Compressing Data Cube in Parallel OLAP Systems

Compressing Data Cube in Parallel OLAP Systems

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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 lore olivera and minimizing the decompression penalty at run-time.The experimental results demonstrate that the typical compression ratio is about 30:1 without sacrificing running kbrovet-ca1 chewable tablets for dogs time.

This paper also demonstrates that the compression method is suitable for Hilbert Space Filling Curve, a mechanism widely used in multi-dimensional indexing.