Abstract
The paper shows an adaptive approach to the query selectivity estimation problem for queries with a range selection condition based on continuous attributes. The selectivity factor estimates a size of data satisfying a query condition. This estimation is calculated at the initial stage of the query processing for choosing the optimal query execution plan. A non-parametric estimator of probability density of attribute values distribution is required for the selectivity calculation. Most of known approaches use equi-width or equi-height histograms as representations of attribute values distributions. The proposed approach uses a new type of histogram based on either an attribute values distribution or a distribution of range bounds of a query selection condition. Applying query-condition-aware histogram lets obtain more accurate selectivity values than using a standard histogram. The approach may be implemented as some extension of query optimizer of DBMS Oracle using ODCI Stats module.
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© 2011 Springer-Verlag Berlin Heidelberg
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Augustyn, D.R. (2011). Query-Condition-Aware Histograms in Selectivity Estimation Method. In: Czachórski, T., Kozielski, S., Stańczyk, U. (eds) Man-Machine Interactions 2. Advances in Intelligent and Soft Computing, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23169-8_47
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DOI: https://doi.org/10.1007/978-3-642-23169-8_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23168-1
Online ISBN: 978-3-642-23169-8
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