{"id":"https://openalex.org/W2163371797","doi":"https://doi.org/10.1145/2351476.2351481","title":"Autonomous database partitioning using data mining on single computers and cluster computers","display_name":"Autonomous database partitioning using data mining on single computers and cluster computers","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W2163371797","doi":"https://doi.org/10.1145/2351476.2351481","mag":"2163371797"},"language":"en","primary_location":{"id":"doi:10.1145/2351476.2351481","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2351476.2351481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Database Engineering &amp; Applications Sysmposium on - IDEAS '12","raw_type":"proceedings-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/A5048225132","display_name":"Liangzhe Li","orcid":null},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liangzhe Li","raw_affiliation_strings":["University of Oklahoma, Norman, OK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oklahoma, Norman, OK","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071062190","display_name":"Le Gruenwald","orcid":"https://orcid.org/0000-0002-5245-4747"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Le Gruenwald","raw_affiliation_strings":["University of Oklahoma, Norman, OK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oklahoma, Norman, OK","institution_ids":["https://openalex.org/I8692664"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I8692664"],"apc_list":null,"apc_paid":null,"fwci":1.4909,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84715629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"32","last_page":"41"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9987000226974487,"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":0.9987000226974487,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9984999895095825,"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/T11106","display_name":"Data Management and Algorithms","score":0.9976999759674072,"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":0.8870431184768677},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.6352177858352661},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6189677715301514},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6084727048873901},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.55936598777771},{"id":"https://openalex.org/keywords/view","display_name":"View","score":0.5263582468032837},{"id":"https://openalex.org/keywords/response-time","display_name":"Response time","score":0.44829583168029785},{"id":"https://openalex.org/keywords/database-tuning","display_name":"Database tuning","score":0.43823152780532837},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33699876070022583},{"id":"https://openalex.org/keywords/database-design","display_name":"Database design","score":0.2960413694381714},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.14529821276664734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08441048860549927}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8870431184768677},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.6352177858352661},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6189677715301514},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6084727048873901},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.55936598777771},{"id":"https://openalex.org/C54239708","wikidata":"https://www.wikidata.org/wiki/Q1329910","display_name":"View","level":3,"score":0.5263582468032837},{"id":"https://openalex.org/C19012869","wikidata":"https://www.wikidata.org/wiki/Q578372","display_name":"Response time","level":2,"score":0.44829583168029785},{"id":"https://openalex.org/C107535962","wikidata":"https://www.wikidata.org/wiki/Q2459880","display_name":"Database tuning","level":4,"score":0.43823152780532837},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33699876070022583},{"id":"https://openalex.org/C148840519","wikidata":"https://www.wikidata.org/wiki/Q1049878","display_name":"Database design","level":2,"score":0.2960413694381714},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.14529821276664734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08441048860549927},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2351476.2351481","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2351476.2351481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Database Engineering &amp; Applications Sysmposium on - IDEAS '12","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.660.1981","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.660.1981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.ou.edu/%7Edatabase/autoclust/documents/LiangzheLi-IDEAS-2012.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W116329957","https://openalex.org/W1482997398","https://openalex.org/W1494303988","https://openalex.org/W1554451661","https://openalex.org/W1556530724","https://openalex.org/W1867390120","https://openalex.org/W1965641473","https://openalex.org/W1997020216","https://openalex.org/W1997375126","https://openalex.org/W2039795745","https://openalex.org/W2066771339","https://openalex.org/W2108094106","https://openalex.org/W2114679600","https://openalex.org/W2119430004","https://openalex.org/W2127126492","https://openalex.org/W2158491997","https://openalex.org/W2161906280","https://openalex.org/W2168780254","https://openalex.org/W2270383478"],"related_works":["https://openalex.org/W2041090168","https://openalex.org/W2033980616","https://openalex.org/W2521597029","https://openalex.org/W1526122737","https://openalex.org/W2003701127","https://openalex.org/W2375855311","https://openalex.org/W2365999782","https://openalex.org/W2118731196","https://openalex.org/W2129469317","https://openalex.org/W750475535"],"abstract_inverted_index":{"One":[0],"of":[1,10,21,34,81,100,175,179,212],"the":[2,8,32,41,53,57,66,101,173,191],"most":[3],"important":[4],"metrics":[5],"in":[6],"measuring":[7],"performance":[9,174],"a":[11,180],"database":[12,54,131,138,198],"system":[13,55],"is":[14,19,29,43,49,89,108,150],"query":[15,58,67,207],"response":[16,68],"time,":[17,78],"which":[18],"composed":[20],"I/O":[22,27,74,106],"time":[23,28,48,69,75],"and":[24,39,159,187],"CPU":[25,47,77],"time.":[26],"decided":[30,50],"by":[31,51],"amount":[33],"data":[35,42,86,94,110],"read/write":[36],"from/to":[37],"disks":[38,88,112],"how":[40,52],"located":[44],"on":[45,111,152,183,195],"disks.":[46],"performs":[56],"operations.":[59],"So":[60],"if":[61],"we":[62,70],"want":[63],"to":[64,104],"reduce":[65,72,105],"can":[71],"either":[73],"or":[76,79],"both":[80,184,210],"them.":[82],"We":[83],"know":[84],"retrieving":[85,93],"from":[87,95,157],"much":[90],"slower":[91],"than":[92],"main":[96],"memory.":[97],"Hence,":[98],"one":[99],"common":[102],"ways":[103],"times":[107],"clustering":[109,133],"so":[113],"that":[114,178,203],"queries":[115,158],"will":[116],"access":[117],"only":[118],"relevant":[119],"data.":[120],"This":[121],"paper":[122,167],"introduces":[123],"an":[124],"efficient":[125],"algorithm,":[126],"called":[127,136],"AutoClust,":[128],"for":[129,141,209],"automatic":[130,137],"attribute":[132],"(or":[134],"also":[135],"vertical":[139],"partitioning)":[140],"single":[142,185],"computers":[143,186,189],"as":[144,146],"well":[145],"cluster":[147,188],"computers.":[148,213],"It":[149],"based":[151],"closed":[153],"item":[154],"sets":[155],"mined":[156],"their":[160],"attributes":[161],"using":[162,190],"association":[163],"rule":[164],"mining.":[165],"The":[166,200],"then":[168],"presents":[169],"experimental":[170],"results":[171],"comparing":[172],"AutoClust":[176,204],"with":[177],"baseline":[181],"algorithm":[182],"TPC-H":[192],"benchmark":[193],"running":[194],"major":[196],"commercial":[197],"systems.":[199],"experiments":[201],"show":[202],"has":[205],"better":[206],"costs":[208],"types":[211]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
