A highly performance dimension hierarchy aggregate cube and its incremental update algorithm

Abstract

Multidimensional online analytical processing (MOLAP) is a important application on multidimensional data warehouse. We often execute range queries on aggregate cube computed by pre-aggregate technique in MOLAP. In this paper, we proposes to create a highly performance dimension hierarchy aggregate cube (DHAC) and its novel incremental update algorithm with the dimension hierarchy aggregate technique on the cube. By using the hierarchical prefix of the dimension hierarchy aggregate tree, the DHAC can incrementally update all the affected ancestors while updating a cell in it. The DHAC can also incrementally update without being recreated while being added new dimension data in it. As a result, this algorithm can greatly reduce the update time. We have compared the algorithms of DHAC with the other existed ones such as DDC (dynamic data cube) by experiment. The analytical and experimental results show that the algorithms of DHAC proposed in this paper are more efficient than the other existed ones.