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Open Access Publications from the University of California

Compressed bitmap indices for efficient query processing


Many database applications make extensive use of bitmap indexing schemes. In this paper, we study how to improve the efficiencies of these indexing schemes by proposing new compression schemes for the bitmaps. Most compression schemes are designed primarily to achieve good compression. During query processing they can be orders of magnitude slower than their uncompressed counterparts. The new schemes are designed to bridge this performance gap by reducing compression effectiveness and improving operation speed. In a number of tests on both synthetic data and real application data, we found that the new schemes significantly outperform the well-known compression schemes while using only modestly more space. For example, compared to the Byte-aligned Bitmap Code, the new schemes are 12 times faster and it uses only 50 percent more space. The new schemes use much less space(<30\ percent) than the uncompressed scheme and are faster in a majority of the test cases.

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