On Answering Queries in the Presence of Limited Access Patterns

  • Chen Li
  • Edward Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1973)


In information-integration systems, source relations often have limitations on access patterns to their data; i.e., when one must provide values for certain attributes of a relation in order to retrieve its tuples. In this paper we consider the following fundamental problem: can we compute the complete answer to a query by accessing the relations with legal patterns? The complete answer to a query is the answer that we could compute if we could retrieve all the tuples from the relations. We give algorithms for solving the problem for various classes of queries, including conjunctive queries, unions of conjunctive queries, and conjunctive queries with arithmetic comparisons. We prove the problem is undecidable for datalog queries. If the complete answer to a query cannot be computed, we often need to compute its maximal answer. The second problem we study is, given two conjunctive queries on relations with limited access patterns, how to test whether the maximal answer to the first query is contained in the maximal answer to the second one? We show this problem is decidable using the results of monadic programs.


Binding Pattern Complete Answer Conjunctive Query Query Planning Answering Query 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    F. N. Afrati, M. Gergatsoulis, and T. G. Kavalieros. Answering queries using materialized views with disjunctions. In ICDT, pages 435–452, 1999.Google Scholar
  2. 2.
    C. Beeri and R. Ramakrishnan. On the power of magic. In PODS, pages 269–283, 1987.Google Scholar
  3. 3.
    D. Calvanese, G. D. Giacomo, M. Lenzerini, and M. Y. Vardi. Query answering using views for data integration over the Web. WebDB, pages 73–78, 1999.Google Scholar
  4. 4.
    A. K. Chandra and P. M. Merlin. Optimal implementation of conjunctive queries in relational data bases. STOC, pages 77–90, 1977.Google Scholar
  5. 5.
    S. Chaudhuri and M. Y. Vardi. On the equivalence of recursive and nonrecursive datalog programs. In PODS, pages 55–66, 1992.Google Scholar
  6. 6.
    S. S. Cosmadakis, H. Gaifman, P. C. Kanellakis, and M. Y. Vardi. Decidable optimization problems for database logic programs. STOC, pages 477–490, 1988.Google Scholar
  7. 7.
    O. M. Duschka. Query planning and optimization in information integration. Ph.D. Thesis, Computer Science Dept., Stanford Univ., 1997.Google Scholar
  8. 8.
    O. M. Duschka and A. Y. Levy. Recursive plans for information gathering. In IJCAI, 1997.Google Scholar
  9. 9.
    D. Florescu, A. Levy, I. Manolescu, and D. Suciu. Query optimization in the presence of limited access patterns. In SIGMOD, pages 311–322, 1999Google Scholar
  10. 10.
    H. Gaifman, H. G. Mairson, Y. Sagiv, and M. Y. Vardi. Undecidable optimization problems for database logic programs. Journal of the ACM, pages 6837 13, 1993Google Scholar
  11. 11.
    A. Gupta, Y. Sagiv, J. D. Ullman, and J. Widom. Constraint checking with partial information. In PODS, pages 45–55, 1994Google Scholar
  12. 12.
    A. Klug. On conjunctive queries containing inequalities. Journal of the ACM, 35(1):146–160, January 1988.zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    A. Y. Levy. Obtaining complete answers from incomplete databases. In Proc. of VLDB, pages 402–412, 1996Google Scholar
  14. 14.
    A. Y. Levy, A. O. Mendelzon, Y. Sagiv, and D. Srivastava. Answering queries using views. In PODS, pages 95–104, 1995.Google Scholar
  15. 15.
    C. Li. Computing complete answers to queries in the presence of limited access patterns (extended version). Technical report, Computer Science Dept., Stanford Univ., 1999.
  16. 16.
    C. Li and E. Chang. Testing query containment in the presence of limi-ted access patterns. Technical report, Computer Science Dept., Stanford Univ.,, 1999.
  17. 17.
    C. Li and E. Chang. Query planning with limited source capabilities. In ICDE, pages 401–412, 2000Google Scholar
  18. 18.
    C. Li, R. Yerneni, V. Vassalos, H. Garcia-Molina, Y. Papakonstantinou, J. D. Ullman, and M. Valiveti. Capability based mediation in TSIMMIS. In SIGMOD, pages 564–566, 1998.Google Scholar
  19. 19.
    T. Millstein, A. Levy, and M. Friedman. Query containment for data integration systems. In PODS, 2000.Google Scholar
  20. 20.
    T. Milo and S. Zohar. Using schema matching to simplify heterogeneous data translation. In Proc. of VLDB, pages 122–133, 1998.Google Scholar
  21. 21.
    A. Rajaraman, Y. Sagiv, and J. D. Ullman. Answering queries using templates with binding patterns. In PODS, pages 105–112, 1995.Google Scholar
  22. 22.
    Y. Sagiv and M. Yannakakis. Equivalences among relational expressions with the union and difference operators. Journal of the ACM, 27(4):633–655, 1980.zbMATHCrossRefMathSciNetGoogle Scholar
  23. 23.
    O. Shmueli. Equivalence of datalog queries is undecidable. Journal of Logic Pro-gramming, 15(3):231–241, 1993.zbMATHCrossRefMathSciNetGoogle Scholar
  24. 24.
    J. D. Ullman. Principles of Database and Knowledge-base Systems, Volumes II: The New Technologies. Computer Science Press, New York, 1989.Google Scholar
  25. 25.
    J. D. Ullman. Information integration using logical views. In ICDT, pages 19–40, 1997.Google Scholar
  26. 26.
    G. Wiederhold. Mediators in the architecture of future information systems. IEEE Computer, 25(3):38–49, 1992.Google Scholar
  27. 27.
    R. Yerneni, C. Li, H. Garcia-Molina, and J. D. Ullman. Computing capabilities of mediators. In SIGMOD, pages 443–454, 1999.Google Scholar
  28. 28.
    R. Yerneni, C. Li, J. D. Ullman, and H. Garcia-Molina. Optimizing large join queries in mediation systems. In ICDT, pages 348–364, 1999.Google Scholar
  29. 29.
    X. Zhang and M. Ozsoyoglu. On efficient reasoning with implication constraints. In DOOD, pages 236–252, 1993Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Chen Li
    • 1
  • Edward Chang
    • 2
  1. 1.Computer Science DepartmentStanford UniversityUSA
  2. 2.ECE DepartmentUniversity of CaliforniaUSA

Personalised recommendations