【摘要】 由于数据仓库中存储着不同粒度、容量巨大的数据记录 ,所以如何有效地执行联机分析处理 (OLAP)查询操作 ,特别是连接和聚集操作 ,便成为数据仓库领域的核心问题之一 为此 ,提出了一种降低连接和聚集操作的新算法 (joinandaggregationbasedonthecomplexmulti dimensionalhierarchies,JACMDH) 算法充分考虑了复杂多维层次的特点 ,在原有的位图连接索引 (bitmapjoinindex)的基础上 ,采用层次联合代理 (hierarchycombinedsurrogate)和预先分组排序的方法 ,使得复杂的多维层次上的连接和聚集操作转化成事实表上的区域查询 ,从而在处理多维层次聚集的同时 ,提高了连接和聚集的效率 算法性能分析和实验数据表明 ,JACMDH算法和目前流行的算法相比 ,其性能有显著的提高更多还原

【Abstract】 Enormous volume of data reside in data warehouse, so it is important to process efficiently expensive queries including join and aggregate operation. In this paper, a new method (JACMDH algorithm) is proposed for processing time-consuming join and aggregate operation. This algorithm takes into consideration the characteristics of the complex multi-dimensional hierarchies and adopts hierarchy combined surrogate/pre-grouping and pre-sorting on the basis of bitmap join index. It improves the join and aggregate efficiency by translating join and aggregate operation of complex multi-dimensional hierarchies into range queries of fact table. The performance analysis and the experimental result, show that the performance of JACMDH algorithm can be improved dramatically, compared with current method for aggregation query evaluation.更多还原