{"id":"https://openalex.org/W4391054867","doi":"https://doi.org/10.14778/3632093.3632098","title":"OmniSketch: Efficient Multi-Dimensional High-Velocity Stream Analytics with Arbitrary Predicates","display_name":"OmniSketch: Efficient Multi-Dimensional High-Velocity Stream Analytics with Arbitrary Predicates","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4391054867","doi":"https://doi.org/10.14778/3632093.3632098"},"language":"en","primary_location":{"id":"doi:10.14778/3632093.3632098","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632098","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":true,"oa_status":"green","oa_url":"https://pure.tue.nl/ws/files/385817573/3632093.3632098.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092865516","display_name":"Wieger R. Punter","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Wieger R. Punter","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074684566","display_name":"Odysseas Papapetrou","orcid":"https://orcid.org/0000-0003-0045-1648"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Odysseas Papapetrou","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023079617","display_name":"Minos Garofalakis","orcid":"https://orcid.org/0000-0003-0285-3907"},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Minos Garofalakis","raw_affiliation_strings":["ATHENA Research Center & Technical Univ. of Crete"],"affiliations":[{"raw_affiliation_string":"ATHENA Research Center & Technical Univ. of Crete","institution_ids":["https://openalex.org/I55741626"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092865516"],"corresponding_institution_ids":["https://openalex.org/I83019370"],"apc_list":null,"apc_paid":null,"fwci":1.389,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83135058,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"319","last_page":"331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9991999864578247,"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":0.9991999864578247,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9987000226974487,"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/T11106","display_name":"Data Management and Algorithms","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8864442110061646},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7866938710212708},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.6868065595626831},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6511934995651245},{"id":"https://openalex.org/keywords/online-analytical-processing","display_name":"Online analytical processing","score":0.6294910311698914},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5254249572753906},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5089206695556641},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4932986795902252},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47829538583755493},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.42121466994285583},{"id":"https://openalex.org/keywords/stream-processing","display_name":"Stream processing","score":0.41250425577163696},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36675184965133667},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.3207363486289978},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24687930941581726},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.23221543431282043},{"id":"https://openalex.org/keywords/data-warehouse","display_name":"Data warehouse","score":0.2161928117275238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10980305075645447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8864442110061646},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7866938710212708},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6868065595626831},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6511934995651245},{"id":"https://openalex.org/C201932085","wikidata":"https://www.wikidata.org/wiki/Q642514","display_name":"Online analytical processing","level":3,"score":0.6294910311698914},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5254249572753906},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5089206695556641},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4932986795902252},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47829538583755493},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.42121466994285583},{"id":"https://openalex.org/C107027933","wikidata":"https://www.wikidata.org/wiki/Q2006448","display_name":"Stream