Abstract
In an OLAP system, we can use data cubes (precomputed multidimensional views of data) to support real-time queries. To reduce the maintenance cost, which is related to the number of cubes materialized, some cubes can be merged, but the resulting larger cubes will increase the response time of answering some queries. In order to satisfy the maintenance bound and response time bound given by the user, we may have to sacrifice some of the queries and not to take them into our consideration. The optimization problem in the data cube system design is to optimize an initial set of cubes such that the system can answer a maximum number of queries and satisfy the bounds. This is an NP-complete problem. Approximate algorithms Greedy Removing and 2-Greedy Merging are proposed. Experiments have been done on a census database and the results show that our approach is both effective and efficient.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
S. Chaudhuri et al. An Overview of Data Warehousing and OLAP Technology. ACM-SIGMOD Record, Vol. 26 No.1 P.65–74, March 1997
D.W. Cheung, B. Zhou, B. Kao, H. Lu, T.W. Lam and H.F. Ting, Requirement-based Design of Data Cube Schema. In Proc. Eighth Int’l Conf. on Information and Knowledge Management (CIKM), Kanas City, Missouri, Nov 2–6 1999.
J. Gray, A. Bosworth, A. Layman, and H. Piramish. Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-total. In Proceeding of the 12th Intl. Conference on Data Engineering, pages 152–159, New Orleans, February 1996.
E. Hung and D. W. Cheung. Optimization in Data Cube System Design. Working paper.
V. Harinarayan, A. Rajaraman, and J. D. Ullman. Implementing data cubes efficiently. In Proceedings of the ACM SIGMOD Conference on Management of Data, pages 205–216, Montreal, Quebec, June 1996.
P. O’Neill and G. Graefe. Multi-Table Joins Through Bitmapped Join Indexes. In SIGMOD Record, pages 8–11, September 1995.
P. O’Neil and D. Quass. Improved Query Performace with Variant Indexes. In Proceedings of the ACM SIGMOD Conference on Management of Data, pages 38–49, Tucson, Arizona, May 1997.
A. Shukla, P.M. Deshpande, J.F. Naughton. Materialized View Selection for Multidimensional Datasets. In Proceedings of the International Conference on Very Large Databases, pages 488–499, New York, USA, 1998
Transaction Processing Performance Council. TPC Benchmark D(Dicision Support), Standard Specification, Revision 1.2.3. San Jose, CA, USA, 1997
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hung, E., Cheung, D.W., Kao, B., Liang, Y. (2000). An Optimization Problem in Data Cube System Design. In: Terano, T., Liu, H., Chen, A.L.P. (eds) Knowledge Discovery and Data Mining. Current Issues and New Applications. PAKDD 2000. Lecture Notes in Computer Science(), vol 1805. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45571-X_10
Download citation
DOI: https://doi.org/10.1007/3-540-45571-X_10
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67382-8
Online ISBN: 978-3-540-45571-4
eBook Packages: Springer Book Archive