Abstract
In ‘Associative Caching’ each client computer keeps a copy of its query result sets in its own local database. The purpose is to reduce the size and frequency of queries to the remote data server accessed by wide-area network. For each new query the client tries to find some or all of the required data in its local collection of result sets. This is done by syntactic comparison of the new query with each previous query, to detect overlapping data sets. Attribute-Pair Range Rules are subset descriptors which the server derives from its data, for its own use in query optimisation. These subset descriptors can be further utilized to provide descriptors for each query result set. This new information enables clients to exploit their cached data for syntactically unrelated queries.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Adali, S., Candan, K. S., Papakonstantinou, Y., Subrahmanian, V. S.: Query Caching and Optimization in Distributed Mediator Systems. Proc ACM SIGMOD Conf. (1996) 137–148.
Amsaleg, L., Bonnet, P., Franklin, M. J., Tomasic, A. and Urhan, T.: Improving Responsiveness for Wide-Area Data Access. Data Engineering Bulletin 20(3): 3–11 (1997).
Arens, Y., Knoblock, C. A.: Intelligent Caching: Selecting, Representing, and Reusing Data in an Information Server. Proc. CIKM/rs94, Third International Conference on Information and Knowledge Management (1994) 433–438.
Basu, J., Poess, M. and Keller, A. M.: High Performance and Scalability Through Associative Client-Side Caching, Seventh International Workshop on High Performance Transaction Systems, Pacific Grove, CA, September 1997.
Basu, J., Poess, M. and Keller, A. M.: Performance Analysis of an Associative Caching Scheme for Client-Server Databases, Technical Note STAN-CS-TN-97-61, Stanford University, Computer Science Dept., September 1997.
Bonnet, P., Tomasic, A.: Partial Answers for Unavailable Data Sources. Proc. FQAS/rs98, Third International Conference on Flexible Query Answering Systems (1998) 43–54. (LNCS 1495).
Dar, S., Franklin, M. J., Jonsson, B. T., Srivastava, D., Tan, M.: Semantic Data Caching and Replacement, Proc. 22nd VLDB Conference (1996) 330–341.
Franklin, M., Kossmann, D.: Cache Investment Strategies. Univ. of Maryland Technical Report CS-TR-3803/UMIACS-TR-97-50, May, 1997.
Hsu, C-N., Knoblock, C. A.: Discovering Robust Knowledge from Databases that Change. Journal of Data Mining and Knowledge Discovery, 2, 1–28 (1998).
Hsu, C-N., Knoblock, C. A.: Semantic Query Optimization for Query Plans of Heterogeneous Multi-Database Systems. IEEE Transactions on Knowledge and Data Engineering, accepted for publication, 1999.
Keller, A. M., Basu, J.: A Predicate-based Caching Scheme for Client-Server Database Architectures. VLDB Journal 5(1) 1996, 35–47.
Lowden, B.G.T., Robinson, J., Lim, K.Y.: A Semantic Query Optimiser using Automatic Rule Derivation. WITS/rs95, 5th Intl. Workshop on Information Technologies and Systems (1995) 68–76.
Piatetsky-Shapiro, G.: Discovery, Analysis and Presentation of Strong Rules, Knowledge Discovery in Databases, Eds. G. Piatetsky-Shapiro and W. J. Frawley, MIT Press (1991) 229–248.
Qian, X.: Query Folding. 12th IEEE Intl. Conference on Data Engineering (1996) 48–55.
Robinson, J., Lowden, B. G. T.: Data Analysis for Query Processing. 2nd Intl. Symposium on Intelligent Data Analysis (1997) 447–458. (LNCS 1280)
Robinson, J., Lowden, B. G. T.: Attribute-Pair Range Rules. Proc. DEXA/rs98, 9th Intl. Conference on Database and Expert Systems Applications (1998) 680–691. (LNCS 1460)
Robinson, J., Lowden, B. G. T.: Semantic Query Optimisation and Rule Graphs. KRDB/rs98, 5th International Workshop on Knowledge Representation meets Data Bases (1998).
Shekhar, S., Hamidzadeh, B., Kohli, A. and Coyle, M.: Learning transformation rules for semantic query optimization: A data-driven approach, IEEE Transactions on Knowledge and Data Engineering, 5(6), 950–964, 1993.
Shenoy, S.T., Ozsoyoglu, Z.M.: A System for Semantic Query Optimization, Proc ACM SIGMOD Conference, 1987, pp 181–195
Siegel, M., Sciore, E. and Salveter, S.: A Method for Automatic Rule Derivation to Support Semantic Query Optimization, ACM TODS 17(4) 563–600, 1992.
Srivastava, D., Dar, S., Jagadish, H. V. and Levy, A. Y.: Answering Queries with Aggregation Using Views, Proc. 22nd VLDB Conference (1996) 318–329.
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
Robinson, J., Lowden, B.G.T. (2000). Extending the Re-use of Query Results at Remote Client Sites. In: Ibrahim, M., Küng, J., Revell, N. (eds) Database and Expert Systems Applications. DEXA 2000. Lecture Notes in Computer Science, vol 1873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44469-6_50
Download citation
DOI: https://doi.org/10.1007/3-540-44469-6_50
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67978-3
Online ISBN: 978-3-540-44469-5
eBook Packages: Springer Book Archive