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A Study on Workload Imbalance Issues in Data Intensive Distributed Computing

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Databases in Networked Information Systems (DNIS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5999))

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Abstract

In recent years, several frameworks have been developed for processing very large quantities of data on large clusters of commodity PCs. These frameworks have focused on fault-tolerance and scalability. However, when using heterogeneous environments these systems do not offer optimal workload balancing. In this paper we present Jumbo, a distributed computation platform designed to explore possible solutions to this issue.

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References

  1. Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. In: OSDI 2004: Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation, Berkeley, CA, USA, p. 10. USENIX Association (2004)

    Google Scholar 

  2. Ghemawat, S., Gobioff, H., Leung, S.T.: The google file system. In: SOSP 2003: Proceedings of the nineteenth ACM symposium on Operating systems principles, pp. 29–43. ACM Press, New York (2003)

    Chapter  Google Scholar 

  3. Apache: Hadoop core, http://hadoop.apache.org/core

  4. Isard, M., Budiu, M., Yu, Y., Birrell, A., Fetterly, D.: Dryad: distributed data-parallel programs from sequential building blocks. SIGOPS Oper. Syst. Rev. 41(3), 59–72 (2007)

    Article  Google Scholar 

  5. Li, H., Wang, Y., Zhang, D., Zhang, M., Chang, E.Y.: Pfp: parallel fp-growth for query recommendation. In: RecSys 2008: Proceedings of the 2008 ACM conference on Recommender systems, pp. 107–114. ACM, New York (2008)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, Japan

    Sven Groot, Kazuo Goda & Masaru Kitsuregawa

Authors
  1. Sven Groot
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  2. Kazuo Goda
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  3. Masaru Kitsuregawa
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Editor information

Editors and Affiliations

  1. Graduate Department of Computer and Information Systems, University of Aizu, Ikki Machi, Aizu-Wakamatsu, 965-8580, Fukushima, Japan

    Shinji Kikuchi , Shelly Sachdeva  & Subhash Bhalla ,  & 

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Groot, S., Goda, K., Kitsuregawa, M. (2010). A Study on Workload Imbalance Issues in Data Intensive Distributed Computing. In: Kikuchi, S., Sachdeva, S., Bhalla, S. (eds) Databases in Networked Information Systems. DNIS 2010. Lecture Notes in Computer Science, vol 5999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12038-1_3

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  • DOI: https://doi.org/10.1007/978-3-642-12038-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12037-4

  • Online ISBN: 978-3-642-12038-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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