skip to main content
article
Free Access

Eliminating costly redundant computations from SQL trigger executions

Published:01 June 1997Publication History
Skip Abstract Section

Abstract

Active database systems are now in widespread use. The use of triggers in these systems, however, is difficult because of the complex interaction between triggers, transactions, and application programs. Repeated calculations of rules may incur costly redundant computations in rule conditions and actions. In this paper, we focus on active relational database systems supporting SQL triggers. In this context, we provide a powerful and complete solution to eliminate redundant computations of SQL triggers when they are costly. We define a model to describe programs, rules and their interactions. We provide algorithms to extract invariant subqueries from trigger's condition and action. We define heuristics to memorize the most “profitable” invariants. Finally, we develop a rewriting technique that enables to generate and execute the optimized code of SQL triggers.

References

  1. BCL89 Jose A. Blakeley, Neil Coburn, and Per-Ake Larson. Updating Derived Relations: Detecting Irrelevant and Autonomously Computable Updates. A CM Trans. on Database Systems, 14(3):369-400, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. CPM96 R. Cochrane, H. Pirahesh, and N. Mattos. Integrating Triggers and Declarative Constraints in SQL. In Proceedings on the 22nd Conference on of Very Large Data Bases. September 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. For82 C. Forgy. RETE, a fast algorithm for the many patterns many objects match problem. J. Artificial Intelligence, 19:17-37, 1982.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. FRS93 F. Fabret, M. R6gnier, and E. Simon. An Adaptative Algorithm for Incremental Evaluation of Production Rules. In Proc. International Conference on Very Large Databases, Dublin, Ireland, Aug. 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. FT95 P. Fraternali and L. Tanca. A Structured Approach for the Definition of the Semantics of Active Databases. A CM Transactions On Database Systems, December 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. GM93 G. Graefe and W. J. McKenna. The Volcane Optimiser generator: Extensibility and efficient search. In IEEE international Conference on Data Engineering, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. GM95 A. Gupta and I. S. Mumick. Maintenance of materialized views: Problems, techniques and applications. IEEE Dataengineering Bulletin, 18(2), 1995. Special Issue on Materialized Views and Data Warehousing.Google ScholarGoogle Scholar
  8. GMR95 A. Gupta, I.S. Mumick, and K. Ross. Adaptating Materialized Views after redefinitions. In Proceedings of A CM SIGMOD internationnal Conference on Management o.t Data, San Jose, May 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Han92 E. Hanson. Rule Condition Testing and Action Execution in Ariel. Proc. of the A CM SIGMOD International Conference on Management of Data, pages 49-58, June 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. HRU96 V. Harinarayan, A. Rajaraman, and J. Ullman. Implementing Data Cubes Efficiently. Proc. of the ACM SIGMOD International Conference on Management of Data, June 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. jM93 W.j. McKenna. Efficient search in extensible databse optimisation: The Volcano Optimiser generator. Ph.d. thesis, University of Colorado, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. KP81 S. Koenig and R. Paige. A Transformational Framework for the Automatic Control of Derived Data. In Proc. International Con}erence on Very Large Databases, 1981.Google ScholarGoogle Scholar
  13. LFS97 F. Llirbat, F. Fabret, and E. Simon. Eliminating Costly Redundant Computations from SQL Trigger Execution. An extended version of this paper. At http//rodin.inria/personnes/francois.llirbat/pub.htmI, 1997.Google ScholarGoogle Scholar
  14. Mir87 D.P. Miranker. TREAT: A Better Match Algorithm for AI Production Systems. In Proceedings of the National Conference on Artificial Intelligence, Seattle, Washington, 1987.Google ScholarGoogle Scholar
  15. RSS96 K.A. Ross, D. Srivastava, and S. Sudarshan. Materialized View Maintenance and Integrity Constraint Checking: Trading Space for Time. in In Proc. of the A CM SIGMOD International Conference, june 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. SLR93 T. Sellis, C. Lin, and L. Raschid. Coupling Production Systems and Database Systems: A Homogeneous Approach. IEEE Transaction on Knowledge and Data Engineering, 5:240-256, April 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. WC96 J. Widom and S. Ceri. Active Database Systems: T~iggers and Rules for Advanced Database Processing. Morgan-Kaufmann, San Francisco, California, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Eliminating costly redundant computations from SQL trigger executions

                Recommendations

                Comments

                Login options

                Check if you have access through your login credentials or your institution to get full access on this article.

                Sign in

                Full Access

                • Published in

                  cover image ACM SIGMOD Record
                  ACM SIGMOD Record  Volume 26, Issue 2
                  June 1997
                  583 pages
                  ISSN:0163-5808
                  DOI:10.1145/253262
                  Issue’s Table of Contents
                  • cover image ACM Conferences
                    SIGMOD '97: Proceedings of the 1997 ACM SIGMOD international conference on Management of data
                    June 1997
                    594 pages
                    ISBN:0897919114
                    DOI:10.1145/253260

                  Copyright © 1997 ACM

                  Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                  Publisher

                  Association for Computing Machinery

                  New York, NY, United States

                  Publication History

                  • Published: 1 June 1997

                  Check for updates

                  Qualifiers

                  • article

                PDF Format

                View or Download as a PDF file.

                PDF

                eReader

                View online with eReader.

                eReader