Set-oriented production rules in relational database systems

ABSTRACT

We propose incorporating a production rules facility into a relational database system. Such a facility allows definition of database operations that are automatically executed whenever certain conditions are met. In keeping with the set-oriented approach of relational data manipulation languages, our production rules are also set-oriented—they are triggered by sets of changes to the database and may perform sets of changes. The condition and action parts of our production rules may refer to the current state of the database as well as to the sets of changes triggering the rules. We define a syntax for production rule definition as an extension to SQL. A model of system behavior is used to give an exact semantics for production rule execution, taking into account externally-generated operations, self-triggering rules, and simultaneous triggering of multiple rules.

REFERENCES

• BF*85: Lee Brownston , Robert Farrell , Elaine Kant , Nancy Martin, Programming expert systems in OPS5: an introduction to rule-based programming, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1985
• CJL88: M J Carey, R Jauhart, and M Lvny On Transactwn Boundames zn A ctzve Databases A Performance Perspectzve Techmcal Report 796, Computer Sciences Department, Umversxty of Wisconsin, November 1988
• Cod70: E. F. Codd, A relational model of data for large shared data banks, Communications of the ACM, v.13 n.6, p.377-387, June 1970 [doi>10.1145/362384.362685]
• Coh89: D. Cohen, Compiling complex database transition triggers, Proceedings of the 1989 ACM SIGMOD international conference on Management of data, p.225-234, June 1989, Portland, Oregon, United States
• CW90: S Cen and J Wldom Demvmg Productzon Rules /or Constraint Maintenance IBM Research Report RJ 7348, IBM Almaden Research Center, March 1990
• DE89: L M L Delcambre and J N Ethezedge The Relational Produchon Language a produchon language for relational databases In L Kerschberg, echtor, Expert Database Systems~ Procee&ngs from the Second Internat,onal Conference, pages 333-351, Benjamin/Cummings, Redwood Cxty, Cahforma, 1989
• dMS88: Christophe de Maindreville , Eric Simon, A Production Rule-Based Approach to Deductive Databases, Proceedings of the Fourth International Conference on Data Engineering, p.234-241, February 01-05, 1988
• Esw76: K P Eswaran Speczficatwns, Implementatzons and Interactzons of a Tmgger Subsystem zn an Integrated Database System IBM Research Report RJ 1820, IBM San Jose Research Laboratory, August 1976
• FPT88: S J Fmkelstem, H Ptrahesh, and M Tsangans Rule support for Starburst 1988 Unpubhshed notes
• Han89: E. N. Hanson, An initial report on the design of Ariel DBMS with an integrated production rule system, ACM SIGMOD Record, v.18 n.3, p.12-19, Sep. 1989 [doi>10.1145/71031.71033]
• HFLP89: L. M. Haas , J. C. Freytag , G. M. Lohman , H. Pirahesh, Extensible query processing in starburst, Proceedings of the 1989 ACM SIGMOD international conference on Management of data, p.377-388, June 1989, Portland, Oregon, United States
• IBM88: IBM Systems Apphcatwn Archztecture, Common Programming Interface Database Reference IBM Form Number SC26-4348-1, October 1988
• KDM88: Angelika M. Kotz , Klaus R. Dittrich , Jutta A. Mülle, Supporting Semantic Rules by a Generalized Event/Trigger Mechanism, Proceedings of the International Conference on Extending Database Technology: Advances in Database Technology, p.76-91, March 14-18, 1988
• LMP87: Bruce Lindsay , John McPherson , Hamid Pirahesh, A data management extension architecture, Proceedings of the 1987 ACM SIGMOD international conference on Management of data, p.220-226, May 27-29, 1987, San Francisco, California, United States
• MD89: Dennis McCarthy , Umeshwar Dayal, The architecture of an active database management system, Proceedings of the 1989 ACM SIGMOD international conference on Management of data, p.215-224, June 1989, Portland, Oregon, United States
• Mor83: Matthew Morgenstern, Active Databases as a Paradigm for Enhanced Computing Environments, Proceedings of the 9th International Conference on Very Large Data Bases, p.34-42, October 31-November 02, 1983
• RS89: L Rasclud and S Y W Su A transactxon oriented mechamsm to control processing m a knowledge base management system In L Kersehberg, editor, Expert Database Systems--Proceedings from the Second Internatwnal Conference, pages 353- 373, BenJamin/Cummings, Redwood Cxty, Cahforma, 1989
• SdM88: E. Simon de Maindreville, Deciding whether a production rule is relational computable, Lecture notes in computer science on ICDT '88, p.205-222, October 1988, Bruges, Belgium
• SHP88: Michael Stonebraker , Eric N. Hanson , Spyros Potamianos, The POSTGRES Rule Manager, IEEE Transactions on Software Engineering, v.14 n.7, p.897-907, July 1988 [doi>10.1109/32.42733]
• SJGP90: Michael Stonebraker , Anant Jhingran , Jeffrey Goh , Spyros Potamianos, On rules, procedure, caching and views in data base systems, Proceedings of the 1990 ACM SIGMOD international conference on Management of data, p.281-290, May 23-26, 1990, Atlantic City, New Jersey, United States
• SLR88: T. Sellis , C. C. Lin , L. Raschid, Implementing large production systems in a DBMS environment: concepts and algorithms, Proceedings of the 1988 ACM SIGMOD international conference on Management of data, p.404-423, June 01-03, 1988, Chicago, Illinois, United States
• Tzv88: A Tzweh On the couphng of a productmn system shell and a D BMS In Proc of the Thzrd Internatwnal Conference on Data and Knowledge Bases, pages 291-309, Jerusalem, Israel, June 1988
• WF89a: J Widom and S J Fmkelstem A Syntax and Semantzcs for Set-Omented Productwn Rules zn Relatwnal Database Systems IBM Research Report RJ 6880, IBM Almaden Research Center, June 1989 Revxsed March, 1990
• WF89b: J. Widom , S. J. Finkelstein, A syntax and semantics for set-oriented production rules in relational database systems, ACM SIGMOD Record, v.18 n.3, p.36-45, Sep. 1989 [doi>10.1145/71031.71036]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.1 Logical Design
          Subjects: Data models

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.3 Languages

          Nouns: SQL

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Representations (procedural and rule-based)

General Terms:
Algorithms, Design, Languages