{"id":"https://openalex.org/W3188064594","doi":"https://doi.org/10.14778/3476249.3476298","title":"Phoebe","display_name":"Phoebe","publication_year":2021,"publication_date":"2021-07-01","ids":{"openalex":"https://openalex.org/W3188064594","doi":"https://doi.org/10.14778/3476249.3476298","mag":"3188064594"},"language":"en","primary_location":{"id":"doi:10.14778/3476249.3476298","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3476249.3476298","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2110.02313","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yiwen Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yiwen Zhu","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Matteo Interlandi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Matteo Interlandi","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Abhishek Roy","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Abhishek Roy","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Krishnadhan Das","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Krishnadhan Das","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hiren Patel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hiren Patel","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Malay Bag","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Malay Bag","raw_affiliation_strings":["Facebook"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hitesh Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hitesh Sharma","raw_affiliation_strings":["Google"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":null,"display_name":"Alekh Jindal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alekh Jindal","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7002,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87651326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"14","issue":"11","first_page":"2505","last_page":"2518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9819999933242798,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9804999828338623,"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/scalability","display_name":"Scalability","score":0.6714000105857849},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5450999736785889},{"id":"https://openalex.org/keywords/integer-programming","display_name":"Integer programming","score":0.5310999751091003},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.398499995470047},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.39579999446868896},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.38269999623298645},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.3813999891281128},{"id":"https://openalex.org/keywords/programming-paradigm","display_name":"Programming paradigm","score":0.37459999322891235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7174999713897705},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6714000105857849},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5450999736785889},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41449999809265137},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3813999891281128},{"id":"https://openalex.org/C34165917","wikidata":"https://www.wikidata.org/wiki/Q188267","display_name":"Programming paradigm","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C173404611","wikidata":"https://www.wikidata.org/wiki/Q528588","display_name":"Constraint programming","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3476249.3476298","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3476249.3476298","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"},{"id":"pmh:oai:arXiv.org:2110.02313","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.02313","pdf_url":"https://arxiv.org/pdf/2110.02313","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2110.02313","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.02313","pdf_url":"https://arxiv.org/pdf/2110.02313","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1970970009","https://openalex.org/W2009584448","https://openalex.org/W2026427349","https://openalex.org/W2068158423","https://openalex.org/W2081728040","https://openalex.org/W2090673017","https://openalex.org/W2105947650","https://openalex.org/W2109341366","https://openalex.org/W2110086534","https://openalex.org/W2119400430","https://openalex.org/W2132823934","https://openalex.org/W2141742398","https://openalex.org/W2151251992","https://openalex.org/W2151838019","https://openalex.org/W2152558130","https://openalex.org/W2194775991","https://openalex.org/W2336721351","https://openalex.org/W2521140588","https://openalex.org/W2528415359","https://openalex.org/W2612261081","https://openalex.org/W2799060872","https://openalex.org/W2799237774","https://openalex.org/W2892597164","https://openalex.org/W2911464154","https://openalex.org/W2911540814","https://openalex.org/W2911964244","https://openalex.org/W2922522433","https://openalex.org/W2955798121","https://openalex.org/W2963853546","https://openalex.org/W2969671095","https://openalex.org/W2970148517","https://openalex.org/W2985275869","https://openalex.org/W2997171439","https://openalex.org/W2998704965","https://openalex.org/W3013555795","https://openalex.org/W3024738030","https://openalex.org/W3031623163","https://openalex.org/W3032560301","https://openalex.org/W3097225903"],"related_works":[],"abstract_inverted_index":{"Easy-to-use":[0],"programming":[1,169],"interfaces":[2],"paired":[3],"with":[4,43,218],"cloud-scale":[5],"processing":[6],"engines":[7],"have":[8],"enabled":[9],"big":[10],"data":[11,46],"system":[12],"users":[13],"to":[14,97,110,114],"author":[15],"arbitrarily":[16],"complex":[17],"analytical":[18,32],"jobs":[19,33,213],"over":[20],"massive":[21],"volumes":[22],"of":[23,31,39,63,86,101,108,120,132,182,190,229,239],"data.":[24],"However,":[25],"as":[26,166],"the":[27,99,105,141,145,150,156,179,183,188,201,237,240],"complexity":[28,238],"and":[29,56,88,104,125,148,171,195,210],"scale":[30],"increase,":[34],"they":[35],"encounter":[36],"a":[37,84,133,173],"number":[38],"unforeseen":[40],"problems,":[41],"hotspots":[42,205],"large":[44],"intermediate":[45],"on":[47,204,216],"temporary":[48,202],"storage,":[49],"longer":[50],"job":[51,102],"recovery":[52],"time":[53,152],"after":[54],"failures,":[55],"worse":[57],"query":[58],"optimizer":[59],"estimates":[60],"being":[61],"examples":[62],"issues":[64],"that":[65,177,197,225],"we":[66,75,162,198],"are":[67],"facing":[68],"at":[69,92],"Microsoft.":[70],"To":[71],"address":[72],"these":[73,160],"issues,":[74],"propose":[76,172],"Phoebe,":[77],"an":[78,89,167],"efficient":[79],"learning-based":[80],"checkpoint":[81,164],"optimizer.":[82],"Given":[83],"set":[85,107],"constraints":[87],"objective":[90],"function":[91],"compile-time,":[93],"Phoebe":[94,118,135,191,222],"is":[95,231],"able":[96],"determine":[98],"decomposition":[100],"plans,":[103],"optimal":[106],"checkpoints":[109,230],"preserve":[111],"their":[112],"outputs":[113],"durable":[115],"global":[116],"storage.":[117],"consists":[119],"three":[121],"machine":[122],"learning":[123],"predictors":[124],"one":[126],"optimization":[127,165],"module.":[128],"For":[129],"each":[130],"stage":[131],"job,":[134],"makes":[136],"accurate":[137],"predictions":[138],"for:":[139],"(1)":[140],"execution":[142],"time,":[143],"(2)":[144],"output":[146],"size,":[147],"(3)":[149],"start/end":[151],"taking":[153],"into":[154],"account":[155],"inter-stage":[157],"dependencies.":[158],"Using":[159],"predictions,":[161],"formulate":[163],"integer":[168],"problem":[170],"scalable":[174],"heuristic":[175],"algorithm":[176],"meets":[178],"latency":[180],"requirement":[181],"production":[184,193],"environment.":[185],"We":[186],"demonstrate":[187],"effectiveness":[189],"in":[192],"workloads,":[194],"show":[196],"can":[199],"free":[200],"storage":[203],"by":[206],"more":[207],"than":[208],"70%":[209],"restart":[211],"failed":[212],"68%":[214],"faster":[215],"average":[217],"minimum":[219],"performance":[220],"impact.":[221],"also":[223],"illustrates":[224],"adding":[226],"multiple":[227],"sets":[228],"not":[232],"cost-efficient,":[233],"which":[234],"dramatically":[235],"reduces":[236],"optimization.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2021-08-16T00:00:00"}