{"id":"https://openalex.org/W3083806692","doi":"https://doi.org/10.1145/1114244.1114251","title":"Synopses for query optimization","display_name":"Synopses for query optimization","publication_year":2005,"publication_date":"2005-12-01","ids":{"openalex":"https://openalex.org/W3083806692","doi":"https://doi.org/10.1145/1114244.1114251","mag":"3083806692"},"language":"en","primary_location":{"id":"doi:10.1145/1114244.1114251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1114244.1114251","pdf_url":null,"source":{"id":"https://openalex.org/S90119964","display_name":"ACM Transactions on Database Systems","issn_l":"0362-5915","issn":["0362-5915","1557-4644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Database Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103280746","display_name":"Raghav Kaushik","orcid":"https://orcid.org/0000-0003-1457-1384"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raghav Kaushik","raw_affiliation_strings":["Microsoft Research, Redmond, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017678555","display_name":"Jeffrey F. Naughton","orcid":"https://orcid.org/0000-0002-3710-8096"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey F. Naughton","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, WI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, WI","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051301731","display_name":"Raghu Ramakrishnan","orcid":"https://orcid.org/0009-0007-5086-7664"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raghu Ramakrishnan","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, WI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, WI","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012670075","display_name":"Venkatesan Chakravarthy","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Venkatesan T. Chakravarthy","raw_affiliation_strings":["IBM India Research Lab, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM India Research Lab, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2703,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.70759751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"30","issue":"4","first_page":"1102","last_page":"1127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/joins","display_name":"Joins","score":0.9022568464279175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.890800952911377},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.701386570930481},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6065576076507568},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5430755615234375},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5322693586349487},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.5307488441467285},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4438695013523102},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.425296813249588},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.41396039724349976},{"id":"https://openalex.org/keywords/materialized-view","display_name":"Materialized view","score":0.41157758235931396},{"id":"https://openalex.org/keywords/view","display_name":"View","score":0.39317888021469116},{"id":"https://openalex.org/keywords/database-design","display_name":"Database design","score":0.17081493139266968},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08968585729598999}],"concepts":[{"id":"https://openalex.org/C2778692605","wikidata":"https://www.wikidata.org/wiki/Q4041866","display_name":"Joins","level":2,"score":0.9022568464279175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.890800952911377},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.701386570930481},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6065576076507568},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5430755615234375},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5322693586349487},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.5307488441467285},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4438695013523102},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.425296813249588},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.41396039724349976},{"id":"https://openalex.org/C98199447","wikidata":"https://www.wikidata.org/wiki/Q2445044","display_name":"Materialized view","level":4,"score":0.41157758235931396},{"id":"https://openalex.org/C54239708","wikidata":"https://www.wikidata.org/wiki/Q1329910","display_name":"View","level":3,"score":0.39317888021469116},{"id":"https://openalex.org/C148840519","wikidata":"https://www.wikidata.org/wiki/Q1049878","display_name":"Database design","level":2,"score":0.17081493139266968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08968585729598999},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1114244.1114251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1114244.1114251","pdf_url":null,"source":{"id":"https://openalex.org/S90119964","display_name":"ACM