{"id":155391,"date":"2008-04-01T00:00:00","date_gmt":"2008-04-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/diagnosing-estimation-errors-in-page-counts-using-execution-feedback\/"},"modified":"2018-10-16T19:57:02","modified_gmt":"2018-10-17T02:57:02","slug":"diagnosing-estimation-errors-in-page-counts-using-execution-feedback","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/diagnosing-estimation-errors-in-page-counts-using-execution-feedback\/","title":{"rendered":"Diagnosing Estimation Errors in Page Counts using Execution Feedback"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Errors in estimating page counts can lead to poor choice of access methods and in turn to poor quality plans. Although there is past work in using execution feedback for accurate cardinality estimation, the problem of inaccurate estimation of page counts has not been addressed. In this paper, we present novel mechanisms for diagnosing errors in page count<br \/>\nby monitoring query execution at low overhead. Detection of inaccuracy in the optimizer estimates of page count can be leveraged by database administrators to improve plan quality. We have prototyped our techniques in the Microsoft SQL Server engine, and our experiments demonstrate the ability to estimate page counts accurately using execution feedback with low overhead. For queries on several real world databases, we observe significant improvement in plan quality when page counts obtained from execution feedback are used instead of the traditional optimizer estimations.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Errors in estimating page counts can lead to poor choice of access methods and in turn to poor quality plans. Although there is past work in using execution feedback for accurate cardinality estimation, the problem of inaccurate estimation of page counts has not been addressed. In this paper, we present novel mechanisms for diagnosing errors [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13555],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-155391","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-search-information-retrieval","msr-locale-en_us"],"msr_publishername":"IEEE Computer Society","msr_edition":"24th International Conference on Data 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