{"id":"https://openalex.org/W4317641620","doi":"https://doi.org/10.14778/3565838.3565846","title":"Cost-Based or Learning-Based?","display_name":"Cost-Based or Learning-Based?","publication_year":2022,"publication_date":"2022-09-01","ids":{"openalex":"https://openalex.org/W4317641620","doi":"https://doi.org/10.14778/3565838.3565846"},"language":"en","primary_location":{"id":"doi:10.14778/3565838.3565846","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3565838.3565846","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","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/A5101426810","display_name":"Xiang Yu","orcid":"https://orcid.org/0000-0001-9431-5131"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiang Yu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101797040","display_name":"Chengliang Chai","orcid":"https://orcid.org/0000-0001-8080-5594"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengliang Chai","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451576","display_name":"Guoliang Li","orcid":"https://orcid.org/0000-0002-1398-0621"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Li","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100659171","display_name":"Jiabin Liu","orcid":"https://orcid.org/0000-0001-6914-8941"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiabin Liu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101426810"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":8.2147,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.98463337,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"15","issue":"13","first_page":"3924","last_page":"3936"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9966999888420105,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9966999888420105,"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"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8596744537353516},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6031292676925659},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5534199476242065},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.5509369969367981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4872781038284302},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4700906276702881},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4112773537635803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8596744537353516},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6031292676925659},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5534199476242065},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.5509369969367981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4872781038284302},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4700906276702881},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4112773537635803},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3565838.3565846","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3565838.3565846","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","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":37,"referenced_works":["https://openalex.org/W1560021816","https://openalex.org/W2026966899","https://openalex.org/W2126316555","https://openalex.org/W2396309311","https://openalex.org/W2563724055","https://openalex.org/W2911464154","https://openalex.org/W2970148517","https://openalex.org/W2970851599","https://openalex.org/W2991530444","https://openalex.org/W2997325344","https://openalex.org/W2998249308","https://openalex.org/W2999324038","https://openalex.org/W3006978394","https://openalex.org/W3013555795","https://openalex.org/W3014596384","https://openalex.org/W3025775630","https://openalex.org/W3029535034","https://openalex.org/W3030387435","https://openalex.org/W3037852608","https://openalex.org/W3097225903","https://openalex.org/W3099273181","https://openalex.org/W3105457604","https://openalex.org/W3124277639","https://openalex.org/W3134774296","https://openalex.org/W3174465898","https://openalex.org/W3175777295","https://openalex.org/W3196849431","https://openalex.org/W3198024709","https://openalex.org/W3203329898","https://openalex.org/W4205381461","https://openalex.org/W4206064074","https://openalex.org/W4206830372","https://openalex.org/W4210494082","https://openalex.org/W4283367762","https://openalex.org/W4312929313","https://openalex.org/W4367046738","https://openalex.org/W6772169254"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2779562428","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W1987753576","https://openalex.org/W3170094116"],"abstract_inverted_index":{"Traditional":[0],"cost-based":[1,130],"optimizers":[2,27,43,89],"are":[3,100],"efficient":[4],"and":[5,69,90,126,149,167,204,211],"stable":[6],"to":[7,105,121,132,136,144,218],"generate":[8,19,106,122,137],"optimal":[9,158],"plans":[10,21,36,84,139,148],"for":[11,22,47,170],"simple":[12],"SQL":[13],"queries,":[14],"but":[15],"they":[16],"may":[17],"not":[18],"high-quality":[20,35,82,107],"complicated":[23],"queries.":[24],"Thus":[25],"learning-based":[26,42,119],"have":[28,51],"been":[29],"proposed":[30],"recently":[31],"that":[32,50,65,116,197],"can":[33],"learn":[34],"based":[37],"on":[38,193],"past":[39],"experiences.":[40],"However,":[41],"cannot":[44],"work":[45],"well":[46],"dynamic":[48],"workloads":[49],"different":[52,146],"distributions":[53],"with":[54],"training":[55],"examples.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"propose":[61,110,155],"a":[62,111,129],"hybrid":[63],"optimizer":[64],"adopts":[66],"the":[67,71,93,97,118,134,151,164,168,176,179,185,188,201,206,212],"advantages":[68],"avoids":[70],"shortcomings":[72],"of":[73,77,88,178],"these":[74],"two":[75,101],"types":[76],"optimizers,":[78],"which":[79,162],"first":[80],"generates":[81],"candidate":[83,113,147],"from":[85,96],"each":[86,171],"type":[87],"then":[91,127],"selects":[92],"best":[94,152],"plan":[95,159,186],"candidates.":[98,141],"There":[99],"challenges.":[102],"(1)":[103],"How":[104,143],"candidates?":[108],"We":[109,154,183],"hint-based":[112],"generation":[114],"method":[115,120,131,199],"leverages":[117],"highly":[123],"beneficial":[124],"hints":[125,135],"uses":[128],"supplement":[133],"complete":[138],"as":[140],"(2)":[142],"evaluate":[145],"select":[150,184],"one?":[153],"an":[156],"uncertainty-based":[157],"selection":[160],"model,":[161],"predicts":[163],"execution":[165,180],"time":[166,181],"uncertainty":[169,174,189],"plan.":[172],"The":[173],"reflects":[175],"confidence":[177],"prediction.":[182],"using":[187],"model.":[190],"Experiment":[191],"results":[192],"real":[194],"datasets":[195],"showed":[196],"our":[198],"outperformed":[200],"state-of-the-art":[202],"baselines,":[203],"reduced":[205],"total":[207],"latency":[208,214],"by":[209,215],"25%":[210],"tail":[213],"65%":[216],"compared":[217],"PostgreSQL.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":15}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}