Abstract
Aggregate queries are frequent in massive database applications. Their execution tends to be time consuming and costly. Therefore efficiently executing aggregate queries is very important. Semantic cache is a novel method for aiding query evaluation that reuses results of previously answered queries. But little work has been done on semantic cache involving aggregate queries. This is a limiting factor in its applicability. To use semantic cache in massive database applications, it is necessary to extend semantic cache to process aggregate query. In this paper, query matching is identified as a foundation for answering aggregate query by semantic caches. Firstly a formal semantic cache model for aggregate query is proposed. Based on this model, we discuss aggregate query matching. Two algorithms are presented for aggregate query matching. These two algorithms have been implemented in a massive database application project. The practice shows the algorithms are efficient.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dar, S., Franklin, M.J., Jonsson, B.T., Srivastava, D., Tan, M.: Semantic data caching and replacement. In: Proc. of 22th Int’l Conf. on Very Large Data Bases, Mumbai (Bombay), pp. 330–341. Morgan Kaufmann, India (1996)
Godfrey, P., Gryz, J.: Answering Queries by Semantic Caches. In: Bench-Capon, T.J.M., Soda, G., Tjoa, A.M. (eds.) DEXA 1999. LNCS, vol. 1677, pp. 485–498. Springer, Heidelberg (1999)
Ren, Q., Dunham, M.H., Kumar, V.: Semantic Caching and Query Processing. IEEE Transactions on Knowledge and Data Engineering 15(1), 192–210 (2003)
Basu, J.: Associative caching in client-server databases: [PhD dissertation]. Stanford University (1998)
Lee, D., Chu, W.W.: Semantic caching via query matching for web sources. In: Proc. of the 8th international conference on Information and knowledge management, pp. 77–85. ACM Press, Kansas City (1999)
Zaharioudakis, M., Cochrane, R., Lapis, G., Pirahesh, H., Urata, M.: Answering Complex SQL Queries Using Automatic Summary Tables. In: Proc. ACM SIGMOD Int’l Conf. on Management of Data, pp. 105–116. ACM Press, Dallas (2000)
Gupta, A., Harinarayan, V., Quass, D.: Aggregate-query processing in data warehousing environments. In: Proc. of 21th Int’l Conf. on Very Large Data Bases, pp. 358–369. Morgan Kaufmann, Zurich (1995)
Srivastava, D., Dar, S., Jagadish, H.V., Levy, A.: Answering queries with aggregation using views. In: Proc. of 22th Int’l Conf. on Very Large Data Bases, Mumbai (Bombay), pp. 318–329. Morgan Kaufmann, India (1996)
Cohen, S., Nutt, W.: Rewriting aggregate queries using views. In: Proc. of 18th Symposium on Principles of Database Systems, May 1999, ACM Press, Philadelphia (1999)
Sun, X.H., Kamel, N., Ni, L.M.: Solving implication problems in database applications. In: Proc. ACM SIGMOD Int’l. Conf. on Management of Data, pp. 185–192. ACM Press, Portland (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cai, J., Jia, Y., Yang, S., Zou, P. (2005). A Method of Aggregate Query Matching in Semantic Cache for Massive Database Applications. In: Cao, J., Nejdl, W., Xu, M. (eds) Advanced Parallel Processing Technologies. APPT 2005. Lecture Notes in Computer Science, vol 3756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573937_47
Download citation
DOI: https://doi.org/10.1007/11573937_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29639-3
Online ISBN: 978-3-540-32107-1
eBook Packages: Computer ScienceComputer Science (R0)