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Dynamic declustering methods for parallel grid files

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Parallel Computation (ACPC 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1127))

Abstract

Several declustering functions for distributing multi-attribute data on a set of disks have been proposed in recent years. Since these functions map grid regions to disks in a static way, performance deteriorates in case of dynamic datasets and/or non-stationary data distributions. We first analyze how declustering functions can be extended in order to deal with dynamic datasets without requiring periodic reorganizations. In order to support dynamic declustering, we propose to organize the directory as a parallel Multilevel Grid File. On this structure we experiment five dynamic declustering functions and two index-based allocation methods that only use locally available information. This first comparison among the two approaches reveals that methods based on local criteria always yield better results.

This work has been partially supported by the ESPRIT LTR project no. 9141, HERMES, and by Italian CNR, Grant no. 95.00443.CT12.

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Author information

Authors and Affiliations

  1. DEIS-CSITE-CNR, University of Bologna, Italy

    Paolo Ciaccia

  2. CINECA, Casalecchio di Reno, Bologna, Italy

    Arianna Veronesi

Authors
  1. Paolo Ciaccia
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  2. Arianna Veronesi
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László Böszörményi

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© 1996 Springer-Verlag Berlin Heidelberg

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Ciaccia, P., Veronesi, A. (1996). Dynamic declustering methods for parallel grid files. In: Böszörményi, L. (eds) Parallel Computation. ACPC 1996. Lecture Notes in Computer Science, vol 1127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61695-0_10

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  • DOI: https://doi.org/10.1007/3-540-61695-0_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61695-5

  • Online ISBN: 978-3-540-70645-8

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