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Compressing Data Cube in Parallel OLAP Systems Cover

Compressing Data Cube in Parallel OLAP Systems

By: Frank Dehne,  Todd Eavis and  Boyong Liang  
Open Access
|Mar 2007

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: https://doi.org/10.2481/dsj.6.S184 | Journal eISSN: 1683-1470
Language: English
Published on: Mar 28, 2007
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2007 Frank Dehne, Todd Eavis, Boyong Liang, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.