A clustered Dwarf structure to speed up queries on data cubes

Authors:
Fangling Leng;Yubin Bao;Daling Wang;Ge Yu
Affiliations:
School of Information Science & Engineering, Northeastern University, Shenyang, P. R.China;School of Information Science & Engineering, Northeastern University, Shenyang, P. R.China;School of Information Science & Engineering, Northeastern University, Shenyang, P. R.China;School of Information Science & Engineering, Northeastern University, Shenyang, P. R.China
Venue:
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Year:
2007

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Abstract

Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. So we propose two novel clustering methods for query optimization: the recursion clustering method for point queries and the hierarchical clustering method for range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.