OLAP (online analytical processing) queries are complex. When implemented in SQL (structured query language), they usually involve multi-table join and aggregate operations. As a result, how to improve the performance of the multi-table join and aggregate operations becomes a key issue for ROLAP (relational OLAP) query evaluation. To solve this problem, an aggregation algorithm based on group numbers named MuGA (group number based aggregation with multi-table join) is proposed in this paper. By taking the characteristics of star schema into consideration, the algorithm combines the aggregation operation with the novel multi-table join algorithm, Mjoin (multi-table join), and replaces the sorting and hashing method by computed group numbers in aggregation computing. As a result, the algorithm can not only reduce the CPU time, but also reduce the disk I/Os for OLAP queries. As illustrated by the experiments, the performance of the algorithm MuGA is superior to original aggregation methods and the new sorting based method for aggregation.