NDLI: Range-based bitmap indexing for high cardinality attributes with skew

Content Provider	IEEE Xplore Digital Library
Author	Kun-Lung Wu Yu, P.S.
Copyright Year	1998
Description	Author affiliation: IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA (Kun-Lung Wu)
Abstract	Bitmap indexing, though effective for low cardinality attributes, can be rather costly in storage overhead for high cardinality attributes. Range-based bitmap (RBM) indexing can be used to reduce this storage overhead. The attribute values are partitioned into ranges and a bitmap vector is used to represent a range. With RBM, however, the number of records assigned to different ranges can be highly uneven, resulting in non-uniform search times for different queries. We present and evaluate a dynamic bucket expansion and contraction (DBEC) approach to simultaneously constructing range-based bitmap indexes for multiple high-cardinality attributes. Simulations are conducted to evaluate this DBEC approach. Both synthetic and real data are used in the simulations. The results show that (1) with highly skewed data, DBEC performs quite well compared with a simple approach and (2) DBEC compares favorably with the optimal approach.
Starting Page	61
Ending Page	66
File Size	150799
Page Count	6
File Format	PDF
ISBN	0818685859
ISSN	07303157
DOI	10.1109/CMPSAC.1998.716637
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-08-21
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Indexing Multidimensional systems Data analysis Decision support systems Simultaneous localization and mapping Decoding
Content Type	Text
Resource Type	Article
Subject	Software Computer Science Applications

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