On the performance of bitmap indices for high cardinality attributes

  • Authors:

  • Kesheng Wu;Ekow Otoo;Arie Shoshani

  • Affiliations:

  • Lawrence Berkeley National Laboratory, Berkeley, CA;Lawrence Berkeley National Laboratory, Berkeley, CA;Lawrence Berkeley National Laboratory, Berkeley, CA

  • Venue:
  • VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
  • Year:
  • 2004

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Abstract

It is well established that bitmap indices are efficient for read-only attributes with low attribute cardinalities. For an attribute with a high cardinality, the size of the bitmap index can be very large. To overcome this size problem, specialized compression schemes are used. Even though there are empirical evidences that some of these compression schemes work well, there has not been any systematic analysis of their effectiveness. In this paper, we systematically analyze the two most efficient bitmap compression techniques, the Byte-aligned Bitmap Code (BBC) and the Word-Aligned Hybrid (WAH) code. Our analyses show that both compression schemes can be optimal. We propose a novel strategy to select the appropriate algorithms so that this optimality is achieved in practice. In addition, our analyses and tests show that the compressed indices are relatively small compared with commonly used indices such as B-trees. Given these facts, we conclude that bitmap index is efficient on attributes of low cardinalities as well as on those of high cardinalities.