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Immune Algorithm for Bitmap Join Indexes

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Neural Information Processing (ICONIP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7665))

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Abstract

Bitmap join indexes are designed to prejoin the facts and dimension tables in data warehouses modeled by a star schema. They are defined on the fact table using attributes which belong to one or many dimension tables. The index selection process has become an important issue regarding the complexity of the search space to explore. Thus, the indexes can be defined on several attributes from several dimension tables (that may contain hundreds of attributes). However, only a few selection algorithms were proposed. In this article, we present a bitmap join indexes selection approach based on artificial immune algorithm. An experimental study was conducted on the dataset generated from APB-1 benchmark in order to compare the artificial immune algorithm with other algorithms.

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Author information

Authors and Affiliations

  1. National High School of Computer Science, Algiers, Algeria

    Amina Gacem

  2. Algeria Houari Boumediene University of Science and Technology, Algiers, Algeria

    Kamel Boukhalfa

Authors
  1. Amina Gacem
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  2. Kamel Boukhalfa
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Gacem, A., Boukhalfa, K. (2012). Immune Algorithm for Bitmap Join Indexes. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34487-9_68

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  • DOI: https://doi.org/10.1007/978-3-642-34487-9_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34486-2

  • Online ISBN: 978-3-642-34487-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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