Tableau Techniques for Querying Information Sources through Global Schemas

  • Gösta Grahne
  • Alberto O. Mendelzon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1540)

Abstract

The foundational homomorphism techniques introduced by Chandra and Merlin for testing containment of conjunctive queries have recently attracted renewed interest due to their central role in information integration applications. We show that generalizations of the classical tableau representation of conjunctive queries are useful for computing query answers in information integration systems where information sources are modeled as views defined on a virtual global schema. We consider a general situation where sources may or may not be known to be correct and complete. We characterize the set of answers to a global query and give algorithms to compute a finite representation of this possibly infinite set, as well as its certain and possible approximations. We show how to rewrite a global query in terms of the sources in two special cases, and show that one of these is equivalent to the Information Manifold rewriting of Levy et al.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. AD98.
    Abiteboul S., O. M. Duschka: Complexity of Answering Queries Using Materialized Views. Proc. 9th Annual ACM Symp. on the Theory of Computing, pp. 254–263.Google Scholar
  2. AHV95.
    Abiteboul S., R. Hull, and V. Vianu. Foundations of Databases. Addison-Wesley, Reading Ma. 1995.MATHGoogle Scholar
  3. AKG91.
    Abiteboul S., P. C. Kanellakis, G. Grahne. On the Representation and Querying of Sets of Possible Worlds. Theoretical Computer Science 78:1, 1991, pp. 158–187MathSciNetGoogle Scholar
  4. ASU79.
    Aho A.V., Y. Sagiv, J. D. Ullman. Equivalences Among Relational Expressions. SIAM J. Comput. 8:2, 1979, pp. 218–246MATHCrossRefMathSciNetGoogle Scholar
  5. BV81.
    Beeri C, M. Y. Vardi. The Implication Problem for Data Dependencies. Proc. 8th International Colloquium on Automata, Languages and Programming, pp. 73–85Google Scholar
  6. CM77.
    Chandra A.K. and Merlin P. M. Optimal implementation of conjunctive queries in relational databases. Conference Record of the 9th Annual ACM Symposium on Theory of Computing, pp. 77–90.Google Scholar
  7. FKUV86.
    Fagin R., G. M. Kuper, J. D. Ullman, M. Y. Vardi. Updating Logical Databases. In P. C. Kanellakis and F. Preparata (Editors) Advances in Computing Research, Vol. 3, pp. 1–18. JAI Press Inc., Greenwich, CT, 1986.Google Scholar
  8. Gra91.
    Grahne G. The Problem of Incomplete Information in Relational Databases. Lecture Notes in Computer Science, vol. 554. Springer-Verlag, Berlin 1991.MATHGoogle Scholar
  9. IL84.
    Imielinski T, W. Lipski Jr. Incomplete Information in Relational Databases. J. ACM 31:4, 1984, pp. 761–791MATHCrossRefMathSciNetGoogle Scholar
  10. Kan95.
    Kanellakis P.C. Constraint Programming and Database Languages: A Tutorial. Proc. 14th ACM Symp. on Principles of Database Systems, pp. 46–53.Google Scholar
  11. KKR90.
    Kanellakis P.C., G. M. Kuper, P. Z. Revesz. Constraint Query Languages. Proc. 9th ACM Symp. on Principles of Database Systems, pp. 299–313.Google Scholar
  12. Lev96.
    Levy A.Y. Obtaining Complete Answers from Incomplete Databases. Proc. 22nd Int’l. Conf. on Very Large Databases, pp. 402–412.Google Scholar
  13. LM*95.
    Levy A.Y., A. O. Mendelzon, Y. Sagiv, D. Srivastava: Answering Queries Using Views. Proc. 14th ACM Symp. on Principles of Database Systems, pp. 95–104.Google Scholar
  14. LRO96.
    Levy A.Y., A. Rajaraman and J. J. Ordille. Querying Heterogeneous Information Sources Using Source Descriptions. Proc. 22nd Int’l. Conf. on Very Large Databases, pp. 251–262.Google Scholar
  15. MRW86.
    Maier D., D. Rozenshtein, D. S. Warren. Window Functions. In P. C. Kanellakis and F. Preparata (Editors) Advances in Computing Research, Vol. 3, pp. 213–246, JAI Press Inc., Greenwich, CT, 1986.Google Scholar
  16. Men84.
    Mendelzon A.O. Database States and Their Tableaux. ACM Trans. on Databases Systems 9:2, 1984, pp. 264–282MATHCrossRefMathSciNetGoogle Scholar
  17. Mot97.
    Motro A. Multiplex: A Formal Model for Multidatabases and Its Implementation. Technical Report ISSE-TR-95-103.Google Scholar
  18. vdM93.
    van der Meyden R. Recursively Indefinite Databases, Theoretical Computer Science 116(1,2), 1993, pp. 151–194MATHCrossRefMathSciNetGoogle Scholar
  19. vdM98.
    van der Meyden R. Logical Approaches to Incomplete Information: A Survey. In J. Chomicki and G. Saake (Editors) Logics for Databases and Information Systems. Kluwer Academic Publishers, 1998, pp. 307–356Google Scholar
  20. TSI94.
    Tsatalos, O.G, M.H. Solomon, Y.E. Ioannidis. The GMAP: A Versatile Tool for Physical Data Independence. Proc. 20th Int’l. Conf. on Very Large Databases, pp. 367–378.Google Scholar
  21. Ull82.
    Ullman J.D. The U. R. Strikes Back. Proc. 1st ACM Symp. on Principles of Database Systems, pp. 10–22.Google Scholar
  22. Ull97.
    Ullman J.D. Information Integration Using Logical Views. Proc. 6th Int’l. Symp. on Database Theory, pp. 19–40.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Gösta Grahne
    • 1
  • Alberto O. Mendelzon
    • 2
  1. 1.Department of Computer ScienceConcordia UniversityMontrealCanada
  2. 2.Department of Computer ScienceUniversity of TorontoTorontoCanada

Personalised recommendations