Article

A clustered Dwarf structure to speed up queries on data cubes

Authors:

Fangling Leng,

Yubin Bao,

Daling Wang,

Ge YuAuthors Info & Claims

DaWaK'07: Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery

Pages 170 - 180

Published: 03 September 2007 Publication History

Publisher Site

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.

References

[1]

Sismanis, Y., Roussopoulos, N., Deligianannakis, A., Kotidis, Y.: Dwarf: Shrinking the Petacube. In: SIGMOD, pp. 564-475 (2002)

Digital Library

Google Scholar

[2]

Wang, W., Feng, J., Lu, H., Yu, J.X.: Condensed Cube: An Effective Approach to Reducing Data Cube Size. In: ICDE, pp. 155-165 (2002)

Digital Library

Google Scholar

[3]

Vitter, J. S., Wang, M., Iyer, B.: Data Cube Approximation and Histograms via Wavelets. In: CIKM, pp. 96-104 (1998)

Digital Library

Google Scholar

[4]

Barbara, D., Sullivan, M.: A Space-Efficient Way to Support Approximate Multidimensional Databases. Technical report, ISSE-TR-98-03 (1998)

Google Scholar

[5]

Gibbons, P. B., Matias, Y.: New Sampling-Based Summary Statistics for Improving Approximate Query Answers. In: SIGMOD, pp. 331-342 (1998)

Digital Library

Google Scholar

[6]

Acharya, S., Gibbons, P. B., Poosala, V.: Congressional Samples for Approximate Answering of Group-By Queries. In: SIGMOD, pp. 487-498 (2000)

Digital Library

Google Scholar

[7]

Shanmugasundaram, J., Fayyad, U., Bradley, P. S.: Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions. In: KDD, pp. 223-232 (1999)

Digital Library

Google Scholar

[8]

Beyer, K., Ramakrishnan, R.: Bottom-Up Computation of Sparse and Iceberg Cubes. In: SIGMOD, pp. 359-370 (1999)

Digital Library

Google Scholar

[9]

Xin, D., Han, J., Li, X., Wah, B. W.: Star-Cubing: Computing Iceberg Cubes by Top-Down and Bottom-Up Integration. In: VLDB, pp. 476-487 (2003)

Digital Library

Google Scholar

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Information & Contributors

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Published In

DaWaK'07: Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery

September 2007

480 pages

ISBN:3540745521

Editors:
Il Yeal Song
Drexel University, College of Information Science and Technology, Philadelphia, PA
,
Johann Eder
University of Vienna, Faculty of Computer Science, Wien, Austria
,
Tho Manh Nguyen
Vienna University of Technology, Institute of Software Technology and Interactive Systems, Wien, Austria

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 03 September 2007

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