Rewriting OLAP queries using materialized views and dimension hierarchies in data warehouses

OLAP queries involve a lot of aggregations on a large amount of data in data warehouses. To process expen-sive OLAP queries efficiently, we propose a new method for rewriting a given OLAP query using various kinds of mate-rialized aggregate views which already exist in data ware-houses. We first define the normal forms of OLAP queries and materialized views based on the lattice of dimension hierarchies, the semantic information in data warehouses. Conditions for usability of a materialized view in rewrit-ing a given query are specified by relationships between the components of their normal forms. We present a rewriting algorithm for OLAP queries that effectively utilizes exist-ing materialized views. The proposed algorithm can make use of materialized views having different selection gran-ularities, selection regions, and aggregation granularities together to generate an efficient rewritten query. 1