Hash-based symmetric data structure and join algorithm for OLAP applications

The star schema is often used in dimensional approaches applied to OLAP applications. The fact table in the star schema typically contains a huge amount of data. When some of the dimension tables are also very large, it may take too much time and storage to join the fact table with these dimension tables. The performance of the join algorithm becomes critical under such a condition. The fluent join is a join algorithm that operates on relations organized as multidimensional linear hash files. Like a merge join on relations which are already sorted on the joining key, its execution reads each page in the operand relations no more than once and does not create intermediate result files. Unlike sorting, the multi-dimensional linear hash can cluster records in several keys symmetrically. In this paper, the concept of the fluent join is applied to an OLAP system to cluster records in each table on the joining keys. As a result, the algorithm yields symmetric performances on joins with different dimension tables.