OLAP中一种有效的向下钻取路径修剪方法

Dehui Zhang, Shiwei Tang, Dongqing Yang, Lizheng Jiang
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引用次数: 1

摘要

多维数据结构的复杂性影响了OLAP的效率,因为在分析时需要选择的下钻路径太多。而文献中的大多数方法都是与一些特定的分析任务相关联的,因此无法得到合理的效果。在本文中,我们提出了一种与分析任务无关的新方法,我们试图修剪无效的钻取操作。采用向量角法对每次钻取的有效性进行评价。给出了相应的路径修剪算法,该算法以事实表作为输入,只需扫描一次,是有效的。实验结果表明,该方法可行、有效,具有抗稀疏性和抗偏性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Effective Drill-Down Paths Pruning Method in OLAP
The complexity of multi-dimensional data structure affects the efficiency of OLAP, because there are too many drill-down paths to be chosen from when analysis. While most methods in the literature are associated to some specific analysis tasks, so they cannot get reasonable effect. In this paper, we proposed a new method that is irrelevant to analysis task that we try to prune the invalid drill-down operations. The vectorial angle method is employed to evaluate the validness of every drill-down operation. We give the corresponding path pruning algorithm, and it is effective that it takes the fact table as the input in only one pass scanning. The experiments show that our method is feasible, effective, sparsity-proof and skewness-proof
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