ACM SIGMOD Anthology ACM SIGMOD dblp.uni-trier.de

A Predicate Matching Algorithm for Database Rule Systems.

Eric N. Hanson, Moez Chaabouni, Chang-Ho Kim, Yu-Wang Wang: A Predicate Matching Algorithm for Database Rule Systems. SIGMOD Conference 1990: 271-280
@inproceedings{DBLP:conf/sigmod/HansonCKW90,
  author    = {Eric N. Hanson and
               Moez Chaabouni and
               Chang-Ho Kim and
               Yu-Wang Wang},
  editor    = {Hector Garcia-Molina and
               H. V. Jagadish},
  title     = {A Predicate Matching Algorithm for Database Rule Systems},
  booktitle = {Proceedings of the 1990 ACM SIGMOD International Conference on
               Management of Data, Atlantic City, NJ, May 23-25, 1990},
  publisher = {ACM Press},
  year      = {1990},
  pages     = {271-280},
  ee        = {http://doi.acm.org/10.1145/93597.98736, db/conf/sigmod/HansonCKW90.html},
  crossref  = {DBLP:conf/sigmod/90},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Forward-chaining rule systems must test each newly asserted fact against a collection of predicates to find those rules that match the fact. Expert system rule engines use a simple combination of hashing and sequential search for this matching. We introduce an algorithm for finding the matching predicates that is more efficient than the standard algorithm when the number of predicates is large. We focus on equality and inequality predicates on totally ordered domains. This algorithm is well-suited for database rule systems, where predicate-testing speed is critical. A key component of the algorithm is the interval binary search tree (IBS-tree). The IBS-tree is designed to allow efficient retrieval of all intervals (e. g. range predicates) that overlap a point, while allowing dynamic insertion and deletion of intervals. The algorithm could also be used to improve the performance of forward-chaining inference engines for large expert systems applications.

Copyright © 1990 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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Hector Garcia-Molina, H. V. Jagadish (Eds.): Proceedings of the 1990 ACM SIGMOD International Conference on Management of Data, Atlantic City, NJ, May 23-25, 1990. ACM Press 1990 BibTeX , SIGMOD Record 19(2), June 1990
Contents

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Referenced by

  1. Himanshu Gupta, Divesh Srivastava: The Data Warehouse of Newsgroups. ICDT 1999: 471-488
  2. Eric N. Hanson, Chris Carnes, Lan Huang, Mohan Konyala, Lloyd Noronha, Sashi Parthasarathy, J. B. Park, Albert Vernon: Scalable Trigger Processing. ICDE 1999: 266-275
  3. Eric N. Hanson, I.-Cheng Chen, Roxana Dastur, Kurt Engel, Vijay Ramaswamy, Wendy Tan, Chun Xu: A Flexible and Recoverable Client/Server Database Event Notification System. VLDB J. 7(1): 12-24(1998)
  4. Lars Bækgaard, Leo Mark: Incremental Computation of Set Difference Views. IEEE Trans. Knowl. Data Eng. 9(2): 251-261(1997)
  5. Arthur M. Keller, Julie Basu: A Predicate-based Caching Scheme for Client-Server Database Architectures. VLDB J. 5(1): 35-47(1996)
  6. Eric N. Hanson: The Design and Implementation of the Ariel Active Database Rule System. IEEE Trans. Knowl. Data Eng. 8(1): 157-172(1996)
  7. Rosa Meo, Giuseppe Psaila, Stefano Ceri: Composite Events in Chimera. EDBT 1996: 56-76
  8. Jennifer Widom, Stefano Ceri (Eds.): Active Database Systems: Triggers and Rules For Advanced Database Processing. Morgan Kaufmann 1996, ISBN 1-55860-304-2
    Contents
  9. Lars Bækgaard, Leo Mark: Incremental Computation of Nested Relational Query Expressions. ACM Trans. Database Syst. 20(2): 111-148(1995)
  10. A. Prasad Sistla, Ouri Wolfson: Temporal Triggers in Active Databases. IEEE Trans. Knowl. Data Eng. 7(3): 471-486(1995)
  11. Lars Bækgaard, Leo Mark: Incremental Computation of Time-Varying Query Expressions. IEEE Trans. Knowl. Data Eng. 7(4): 583-590(1995)
  12. Ernest Teniente, Toni Urpí: A Common Framework for Classifying and Specifying Deductive Database Updating Problems. ICDE 1995: 173-182
  13. Michael Stonebraker: The Integration of Rule Systems and Database Systems. IEEE Trans. Knowl. Data Eng. 4(5): 415-423(1992)
  14. Sharma Chakravarthy, Eric N. Hanson, Stanley Y. W. Su: Active Data/Knowledge Bases Research At the University of Florida. IEEE Data Eng. Bull. 15(1-4): 35-39(1992)
  15. Eric N. Hanson: Rule Condition Testing and Action Execution in Ariel. SIGMOD Conference 1992: 49-58
  16. Yu-Wang Wang, Eric N. Hanson: A Performance Comparison of the Rete and TREAT Algorithms for Testing Database Rule Conditions. ICDE 1992: 88-97
  17. Timos K. Sellis, Chih-Chen Lin: A Geometric Approach to Indexing Large Rule Bases. EDBT 1992: 405-420
  18. Jennifer Widom, Roberta Cochrane, Bruce G. Lindsay: Implementing Set-Oriented Production Rules as an Extension to Starburst. VLDB 1991: 275-285
  19. Ulf Schreier, Hamid Pirahesh, Rakesh Agrawal, C. Mohan: Alert: An Architecture for Transforming a Passive DBMS into an Active DBMS. VLDB 1991: 469-478
  20. Ouri Wolfson, Hasanat M. Dewan, Salvatore J. Stolfo, Yechiam Yemini: Incremental Evaluation of Rules and its Relationship to Parallelism. SIGMOD Conference 1991: 78-87
  21. Bernhard Seeger, Hans-Peter Kriegel: The Buddy-Tree: An Efficient and Robust Access Method for Spatial Data Base Systems. VLDB 1990: 590-601
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