{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,5]],"date-time":"2024-10-05T00:10:08Z","timestamp":1728087008495},"reference-count":11,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:p>Manual analysis on plan regression is both labor-intensive and inefficient for a large query plan and numerous queries. In this paper, we demonstrate AutoDI, an automatic detection and inference tool that has been developed to investigate why a sub-optimal plan is obtained by analyzing two different plans of the same query. AutoDI consists of two main modules,<jats:italic>Difference Finder<\/jats:italic>and<jats:italic>Inference.<\/jats:italic>The former aims to find where the two plans are different, and the latter tries to obtain the reasons why the differences come out. In our demonstration, we use a real plan regression in TiDB to show how AutoDI works.<\/jats:p>","DOI":"10.14778\/3554821.3554860","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T22:28:39Z","timestamp":1664490519000},"page":"3626-3629","source":"Crossref","is-referenced-by-count":0,"title":["AutoDI"],"prefix":"10.14778","volume":"15","author":[{"given":"Hai","family":"Lan","sequence":"first","affiliation":[{"name":"RMIT University"}]},{"given":"Yuanjia","family":"Zhang","sequence":"additional","affiliation":[{"name":"PingCAP"}]},{"given":"Zhifeng","family":"Bao","sequence":"additional","affiliation":[{"name":"RMIT University"}]},{"given":"Yu","family":"Dong","sequence":"additional","affiliation":[{"name":"PingCAP"}]},{"given":"Dongxu","family":"Huang","sequence":"additional","affiliation":[{"name":"PingCAP"}]},{"given":"Liu","family":"Tang","sequence":"additional","affiliation":[{"name":"PingCAP"}]},{"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"PingCAP"}]}],"member":"320","published-online":{"date-parts":[[2022,9,29]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"June 2022. SQL Plan Management. https:\/\/www.oracle.com\/technetwork\/database\/bi-datawarehousing\/twp-sql-plan-mgmt-19c-5324207.pdf. June 2022. SQL Plan Management. https:\/\/www.oracle.com\/technetwork\/database\/bi-datawarehousing\/twp-sql-plan-mgmt-19c-5324207.pdf."},{"key":"e_1_2_1_2_1","unstructured":"June 2022. SQL Server Compare Showplan. https:\/\/docs.microsoft.com\/en-us\/sql\/relational-databases\/performance\/compare-execution-plans?view=sql-server-ver15. June 2022. SQL Server Compare Showplan. https:\/\/docs.microsoft.com\/en-us\/sql\/relational-databases\/performance\/compare-execution-plans?view=sql-server-ver15."},{"key":"e_1_2_1_3_1","unstructured":"June 2022. SQL Tuning Advisor. https:\/\/docs.oracle.com\/database\/121\/TGSQL\/tgsql_sqltune.htm. June 2022. SQL Tuning Advisor. https:\/\/docs.oracle.com\/database\/121\/TGSQL\/tgsql_sqltune.htm."},{"key":"e_1_2_1_4_1","unstructured":"June 2022. SQL Tuning Advisor. https:\/\/docs.microsoft.com\/en-us\/sql\/tools\/dta\/tutorial-database-engine-tuning-advisor?view=sql-server-ver15. June 2022. SQL Tuning Advisor. https:\/\/docs.microsoft.com\/en-us\/sql\/tools\/dta\/tutorial-database-engine-tuning-advisor?view=sql-server-ver15."},{"key":"e_1_2_1_5_1","volume-title":"Waas","author":"Gu Zhongxian","year":"2012","unstructured":"Zhongxian Gu , Mohamed A. Soliman , and Florian M . Waas . 2012 . Testing the accuracy of query optimizers. In DBTest . 11. Zhongxian Gu, Mohamed A. Soliman, and Florian M. Waas. 2012. Testing the accuracy of query optimizers. In DBTest. 11."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415535"},{"key":"e_1_2_1_7_1","first-page":"204","article-title":"How Good Are Query Optimizers, Really","volume":"9","author":"Leis Viktor","year":"2015","unstructured":"Viktor Leis , Andrey Gubichev , Atanas Mirchev , Peter A. Boncz , Alfons Kemper , and Thomas Neumann . 2015 . How Good Are Query Optimizers, Really ? VLDB 9 , 3 (2015), 204 -- 215 . Viktor Leis, Andrey Gubichev, Atanas Mirchev, Peter A. Boncz, Alfons Kemper, and Thomas Neumann. 2015. How Good Are Query Optimizers, Really? VLDB 9, 3 (2015), 204--215.","journal-title":"VLDB"},{"key":"e_1_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Zhan Li Olga Papaemmanouil and Mitch Cherniack. 2016. OptMark: A Toolkit for Benchmarking Query Optimizers. In CIKM. 2155--2160. Zhan Li Olga Papaemmanouil and Mitch Cherniack. 2016. OptMark: A Toolkit for Benchmarking Query Optimizers. In CIKM. 2155--2160.","DOI":"10.1145\/2983323.2983658"},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Matthew Perron Zeyuan Shang Tim Kraska and Michael Stonebraker. 2019. How I Learned to Stop Worrying and Love Re-optimization. In ICDE. 1758--1761. Matthew Perron Zeyuan Shang Tim Kraska and Michael Stonebraker. 2019. How I Learned to Stop Worrying and Love Re-optimization. In ICDE. 1758--1761.","DOI":"10.1109\/ICDE.2019.00191"},{"key":"e_1_2_1_10_1","unstructured":"Florian M. Waas Leo Giakoumakis and Shin Zhang. 2011. Plan space analysis: an early warning system to detect plan regressions in cost-based optimizers. In DBTest. 2. Florian M. Waas Leo Giakoumakis and Shin Zhang. 2011. Plan space analysis: an early warning system to detect plan regressions in cost-based optimizers. In DBTest. 2."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/1454159.1454175"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3554821.3554860","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,4]],"date-time":"2024-10-04T23:40:36Z","timestamp":1728085236000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3554821.3554860"}},"subtitle":["towards an automatic plan regression analysis"],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":11,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["10.14778\/3554821.3554860"],"URL":"https:\/\/doi.org\/10.14778\/3554821.3554860","relation":{},"ISSN":["2150-8097"],"issn-type":[{"type":"print","value":"2150-8097"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}