{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T22:37:00Z","timestamp":1778279820777,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,10]]},"DOI":"10.1145\/3514221.3517885","type":"proceedings-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T02:33:49Z","timestamp":1655001229000},"page":"931-944","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":72,"title":["Balsa: Learning a Query Optimizer Without Expert Demonstrations"],"prefix":"10.1145","author":[{"given":"Zongheng","family":"Yang","sequence":"first","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA, USA"}]},{"given":"Wei-Lin","family":"Chiang","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA, USA"}]},{"given":"Sifei","family":"Luan","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA, USA"}]},{"given":"Gautam","family":"Mittal","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA, USA"}]},{"given":"Michael","family":"Luo","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA, USA"}]},{"given":"Ion","family":"Stoica","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2022,6,11]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3322967"},{"key":"e_1_3_2_1_2_1","unstructured":"Ilge Akkaya Marcin Andrychowicz Maciek Chociej Mateusz Litwin Bob McGrew Arthur Petron Alex Paino Matthias Plappert Glenn Powell Raphael Ribas et al. 2019. Solving rubik's cube with a robot hand. arXiv preprint arXiv:1910.07113 (2019)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295288"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-58907-4_6"},{"key":"e_1_3_2_1_5_1","volume-title":"Commit history of the PostgreSQL optimizer. https:\/\/github.com\/postgres\/postgres\/commits\/master\/src\/backend\/optimizer\/. [Online","author":"SQL","year":"2021","unstructured":"PostgreSQL developers. [n.,d.]. Commit history of the PostgreSQL optimizer. https:\/\/github.com\/postgres\/postgres\/commits\/master\/src\/backend\/optimizer\/. [Online; accessed February, 2021]."},{"key":"e_1_3_2_1_6_1","unstructured":"NTT OSS Center DBMS Development and Support Team. 2020. pg_hint_plan. https:\/\/github.com\/ossc-db\/pg_hint_plan."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.14778\/3329772.3329780"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3389704"},{"key":"e_1_3_2_1_9_1","volume-title":"2020 b. DeepDB: Learn from Data, not from Queries! Proceedings of the VLDB Endowment","author":"Hilprecht Benjamin","year":"2020","unstructured":"Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, and Carsten Binnig. 2020 b. DeepDB: Learn from Data, not from Queries! Proceedings of the VLDB Endowment, Vol. 13, 7 (2020), 992--1005."},{"key":"e_1_3_2_1_10_1","volume-title":"How We Built a Cost-Based SQL Optimizer. https:\/\/www.cockroachlabs.com\/blog\/building-cost-based-sql-optimizer\/. [Online","author":"Kimball Andy","year":"2020","unstructured":"Andy Kimball. 2018. How We Built a Cost-Based SQL Optimizer. https:\/\/www.cockroachlabs.com\/blog\/building-cost-based-sql-optimizer\/. [Online; accessed December, 2020]."},{"key":"e_1_3_2_1_11_1","volume-title":"Learned Cardinalities: Estimating Correlated Joins with Deep Learning. In CIDR","author":"Kipf Andreas","year":"2019","unstructured":"Andreas Kipf, Thomas Kipf, Bernhard Radke, Viktor Leis, Peter A. Boncz, and Alfons Kemper. 2019. Learned Cardinalities: Estimating Correlated Joins with Deep Learning. In CIDR 2019, 9th Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 13--16, 2019, Online Proceedings."},{"key":"e_1_3_2_1_12_1","volume-title":"Learning to Optimize Join Queries With Deep Reinforcement Learning. CoRR","author":"Krishnan Sanjay","year":"2018","unstructured":"Sanjay Krishnan, Zongheng Yang, Ken Goldberg, Joseph M. Hellerstein, and Ion Stoica. 2018. Learning to Optimize Join Queries With Deep Reinforcement Learning. CoRR, Vol. abs\/1808.03196 (2018). arxiv: 1808.03196 http:\/\/arxiv.org\/abs\/1808.03196"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.14778\/2850583.2850594"},{"key":"e_1_3_2_1_14_1","volume-title":"Query optimization through the looking glass, and what we found running the join order benchmark. The VLDB Journal","author":"Leis Viktor","year":"2018","unstructured":"Viktor Leis, Bernhard Radke, Andrey Gubichev, Atanas Mirchev, Peter Boncz, Alfons Kemper, and Thomas Neumann. 2018. Query optimization through the looking glass, and what we found running the join order benchmark. The VLDB Journal (2018), 1--26."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3452838"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/3342263.3342644"},{"key":"e_1_3_2_1_17_1","volume-title":"13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18)","author":"Moritz Philipp","year":"2018","unstructured":"Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I Jordan, et al. 2018. Ray: A distributed framework for emerging AI applications. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18). 561--577."},{"key":"e_1_3_2_1_18_1","volume-title":"Materialize: Roadmap to Building a Streaming Database on Timely Dataflow. https:\/\/materialize.com\/blog-roadmap\/. [Online","author":"Narayan Arjun","year":"2020","unstructured":"Arjun Narayan. 