{"id":155421,"date":"2004-06-01T00:00:00","date_gmt":"2004-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/estimating-progress-of-execution-for-sql-queries\/"},"modified":"2018-10-16T19:57:42","modified_gmt":"2018-10-17T02:57:42","slug":"estimating-progress-of-execution-for-sql-queries","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/estimating-progress-of-execution-for-sql-queries\/","title":{"rendered":"Estimating Progress of Execution for SQL Queries"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Today\u2019s database systems provide little feedback to the user\/DBA on how much of a SQL query\u2019s execution has been completed. For long running queries, such feedback can be very useful, for example, to help decide whether the query should be terminated or allowed to run to completion. Although the above requirement is easy to express, developing a robust indicator of progress for query execution is challenging. In this paper, we study the above problem and present techniques that can form the basis for effective progress estimation. The results of experimentally validating our techniques in Microsoft SQL Server are promising.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Today\u2019s database systems provide little feedback to the user\/DBA on how much of a SQL query\u2019s execution has been completed. For long running queries, such feedback can be very useful, for example, to help decide whether the query should be terminated or allowed to run to completion. Although the above requirement is easy to express, [&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-155421","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-search-information-retrieval","msr-locale-en_us"],"msr_publishername":"Association for Computing Machinery, Inc.","msr_edition":"SIGMOD","msr_affiliation":"","msr_published_date":"2004-06-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"209904","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"progress.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/progress-1.pdf","id":209904,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":209904,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/progress-1.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"surajitc","user_id":33764,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=surajitc"},{"type":"user_nicename","value":"viveknar","user_id":34602,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=viveknar"},{"type":"user_nicename","value":"ravirama","user_id":33354,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=ravirama"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[957177],"msr_project":[169456],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":169456,"post_title":"AutoAdmin","post_name":"autoadmin","post_type":"msr-project","post_date":"2001-11-02 14:41:11","post_modified":"2019-02-05 12:04:17","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/autoadmin\/","post_excerpt":"Database management systems provide functionality that is central to developing business applications. Therefore, database management systems are increasingly being used as an important component in applications. Yet, the problem of tuning database management systems for achieving required performance is significant, and results in high total cost of ownership (TCO). The goal of our research in the AutoAdmin project is to make database systems self-tuning and self-administering. 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