SPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries

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dc.contributor.authorNam, Yoon-Minko
dc.contributor.authorKim, Min-Sooko
dc.contributor.authorHan, Donghyoungko
dc.date.accessioned2020-11-11T04:55:21Z-
dc.date.available2020-11-11T04:55:21Z-
dc.date.created2020-11-09-
dc.date.created2020-11-09-
dc.date.created2020-11-09-
dc.date.issued2020-06-18-
dc.identifier.citation2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020, pp.2055 - 2070-
dc.identifier.issn0730-8078-
dc.identifier.urihttp://hdl.handle.net/10203/277212-
dc.description.abstractThe concept of OLAP query processing is now being widely adopted in various applications. The number of complex queries containing the joins between non-unique keys (called FK-FK joins) increases in those applications. However, the existing in-memory OLAP systems tend not to handle such complex queries efficiently since they generate a large amount of intermediate results or incur a huge amount of probe cost. In this paper, we propose an effective query planning method for complex OLAP queries. It generates a query plan containing n-ary join operators based on a cost model. The plan does not generate intermediate results for processing FK-FK joins and significantly reduces the probe cost. We also propose an efficient processing method for n-ary join operators. We implement the prototype system SPRINTER by integrating our proposed methods into an open-source in-memory OLAP system. Through experiments using the TPC-DS benchmark, we have shown that SPRINTER outperforms the state-of-the-art OLAP systems for complex queries.-
dc.languageEnglish-
dc.publisherAssociation for Computing Machinery-
dc.titleSPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries-
dc.typeConference-
dc.identifier.wosid000644433700136-
dc.identifier.scopusid2-s2.0-85086257165-
dc.type.rimsCONF-
dc.citation.beginningpage2055-
dc.citation.endingpage2070-
dc.citation.publicationname2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationPortland-
dc.identifier.doi10.1145/3318464.3380565-
dc.contributor.localauthorKim, Min-Soo-
dc.contributor.nonIdAuthorNam, Yoon-Min-
dc.contributor.nonIdAuthorHan, Donghyoung-
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CS-Conference Papers(학술회의논문)
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