Bitmap Index Design and Evaluation.

Chee Yong Chan, Yannis E. Ioannidis: Bitmap Index Design and Evaluation. SIGMOD Conference 1998: 355-366

@inproceedings{DBLP:conf/sigmod/ChanI98,
  author    = {Chee Yong Chan and
               Yannis E. Ioannidis},
  editor    = {Laura M. Haas and
               Ashutosh Tiwary},
  title     = {Bitmap Index Design and Evaluation},
  booktitle = {SIGMOD 1998, Proceedings ACM SIGMOD International Conference
               on Management of Data, June 2-4, 1998, Seattle, Washington, USA},
  publisher = {ACM Press},
  year      = {1998},
  isbn      = {0-89791-995-5},
  pages     = {355-366},
  ee        = {http://doi.acm.org/10.1145/276304.276336, db/conf/sigmod/ChanI98.html},
  crossref  = {DBLP:conf/sigmod/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

Bitmap indexing has been touted as a promising approach for processing complex adhoc queries in read-mostly environments, like those of decision support systems. Nevertheless, only few possible bitmap schemes have been proposed in the past and very little is known about the space-time tradeoff that they offer. In this paper, we present a general framework to study the design space of bitmap indexes for selection queries and examine the disk-space and time characteristics that the various alternative index choices offer. In particular, we draw a parallel between bitmap indexing and number representation in different number systems, and define a space of two orthogonal dimensions that captures a wide array of bitmap indexes, both old and new. Within that space, we identify (analytically or experimentally) the following interesting points: (1) the time-optimal bitmap index; (2) the space-optimal bitmap index; (3) the bitmap index with the optimal space-time tradeoff (knee); and (4) the time-optimal bitmap index under a given disk-space constraint. Finally, we examine the impact of bitmap compression and bitmap buffering on the space-time tradeoffs among those indexes. As part of this work, we also describe a bitmap-index-based evaluation algorithm for selection queries that represents an improvement over earlier proposals. We believe that this study offers a useful first set of guidelines for physical database design using bitmap indexes.

Copyright © 1998 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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Printed Edition

Laura M. Haas, Ashutosh Tiwary (Eds.): SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, USA. ACM Press 1998, ISBN 0-89791-995-5 BibTeX , SIGMOD Record 27(2), June 1998
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References

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Referenced by

Alfons Kemper, Donald Kossmann, Christian Wiesner: Generalised Hash Teams for Join and Group-by. VLDB 1999: 30-41
Theodore Johnson: Performance Measurements of Compressed Bitmap Indices. VLDB 1999: 278-289
H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava: What can Hierarchies do for Data Warehouses? VLDB 1999: 530-541
Chee Yong Chan, Yannis E. Ioannidis: Hierarchical Prefix Cubes for Range-Sum Queries. VLDB 1999: 675-686
Ming-Chuan Wu: Query Optimization for Selections Using Bitmaps. SIGMOD Conference 1999: 227-238
Chee Yong Chan, Yannis E. Ioannidis: An Efficient Bitmap Encoding Scheme for Selection Queries. SIGMOD Conference 1999: 215-226

BibTeX

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