{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T09:34:22Z","timestamp":1774949662691,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":45,"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"}],"funder":[{"name":"Mitacs","award":["Accelerate Grant"],"award-info":[{"award-number":["Accelerate Grant"]}]},{"name":"NSERC","award":["CRD grant"],"award-info":[{"award-number":["CRD grant"]}]},{"name":"NSERC","award":["discovery grant"],"award-info":[{"award-number":["discovery grant"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,10]]},"DOI":"10.1145\/3514221.3517900","type":"proceedings-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T02:33:49Z","timestamp":1655001229000},"page":"531-544","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["One Size Does Not Fit All: A Bandit-Based Sampler Combination Framework with Theoretical Guarantees"],"prefix":"10.1145","author":[{"given":"Jinglin","family":"Peng","sequence":"first","affiliation":[{"name":"Simon Fraser University, Burnaby, BC, Canada"}]},{"given":"Bolin","family":"Ding","sequence":"additional","affiliation":[{"name":"Alibaba Group, Seattle, WA, USA"}]},{"given":"Jiannan","family":"Wang","sequence":"additional","affiliation":[{"name":"Simon Fraser University, Burnaby, BC, Canada"}]},{"given":"Kai","family":"Zeng","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Jingren","family":"Zhou","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2022,6,11]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Loan dataset. https:\/\/www.kaggle.com\/skihikingkevin\/online-p2p-lending."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335450"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2593667"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2465351.2465355"},{"key":"e_1_3_2_1_5_1","volume-title":"Finite-time analysis of the multiarmed bandit problem. Machine Learning, 47(2--3):235--256","author":"Auer P.","year":"2002","unstructured":"P. Auer, N. Cesa-Bianchi, and P. Fischer. Finite-time analysis of the multiarmed bandit problem. Machine Learning, 47(2--3):235--256, 2002."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/872757.872822"},{"key":"e_1_3_2_1_7_1","volume-title":"Constrained optimization and Lagrange multiplier methods","author":"Bertsekas D. P.","year":"2014","unstructured":"D. P. Bertsekas. Constrained optimization and Lagrange multiplier methods. Academic press, 2014."},{"key":"e_1_3_2_1_8_1","volume-title":"Optimized stratified sampling for approximate query processing. ACM Transactions on Database Systems (TODS), 32(2):9","author":"Chaudhuri S.","year":"2007","unstructured":"S. Chaudhuri, G. Das, and V. Narasayya. Optimized stratified sampling for approximate query processing. ACM Transactions on Database Systems (TODS), 32(2):9, 2007."},{"key":"e_1_3_2_1_9_1","unstructured":"S. Chaudhuri and V. Narasayya. TPC-D data generation with skew. ftp.research. microsoft.com\/users\/viveknar\/tpcdskew."},{"key":"e_1_3_2_1_10_1","first-page":"2492","volume-title":"International Conference on Machine Learning","author":"Chen Y.","year":"2016","unstructured":"Y. Chen and Z. Ghahramani. Scalable discrete sampling as a multi-armed bandit problem. In International Conference on Machine Learning, pages 2492--2501. PMLR, 2016."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3035921"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807295"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2915249"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.14778\/3115404.3115418"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00051"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177731356"},{"key":"e_1_3_2_1_17_1","volume-title":"SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, May 13--15, 1997","author":"Hellerstein J. M.","year":"1997","unstructured":"J. M. Hellerstein, P. J. Haas, and H. J. Wang. Online aggregation. In J. Peckham, editor, SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, May 13--15, 1997, Tucson, Arizona, USA, pages 171--182. ACM Press, 1997."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.14778\/3372716.3372726"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3517900"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.14778\/3352063.3352130"},{"key":"e_1_3_2_1_21_1","first-page":"631","volume-title":"Proceedings of the 2016 International Conference on Management of Data, SIGMOD Conference 2016","author":"Kandula S.","year":"2016","unstructured":"S. Kandula, A. Shanbhag, A. Vitorovic, M. Olma, R. Grandl, S. Chaudhuri, and B. Ding. Quickr: Lazily approximating complex adhoc queries in bigdata clusters. In F. \u00d6zcan, G. Koutrika, and S. Madden, editors, Proceedings of the 2016 International Conference on Management of Data, SIGMOD Conference 2016, San Francisco, CA, USA, June 26 - July 01, 2016, pages 631--646. ACM, 2016."