{"id":158906,"date":"2010-03-01T00:00:00","date_gmt":"2010-03-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/rule-profiling-for-query-optimizers-and-their-implications\/"},"modified":"2018-10-16T21:05:54","modified_gmt":"2018-10-17T04:05:54","slug":"rule-profiling-for-query-optimizers-and-their-implications","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/rule-profiling-for-query-optimizers-and-their-implications\/","title":{"rendered":"Rule Profiling for Query Optimizers and their Implications"},"content":{"rendered":"<div class=\"asset-content\">\n<p>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 \u201cprofiling\u201d 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.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>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 \u201cprofiling\u201d transformation rules in Microsoft SQL [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563,13560],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-158906","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-research-area-programming-languages-software-engineering","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"International Conference of Data Engineering 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