Optimizing queries with aggregate views

  • Surajit Chaudhuri
  • Kyuseok Shim
Optimization
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1057)

Abstract

Complex queries, with aggregates, views and nested subqueries are important in decision-support applications. Such queries are represented as multi-block queries where a query block may be a view definition containing aggregates or a correlated nested subquery. Beyond transformations that propagate predicates across blocks, the problem of optimizing such queries has not been addressed adequately. In this paper, we show how such queries can be optimized in a cost-based fashion. The crux of our solution is a careful treatment of group-by and aggregation operators that occur among views.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [CS94]
    S. Chaudhuri and K. Shim. Including group-by in query optimization. In Proc. of the 20th VLDB Conference, Santiago, Chile, Sept 1994.Google Scholar
  2. [CS96]
    S. Chaudhuri and K. Shim. Complex queries: A unified approach. Technical report, Hewlett-Packard Laboratories, Palo Alto, In preparation, 1996.Google Scholar
  3. [Day87]
    U. Dayal. Of nests and trees: A unified approach to processing queries that contain nested subqueries, aggregates, and quantifiers. In Proc. of the 13th VLDB Conference, Brighton, August 1987.Google Scholar
  4. [GHQ95]
    A. Gupta, V. Harinarayan, and D. Quass. Aggregate-query processing in data warehousing environments. In Proc. of the 21th VLDB Conference, Zurich, Sept 1995.Google Scholar
  5. [GW87]
    Richard A. Ganski and Harry K. T. Wong. Optimization of nested SQL queries revisited. In Proc. of the ACM SIGMOD, San Francisco, May 1987.Google Scholar
  6. [ISO92]
    ISO. Database Language SQL ISO/IEC. Document ISO/IEC 9075, 1992.Google Scholar
  7. [Kim82]
    W. Kim. On optimizing an SQL-Like nested query. ACM TODS, Sept 1982.Google Scholar
  8. [LMS94]
    A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proc. of the 20th VLDB Conference, Santiago, Chile, Sept 1994.Google Scholar
  9. [MFPR90]
    Inderpal Singh Mumick, Sheldon J. Finkelstein, Hamid Pirahesh, and Raghu Ramakrishnan. Magic is relevant. In Proc. of the ACM SIGMOD, Atlantic City, May 1990.Google Scholar
  10. [Mur92]
    M. Muralikrishna. Improved unnesting algorithms for join aggregate SQL queries. In Proc. of the 18th VLDB Conference, Vancouver, Canada, August 1992.Google Scholar
  11. [PHH92]
    H. Pirahesh, Joseph M. Hellerstein, and Waqar Hasan. Extensible/rule based query optimization in starburst. In Proc. of the ACM SIGMOD, San Diego, May 1992.Google Scholar
  12. [SAC+79]
    P. G. Selinger, M. M. Astrahan, D. D. Chamberlin, R. A. Lorie, and T. G. Price. Access path selection in a relational database management system. In Proc. of the ACM SIGMOD, Boston, June 1979.Google Scholar
  13. [YL94]
    W. P. Yan and P. A. Larson. Performing group-by before join. In Proc. of International Conference on Data Engineering, Houston, Feb 1994.Google Scholar
  14. [YL95]
    W. P. Yan and P. A. Larson. Eager aggregation and lazy aggregation. In Proc. of the 21st VLDB Conference, Zurich, Sept 1995.Google Scholar

Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • Surajit Chaudhuri
    • 1
  • Kyuseok Shim
    • 2
  1. 1.Hewlett-Packard LaboratoriesPalo AltoUSA
  2. 2.IBM Almaden Research CenterSan JoseUSA

Personalised recommendations