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00100"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/3229863.3240493"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247480.1247502"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41019-018-0074-4"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-49819-5_6"},{"key":"e_1_3_2_1_27_1","first-page":"1275","volume-title":"SIGMOD '21: International Conference on Management of Data","author":"Marcus R.","year":"2021","unstructured":"R. Marcus, P. Negi, H. Mao, N. Tatbul, M. Alizadeh, and T. Kraska. Bao: Making learned query optimization practical. In G. Li, Z. Li, S. Idreos, and D. Srivastava, editors, SIGMOD '21: International Conference on Management of Data, Virtual Event, China, June 20--25, 2021, pages 1275--1288. ACM, 2021."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3056098"},{"issue":"3","key":"e_1_3_2_1_29_1","first-page":"3","article-title":"A handbook for building an approximate query engine","volume":"38","author":"Mozafari B.","year":"2015","unstructured":"B. Mozafari and N. Niu. A handbook for building an approximate query engine. IEEE Data Eng. Bull., 38(3):3--29, 2015.","journal-title":"IEEE Data Eng. Bull."},{"key":"e_1_3_2_1_30_1","unstructured":"F. Olken. Random Sampling from Databases. PhD thesis University of California at Berkeley 1993."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00050"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402748"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2016.7498287"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196905"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3064013"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3183747"},{"key":"e_1_3_2_1_37_1","volume-title":"Guide to performance and tuning: Query performance and sampled selectivity","author":"Proteau C.","year":"2004","unstructured":"C. Proteau. Guide to performance and tuning: Query performance and sampled selectivity, 2004."},{"key":"e_1_3_2_1_38_1","volume-title":"Elements of survey sampling","author":"Singh R.","year":"2013","unstructured":"R. Singh and N. S. Mangat. Elements of survey sampling, volume 15. Springer Science & Business Media, 2013."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-007-0789-4"},{"key":"e_1_3_2_1_40_1","volume-title":"Introduction to multi-armed bandits. Foundations and Trends\u00ae in Machine Learning, 12(1--2):1--286","author":"A. Slivkins","year":"2019","unstructured":"A. Slivkins et al. Introduction to multi-armed bandits. Foundations and Trends\u00ae in Machine Learning, 12(1--2):1--286, 2019."},{"key":"e_1_3_2_1_41_1","first-page":"419","volume-title":"Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1995","author":"Veach E.","year":"1995","unstructured":"E. Veach and L. J. Guibas. Optimally combining sampling techniques for monte carlo rendering. In S. G. Mair and R. Cook, editors, Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1995, Los Angeles, CA, USA, August 6--11, 1995, pages 419--428. ACM, 1995."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824051"},{"key":"e_1_3_2_1_43_1","first-page":"1","volume-title":"CHI '21: CHI Conference on Human Factors in Computing Systems, Virtual Event \/ Yokohama, Japan, May 8--13, 2021","author":"Yan J. N.","year":"2021","unstructured":"J. N. Yan, Z. Gu, and J. M. Rzeszotarski. Tessera: Discretizing data analysis workflows on a task level. In Y. Kitamura, A. Quigley, K. Isbister, T. Igarashi, P. Bj\u00f8rn, and S. M. Drucker, editors, CHI '21: CHI Conference on Human Factors in Computing Systems, Virtual Event \/ Yokohama, Japan, May 8--13, 2021, pages 20:1--20:15. ACM, 2021."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2588579"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3183739"}],"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\/3514221.3517900","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514221.3517900","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:05Z","timestamp":1750183805000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517900"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,10]]},"references-count":45,"alternative-id":["10.1145\/3514221.3517900","10.1145\/3514221"],"URL":"https:\/\/doi.org\/10.1145\/3514221.3517900","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"}}]}}