【摘要】 数据立方的计算是数据仓库和0LAP研究的一个重要方向,同时又是数据仓库中代价很大的操作。针对在生物信息、统计分析、文本处理等领域中存在的基数较小的高维数据集,X.L.Li等人提出了 Frag-Cubing算法。为了提高Frag-Cubig算法的效率,本文提出了基于分片思想的算法CBFrag-Cubing。该算法使用了位图索引结构,优化了数据立方的存储,减少了数据立方的计算时间。实验表明,与Frag-Cubing算法相比,该算法在存储空间上至少节省25％,在计算时间上节省30％。更多还原

【Abstract】 The computation of data cube is one of the most essential but expensive issues in data warehouse and OLAP. Frag-Cubing algorithm is recently proposed to perform data cubing on such data sets, which exist in applications like bioinformatics, statistics, and text processing that characterized by high dimensionality and low cardinality. In order to enhance efficiency of Frag-Cubing algorithm, a partition-based CBFrag-Cubing algorithm is proposed. It uses Com- pressed bitmap index to optimize the storage of cube, and reduces the computing time. Experimental results show that, compared with Frag-Cubing algorithm, the CBFrag-Cubing algorithm saves at least 25% on storage space and about 30% on computing time.更多还原