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AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions
Journal
Proceedings 2003 VLDB Conference: 29th International Conference on Very Large Databases (VLDB)
Date Issued
2003-01-01
Author(s)
Hulgeri, Arvind
Sudarshan, S.
Abstract
This chapter proposes a heuristic solution for the parametric query optimization (PQO) problem for the case when the cost functions may be nonlinear in the given parameters. This solution is minimally intrusive in the sense that an existing query optimizer can be used with minor modifications. The chapter implements the heuristic and the results of the tests on the TPCD benchmark indicate that the heuristic is very effective. The minimal intrusiveness, generality in terms of cost functions and number of parameters and good performance indicates that the solution is of significant practical importance. The cost of a query plan depends on many parameters, such as predicate selectivities and available memory, whose values may not be known at optimization time. PQO optimizes a query into a number of candidate plans, each optimal for some region of the parameter space.