{"id":"https://openalex.org/W7225129286","doi":"https://doi.org/10.1145/3799682.3840797","title":"GPU-Accelerated Parquet Compaction and Index Construction for High-Cardinality Time-Series Databases","display_name":"GPU-Accelerated Parquet Compaction and Index Construction for High-Cardinality Time-Series Databases","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7225129286","doi":"https://doi.org/10.1145/3799682.3840797"},"language":"en","primary_location":{"id":"doi:10.1145/3799682.3840797","doi":"https://doi.org/10.1145/3799682.3840797","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840797","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3799682.3840797","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033640158","display_name":"Ziyue Xu","orcid":"https://orcid.org/0009-0000-5171-2794","observed_orcids":["https://orcid.org/0009-0000-5171-2794","https://orcid.org/0000-0003-2797-4596"]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyue Xu","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0000-5171-2794","affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160380326","display_name":"Ke Wang","orcid":"https://orcid.org/0009-0004-7797-5380","observed_orcids":["https://orcid.org/0009-0004-7797-5380"]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Wang","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0004-7797-5380","affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367433","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0003-0387-2501","observed_orcids":["https://orcid.org/0000-0003-0387-2501"]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wang","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-0387-2501","affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100390120","display_name":"Xiaoguang Liu","orcid":"https://orcid.org/0000-0002-9010-3278","observed_orcids":["https://orcid.org/0000-0002-9010-3278"]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoguang Liu","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-9010-3278","affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.83430018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5510","last_page":"5520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9502000212669373,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9502000212669373,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.026599999517202377,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.006000000052154064,"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/lsm-tree","display_name":"LSM-tree","score":0.6690000295639038},{"id":"https://openalex.org/keywords/time-series-databases","display_name":"time series databases","score":0.875},{"id":"https://openalex.org/keywords/gpu-acceleration","display_name":"GPU acceleration","score":0.8989999890327454},{"id":"https://openalex.org/keywords/radix-sort","display_name":"radix sort","score":0.7580000162124634},{"id":"https://openalex.org/keywords/cpu-gpu-collaboration","display_name":"CPU-GPU collaboration","score":0.7239999771118164}],"concepts":[{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.5687999725341797},{"id":"https://openalex.org/C196715460","wikidata":"https://www.wikidata.org/wiki/Q1414356","display_name":"Compaction","level":2,"score":0.5677000284194946},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5396999716758728},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.31529998779296875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3077999949455261},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.2768000066280365},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.2685999870300293},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.23960000276565552},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.22470000386238098},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2222999930381775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3799682.3840797","doi":"https://doi.org/10.1145/3799682.3840797","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840797","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3799682.3840797","doi":"https://doi.org/10.1145/3799682.3840797","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840797","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1978665131","https://openalex.org/W2005112390","https://openalex.org/W2074935284","https://openalex.org/W2115613939","https://openalex.org/W2145195191","https://openalex.org/W2169384417","https://openalex.org/W2294581520","https://openalex.org/W2749874879","https://openalex.org/W3015823898","https://openalex.org/W3197204476","https://openalex.org/W4388977666","https://openalex.org/W4398234834","https://openalex.org/W4407367313","https://openalex.org/W4408943130","https://openalex.org/W4412082680","https://openalex.org/W4413978042","https://openalex.org/W4413978152","https://openalex.org/W7161631589","https://openalex.org/W7167884576"],"related_works":["https://openalex.org/W3149515612","https://openalex.org/W2978627851","https://openalex.org/W4388679869","https://openalex.org/W3006556470","https://openalex.org/W7208629061","https://openalex.org/W3041063623","https://openalex.org/W2781280098","https://openalex.org/W2396127626","https://openalex.org/W4214675477","https://openalex.org/W7160080518"],"abstract_inverted_index":{"Time-series":[0],"databases":[1],"commonly":[2],"employ":[3],"LSM-Tree":[4],"with":[5,123,210],"Parquet":[6,53,77,84],"columnar":[7],"storage,":[8],"where":[9],"compaction":[10,28,78,190],"and":[11,22,33,61,79,89,117,132,142,169,185,204],"index":[12,66,80,164,200],"construction":[13,201],"act":[14],"as":[15,42],"major":[16],"performance":[17],"bottlenecks":[18],"in":[19],"high-cardinality":[20],"IoT":[21],"cloud":[23],"monitoring":[24],"scenarios.":[25],"Traditional":[26],"CPU-only":[27],"suffers":[29],"from":[30],"low":[31],"parallelism":[32],"high":[34],"computation":[35],"overhead,":[36],"while":[37],"mainstream":[38],"GPU":[39,114,139,159],"solutions":[40],"such":[41],"cuDF":[43,186],"fail":[44],"to":[45,47,96,112,172],"adapt":[46],"time-series":[48],"features.":[49],"They":[50],"load":[51],"complete":[52],"files":[54],"without":[55],"optimization":[56],"for":[57,76],"string":[58,108],"primary":[59,93],"keys":[60,109,131],"lack":[62],"an":[63,194],"end-to-end":[64,206],"accelerated":[65],"building":[67],"workflow.":[68],"This":[69],"work":[70],"presents":[71],"a":[72,157],"CPU-GPU":[73],"collaborative":[74],"framework":[75,127,181],"construction.":[81],"It":[82,188],"partitions":[83],"row":[85],"groups":[86],"into":[87,110],"overlapping":[88],"non-overlapping":[90],"segments":[91],"by":[92,192,202,208],"key":[94],"ranges":[95],"avoid":[97],"unnecessary":[98],"global":[99,102],"sorting.":[100],"A":[101,146],"dictionary":[103],"alignment":[104],"scheme":[105],"transforms":[106],"variable-length":[107],"integers":[111],"eliminate":[113],"warp":[115],"divergence":[116],"enable":[118],"efficient":[119],"radix":[120],"sort.":[121],"Combined":[122],"lazy":[124],"materialization,":[125],"the":[126,173,177],"only":[128,167],"processes":[129],"sorting":[130],"delays":[133],"metric":[134],"field":[135],"parsing,":[136],"significantly":[137],"reducing":[138],"memory":[140],"consumption":[141],"data":[143],"transfer":[144],"cost.":[145],"two-phase":[147],"adaptive":[148],"cost":[149],"model":[150],"enables":[151],"effective":[152],"heterogeneous":[153],"task":[154],"scheduling.":[155],"Additionally,":[156],"parallel":[158],"pipeline":[160],"accelerates":[161],"tag":[162],"inverted":[163],"construction,":[165],"leaving":[166],"FST":[168],"bitmap":[170],"generation":[171],"CPU.":[174],"Evaluated":[175],"on":[176],"TSBS":[178],"benchmark,":[179],"our":[180],"outperforms":[182],"CPU":[183],"baselines":[184],"substantially.":[187],"cuts":[189],"time":[191],"nearly":[193],"order":[195],"of":[196],"magnitude,":[197],"speeds":[198],"up":[199],"3.8\u00d7\u20135.2\u00d7,":[203],"boosts":[205],"throughput":[207],"7.0%\u201316.0%":[209],"stable":[211],"query":[212],"latency.":[213]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-03T00:00:00"}
