Optimized processing of multiple aggregate continuous queries

Shenoda Guirguis, Mohamed A. Sharaf, Panos K. Chrysanthis, Alexandros Labrinidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

Data Streams Management Systems are designed to support monitoring applications, which require the processing of hundreds of Aggregate Continuous Queries (ACQs). These ACQs typically have different time granularities, with possibly different selection predicates and group-by attributes. In order to achieve scalability in the presence of heavy workloads, in this paper, we introduce the concept of 'Weaveability' as an indicator of the potential gains of sharing the processing of ACQs. We then propose Weave Share, a cost-based optimizer that exploits weaveability to optimize the shared processing of ACQs. Our experimental analysis shows that Weave Share outperforms the alternative sharing schemes generating up to four orders of magnitude better quality plans. Finally, we describe a practical implementation of the Weave Share optimizer.

Original languageEnglish
Title of host publicationCIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management
Pages1515-1524
Number of pages10
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: Oct 24 2011Oct 28 2011

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference20th ACM Conference on Information and Knowledge Management, CIKM'11
Country/TerritoryUnited Kingdom
CityGlasgow
Period10/24/1110/28/11

Keywords

  • aggregate continuous queries
  • data streams
  • query optimization

ASJC Scopus subject areas

  • General Decision Sciences
  • General Business,Management and Accounting

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