Encyclopedia of Database Systems

2009 Edition
| Editors: LING LIU, M. TAMER ÖZSU

Query Optimization (in Relational Databases)

  • Thomas Neumann
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-39940-9_293

Synonyms

Definition

Database queries are given in declarative languages, typically SQL. The goal of query optimization is to choose the best execution strategy for a given query under the given resource constraints. While the query specifies the user intent (i.e., the desired output), it does not specify how the output should be produced. This allows for optimization decisions, and for many queries there is a wide range of possible execution strategies, which can differ greatly in their resulting performance. This renders query optimization an important step during query processing.

Historical Background

One of the first papers to discuss query optimization in relational database systems was the seminal System R paper [2]. It introduced a dynamic programming algorithm for optimizing the join order, and coined the concept of interesting orders for exploiting available orderings. Later approaches increased the set of optimized operators, and included a rule based...

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Recommended Reading

  1. 1.
    Chaudhuri S. An overview of query optimization in relational systems. In Proc. 17th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 1998, pp. 34–43.Google Scholar
  2. 2.
    Garcia-Molina H., Ullman J.D., and Widom J. Database system implementation. Prentice-Hall, 2000.Google Scholar
  3. 3.
    Graefe G. The cascades framework for query optimization. Q. Bull. IEEE TC on Data Engineering, 18(3):19–29, 1995.Google Scholar
  4. 4.
    Graefe G. and McKenna W.J. The volcano optimizer generator: Extensibility and efficient search. In Proc. 9th Int. Conf. on Data Engineering, 1993, pp. 209–218.Google Scholar
  5. 5.
    Haas L.M., Freytag J.C., Lohman G.M., and Pirahesh H. Extensible query processing in starburst. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1989, pp. 377–388.Google Scholar
  6. 6.
    Moerkotte G. Building query compilers, available at http://db.informatik.uni-mannheim.de/moerkotte.html.en, 2006.Google Scholar
  7. 7.
    Muralikrishna M. Improved unnesting algorithms for join aggregate SQL Queries. In Proc. 18th Int. Conf. on Very Large Data Bases, 1992, pp. 91–102.Google Scholar
  8. 8.
    Rao J., Lindsay B.G., Lohman G.M., Pirahesh H., and Simmen D.E. Using EELS, a practical approach to outerjoin and antijoin reordering. In Proc. 17th Int. Conf. on Data Engineering, 2001, pp. 585–594.Google Scholar
  9. 9.
    Selinger P.G., Astrahan M.M., Chamberlin D.D., Lorie R.A., and Price T.G. Access path selection in a relational database management System. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1979, pp. 23–34.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Thomas Neumann
    • 1
  1. 1.Max-Planck Institute for InformaticsSaarbrückenGermany