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PAR\n            <jats:sup>2<\/jats:sup>\n            QO strategically obtains plans from a well-balanced set of probe locations informed by the workload, and caches them as plan-penalty profiles. At runtime, PAR\n            <jats:sup>2<\/jats:sup>\n            QO selects the plan with the lowest expected penalty, explicitly accounting for selectivity uncertainties. Extensive experiments show that PAR\n            <jats:sup>2<\/jats:sup>\n            QO delivers significant speedups over existing methods while ensuring robustness against performance degradation. Additionally, we introduce\n            <jats:bold>CARVER<\/jats:bold>\n            , a workload generator aimed at covering possible cardinalities of subqueries. Not only does CARVER provide a more comprehensive way to evaluate PQO methods, but when used for training learned methods, it can also enhance their generalizability and stability.\n          <\/jats:p>","DOI":"10.14778\/3749646.3749711","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T17:55:06Z","timestamp":1757008506000},"page":"4532-4545","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["PAR2QO: Parametric Penalty-Aware Robust Query Optimization"],"prefix":"10.14778","volume":"18","author":[{"given":"Haibo","family":"Xiu","sequence":"first","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianyu","family":"Yang","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pankaj K.","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Yang","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,9,4]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920983"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2012.57"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3639309"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066172"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066171"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2008.160"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807226"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/543613.543651"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/303976.303990"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.14778\/1454159.1454173"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/3484224.3484234"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1561\/1900000077"},{"key":"e_1_2_1_13_1","volume-title":"Proceedings of the 33rd International Conference on Very Large Data Bases","author":"Doraiswamy Harish","year":"2007","unstructured":"Harish Doraiswamy, Pooja N. 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