Rule Profiling for Query Optimizers and their Implications

Many modern optimizers use a transformation rule

based framework. While there has been a lot of work on

identifying new transformation rules, there has been little work

focused on empirically evaluating the effectiveness of these

transformation rules. In this paper we present the results of an

empirical study of “profiling” transformation rules in Microsoft

SQL Server using a diverse set of real world and benchmark

query workloads. We also discuss the implications of these

results for designing and testing query optimizers.

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In  International Conference of Data Engineering (ICDE)

Publisher  IEEE
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