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Research Papers

Compressing Data Cube in Parallel OLAP Systems

Authors:

Frank Dehne ,

School of Computer Science, Carleton University, 1125 Colonel By Drive, Ottawa, Canada K1S 5B6
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Todd Eavis,

Computer Science Software Engineering, Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Canada, H3G 1M8
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Boyong Liang

School of Computer Science, Carleton University, 1125 Colonel By Drive, Ottawa, Canada K1S 5B6
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Abstract

This paper proposes an efficient algorithm to compress the cubes in the progress of the parallel data cube generation. This low overhead compression mechanism provides block-by-block and record-by-record compression by using tuple difference coding techniques, thereby maximizing the compression ratio and minimizing the decompression penalty at run-time. The experimental results demonstrate that the typical compression ratio is about 30:1 without sacrificing running time. This paper also demonstrates that the compression method is suitable for Hilbert Space Filling Curve, a mechanism widely used in multi-dimensional indexing.

DOI: http://doi.org/10.2481/dsj.6.S184
How to Cite: Dehne, F., Eavis, T. & Liang, B., (2007). Compressing Data Cube in Parallel OLAP Systems. Data Science Journal. 6, pp.S184–S197. DOI: http://doi.org/10.2481/dsj.6.S184
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Published on 28 Mar 2007.
Peer Reviewed

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