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Research Papers

Compressing Data Cube in Parallel OLAP Systems

Authors
  • Frank Dehne
  • Todd Eavis
  • Boyong Liang

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.

Year: 2007
Volume 6
Page/Article: S184-S197
DOI: 10.2481/dsj.6.S184
Published on Mar 28, 2007
Peer Reviewed