The premise behind developing powerful declarative database languages is compelling: by enabling users to specify their queries (and their integrity constraints) in a clear, non-operational way, they make the user's task easier, and provide the database system with more opportunities for optimization. Relational database systems offer a striking proof that this premise is indeed valid. The most popular relational query language, SQL, is based upon relational algebra and calculus, i.e., a small fragment of first-order logic, and the ease of writing queries in SQL (in comparison to more navigational languages) has been an important factor in the commercial success of relational databases. It is well-known that SQL has some important limitations, in spite of its success and popUlarity. Notably, the query language is non-recursive, and support for integrity constraints is limited. Indeed, recognizing these problems, the latest standard, SQL-92, provides increased support for integrity constraints, and it is anticipated that the successor to the SQL-92 standard, called SQL3, RECURSIVE UNION operation . Logic database systems have will include a concentrated on these extensions to the relational database paradigm, and some systems (e.g., Bull's DEL prototype) have even incorporated object-oriented features (another extension likely to appear in SQL3).
|Series:||The Springer International Series in Engineering and Computer Science , #296|
|Edition description:||Softcover reprint of the original 1st ed. 1995|
|Product dimensions:||6.10(w) x 9.25(h) x 0.03(d)|
Table of ContentsPreface. 1. Applications of Deductive Object-Oriented Databases Using DEL; O.D. Friesen, G. Gauthier-Villars, L. Vieille. 2. Q-Data: Using Deductive Database Technology to Improve Data Quality; A. Sheth, C. Wood, V. Kashyap. 3. A Deductive Front-End for Relational Databases; B. Livezey, E. Simoudis. 4. An ADITI Implementation of a Flights Database; J. Harland, K. Ramamohanarao. 5. Using LDL++ for Spatio-Temporal Reasoning in Atmospheric Science Databases; R.R. Muntz, E. Shek, C. Zaniolo. 6. MIMSY: a System for Stock Market Analysis; W.G. Roth, R. Ramakrishnan, P. Seshadri. 7. Efficient Evaluation of Visual Queries Using Deductive Databases; D. Vista, P.T. Wood. 8. Demand Interprocedural Program Analysis Using Logic Databases; T.W. Reps. 9. AMOS: a Natural Language Parser Implemented as a Deductive Database in LOLA; G. Specht, B. Freitag. 10. Programming the PTQ Grammar in XSB; D.S. Warren. 11. Querying with Generalized Quantifiers; A. Badia, D. Van Gucht, M. Gyssens. 12. Requirements for a Deductive Query Language in a Genome-Mapping Database; N. Goodman, S. Rozen, L. Stein. Index.