2020. Materialize: Roadmap to Building a Streaming Database on Timely Dataflow. https:\/\/materialize.com\/blog-roadmap\/. [Online; accessed December, 2020]."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.14778\/3407790.3407807"},{"key":"e_1_3_2_1_20_1","volume-title":"Generative language modeling for automated theorem proving. arXiv preprint arXiv:2009.03393","author":"Polu Stanislas","year":"2020","unstructured":"Stanislas Polu and Ilya Sutskever. 2020. Generative language modeling for automated theorem proving. arXiv preprint arXiv:2009.03393 (2020)."},{"key":"e_1_3_2_1_21_1","first-page":"387","article-title":"DeWitt clauses: Can we protect purchasers without hurting","volume":"25","author":"Read Anthony G","year":"2006","unstructured":"Anthony G Read. 2006. DeWitt clauses: Can we protect purchasers without hurting Microsoft. Rev. Litig., Vol. 25 (2006), 387.","journal-title":"Microsoft. Rev. Litig."},{"key":"e_1_3_2_1_22_1","volume-title":"Nature","volume":"588","author":"Schrittwieser Julian","year":"2020","unstructured":"Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, et al. 2020. Mastering atari, go, chess and shogi by planning with a learned model. Nature, Vol. 588, 7839 (2020), 604--609."},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the 1979 ACM SIGMOD International Conference on Management of Data","author":"Selinger P. Griffiths","unstructured":"P. Griffiths Selinger, M. M. Astrahan, D. D. Chamberlin, R. A. Lorie, and T. G. Price. 1979. Access Path Selection in a Relational Database Management System. In Proceedings of the 1979 ACM SIGMOD International Conference on Management of Data (Boston, Massachusetts) (SIGMOD '79). Association for Computing Machinery, New York, NY, USA, 23--34."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.14778\/3436905.3436907"},{"key":"e_1_3_2_1_25_1","volume-title":"Mastering the game of Go with deep neural networks and tree search. Nature","author":"Silver David","year":"2016","unstructured":"David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis. 2016. Mastering the game of Go with deep neural networks and tree search. Nature, Vol. 529, 7587 (01 Jan 2016), 484--489."},{"key":"e_1_3_2_1_26_1","volume-title":"Nature","volume":"550","author":"Silver David","year":"2017","unstructured":"David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, and Demis Hassabis. 2017. Mastering the game of Go without human knowledge. Nature, Vol. 550, 7676 (01 Oct 2017), 354--359."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.14778\/3368289.3368296"},{"key":"e_1_3_2_1_28_1","volume-title":"Reinforcement learning: An introduction","author":"Sutton Richard S","unstructured":"Richard S Sutton and Andrew G Barto. 2018. Reinforcement learning: An introduction .MIT press."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202133"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3300088"},{"key":"e_1_3_2_1_31_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_1_32_1","volume-title":"Nature","volume":"575","author":"Vinyals Oriol","year":"2019","unstructured":"Oriol Vinyals, Igor Babuschkin, Wojciech M Czarnecki, Micha\u00ebl Mathieu, Andrew Dudzik, Junyoung Chung, David H Choi, Richard Powell, Timo Ewalds, Petko Georgiev, et al. 2019. Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature, Vol. 575, 7782 (2019), 350--354."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45033-5_5"},{"key":"e_1_3_2_1_34_1","volume-title":"Are We Ready For Learned Cardinality Estimation? arXiv preprint arXiv:2012.06743","author":"Wang Xiaoying","year":"2020","unstructured":"Xiaoying Wang, Changbo Qu, Weiyuan Wu, Jiannan Wang, and Qingqing Zhou. 2020. Are We Ready For Learned Cardinality Estimation? arXiv preprint arXiv:2012.06743 (2020)."},{"key":"e_1_3_2_1_35_1","unstructured":"Eric W Weisstein. [n. d.]. Mode. MathWorld--A Wolfram Web Resource. https:\/\/mathworld.wolfram.com\/Mode.html."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.14778\/3291264.3291267"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.14778\/3421424.3421432"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.14778\/3368289.3368294"}],"event":{"name":"SIGMOD\/PODS '22: International Conference on Management of Data","location":"Philadelphia PA USA","acronym":"SIGMOD\/PODS '22","sponsor":["SIGMOD ACM Special Interest Group on Management of Data"]},"container-title":["Proceedings of the 2022 International Conference on Management of Data"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517885","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514221.3517885","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:36Z","timestamp":1750188636000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517885"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,10]]},"references-count":38,"alternative-id":["10.1145\/3514221.3517885","10.1145\/3514221"],"URL":"https:\/\/doi.org\/10.1145\/3514221.3517885","relation":{},"subject":[],"published":{"date-parts":[[2022,6,10]]},"assertion":[{"value":"2022-06-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}