu Shyang Tan1,*,
  2. Jiaqi Tan2,
  3. Eng Siong Chng1,
  4. Bu-Sung Lee1,
  5. Jiaming Li1,
  6. Susumu Date3,
  7. Hui Ping Chak1,
  8. Xiong Xiao1,
  9. Atsushi Narishige3

Article first published online: 23 MAY 2011

DOI: 10.1002/spe.1082

Additional Information

How to Cite

Tan, Y. S., Tan, J., Chng, E. S., Lee, B.-S., Li, J., Date, S., Chak, H. P., Xiao, X. and Narishige, A. (2011), Hadoop framework: impact of data organization on performance. Softw: Pract. Exper.. doi: 10.1002/spe.1082

Author Information

  1. 1

    School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

  2. 2

    DSO National Laboratories, Singapore, Singapore

  3. 3

    Osaka University, Osaka, Japan

*School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

Publication History

  1. Article first published online: 23 MAY 2011
  2. Manuscript Accepted: 27 FEB 2011
  3. Manuscript Revised: 30 DEC 2010
  4. Manuscript Received: 28 JUN 2010

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Keywords:

  • mapreduce;
  • hadoop;
  • performance tuning;
  • distributed computing

Abstract

Hadoop, based on the popular MapReduce framework, is an open-source distributed computing framework that has been gaining much popularity and usage. It aims to allow programmers to focus on building applications that deals with processing large amount of data, without having to handle other issues when performing parallel computations. However, tuning the performance of Hadoop applications is not an easy task due to the level of abstraction of the framework. In this paper, we present three case studies and some of the challenges and issues that are to be considered in performance tuning when running applications in Hadoop. The focus is mainly on the impact of input data on Hadoop's performance and how they can be tuned. Copyright © 2011 John Wiley & Sons, Ltd.

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