{"id":724819,"date":"2021-02-09T13:38:43","date_gmt":"2021-02-09T21:38:43","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=724819"},"modified":"2021-02-09T13:38:43","modified_gmt":"2021-02-09T21:38:43","slug":"split-query-processing-in-polybase","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/split-query-processing-in-polybase\/","title":{"rendered":"Split query processing in polybase"},"content":{"rendered":"
This paper presents Polybase, a feature of SQL Server PDW V2 that allows users to manage and query data stored in a Hadoop cluster using the standard SQL query language. Unlike other database systems that provide only a relational view over HDFS-resident data through the use of an external table mechanism, Polybase employs a split query processing paradigm in which SQL operators on HDFS-resident data are translated into MapReduce jobs by the PDW query optimizer and then executed on the Hadoop cluster. The paper describes the design and implementation of Polybase along with a thorough performance evaluation that explores the benefits of employing a split query processing paradigm for executing queries that involve both structured data in a relational DBMS and unstructured data in Hadoop. Our results demonstrate that while the use of a split-based query execution paradigm can improve the performance of some queries by as much as 10X, one must employ a cost-based query optimizer that considers a broad set of factors when deciding whether or not it is advantageous to push a SQL operator to Hadoop. These factors include the selectivity factor of the predicate, the relative sizes of the two clusters, and whether or not their nodes are co-located. In addition, differences in the semantics of the Java and SQL languages must be carefully considered in order to avoid altering the expected results of a query.<\/p>\n","protected":false},"excerpt":{"rendered":"
This paper presents Polybase, a feature of SQL Server PDW V2 that allows users to manage and query data stored in a Hadoop cluster using the standard SQL query language. Unlike other database systems that provide only a relational view over HDFS-resident data through the use of an external table mechanism, Polybase employs a split […]<\/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":[13547],"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":[246691,248884,252091,251551,252088,252079,249145,252076,252082,252085],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-724819","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us","msr-field-of-study-computer-science","msr-field-of-study-database","msr-field-of-study-language-integrated-query","msr-field-of-study-query-by-example","msr-field-of-study-query-expansion","msr-field-of-study-query-language","msr-field-of-study-query-optimization","msr-field-of-study-sargable","msr-field-of-study-spatial-query","msr-field-of-study-view"],"msr_publishername":"ACM","msr_edition":"","msr_affiliation":"","msr_published_date":"2013-6-21","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":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"doi","viewUrl":"false","id":"false","title":"10.1145\/2463676.2463709","label_id":"243106","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/dl.acm.org\/doi\/10.1145\/2463676.2463709","label_id":"243109","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/dblp.uni-trier.de\/db\/conf\/sigmod\/sigmod2013.html#DeWittHNSAAFG13","label_id":"243109","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/doi.acm.org\/10.1145\/2463676.2463709","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"David J. 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