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Compressing Data Cube in Parallel OLAP Systems

机译:在并行OLAP系统中压缩数据多维数据集

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References(49) 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.
机译:参考文献(49)本文提出了一种在并行数据多维数据集生成过程中压缩多维数据集的有效算法。这种低开销的压缩机制通过使用元组差异编码技术提供了逐块和逐记录的压缩,从而最大程度地提高了压缩率,并使运行时的解压缩损失最小。实验结果表明,在不牺牲运行时间的情况下,典型压缩比约为30:1。本文还证明了压缩方法适用于希尔伯特空间填充曲线,后者是一种广泛用于多维索引的机制。

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