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Java as a basis for parallel data mining in workstation clusters

  • Workshop: Java in HPC
  • Conference paper
  • First Online:
High-Performance Computing and Networking (HPCN-Europe 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1593))

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Abstract

The exploitation of hidden information from large datasets by means of data mining techniques suffers from long response times. We address this problem by using the processing power of workstation clusters and have studied the performance of OLAP queries as a first step towards a portable data mining platform.

The results of our study suggest that with the availability of parallel workstation clusters that are equipped with high performance communication networks, fine-grained and communication-intensive parallelizations of queries are promising—even though they are considered too costly in traditional database systems.

The paper describes our Java framework for parallel OLAP-type query execution, necessary optimizations to the standard Java implementation, and analyzes the performance of non-standard parallel execution schemes on a workstation cluster.

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Authors and Affiliations

  1. Department of Computer Science, Universität Karlsruhe, Am Fasanengarten 5, D-76128, Karlsruhe, Germany

    Matthias Gimbel

Authors
  1. Matthias Gimbel
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Editor information

Peter Sloot Marian Bubak Alfons Hoekstra Bob Hertzberger

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© 1999 Springer-Verlag

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Gimbel, M. (1999). Java as a basis for parallel data mining in workstation clusters. In: Sloot, P., Bubak, M., Hoekstra, A., Hertzberger, B. (eds) High-Performance Computing and Networking. HPCN-Europe 1999. Lecture Notes in Computer Science, vol 1593. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100648

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  • DOI: https://doi.org/10.1007/BFb0100648

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65821-4

  • Online ISBN: 978-3-540-48933-7

  • eBook Packages: Springer Book Archive

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