{"id":"https://openalex.org/W6929546086","doi":"https://doi.org/10.5075/epfl-thesis-7290","title":"Squall: Scalable Real-time Analytics using Efficient, Skew-resilient Join Operators","display_name":"Squall: Scalable Real-time Analytics using Efficient, Skew-resilient Join Operators","publication_year":2016,"publication_date":"2016-10-31","ids":{"openalex":"https://openalex.org/W6929546086","doi":"https://doi.org/10.5075/epfl-thesis-7290"},"language":"en","primary_location":{"id":"pmh:oai:infoscience.tind.io:222793","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/130875","pdf_url":"http://infoscience.epfl.ch/record/222793","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doctoral thesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://infoscience.epfl.ch/record/222793","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Vitorovi\u0107, Aleksandar","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vitorovi\u0107, Aleksandar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.12549999356269836,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.12549999356269836,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11332","display_name":"Genomics, phytochemicals, and oxidative stress","score":0.10750000178813934,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10650","display_name":"Food Drying and Modeling","score":0.06620000302791595,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/joins","display_name":"Joins","score":0.7271000146865845},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6621999740600586},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5414999723434448},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5248000025749207},{"id":"https://openalex.org/keywords/tuple","display_name":"Tuple","score":0.5108000040054321},{"id":"https://openalex.org/keywords/spark","display_name":"SPARK (programming language)","score":0.47189998626708984},{"id":"https://openalex.org/keywords/clickstream","display_name":"Clickstream","score":0.414000004529953},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.4074999988079071},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.3995000123977661}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8037999868392944},{"id":"https://openalex.org/C2778692605","wikidata":"https://www.wikidata.org/wiki/Q4041866","display_name":"Joins","level":2,"score":0.7271000146865845},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6621999740600586},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5248000025749207},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.5108000040054321},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.47189998626708984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4471000134944916},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44209998846054077},{"id":"https://openalex.org/C138744977","wikidata":"https://www.wikidata.org/wiki/Q5132438","display_name":"Clickstream","level":5,"score":0.414000004529953},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3788999915122986},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.35260000824928284},{"id":"https://openalex.org/C185410017","wikidata":"https://www.wikidata.org/wiki/Q7171778","display_name":"Petascale computing","level":3,"score":0.34439998865127563},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.32280001044273376},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31690001487731934},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C2767350","wikidata":"https://www.wikidata.org/wiki/Q6662173","display_name":"Business intelligence","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.2538999915122986}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:infoscience.tind.io:222793","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/130875","pdf_url":"http://infoscience.epfl.ch/record/222793","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doctoral thesis"},{"id":"pmh:oai:infoscience.epfl.ch:222793","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/222793","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.5075/epfl-thesis-7290","is_oa":true,"landing_page_url":"https://doi.org/10.5075/epfl-thesis-7290","pdf_url":null,"source":{"id":"https://openalex.org/S4306400488","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dissertation"}],"best_oa_location":{"id":"pmh:oai:infoscience.tind.io:222793","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/130875","pdf_url":"http://infoscience.epfl.ch/record/222793","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doctoral thesis"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.5406787395477295}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6929546086.pdf","grobid_xml":"https://content.openalex.org/works/W6929546086.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Squall":[0,107,214],"is":[1,32],"a":[2,12,51,130,181,231,241,247,254],"scalable":[3,125],"online":[4,86,126,170],"query":[5,120,127],"engine":[6],"that":[7,21,165,188,245],"runs":[8],"complex":[9],"analytics":[10],"in":[11,47,169,273,295],"cluster":[13],"using":[14,240],"skew-resilient,":[15],"adaptive":[16],"operators.":[17],"Online":[18],"processing":[19],"implies":[20],"results":[22],"are":[23,97,289],"incrementally":[24],"built":[25],"as":[26,38,70,72],"the":[27,55,61,76,136,143,207,216,238,270],"input":[28,196],"arrives,":[29],"and":[30,43,101,122,151,154,195,252,288],"it":[31],"ubiquitous":[33],"for":[34,124,175,180,198,209,233,256],"many":[35],"applications":[36],"such":[37],"algorithmic":[39],"trading,":[40],"clickstream":[41],"analysis":[42],"business":[44],"intelligence":[45],"(e.g.,":[46],"order":[48],"to":[49,99,103,134,145,152,269,278,285,291],"reach":[50],"potential":[52],"customer":[53],"during":[54],"active":[56],"session).":[57],"This":[58],"thesis":[59],"presents":[60],"overview":[62],"of":[63,79,116,138,184,192,219,264,297],"Squall,":[64],"including":[65],"some":[66,115],"novel":[67,149,226],"join":[68,193],"operators,":[69,121,150],"well":[71,178],"lessons":[73],"learned":[74],"over":[75],"five":[77],"years":[78],"working":[80],"on":[81,142,161],"this":[82],"system.":[83],"Existing":[84,172],"open-source":[85],"systems":[87],"(e.g.":[88,159],"Twitter":[89],"Storm,":[90],"Spark":[91],"Streaming)":[92],"provide":[93],"only":[94,168,179],"hash-joins,":[95],"which":[96,259],"limited":[98],"equi-joins":[100],"prone":[102],"skew.":[104],"In":[105,212],"contrast,":[106,213],"puts":[108],"together":[109],"state-of-the-art":[110],"skew-resilient":[111,227],"partitioning":[112,173,228,266],"schemes":[113,174,267,282],"(including":[114],"our":[117,281],"own),":[118],"local":[119],"techniques":[123],"processing.":[128],"Such":[129],"system":[131],"allows":[132],"us":[133],"leverage":[135],"effect":[137],"various":[139],"design":[140],"choices":[141],"performance,":[144],"seamlessly":[146],"build":[147],"efficient":[148,294],"discover":[153],"address":[155],"new":[156],"skew":[157,271],"types":[158],"dependence":[160],"tuple":[162],"arrival":[163],"order)":[164],"can":[166],"arise":[167],"systems.":[171],"joins":[176,236,258],"work":[177],"narrow":[182],"set":[183],"data":[185,203,221,239],"distribution":[186,204],"properties,":[187],"is,":[189],"specific":[190],"proportion":[191],"output":[194],"sizes":[197],"2-way":[199,234],"joins,":[200],"or":[201],"similar":[202],"among":[205],"all":[206],"relations":[208],"multi-way":[210,257],"joins.":[211],"covers":[215],"entire":[217],"spectrum":[218],"different":[220,265,274],"distributions":[222],"by":[223],"providing":[224],"two":[225],"schemes:":[229],"(a)":[230],"scheme":[232,255],"non-equi":[235],"partitions":[237],"multi-stage":[242],"load-balancing":[243],"algorithm":[244],"contains":[246],"join-specialized":[248],"computational":[249],"geometry":[250],"algorithm,":[251],"(b)":[253],"constructs":[260],"composite":[261],"partitioning,":[262],"consisting":[263],"according":[268],"degree":[272],"relation":[275],"attributes.":[276],"Compared":[277],"state-of-the":[279],"art,":[280],"achieve":[283],"up":[284,290],"15X":[286],"speedup":[287],"5X":[292],"more":[293],"terms":[296],"resource":[298],"consumption.":[299]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
