{"id":155419,"date":"2005-06-01T00:00:00","date_gmt":"2005-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/efficient-computation-of-multiple-group-by-queries\/"},"modified":"2018-10-16T19:57:37","modified_gmt":"2018-10-17T02:57:37","slug":"efficient-computation-of-multiple-group-by-queries","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/efficient-computation-of-multiple-group-by-queries\/","title":{"rendered":"Efficient Computation of Multiple Group-By Queries"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Data analysts need to understand the quality of data in the warehouse. This is often done by issuing many Group By queries on the sets of columns of interest. Since the volume of data in these warehouses can be large, and tables in a data warehouse often contain many columns, this analysis typically requires executing a large number of Group By queries, which can be expensive. We show that the performance of today\u2019s database systems for such data analysis is inadequate. We also show that the problem is computationally hard, and develop efficient techniques for solving it. We demonstrate significant speedup over existing approaches on today\u2019s commercial database systems.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data analysts need to understand the quality of data in the warehouse. This is often done by issuing many Group By queries on the sets of columns of interest. Since the volume of data in these warehouses can be large, and tables in a data warehouse often contain many columns, this analysis typically requires executing [&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-155419","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":"2005-06-01","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":"209525","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"GrpSets.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/GrpSets.pdf","id":209525,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":209525,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/GrpSets.pdf"}],"msr-author-ordering":[{"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":"zmchen","user_id":35150,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=zmchen"}],"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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