Three-level Processing of Multiple Aggregate Continuous Queries
DocUID: 2012-001 Full Text:
PDF Author: Shenoda Guirguis, Panos K. Chrysanthis, Alexandros Labrinidis, Mohamed A. Sharaf
Abstract: Aggregate Continuous Queries (ACQs) are both a very popular class of Continuous Queries (CQs) and also have a potentially high execution cost. As such, optimizing the processing of ACQs is imperative for Data Stream Management Systems (DSMSs) to reach their full potential in supporting (critical) monitoring applications. For multiple ACQs that vary in window specifications and pre-aggregation filters, existing multiple ACQs optimization schemes assume a processing model where each ACQ is computed as a final-aggregation of a sub-aggregation. In this paper, we propose a novel processing model for ACQs, called TriOps, with the goal of minimizing the repetition of operator execution at the sub-aggregation level. We also propose TriWeave, a TriOps-aware multi-query optimizer. We analytically and experimentally demonstrate the performance gains of our proposed schemes which shows their superiority over alternative schemes. Finally, we generalize TriWeave to incorporate the classical subsumption-based multi-query optimization techniques.
Keywords: Data Streams Management Systems, Aggregate Continuous Queries, Multiple Query Optimization, Weaveability, Shared Processing
Published In: Proc. of the 28th IEEE International Conference on Data Engineering
Pages: pp. 929-940
Place Published: Washington DC
Year Published: 2012
Project: AQSIOS Subject Area: Query Processing, Data Streams
Publication Type: Conference Paper
Sponsor: NSF CAREER IIS-0746696, NSF IIS-0534531, Others
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