{"id":"https://openalex.org/W3175055685","doi":"https://doi.org/10.1145/3448016.3457547","title":"Jigsaw: A Data Storage and Query Processing Engine for Irregular Table Partitioning","display_name":"Jigsaw: A Data Storage and Query Processing Engine for Irregular Table Partitioning","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3175055685","doi":"https://doi.org/10.1145/3448016.3457547","mag":"3175055685"},"language":"en","primary_location":{"id":"doi:10.1145/3448016.3457547","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457547","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457547","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457547","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053151130","display_name":"Donghe Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Donghe Kang","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075655663","display_name":"Ruochen Jiang","orcid":"https://orcid.org/0000-0003-3049-9087"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruochen Jiang","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001035930","display_name":"Spyros Blanas","orcid":"https://orcid.org/0009-0004-2703-7177"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Spyros Blanas","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053151130"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":1.7603,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.85319655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"898","last_page":"911"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9994999766349792,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.9994999766349792,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9994000196456909,"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":0.9976000189781189,"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/partition","display_name":"Partition (number theory)","score":0.815403938293457},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7245413064956665},{"id":"https://openalex.org/keywords/tuple","display_name":"Tuple","score":0.6621482372283936},{"id":"https://openalex.org/keywords/column","display_name":"Column (typography)","score":0.6190863251686096},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.587133526802063},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5766046047210693},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5215399265289307},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4953383505344391},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.44465380907058716},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3668375611305237},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1446249783039093},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1041126549243927}],"concepts":[{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.815403938293457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7245413064956665},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.6621482372283936},{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.6190863251686096},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.587133526802063},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5766046047210693},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5215399265289307},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4953383505344391},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.44465380907058716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3668375611305237},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1446249783039093},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1041126549243927},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448016.3457547","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457547","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457547","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3448016.3457547","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457547","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457547","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3365083656","display_name":null,"funder_award_id":"CCF-1816577","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5005952734","display_name":"SHF: Small: Hyperscaling Data Analytics for High-Performance Computers","funder_award_id":"1816577","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307904","display_name":"Oracle","ror":"https://ror.org/006c77m33"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3175055685.pdf","grobid_xml":"https://content.openalex.org/works/W3175055685.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1519039476","https://openalex.org/W1521148341","https://openalex.org/W1547206386","https://openalex.org/W1605782097","https://openalex.org/W1967601791","https://openalex.org/W1981988185","https://openalex.org/W1997375126","https://openalex.org/W2005112390","https://openalex.org/W2006296837","https://openalex.org/W2011395086","https://openalex.org/W2021651899","https://openalex.org/W2035355147","https://openalex.org/W2039795745","https://openalex.org/W2039910065","https://openalex.org/W2063601856","https://openalex.org/W2105252819","https://openalex.org/W2106105896","https://openalex.org/W2109626831","https://openalex.org/W2113045536","https://openalex.org/W2124851765","https://openalex.org/W2133741724","https://openalex.org/W2137156898","https://openalex.org/W2138512691","https://openalex.org/W2140342613","https://openalex.org/W2148291485","https://openalex.org/W2150630976","https://openalex.org/W2162064942","https://openalex.org/W2169188831","https://openalex.org/W2170853664","https://openalex.org/W2247645225","https://openalex.org/W2426624872","https://openalex.org/W2574861468","https://openalex.org/W2605843372","https://openalex.org/W2799237774","https://openalex.org/W2911536067","https://openalex.org/W2915063781","https://openalex.org/W2951321531","https://openalex.org/W2990812675","https://openalex.org/W3020084632","https://openalex.org/W3084584595","https://openalex.org/W3085364173","https://openalex.org/W3098304379","https://openalex.org/W3105820654","https://openalex.org/W4243533704"],"related_works":["https://openalex.org/W4245395944","https://openalex.org/W2143551613","https://openalex.org/W1979740464","https://openalex.org/W2143345456","https://openalex.org/W2138823233","https://openalex.org/W1789991335","https://openalex.org/W2562731034","https://openalex.org/W4315705795","https://openalex.org/W2101053337","https://openalex.org/W2239248532"],"abstract_inverted_index":{"The":[0],"physical":[1],"data":[2,66],"layout":[3],"significantly":[4],"impacts":[5,88],"performance":[6,90],"when":[7,67],"database":[8],"systems":[9],"access":[10],"cold":[11],"data.":[12],"In":[13],"addition":[14],"to":[15,27],"the":[16,41,46],"traditional":[17],"row":[18],"store":[19,22],"and":[20,38,91],"column":[21],"designs,":[23],"recent":[24],"research":[25],"proposes":[26],"partition":[28],"tables":[29],"hierarchically,":[30],"starting":[31],"from":[32],"either":[33],"horizontal":[34],"or":[35],"vertical":[36],"partitions":[37,85],"then":[39],"determining":[40],"best":[42],"partitioning":[43,55,63,81],"strategy":[44],"on":[45],"other":[47],"dimension":[48,75],"independently":[49],"for":[50,76],"each":[51],"partition.":[52],"All":[53],"these":[54],"strategies":[56],"naturally":[57],"produce":[58],"rectangular":[59,62,80],"partitions.":[60],"Coarse-grained":[61],"reads":[64],"unnecessary":[65],"a":[68,94],"table":[69],"cannot":[70],"be":[71],"partitioned":[72],"along":[73],"one":[74],"all":[77],"queries.":[78],"Fine-grained":[79],"produces":[82],"many":[83],"small":[84],"which":[86],"negatively":[87],"I/O":[89],"possibly":[92],"introduces":[93],"high":[95],"tuple":[96],"reconstruction":[97],"overhead.":[98]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}