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  • 标题:HIGH-DIMENSIONAL HIERARCHICAL OLAP : A PREFIX–INDEX HIERARCHICAL CUBING APPROACH
  • 本地全文:下载
  • 作者:KONGFA HU ; ZHE SHENG ; LING CHEN
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2013
  • 卷号:51
  • 期号:1
  • 出版社:Journal of Theoretical and Applied
  • 摘要:The pre-computation of data cubes is critical for improving the response time of OLAP(online analytical processing) systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional OLAP, it might not be practical to build all these cuboids and their indices. In this paper, we propose a multi-dimensional hierarchical cubing algorithm, Prefix-index hierarchical cubing, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low dimensional cube segments. Such an approach permits a significant reduction of CPU and I/O overhead. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.
  • 关键词:Data cube; High dimensional OLAP; Prefix-Indexing cubing
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