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Performance Analysis of MapReduce-Based Distributed Systems for Iterative Data Processing Applications

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Mobile, Ubiquitous, and Intelligent Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 274))

Abstract

Recently, research on big data has been actively made because big data are generated in various scientific applications, such as biology and astronomy. Therefore, distributed data processing techniques have been studied to manage the big data in large number servers. Meanwhile, some scientific applications like genome data analysis require loop control in analyzing big data using a MapReduce framework. In this paper, we first describe the existing MapReduce-based distributed systems which support iterative data processing. In addition, we do the performance analysis of the existing distributed systems in terms of execution time for various scientific applications which require iterative data processing. Finally, based on the performance analysis, we discuss some requirements for a new MapReduce-based distributed system which supports iterative data processing efficiently.

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References

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Author information

Authors and Affiliations

  1. Dept. of Computer Engineering, Chonbuk National University, Jeonju, Republic of Korea

    Min Yoon, Hyeong-il Kim, Heeseung Jo & Jae-woo Chang

  2. Korea Institute of Science and Technology Information, Daejeon, Republic of Korea

    Dong Hoon Choi

Authors
  1. Min Yoon
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  2. Hyeong-il Kim
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  3. Dong Hoon Choi
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  4. Heeseung Jo
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  5. Jae-woo Chang
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Corresponding author

Correspondence to Min Yoon .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Biomedical Informatics Neuroscience, Ohio State University Center for Biomedical Engineering, Columbus, Ohio, USA

    Hojjat Adeli

  3. Dept of Computer Education, Jeju National University Teachers College, Jeju Special Self-Governing Province, Korea, Republic of (South Korea)

    Namje Park

  4. Ryerson University Dept. Computer Science, Toronto, Ontario, Canada

    Isaac Woungang

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© 2014 Springer-Verlag Berlin Heidelberg

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Yoon, M., Kim, Hi., Choi, D.H., Jo, H., Chang, Jw. (2014). Performance Analysis of MapReduce-Based Distributed Systems for Iterative Data Processing Applications. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_45

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  • DOI: https://doi.org/10.1007/978-3-642-40675-1_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40674-4

  • Online ISBN: 978-3-642-40675-1

  • eBook Packages: EngineeringEngineering (R0)

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