Transactions on Database Systems","issn_l":"0362-5915","issn":["0362-5915","1557-4644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Database Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W605043455","https://openalex.org/W1489843519","https://openalex.org/W1566965859","https://openalex.org/W1968829657","https://openalex.org/W1977570286","https://openalex.org/W1987175217","https://openalex.org/W1991271936","https://openalex.org/W2002501531","https://openalex.org/W2005188603","https://openalex.org/W2007069074","https://openalex.org/W2008931591","https://openalex.org/W2010890196","https://openalex.org/W2013092187","https://openalex.org/W2018666252","https://openalex.org/W2026896584","https://openalex.org/W2060091058","https://openalex.org/W2064379477","https://openalex.org/W2066623874","https://openalex.org/W2073476719","https://openalex.org/W2084812512","https://openalex.org/W2118229812","https://openalex.org/W2120108467","https://openalex.org/W2148706674","https://openalex.org/W2153329411","https://openalex.org/W2154198326","https://openalex.org/W2171903035","https://openalex.org/W4231287357","https://openalex.org/W4234667859","https://openalex.org/W4236656499","https://openalex.org/W4237172715","https://openalex.org/W4241185933","https://openalex.org/W6635154084","https://openalex.org/W7073961880"],"related_works":["https://openalex.org/W2378924333","https://openalex.org/W2919686661","https://openalex.org/W1496981381","https://openalex.org/W4372184962","https://openalex.org/W2074877482","https://openalex.org/W2362446711","https://openalex.org/W3156363426","https://openalex.org/W175663584","https://openalex.org/W2942097156","https://openalex.org/W1564408968"],"abstract_inverted_index":{"Database":[0],"systems":[1],"use":[2],"precomputed":[3,172,212,245],"synopses":[4,105],"of":[5,11,19,72,85,103,121,150,168,174,244,256,264],"data":[6,130],"to":[7,39,133,193,206,219],"estimate":[8],"the":[9,31,83,100,166,175,201,221,242,250,254,262,267],"cost":[10],"alternative":[12,20],"plans":[13],"during":[14],"query":[15,107,268],"optimization.":[16],"A":[17],"number":[18,84,263],"synopsis":[21],"structures":[22],"have":[23,37,52],"been":[24,54],"proposed,":[25],"but":[26],"histograms":[27,36,63,122,260],"are":[28,64,181,192],"by":[29],"far":[30],"most":[32],"commonly":[33],"used.":[34],"While":[35],"proved":[38],"be":[40,134,194,215],"very":[41],"effective":[42,217],"in":[43,87,119,136,253,266],"(cost":[44],"estimation":[45],"for)":[46],"single-table":[47,124],"selections,":[48,125],"queries":[49,152,157,226],"with":[50,82,227],"joins":[51,86,154,265],"long":[53],"seen":[55],"as":[56,196,261],"a":[57,60,69,88,110,147,170],"challenge;":[58],"under":[59],"model":[61],"where":[62],"maintained":[65],"for":[66,106,123,142,146,225],"individual":[67],"tables,":[68],"celebrated":[70],"result":[71,234],"Ioannidis":[73],"and":[74,138,209,247],"Christodoulakis":[75],"[1991]":[76],"observes":[77],"that":[78,165,180,211,240],"errors":[79],"propagate":[80],"exponentially":[81],"query.In":[89],"this":[90,233],"article,":[91],"we":[92,98,116,163],"make":[93],"two":[94],"main":[95],"contributions.":[96],"First,":[97],"study":[99,239],"space":[101],"complexity":[102],"using":[104],"optimization":[108],"from":[109],"novel":[111],"information-theoretic":[112],"perspective.":[113],"In":[114],"particular,":[115],"offer":[117],"evidence":[118],"support":[120,232],"including":[126],"an":[127,186,216,237],"analysis":[128],"over":[129],"distributions":[131],"known":[132],"common":[135,151],"practice,":[137],"illustrate":[139],"their":[140],"limitations":[141],"join":[143],"queries.":[144],"Second,":[145],"broad":[148],"class":[149],"involving":[153,158],"(specifically,":[155],"all":[156],"only":[159],"key-foreign":[160,228],"key":[161,229],"joins)":[162],"show":[164],"strategy":[167],"storing":[169],"small":[171],"sample":[173],"database":[176,197],"yields":[177],"probabilistic":[178],"guarantees":[179],"almost":[182],"space-optimal,":[183],"which":[184],"is":[185,200],"important":[187],"property":[188],"if":[189],"these":[190],"samples":[191,213,257],"used":[195],"statistics.":[198],"This":[199],"first":[202],"such":[203],"optimality":[204],"result,":[205],"our":[207],"knowledge,":[208],"suggests":[210],"might":[214],"way":[218],"circumvent":[220],"error":[222],"propagation":[223],"problem":[224],"joins.":[230],"We":[231],"empirically":[235],"through":[236],"experimental":[238],"demonstrates":[241],"effectiveness":[243,255],"samples,":[246],"also":[248],"shows":[249],"increasing":[251],"difference":[252],"versus":[258],"multidimensional":[259],"grows.":[269]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
