Research on Data Cube technology of Dwarf based semantic OLAP

Abstract

The computation of high-dimension Data Cube in data warehouse is of much importance. Dwarf is a highly compressed structure for computing and storing data cubes which can be materialized completely. During the constructing process, each closed node is stored in disk. While the computation of aggregation units needs to access the closed nodes in the disk frequently. For avoid accessing the unnecessary closed nodes in disk, in this paper, we propose an optimized algorithm named Q-Dwarf. The property of this algorithm guarantees that once the closed nodes are written to disk, they will not be read out again, and query algorithm and update algorithm are both based on files. Experimental results show that the performance of the new algorithm outperforms that of the Dwarf algorithm, and the query and update algorithms are efficient for data warehousing.