A Logic-Based Approach to Query Processing in Federated Databases

Abstract Extant work on federated databases has concentrated either on schema integration using semantic models or on query processing using the relational/extended relational model, but both issues have not been addressed using a single framework. In this paper, we explore an alternative approach to database integration using Horn-clause logic as a canonical, intermediate representation. First-order logic is used as a language for expressing the integration of component schemas into a global schema, as well as for specifying integrity constraints associated with global and component schemas. A language based on first-order logic provides the required expressiveness for canonical representation of the global schema at the intermediate level. Global to local query mapping is achieved through the procedural interpretation of logic programming. Query optimization is performed through transformations using integrity constraints, such as functional, inclusion, and data integration dependencies. PROLOG has been used for implementing some of the algorithms described in this paper. The logic-based approach provides a uniform approach for supporting an integrated view of a set of heterogeneous databases, as well as its implementation.

[1]  John Grant,et al.  Foundations of Semantic Query Optimization for Deductive Databases , 1988, Foundations of Deductive Databases and Logic Programming..

[2]  John Wylie Lloyd,et al.  Foundations of Logic Programming , 1987, Symbolic Computation.

[3]  Jeffrey D. Ullman,et al.  Principles of Database and Knowledge-Base Systems, Volume II , 1988, Principles of computer science series.

[4]  R. MacGregor,et al.  Mermaid—A front-end to distributed heterogeneous databases , 1987, Proceedings of the IEEE.

[5]  John Grant,et al.  Logic-based approach to semantic query optimization , 1990, TODS.

[6]  Nick Roussopoulos,et al.  Interoperability of multiple autonomous databases , 1990, CSUR.

[7]  Carlo Zaniolo,et al.  Design of relational views over network schemas , 1979, SIGMOD '79.

[8]  Carlo Zaniolo,et al.  The database language GEM , 1983, SIGMOD '83.

[9]  Yuri Breitbart,et al.  Database integration in a distributed heterogeneous database system , 1986, 1986 IEEE Second International Conference on Data Engineering.

[10]  Erich J. Neuhold,et al.  ViewSystem: integrating heterogeneous information bases by object-oriented views , 1990, [1990] Proceedings. Sixth International Conference on Data Engineering.

[11]  Shamkant B. Navathe,et al.  Relational Schema Integration: Dealing with Inter-Relation Correspondences and Querying Over Component Relations , 1993, Comput. Syst..

[12]  Dennis McLeod,et al.  A federated architecture for information management , 1985, TOIS.

[13]  Robert A. Kowalski,et al.  Logic and semantic networks , 1979, CACM.

[14]  Richard C. T. Lee,et al.  Symbolic logic and mechanical theorem proving , 1973, Computer science classics.

[15]  Shamkant B. Navathe,et al.  An Intuitive Approach to Normalize Network Structured Data , 1980, VLDB.

[16]  Ramez Elmasri,et al.  Fundamentals of Database Systems , 1989 .

[17]  Jack Minker,et al.  Interfacing Predicate Logic Languages and Relational Databases , 1982, ICLP.

[18]  Shamkant B. Navathe,et al.  A logic-based approach to federated databases , 1992 .

[19]  Terry A. Landers,et al.  An Overview of MULTIBASE , 1986, DDB.

[20]  Witold Litwin,et al.  Multidatabase Interoperability , 1986, Computer.

[21]  Stephen Fox,et al.  Heterogeneous distributed database systems for production use , 1990, CSUR.

[22]  Arlette Ferrier,et al.  Heterogeneity in the Distributed Database Management System SIRIUS-DELTA , 1982, VLDB.