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Applying Advanced Methods of Query Selectivity Estimation in Oracle DBMS

  • Dariusz R. Augustyn
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 59)

Abstract

The paper shows the solution of the query selectivity estimation problem for certain types of database queries with a selection condition based on several table attributes. The selectivity parameter allows for estimating a size of data satisfying a query condition. An estimator of a multidimensional probability density function is required for an accurate selectivity calculation for conditions involving many attributes and correlated attribute values. Using multidimensional histogram as a nonparametric density function estimator is mostly too much storage-consuming. The implementation of the known unconventional storage-efficient approach based on Discrete Cosine Transform spectrum of a multidimensional histogram is presented. This solution extends functionality of the Oracle DBMS cost-based query optimizer. The method of experimental obtaining error-optimal parameters values of spectrum storage for typical attributes value distributions is considered.

Keywords

selectivity query estimation multidimensional probability density function Discrete Cosine Transform database query optimizer extension Oracle Data Catridge Interface Statistics 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Dariusz R. Augustyn
    • 1
  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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