Abstract
This article describes the design of a transaction management dedicated to database integrated rule systems. Especially, we look at an object management system which has to integrate several inference mechanisms. The transaction management of such a system has to support various integration architectures equally well with respect to easy and effortless coupling of database and rule system as well as efficient rule evaluation. In the following we develop a classification of inference mechanisms and parallelism in database integrated production rule systems. Thereafter, we describe a transaction management which supports different rule systems that can be described by our classification scheme.
This work wets supported by the EC and the German BMFT. The work of the first author has been funded by the EC within the ESPRIT project 7364 JESSI-Common-Frame. The second author was supported by BMFT grant No. 01 IS 104 A/7
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References
Aiken, A.; Widom, J.; Hellerstein, J.M. Behavior of Database Production Rules: Termination, Confluence, and Observable Determinism Proc. ACM SIGMOD, June 1992, San Diego, CA, pp.59–68
Barghouti, N.S.; Kaiser, G.E. Modelling Concurrency in Rule-Based Development Environments IEEE Expert, Dec. 1990, pp.15–27
Bernstein, P.A.; Hadzilacos, V.; Goodman, N. Concurrency Control and Recovery in Database Systems Addison-Wesley Reading MA, 1987
Brownston, L.; Farrell, R.; Kant, E.; Martin, N. Programming Expert Systems in OPS5 —An Introduction to Rule-Based Programming Addison-Wesley Series in Artificial Intelligence, 1986
Buchmann, A.; Özsu, M.T.; Hornick, M.; Georgakopoulos, D.; Manola, F.A. A Transaction Model for Active Distributed Object Systems in [8]
Boss, B.; v. Bültzingsloewen, G.; Danner, C. Integrating Rule Based Systems with JOKER Proc. IDS-92, International Workshop on Data Base System Intellectualization, Kaliningrad, May 92, published in: System and Machines 5/6 1992
Carey, M.J.; Muhanna, W.A. The Performance of Multiversion Concurrency Control Algorithms ACM Transactions on Computer Systems, 4(4), Nov. 1986, pp.338–378
Elmagarmid, A. K. Database Transaction Models for Advanced Applications Morgan Kaufmann Series in Data Management Systems, San Marco, CA, 1992
Forgy, C.L. Rete: A Fast Algoritm for the Many Pattern/ Many Object Pattern Match Problem Artificial Intelligence, 19-1, 1982, pp.17–37
Gatziu, S.; Geppert, A.; Dittrich, K.R. Integrating Active Concepts into an Object-Oriented Database System Proc. 3rd Int. Workshop on Database Programming Languages (DBPL), Greece August 1991
Garcia-Molina, H.; Salem, K. Sagas Proc. ACM SIGMOD Int. Conf. on Man. of Data, 1987, pp.249–259
Gordin, D.N.; Pasik, A.J. Set-Oriented Constructs: From Rete Rule Bases to Database Systems Proc. ACM SIGMOD Int. Conf. on Man. of Data, 1991, pp.60–67
Gupta, Anoop Parallelism in Production Systems Morgan Kaufmann, Research Notes in Artificial Intelligence, 1987
Hanson, E.N. An Initial Report on The Design of Ariel: A DBMS With an Integrated Production Rule System SIGMOD RECORD, 18-3, Sept. 1989, pp.12–19
Hsu, M.; Ladin, R.; McCarthy, D.R. An Execution Model for Active Data Base Management Systems Proc. 3rd Int. Conf. on Data and Knowledge Bases, Israel 1988, pp.171–179
KEE Version 3.0 Technical Manuals, Intellicorp 1986
Kotz, A. Triggermechanismen in Datenbanksystemen Informatik-Fachberichte, Bd. 201, 1989
Kung, H.T.; Robinson, J.T. On Optimistic Methods for Concurrency Control ACM Transactions on Database Systems 6(2), 1981, pp.213–226
Nilsson, N.J. Priciples of Artificial Intelligence Springer Verlag Berlin-Heidelberg-New York 1982
Pasik, Alexander J. A Source-to-Source Transformation for Increasing Rule-Based System Parallelism IEEE Trans, on Knowledge and Data Engineering, 4-4, Aug.1992, pp.336–343
Ranft, M. Integrating Multiple Concurrency Control Algorithms In Proc. Workshop on Next Generation Information Technologies and Systems (NGITS’93), Haifa, Israel, June 1993
Raschid, L.; Sellis, T.; Delis, A. On the Concurrent Execution of Production Rules in A Database Implementation Technical Report UMIACS-TR-91-125, University of Maryland, September 1991
Raschid, L.; Su, S.Y.W. A Transaction Oriented Mechanism to Control Processing in a Knowledge Base Management System Proc. 2nd Int. Conf. on Expert Database Systems, Vienna, 1988, pp.353–373
Reuter, A.; Wächter, H. The ConTract Model IEEE Data Engineering Bulletin 14(1), 1991,pp.39–43
Rich, E. Artificial Intelligence McGraw-Hill Series in Artificial Intelligence, 1983
Stonebraker, M.; Jhingram, A.; Goh, J.; Potamianos, S. On Rules, Procedures, Caching and Views in Data Base Systems Proc. ACM SIGMOD Int. Conf. on Man. of Data, 1990, pp.281–290
Sellis, T.; Lin, C.-C.; Raschid, L. Data Intensive Production Systems: The DIPS Approach SIGMOD RECORD, 18-3, Sept.1989, pp.52–58
Srivastava, J.; Hwang, K.-W.; Tan, J.S.E. Parallelism in Database Production Systems Proc. 6th Int. Conf. on Data Engineering, LA, Febr. 90, pp.121–128
Ullman, J.D. Principles of Database and Knowledge-Base Systems, Vol.II Computer Science Press 1989
Widom, J; Finkelstein, S.J. A Syntax and Semantics for Set-Oriented Production Rules in Relational Database Systems SIGMOD RECORD, 18-3, Sept.1989, pp.36–45
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© 1994 British Computer Society
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Danner, C., Ranft, M. (1994). Transaction Management to Support Rule Based Database Applications. In: Paton, N.W., Williams, M.H. (eds) Rules in Database Systems. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3225-7_9
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DOI: https://doi.org/10.1007/978-1-4471-3225-7_9
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