A Novel Aggregation Algorithm for Online Analytical Processing Query Evaluation
联机分析查询处理中的一种聚集算法

The OLAP (online analytical processing query) queries are ad-hoc, complex queries, as expressed in SQL, these queries include multi-table join and aggregate operation. In this paper, a novel sorting based aggregation algorithm, MuSA (sort-based aggregation with multi-table join), is given for OLAP query evaluation. In this algorithm, by taking the characteristics of star schema into consideration, the aggregation operation is combined with a novel multi-table join algorithm, MJoin, and the key words mapping technique is used to compress the sorting key which can obviously speed up sorting.Further by esting the group number of query result,the proper sorting methods which can optimize the algorithm for different aggregation queries be chosen.Asbeing illustrated by the experimental result,compared with original methods for aggregation query evaluation,theperfmance of the new algorithm can be improved dramatically.