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Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons127842

Neumann,  Thomas
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Zitation

Moerkotte, G., Neumann, T., & Steidl, G. (2009). Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors. Proceedings of the VLDB Endowment, 2(1), 982-993. Retrieved from http://www.vldb.org/pvldb/2/vldb09-657.pdf.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-1939-5
Zusammenfassung
Query optimizers rely on accurate estimations of the sizes of intermediate results. Wrong size estimations can lead to overly expensive execution plans. We first define the \emph{q-error} to measure deviations of size estimates from actual sizes. The q-error enables the derivation of two important results: (1) We provide bounds such that if the q-error is smaller than this bound, the query optimizer constructs an optimal plan. (2) If the q-error is bounded by a number $q$, we show that the cost of the produced plan is at most a factor of $q^4$ worse than the optimal plan. Motivated by these findings, we next show how to find the best approximation under the q-error. These techniques can then be used to build synopsis for size estimates. Finally, we give some experimental results where we apply the developed techniques.