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Data"],"published-print":{"date-parts":[[2024,3,12]]},"abstract":"<jats:p>Recent efforts in learned cardinality estimation (CE) have substantially improved estimation accuracy and query plans inside query optimizers. However, achieving decent efficiency, scalability, and the support of a wide range of queries at the same time, has remained questionable. Rather than falling back to traditional approaches to trade off one criterion with another, we present a new learned approach that achieves all these. Our method, called ASM, harmonizes autoregressive models for per-table statistics estimation, sampling for merging these statistics for join queries, and multi-dimensional statistics merging that extends the sampling for estimating thousands of sub-queries, without assuming independence between join keys. Extensive experiments show that ASM significantly improves query plans under a similar or smaller overhead than the previous learned methods and supports a wider range of queries.<\/jats:p>","DOI":"10.1145\/3639300","type":"journal-article","created":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T18:51:32Z","timestamp":1711479092000},"page":"1-27","source":"Crossref","is-referenced-by-count":19,"title":["ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0224-2570","authenticated-orcid":false,"given":"Kyoungmin","family":"Kim","sequence":"first","affiliation":[{"name":"Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3940-7311","authenticated-orcid":false,"given":"Sangoh","family":"Lee","sequence":"additional","affiliation":[{"name":"Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4439-6097","authenticated-orcid":false,"given":"Injung","family":"Kim","sequence":"additional","affiliation":[{"name":"Handong Global University, Pohang, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9206-9563","authenticated-orcid":false,"given":"Wook-Shin","family":"Han","sequence":"additional","affiliation":[{"name":"Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,3,26]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/564691.564722"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3319894"},{"key":"e_1_2_1_3_1","volume-title":"Radu Tudor Ionescu, and Mubarak Shah","author":"Croitoru Florinel-Alin","year":"2023","unstructured":"Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, and Mubarak Shah. 2023. 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