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Computing High Dimensional MOLAP with Parallel Shell Mini-cubes

  • Conference paper
Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

MOLAP is a important application on multidimensional data warehouse. We often execute range queries on aggregate cube computed by pre-aggregate technique in MOLAP. For the cube with d dimensions, it can generate 2d cuboids. But in a high-dimensional cube, it might not be practical to build all these cuboids. In this paper, we propose a multi-dimensional hierarchical fragmentation of the fact table based on multiple dimension attributes and their dimension hierarchical encoding. This method partition the high dimensional data cube into shell mini-cubes. The proposed data allocation and processing model also supports parallel I/O and parallel processing as well as load balancing for disks and processors. We have compared the methods of shell mini-cubes with the other existed ones such as partial cube and full cube by experiment. The results show that the algorithms of mini-cubes proposed in this paper are more efficient than the other existed ones.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Yangzhou University,  

    Kong-fa Hu, Chen Ling, Shen Jie, Gu Qi & Xiao-li Tang

Authors
  1. Kong-fa Hu
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  2. Chen Ling
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  3. Shen Jie
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  4. Gu Qi
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  5. Xiao-li Tang
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Hu, Kf., Ling, C., Jie, S., Qi, G., Tang, Xl. (2005). Computing High Dimensional MOLAP with Parallel Shell Mini-cubes. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_149

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  • DOI: https://doi.org/10.1007/11539506_149

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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