基于层次有序维的分组聚集算法  

Aggregation Algorithm Based on Hierarchical Sequence Dimensions

作　　者：王生富[1] 张继福[1] 刘爱琴[1] 荀亚玲[1] 

机构地区：[1]太原科技大学计算机科学与技术学院,山西太原030024

出　　处：《小型微型计算机系统》2010年第6期1133-1137,共5页Journal of Chinese Computer Systems

基　　金：山西省自然科学基金项目(2006011041)资助

摘　　要：在联机分析处理(OLAP)中,有效地维度模型对海量数据的即席复杂分组聚集查询起着关键的作用.在偏序和映射的基础上,通过定义层次有序维,提出一种基于层次有序维的分组聚集算法.该算法利用维属性之间的聚集关系,通过约束层次链中的元素次序,实现了分组聚集计算中多表连接转换为维范围的查询,提高了连接和聚集效率.最后,实验结果验证了该算法的有效性.In OLAP（Online Analytical Processing）,an effective dimension model plays an important role in the complex aggregation queries on massive data set.In this paper,an aggregation algorithm based on hierarchical sequence dimensions is presented by using hierarchical sequence dimensions based on the concepts of partial order and mapping.Using the aggregation relationship between dimensional attributes,the algorithm transforms multi-table joining into dimensional query ranges in the aggregation computing based on group number by restricting the order of elements in hierarchical chain,and improved the efficiency of multi-table join and aggregation.The experimental results validate the validity of the algorithm.

关 键 词：数据仓库 维模型 联机分析处理 聚集查询 多表连接 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]