processing","level":2,"score":0.41250425577163696},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36675184965133667},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3207363486289978},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24687930941581726},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.23221543431282043},{"id":"https://openalex.org/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.2161928117275238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10980305075645447},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3632093.3632098","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632098","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:pure.tue.nl:openaire_cris_publications/2a4cff12-d3fa-40f5-ae89-3d1bf1f4cce8","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/2a4cff12-d3fa-40f5-ae89-3d1bf1f4cce8","pdf_url":"https://pure.tue.nl/ws/files/385817573/3632093.3632098.pdf","source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Punter, W R, Papapetrou, O & Garofalakis, M N 2023, 'OmniSketch : Efficient Multi-Dimensional High-Velocity Stream Analytics with Arbitrary Predicates', Proceedings of the VLDB Endowment, vol. 17, no. 3, pp. 319-331. https://doi.org/10.14778/3632093.3632098","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/2a4cff12-d3fa-40f5-ae89-3d1bf1f4cce8","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/2a4cff12-d3fa-40f5-ae89-3d1bf1f4cce8","pdf_url":"https://pure.tue.nl/ws/files/385817573/3632093.3632098.pdf","source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Punter, W R, Papapetrou, O & Garofalakis, M N 2023, 'OmniSketch : Efficient Multi-Dimensional High-Velocity Stream Analytics with Arbitrary Predicates', Proceedings of the VLDB Endowment, vol. 17, no. 3, pp. 319-331. https://doi.org/10.14778/3632093.3632098","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391054867.pdf","grobid_xml":"https://content.openalex.org/works/W4391054867.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1965972569","https://openalex.org/W1966446553","https://openalex.org/W1995437102","https://openalex.org/W2025051251","https://openalex.org/W2080234606","https://openalex.org/W2080745194","https://openalex.org/W2140431670","https://openalex.org/W2487095677","https://openalex.org/W2912024553","https://openalex.org/W2915063781","https://openalex.org/W3118593453","https://openalex.org/W3198289887","https://openalex.org/W4290802786","https://openalex.org/W4381621962","https://openalex.org/W6798187564","https://openalex.org/W6853596684"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W2886490431","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W4361801939","https://openalex.org/W180351855"],"abstract_inverted_index":{"A":[0],"key":[1],"need":[2],"in":[3,15,22,67,76],"different":[4],"disciplines":[5],"is":[6,35],"to":[7,17,43,73,124],"perform":[8],"analytics":[9,21],"over":[10],"fast-paced":[11,125],"data":[12,128,175],"streams,":[13,33,99],"similar":[14],"nature":[16],"the":[18,44,49,65,88,119,177,180,191],"traditional":[19],"OLAP":[20],"relational":[23],"databases":[24],"-":[25],"i.e.,":[26],"with":[27,137,170,195],"filters":[28,103,138],"and":[29,48,100,104,126,133,156,163,173,182],"aggregates.":[30],"Storing":[31],"unbounded":[32],"however,":[34],"not":[36],"a":[37,152,157],"realistic,":[38],"or":[39],"desired":[40],"approach":[41],"due":[42],"high":[45],"storage":[46],"requirements,":[47],"delays":[50],"introduced":[51],"when":[52],"storing":[53,87],"massive":[54],"data.":[55],"Accordingly,":[56],"many":[57,131],"synopses/sketches":[58],"have":[59],"been":[60],"proposed":[61],"that":[62,79,122,176,183],"can":[63,82,185],"summarize":[64],"stream":[66],"small":[68,72,196],"memory":[69,197],"(usually":[70],"sufficiently":[71],"be":[74,83],"stored":[75],"RAM),":[77],"such":[78],"aggregate":[80],"queries":[81,189],"efficiently":[84],"approximated,":[85],"without":[86],"full":[89],"stream.":[90],"However,":[91],"past":[92],"synopses":[93],"predominantly":[94],"focus":[95],"on":[96,106,139],"summarizing":[97],"single-attribute":[98],"cannot":[101],"handle":[102],"constraints":[105],"arbitrary":[107],"subsets":[108],"of":[109],"multiple":[110,140],"attributes":[111],"efficiently.":[112],"In":[113],"this":[114],"work,":[115],"we":[116],"propose":[117],"OmniSketch,":[118],"first":[120],"sketch":[121,148,178],"scales":[123],"complex":[127,187],"streams":[129],"(with":[130],"attributes),":[132],"supports":[134],"count":[135],"aggregates":[136],"attributes,":[141],"dynamically":[142],"chosen":[143],"at":[144],"query":[145,165],"time.":[146],"The":[147],"offers":[149],"probabilistic":[150],"guarantees,":[151,194],"favorable":[153],"space-accuracy":[154],"tradeoff,":[155],"worst-case":[158],"logarithmic":[159],"complexity":[160],"for":[161,164],"updating":[162],"execution.":[166],"We":[167],"demonstrate":[168],"experimentally":[169],"both":[171],"real":[172],"synthetic":[174],"outperforms":[179],"state-of-the-art,":[181],"it":[184],"approximate":[186],"ad-hoc":[188],"within":[190],"configured":[192],"accuracy":[193],"requirements.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}