Aggregate Sharing in Stream Databases

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dc.contributor.authorWang, Lidanen_US
dc.contributor.authorFreschl, Jeffreyen_US
dc.date.accessioned2012-03-15T17:19:27Z
dc.date.available2012-03-15T17:19:27Z
dc.date.created2005en_US
dc.date.issued2005en_US
dc.description.abstractWe consider the problem of handling aggregate computations in a scalable fashion in stream databases. The queries of interest are sliding-window aggregate queries over a single data stream. In the na�ve approach for this problem, each query is individually processed one at a time, such that no sharing occurs among aggregates in terms of storage and answer computations. We present two new algorithms, TimeGram and OrderedSharing, both of which are designed with sharing among aggregates in mind. Our performance results show that both drastically improve the current performance of STREAM, a stream database system for which we have implemented and evaluated our two algorithms.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationTR1536en_US
dc.identifier.urihttp://digital.library.wisc.edu/1793/60456
dc.publisherUniversity of Wisconsin-Madison Department of Computer Sciencesen_US
dc.titleAggregate Sharing in Stream Databasesen_US
dc.typeTechnical Reporten_US

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