Designing and using views to improve performance of aggregate queries (Extended abstract)

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dc.contributor.author Afrati, F en
dc.contributor.author Chirkova, R en
dc.contributor.author Gupta, S en
dc.contributor.author Loftis, C en
dc.date.accessioned 2014-03-01T02:43:12Z
dc.date.available 2014-03-01T02:43:12Z
dc.date.issued 2005 en
dc.identifier.issn 0302-9743 en
dc.identifier.uri http://hdl.handle.net/123456789/31293
dc.subject Indexation en
dc.subject Materialized Views en
dc.subject Performance Tuning en
dc.subject Point of View en
dc.subject Query Evaluation en
dc.subject Query Rewriting en
dc.subject System Architecture en
dc.subject.classification Computer Science, Theory & Methods en
dc.subject.other Automation en
dc.subject.other Computer aided design en
dc.subject.other Computer architecture en
dc.subject.other Data reduction en
dc.subject.other Data-intensive systems en
dc.subject.other Query rewriting techniques en
dc.subject.other System architecture en
dc.subject.other View selection techniques en
dc.subject.other Query languages en
dc.title Designing and using views to improve performance of aggregate queries (Extended abstract) en
heal.type conferenceItem en
heal.identifier.primary 10.1007/11408079_48 en
heal.identifier.secondary http://dx.doi.org/10.1007/11408079_48 en
heal.language English en
heal.publicationDate 2005 en
heal.abstract Data-intensive systems routinely use derived data (e.g., indexes or materialized views) to improve query-evaluation performance. We present a system architecture for Query-Performance Enhancement by Tuning (QPET), which combines design and use of derived data in an end-to-end approach to automated query-performance tuning. Our focus is on a tradeoff between (1) the amount of system resources spent on designing derived data and on keeping the data up to date, and (2) the degree of the resulting improvement in query performance. From the technical point of view, the novelty that we introduce is that we combine aggregate query rewriting techniques [1,2] and view selection techniques [3] to achieve our goal. © Springer-Verlag Berlin Heidelberg 2005. en
heal.publisher SPRINGER-VERLAG BERLIN en
heal.journalName Lecture Notes in Computer Science en
dc.identifier.doi 10.1007/11408079_48 en
dc.identifier.isi ISI:000229213600045 en
dc.identifier.volume 3453 en
dc.identifier.spage 548 en
dc.identifier.epage 554 en

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