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Calculating Aggregates with Range-Encoded Bit-Sliced Index

  • Kashif Bhutta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2412)

Abstract

This paper proposes, for query optimizing on Data warehouses, the use of range-encoded bitmap index to calculate aggregates. By using space optimal range-encoded bitmap index for range and aggregate predicates, the need of separate indexes for these operations can be eliminated. The proposed algorithm also uses the population ratio of 1’s in a bitmap to decide whether the bitmap has to be scanned from the disk at all; thus exploiting the opportunity of skipping many bitmap scans since processing them does not affect the solution. These optimizations result in significant improvement in query evaluation time.

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References

  1. 1.
    K. Bhutta, Calculating Aggregates with Range-Encoded Bit-Sliced Index, School of Computer Science, University of Windsor, Canada, 2002, http://cs.uwindsor.ca Google Scholar
  2. 2.
    C. Y. Chan, Y. E. Ioannidis, An Efficient Bitmap Encoding Scheme for Selection Queries. In Proc. of the ACM SIGMOD Conference on Management of Data, 1999, pages 215–226Google Scholar
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    M.-C. Wu, Query Optimization for Selections Using Bitmaps. In Proc. of the ACM SIGMOD Conference on Management of Data, 1999, pages 227–238.Google Scholar
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    C-Y. Chan and Y. E. Ioannidis, Bitmap Index Design and Evaluation,. In Proc. of the ACM SIGMOD Conference on Management of Data, 1998, pages 355–366.Google Scholar
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    P. O’Neil and D. Quass, Improved query performance with variant indexes. Proc. ACM SIGMOD Intl. Conference on Management of Data, 1997, Pages 38–49.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Kashif Bhutta
    • 1
  1. 1.University of WindsorCanada

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