Linearly Bounded Reformulations of Conjunctive Databases

Extended Abstract
  • Rada Chirkova
  • Michael R. Genesereth
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1861)


Database reformulation is the process of rewriting the data and rules of a deductive database in a functionally equivalent manner. We focus on the problem of automatically reformulating a database in a way that reduces query processing time while satisfying strong storage space constraints.

In previous work we have investigated database reformulation for the case of unary databases. In this paper we extend this work to arbitrary arity, while concentrating on databases with conjunctive rules. The main result of the paper is that the database reformulation problem is decidable for conjunctive databases.


Query Language View Relation Conjunctive Query Input Query Deductive Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Serge Abiteboul and Oliver Duschka. Complexity of answering queries using materialized views. In PODS-98, pages 254–263.Google Scholar
  2. 2.
    Serge Abiteboul, Richard Hull, and Victor Vianu. Foundations of Databases. Addison-Wesley, Reading, Mass., 1995.zbMATHGoogle Scholar
  3. 3.
    F.N. Afrati, M. Gergatsoulis, and T.G. Kavalieros. Answering queries using materialized views with disjunctions. In ICDT-99, pages 435–452.Google Scholar
  4. 4.
    A.V. Aho, Y. Sagiv, and J.D. Ullman. Equivalences among relational expressions. SIAM J. Comput., 8(2):218–246, 1979.zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    J. Albert, Y. Ioannidis, and R. Ramakrishnan. Conjunctive query equivalence of keyed relational schemas. In PODS-97, pages 44–50.Google Scholar
  6. 6.
    P. Atzeni, G. Ausiello, C. Batini, and M. Moscarini. Inclusion and equivalence between relational database schemata. Theoretical Computer Science, 19:267–285, 1982.zbMATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    C. Batini, M. Lenzerini, and S.B. Navathe. A comparative analysis of methodologies for database schema integration. ACM Computing Surveys, 18(4):323–364, 1986.CrossRefGoogle Scholar
  8. 8.
    C. Beeri, A.O. Mendelzon, Y. Sagiv, and J.D. Ullman. Equivalence of relational database schemes. SIAM J. Comput., 10(2):352–370, 1981.zbMATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Ashok K. Chandra and Philip M. Merlin. Optimal implementation of conjunctive queries in relational data bases. In STOC-77, pages 77–90.Google Scholar
  10. 10.
    E.F. Codd. A relational model of data for large shared data banks. Comm. ACM, 13(6):377–387, June 1970.Google Scholar
  11. 11.
    E.F. Codd. Further normalization of the data base relational model. In R. Rustin, editor, Database Systems, pages 33–64. Prentice Hall Inc., Englewood Cliffs, NJ, 1972.Google Scholar
  12. 12.
    Oliver M. Duschka and Michael R. Genesereth. Answering recursive queries using views. In PODS-97, pages 109–116.Google Scholar
  13. 13.
    Oliver M. Duschka and Michael R. Genesereth. Query planning with disjunctive sources. In AAAI-98 Workshop on AI and Information Integration, 1997.Google Scholar
  14. 14.
    Herbert B. Enderton. A Mathematical Introduction to Logic. Academic Press, New York, 1972.zbMATHGoogle Scholar
  15. 15.
    Fausto Giunchiglia and Toby Walsh. A theory of abstraction. Artificial Intelligence, 57(2–3):323–389, 1992.CrossRefMathSciNetzbMATHGoogle Scholar
  16. 16.
    Himanshu Gupta. Selection of views to materialize in a data warehouse. In ICDT-97, pages 98–112.Google Scholar
  17. 17.
    Himanshu Gupta and Inderpal Singh Mumick. Selection of views to materialize under a maintenance cost constraint. In ICDT-99, pages 453–470.Google Scholar
  18. 18.
    Richard Hull. Managing semantic heterogeneity in databases: a theoretical perspective. In PODS-97, pages 51–61.Google Scholar
  19. 19.
    Richard Hull. Relative information capacity of simple relational database schemata. SIAM J. Comput., 15(3):856–886, August 1986.Google Scholar
  20. 20.
    Won Kim, editor. Modern Database Systems. ACM Press, New York, New York, 1995.zbMATHGoogle Scholar
  21. 21.
    Yannis Kotidis and Nick Roussopoulos. Dynamat: a dynamic view management system for data warehouses. In SIGMOD-99.Google Scholar
  22. 22.
    Alon Y. Levy and P. Pandurang Nayak. A semantic theory of abstractions. In IJCAI-95, pages 196–203.Google Scholar
  23. 23.
    A.Y. Levy, A.O. Mendelzon, Y. Sagiv, and D. Srivastava. Answering queries using views. In PODS-95, pages 95–104.Google Scholar
  24. 24.
    John Wylie Lloyd. Foundations of Logic Programming. Springer-Verlag, 1987.Google Scholar
  25. 25.
    R.J. Miller, Y.E. Ioannidis, and R. Ramakrishnan. The use of information capacity in schema integration and translation. In VLDB-93, pages 120–133.Google Scholar
  26. 26.
    R.J. Miller, Y.E. Ioannidis, and R. Ramakrishnan. Schema equivalence in heterogeneous systems: bridging theory and practice. Information Systems, 19(1):3–31, 1994.CrossRefGoogle Scholar
  27. 27.
    Jack Minker. Logic and databases: a 20 year retrospective. In D. Pedreschi and C. Zaniolo, editors, Logic in Databases, pages 3–57. Springer, 1996. (Proceedings of the LID’96 international workshop).Google Scholar
  28. 28.
    Raghu Ramakrishnan and Jeffrey D. Ullman. A survey of deductive database systems. J. Logic Progr., 23(2):125–149, May 1995.Google Scholar
  29. 29.
    J. Rissanen. On equivalences of database schemes. In PODS-82, pages 23–26.Google Scholar
  30. 30.
    K.A. Ross, D. Srivastava, and S. Sudarshan. Materialized view maintenance and integrity constraint checking: trading space for time. In SIGMOD-96, pages 447–458.Google Scholar
  31. 31.
    Devika Subramanian. A theory of justified reformulations. PhD thesis, Stanford University, 1989.Google Scholar
  32. 32.
    Jeffrey D. Ullman. Information integration using logical views. In ICDT-97, pages 19–40.Google Scholar
  33. 33.
    Jeffrey D. Ullman. Principles of Database and Knowledge-Base Systems, volume I. Computer Science Press, New York, 1988.Google Scholar
  34. 34.
    Jeffrey D. Ullman. Principles of Database and Knowledge-Base Systems, volume II. Computer Science Press, New York, 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Rada Chirkova
    • 1
  • Michael R. Genesereth
    • 1
  1. 1.Stanford UniversityStanfordUSA

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