Progressive Parametric Query Optimization

ABSTRACT:

Commercial applications usually rely on pre-compiled parameterized procedures to interact with a database. Unfortunately, executing a procedure with a collection of parameters totally different from those used at compilation time could be arbitrarily sub-optimal. Parametric question optimization (PQO) attempts to resolve this drawback by exhaustively determining the optimal plans at every point of the parameter house at compile time. However, PQO is probably not value-effective if the query is executed occasionally or if it is executed with values solely inside a subset of the parameter space. In this paper we have a tendency to propose instead to progressively explore the parameter area and build a parametric set up throughout several executions of the identical query. We tend to introduce algorithms that, as parametric plans are populated, will be able to frequently bypass the optimizer however still execute optimal or near-optimal plans.

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