Abstract

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.