{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T19:38:09Z","timestamp":1725478689241},"reference-count":19,"publisher":"Association for Computing Machinery (ACM)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2011,12]]},"abstract":"<jats:p>\n            The need for accurate SQL progress estimation in the context of decision support administration has led to a number of techniques proposed for this task. Unfortunately, no single one of these progress estimators behaves robustly across the variety of SQL queries encountered in practice, meaning that each technique performs poorly for a significant fraction of queries. This paper proposes a novel\n            <jats:italic>estimator selection<\/jats:italic>\n            framework that uses a statistical model to characterize the sets of conditions under which certain estimators outperform others, leading to a significant increase in estimation robustness. The generality of this framework also enables us to add a number of novel \"special purpose\" estimators which increase accuracy further. Most importantly, the resulting model generalizes well to queries very different from the ones used to train it. We validate our findings using a large number of industrial real-life and benchmark workloads.\n          <\/jats:p>","DOI":"10.14778\/2095686.2095696","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"382-393","source":"Crossref","is-referenced-by-count":8,"title":["A statistical approach towards robust progress estimation"],"prefix":"10.14778","volume":"5","author":[{"given":"Arnd Christian","family":"K\u00f6nig","sequence":"first","affiliation":[{"name":"Microsoft Research, Redmond, WA"}]},{"given":"Bolin","family":"Ding","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL"}]},{"given":"Surajit","family":"Chaudhuri","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA"}]},{"given":"Vivek","family":"Narasayya","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA"}]}],"member":"320","published-online":{"date-parts":[[2011,12]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Program for TPC-H data generation with Skew. ftp:\/\/ftp.research.microsoft.com\/users\/viveknar\/TPCDSkew\/.  Program for TPC-H data generation with Skew. ftp:\/\/ftp.research.microsoft.com\/users\/viveknar\/TPCDSkew\/."},{"key":"e_1_2_1_2_1","unstructured":"TPC-H and TPC-DS Benchmarks. http:\/\/www.tpc.org.  TPC-H and TPC-DS Benchmarks. http:\/\/www.tpc.org."},{"key":"e_1_2_1_3_1","first-page":"1110","author":"Agrawal S.","year":"2005","unstructured":"S. Agrawal , S. Chaudhuri , L. Kollar , A. Marathe , V. Narasayya , and M. Syamala . Database Tuning Advisor for Microsoft SQL Server 2005 . In VLDB, pages 1110 -- 1121 , 2004. S. Agrawal, S. Chaudhuri, L. Kollar, A. Marathe, V. Narasayya, and M. Syamala. Database Tuning Advisor for Microsoft SQL Server 2005. In VLDB, pages 1110--1121, 2004.","journal-title":"Database Tuning Advisor for Microsoft SQL Server"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066223"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007568.1007659"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/645791.668131"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989359"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247480.1247598"},{"issue":"5","key":"e_1_2_1_10_1","doi-asserted-by":"crossref","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy Function Approximation: a Gradient Boosting Machine","volume":"29","author":"Friedman J.","year":"2001","unstructured":"J. Friedman . Greedy Function Approximation: a Gradient Boosting Machine . Annals of Statistics , 29 ( 5 ), 2001 . J. Friedman. Greedy Function Approximation: a Gradient Boosting Machine. Annals of Statistics, 29(5), 2001.","journal-title":"Annals of Statistics"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2009.130"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/11687238_54"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007568.1007658"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2005.79"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1508857.1508858"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247480.1247611"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807223"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/505282.505283"},{"key":"e_1_2_1_19_1","volume-title":"Microsoft Research","author":"Wu Q.","year":"2008","unstructured":"Q. Wu , C. J. Burges , K. M. Svore , and J. Gao . Ranking, Boosting, and Model Adaptation. Technical report , Microsoft Research , 2008 . Q. Wu, C. J. Burges, K. M. Svore, and J. Gao. Ranking, Boosting, and Model Adaptation. Technical report, Microsoft Research, 2008."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2095686.2095696","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:46:11Z","timestamp":1672220771000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2095686.2095696"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,12]]},"references-count":19,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2011,12]]}},"alternative-id":["10.14778\/2095686.2095696"],"URL":"https:\/\/doi.org\/10.14778\/2095686.2095696","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2011,12]]}}}