{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T20:43:22Z","timestamp":1765485802882},"reference-count":16,"publisher":"Association for Computing Machinery (ACM)","issue":"1-2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2010,9]]},"abstract":"<jats:p>\n            We describe an automatic database design tool that exploits correlations between attributes when recommending materialized views (MVs) and indexes. Although there is a substantial body of related work exploring how to select an appropriate set of MVs and indexes for a given workload, none of this work has explored the effect of correlated attributes (e.g., attributes encoding related geographic information) on designs. Our tool identifies a set of MVs and secondary indexes such that correlations between the clustered attributes of the MVs and the secondary indexes are enhanced, which can dramatically improve query performance. It uses a form of\n            <jats:italic>Integer Linear Programming<\/jats:italic>\n            (ILP) called\n            <jats:italic>ILP Feedback<\/jats:italic>\n            to pick the best set of MVs and indexes for given database size constraints. We compare our tool with a state-of-the-art commercial database designer on two workloads, APB-1 and SSB (Star Schema Benchmark---similar to TPC-H). Our results show that a correlation-aware database designer can improve query performance up to 6 times within the same space budget when compared to a commercial database designer.\n          <\/jats:p>","DOI":"10.14778\/1920841.1920979","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"1103-1113","source":"Crossref","is-referenced-by-count":30,"title":["CORADD"],"prefix":"10.14778","volume":"3","author":[{"given":"Hideaki","family":"Kimura","sequence":"first","affiliation":[{"name":"Brown University"}]},{"given":"George","family":"Huo","sequence":"additional","affiliation":[{"name":"Google, Inc."}]},{"given":"Alexander","family":"Rasin","sequence":"additional","affiliation":[{"name":"Brown University"}]},{"given":"Samuel","family":"Madden","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}]},{"given":"Stanley B.","family":"Zdonik","sequence":"additional","affiliation":[{"name":"Brown University"}]}],"member":"320","published-online":{"date-parts":[[2010,9]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proc. of VLDB","author":"Agrawal S.","year":"2000","unstructured":"S. Agrawal , S. Chaudhuri , and V. Narasayya . Automated selection of materialized views and indexes in SQL databases . In Proc. of VLDB 2000 , Cairo, Egypt. S. Agrawal, S. Chaudhuri, and V. Narasayya. Automated selection of materialized views and indexes in SQL databases. In Proc. of VLDB 2000, Cairo, Egypt."},{"key":"e_1_2_1_2_1","volume-title":"Proc. of SODA","author":"Arthur D.","year":"2007","unstructured":"D. Arthur : The advantages of careful seeding . In Proc. of SODA 2007 , New Orleans, USA. D. Arthur et al. k-means++: The advantages of careful seeding. In Proc. of SODA 2007, New Orleans, USA."},{"key":"e_1_2_1_3_1","volume-title":"Proc. of VLDB","author":"Brown P.","year":"2003","unstructured":"P. Brown and P. Haas . BHUNT: Automatic discovery of fuzzy algebraic constraints in relational data . In Proc. of VLDB 2003 , Berlin, Germany. P. Brown and P. Haas. BHUNT: Automatic discovery of fuzzy algebraic constraints in relational data. 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Distinct sampling for highly-accurate answers to distinct values queries and event reports. In Proc. of VLDB 2001, Roma, Italy."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007568.1007641"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5555\/1287369.1287432"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687765"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1982.1056489"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1050.0234"},{"key":"e_1_2_1_14_1","volume-title":"APB-1 OLAP Benchmark Release II","author":"OLAP-Council","year":"1998","unstructured":"OLAP-Council . APB-1 OLAP Benchmark Release II , 1998 . OLAP-Council. APB-1 OLAP Benchmark Release II, 1998."},{"key":"e_1_2_1_15_1","volume-title":"Department of Computer Science","author":"P.","year":"2007","unstructured":"P. O'Neil et al. The star schema benchmark (SSB). Technical report , Department of Computer Science , University of Massachusetts at Boston , 2007 . P. O'Neil et al. The star schema benchmark (SSB). Technical report, Department of Computer Science, University of Massachusetts at Boston, 2007."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDEW.2007.4401027"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/1920841.1920979","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T11:42:31Z","timestamp":1672227751000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/1920841.1920979"}},"subtitle":["correlation aware database designer for materialized views and indexes"],"short-title":[],"issued":{"date-parts":[[2010,9]]},"references-count":16,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2010,9]]}},"alternative-id":["10.14778\/1920841.1920979"],"URL":"https:\/\/doi.org\/10.14778\/1920841.1920979","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2010,9]]}}}