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.
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© 2009 Springer-Verlag Berlin Heidelberg
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Augustyn, D.R. (2009). Applying Advanced Methods of Query Selectivity Estimation in Oracle DBMS. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_61
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DOI: https://doi.org/10.1007/978-3-642-00563-3_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00562-6
Online ISBN: 978-3-642-00563-3
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