Handling Estimation Inaccuracy in Query Optimization

Chiraz Moumen (1) , Franck Morvan (1) , Abdelkader Hameurlain (1)

1 IRIT-PYRAMIDE - Optimisation Dynamique de Requêtes Réparties à grande échelle

OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 17164 The contribution was presented at APWeb 2016 : Abstract. Cost-based Optimizers choose query execution plans using a cost model. The latter relies on the accuracy of estimated statistics. Unfortunately, compile-time estimates often differ significantly from run-time values, leading to a suboptimal plan choices. In this paper, we propose a compile-time strategy, wherein the optimization process is fully aware of the estimation inaccuracy. This is ensured by the use of intervals of estimates rather than single-point estimates of error-prone parameters. These intervals serve to identify plans that provide stable performance in several run-time conditions, so called robust. Our strategy relies on a probabilistic approach to decide which plan to choose to start the execution. Our experiments show that our proposal allows a considerable improvement of the ability of a query optimizer to produce a robust execution plan in case of large estimation errors.

Mots clés: Robust plans; Query optimization; Estimation errors

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Chiraz Moumen, Franck Morvan, Abdelkader Hameurlain. Handling Estimation Inaccuracy in Query Optimization. 18th International Asia-Pacific Web Conference (APWeb 2016), Sep 2016, Suzhou, China. pp.355-367, ⟨10.1007/978-3-319-45817-5_28⟩. ⟨hal-01474881⟩