• DocumentCode
    1961521
  • Title

    Automating statistics management for query optimizers

  • Author

    Chaudhuri, Surajit ; Narasayya, Vivek

  • Author_Institution
    Microsoft Corp., Redmond, WA, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    339
  • Lastpage
    348
  • Abstract
    Statistics play a key role in influencing the quality of plans chosen by a database query optimizer. We identify the statistics that are essential for an optimizer. We introduce novel techniques that help significantly reduce the set of statistics that need to be created without sacrificing the quality of query plans generated. We discuss how these techniques can be leveraged to automate statistics management in databases. We have implemented and experimentally evaluated our approach on Microsoft SQL Server 7.0
  • Keywords
    SQL; database theory; optimisation; query processing; relational databases; statistical databases; Microsoft SQL Server; database query optimizer; databases; experiment; query plan quality; statistics management; Costs; Database systems; Indexes; Quality management; Sensitivity analysis; Statistical analysis; Statistical distributions; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 2000. Proceedings. 16th International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1063-6382
  • Print_ISBN
    0-7695-0506-6
  • Type

    conf

  • DOI
    10.1109/ICDE.2000.839433
  • Filename
    839433