{"id":"https://openalex.org/W4312894391","doi":"https://doi.org/10.14778/3554821.3554860","title":"AutoDI","display_name":"AutoDI","publication_year":2022,"publication_date":"2022-08-01","ids":{"openalex":"https://openalex.org/W4312894391","doi":"https://doi.org/10.14778/3554821.3554860"},"language":"en","primary_location":{"id":"doi:10.14778/3554821.3554860","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3554821.3554860","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/A5100772752","display_name":"Hai Lan","orcid":"https://orcid.org/0009-0007-4433-9232"},"institutions":[{"id":"https://openalex.org/I4210095297","display_name":"MIT University","ror":"https://ror.org/00v140q16","country_code":"MK","type":"education","lineage":["https://openalex.org/I4210095297"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU","MK"],"is_corresponding":true,"raw_author_name":"Hai Lan","raw_affiliation_strings":["RMIT University"],"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074883621","display_name":"Yuanjia Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuanjia Zhang","raw_affiliation_strings":["PingCAP"],"affiliations":[{"raw_affiliation_string":"PingCAP","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080660416","display_name":"Zhifeng Bao","orcid":"https://orcid.org/0000-0003-2477-381X"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]},{"id":"https://openalex.org/I4210095297","display_name":"MIT University","ror":"https://ror.org/00v140q16","country_code":"MK","type":"education","lineage":["https://openalex.org/I4210095297"]}],"countries":["AU","MK"],"is_corresponding":false,"raw_author_name":"Zhifeng Bao","raw_affiliation_strings":["RMIT University"],"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101633405","display_name":"Yu Dong","orcid":"https://orcid.org/0000-0003-0170-0546"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Dong","raw_affiliation_strings":["PingCAP"],"affiliations":[{"raw_affiliation_string":"PingCAP","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085463032","display_name":"Dongxu Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongxu Huang","raw_affiliation_strings":["PingCAP"],"affiliations":[{"raw_affiliation_string":"PingCAP","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764956","display_name":"Liu Tang","orcid":"https://orcid.org/0000-0002-0008-8917"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu Tang","raw_affiliation_strings":["PingCAP"],"affiliations":[{"raw_affiliation_string":"PingCAP","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100409912","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0002-0075-7375"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["PingCAP"],"affiliations":[{"raw_affiliation_string":"PingCAP","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100772752"],"corresponding_institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17458067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"12","first_page":"3626","last_page":"3629"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994999766349792,"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/T10772","display_name":"Distributed systems and fault tolerance","score":0.9972000122070312,"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/inference","display_name":"Inference","score":0.7411273121833801},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.7267286777496338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7209689617156982},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5340918898582458},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4758555591106415},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4442160427570343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35661381483078003},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3131079375743866},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16223040223121643},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10449248552322388},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05742940306663513}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7411273121833801},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.7267286777496338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7209689617156982},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5340918898582458},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4758555591106415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4442160427570343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35661381483078003},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3131079375743866},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16223040223121643},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10449248552322388},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05742940306663513},{"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:10.14778/3554821.3554860","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3554821.3554860","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":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1968745093","https://openalex.org/W2396309311","https://openalex.org/W2922302645","https://openalex.org/W3085924233","https://openalex.org/W6712124477"],"related_works":["https://openalex.org/W2511279186","https://openalex.org/W2891342280","https://openalex.org/W3159789586","https://openalex.org/W3186839548","https://openalex.org/W4220799502","https://openalex.org/W4255280496","https://openalex.org/W3207148850","https://openalex.org/W4226135389","https://openalex.org/W4312198914","https://openalex.org/W4292148089"],"abstract_inverted_index":{"Manual":[0],"analysis":[1],"on":[2],"plan":[3,14,39,92],"regression":[4,93],"is":[5,40],"both":[6],"labor-intensive":[7],"and":[8,15,27,59,72],"inefficient":[9],"for":[10],"a":[11,37,90],"large":[12],"query":[13],"numerous":[16],"queries.":[17],"In":[18,85],"this":[19],"paper,":[20],"we":[21,88],"demonstrate":[22],"AutoDI,":[23],"an":[24],"automatic":[25],"detection":[26],"inference":[28],"tool":[29],"that":[30],"has":[31],"been":[32],"developed":[33],"to":[34,64,76,96],"investigate":[35],"why":[36,80],"sub-optimal":[38],"obtained":[41],"by":[42],"analyzing":[43],"two":[44,54,68],"different":[45],"plans":[46,69],"of":[47,53],"the":[48,67,73,78,81],"same":[49],"query.":[50],"AutoDI":[51,99],"consists":[52],"main":[55],"modules,":[56],"Difference":[57],"Finder":[58],"Inference.":[60],"The":[61],"former":[62],"aims":[63],"find":[65],"where":[66],"are":[70],"different,":[71],"latter":[74],"tries":[75],"obtain":[77],"reasons":[79],"differences":[82],"come":[83],"out.":[84],"our":[86],"demonstration,":[87],"use":[89],"real":[91],"in":[94],"TiDB":[95],"show":[97],"how":[98],"works.":[100]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-01-05T00:00:00"}