Query optimization in an extended DBMS

  • Beng Chin Ooi
  • Ron Sacks-Davis
Data Organizations For Extended DBMSs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 367)


Conventional Data Base Management Systems (DBMSs) are not generally effective for applications such as geographic data processing where data have spatial characteristics and queries involve on spatial relationships. These DBMSs can however be extended by supplementing them with special processing subsystems and new indexing structures and by augmenting the query interface language. DBMSs supporting an SQL interface are now widely used. The GEOgraphic Query Language (GEOQL) [18] is an extension of SQL proposed for geographic applications and supports both spatial and aspatial operations. In this paper, we propose a global optimization strategy for the hybrid queries so that a general query involving both spatial and aspatial selection can be executed efficiently. We show that the method is feasible.


Partial Result Parse Tree Decomposition Strategy Query Optimization Final Answer 
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.
    D. J. Abel and J. L. Smith, “A Kernell-Shell Approach to an Extended Relational Spatial Database Management System”, Unpublished paper, CSIRO Canberra, 1987.Google Scholar
  2. 2.
    D. S. Batory and M. Mannino, “Panel on Extensible Database Systems”, Proc. ACM SIGMOD Int. Conf. on Management of Data, Washington D.C., May 1986, 187–190.Google Scholar
  3. 3.
    F. W. Burton, V. J. Kollias and J. G. Kollias, “Permutation Backtracking in Lexicographic Order”, The Computer Journal 27, 4 (1984), 373–376.Google Scholar
  4. 4.
    S. Christodoulakis, “Implications of certain assumptions in database performance evaluation”, ACM Transactions on Database Systems 9, 2 (June 1984), 163–186.Google Scholar
  5. 5.
    M. C. Er, “An efficient implementation of permutation backtracking in lexicographic order”, The Computer Journal 30, 3 (1987).Google Scholar
  6. 6.
    J. C. Freytag, “A rule-based view of query optimization”, Proceedings of SIGMOD '87, San Francisco, California, May 1987, 173–180.Google Scholar
  7. 7.
    R. A. Ganski and H. K. T. Wong, “Optimization of nested SQL queries revisited”, Proceedings of SIGMOD '87, San Francisco, California, May 1987, 23–33.Google Scholar
  8. 8.
    G. Graefe and D. J. DeWitt, “The EXODUS optimizer generator”, Proceedings of SIGMOD '87, San Francisco, California, May 1987, 160–172.Google Scholar
  9. 9.
    P. A. V. Hall, “Optimization of single expressions in a relational data base system”, IBM Journal of Research and Development 20, 3 (May 1976), 244–257.Google Scholar
  10. 10.
    M. Jarke and J. Koch, “Query optimization in database systems”, ACM Computing Surveys 16, 2 (June 1984), 111–152.Google Scholar
  11. 11.
    W. Kim, “On optimizing an SQL-like nested query”, ACM Transactions on Database Systems 7, 3 (September 1982), 443–469.Google Scholar
  12. 12.
    K. J. McDonell, “An overview of the relational test bed (RTB)”, Technical Report 81, Dept. Comp. Sci., Monash University, Vic., Australia, 1986.Google Scholar
  13. 13.
    B. C. Ooi, K. J. McDonell and R. Sacks-Davis, “Spatial kd-tree: an indexing mechanism for spatial database”, Proceedings of the Eleventh IEEE Computer Software and Applications Conference, Tokyo, Japan, October 1987, 433–438.Google Scholar
  14. 14.
    B. C. Ooi, “Efficient Query Processing for Geographic Information Systems”, PhD Thesis, Monash University, 1988.Google Scholar
  15. 15.
    J. A. Orenstein and F. A. Manola, “PROBE spatial data modelling and query processing in an image database application”, IEEE Trans. on Softw. Eng. 14, 5 (1988), 611–629.Google Scholar
  16. 16.
    P. Richard, “Evaluation of the size of a query expressed in relational algebra”, Proc. ACM SIGMOD Int. Conf. on Management of Data, New York, April 1981, 155–163.Google Scholar
  17. 17.
    N. Roussopoulos, C. Faloutsos and T. K. Sellis, “An efficient pictorial database system for PSQL”, IEEE Trans. on Softw. Eng. 14, 5 (1988), 639–650.Google Scholar
  18. 18.
    R. Sacks-Davis, K. J. McDonell and B. C. Ooi, GEOQL — a query language for geographic information systems, Royal Melbourne Institute of Technology, Melbourne, Australia, July 1987.Google Scholar
  19. 19.
    R. Sedgewick, “Permutation generation methods”, ACM Computing Surveys 9, 2 (June 1977), 137–164.Google Scholar
  20. 20.
    E. Wong and K. Youssefi, “Decomposition — a strategy for query processing”, ACM Transactions on Database Systems 1 (1976), 223–241.Google Scholar
  21. 21.
    S. B. Yao, “Optimization of query evaluation algorithms”, ACM Transactions on Database Systems 4, 2 (June 1979), 133–155.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Beng Chin Ooi
    • 1
  • Ron Sacks-Davis
    • 2
  1. 1.Computer Science DepartmentMonash UniversityAustralia
  2. 2.Computer Science DepartmentRoyal Melbourne Institute of TechnologyAustralia

Personalised recommendations