Tuned X-HYBRIDJOIN for Near-real-time Data Warehousing

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aut.relation.endpage505
aut.relation.startpage494
aut.relation.volume7808 LNCS
aut.researcherNaeem, Muhammad Asif
dc.contributor.authorNaeem, MA
dc.date.accessioned2013-06-06T00:06:32Z
dc.date.available2013-06-06T00:06:32Z
dc.date.copyright2013
dc.date.issued2013
dc.description.abstractNear-real-time data warehousing defines how updates from data sources are combined and transformed for storage in a data warehouse as soon as the updates occur. Since these updates are not in warehouse format, they need to be transformed and a join operator is usually required to implement this transformation. A stream-based algorithm called X-HYBRIDJOIN (Extended Hybrid Join), with a favorable asymptotic runtime behavior, was previously proposed. However, X-HYBRIDJOIN does not tune its components under limited available memory resources and without assigning an optimal division of memory to each join component the performance of the algorithm can be suboptimal. This paper presents a variant of X-HYBRIDJOIN called Tuned X-HYBRIDJOIN. The paper shows that after proper tuning the algorithm performs significantly better than that of the previous X-HYBRIDJOIN, and also better as other join operators proposed for this application found in the literature. The tuning approach has been presented, based on measurement techniques and a revised cost model. The experimental results demonstrate the superior performance of Tuned X-HYBRIDJOIN.
dc.identifier.citationLecture Notes in Computer Science Volume 7808, 2013, pp 494-505
dc.identifier.doi10.1007/978-3-642-37401-2_49
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttps://hdl.handle.net/10292/5413
dc.publisherSpringer
dc.relation.isreplacedby10292/5461
dc.relation.isreplacedbyhttp://hdl.handle.net/10292/5461
dc.relation.urihttps://link.springer.com/chapter/10.1007%2F978-3-642-37401-2_49
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).
dc.rights.accessrightsOpenAccess
dc.subjectData warehousing
dc.subjectTuning and performance optimization
dc.subjectData transformation
dc.subjectStream-based joins
dc.titleTuned X-HYBRIDJOIN for Near-real-time Data Warehousing
dc.typeConference Contribution
pubs.elements-id142312
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/School of Computing & Mathematical Science
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