OM: A Tunable Framework for Optimizing Continuous Queries over Data Streams

Dhananjay KulkarniChinya V. Ravishankar

Continuous query (CQ) is an important class of queries in Data Stream Management Systems. While much work has been done on algorithms for processing CQs, less attention has been paid to the issue of optimizing such queries. In this paper, we first argue that parameters such as output rate and main memory utilization are important cost objectives for CQ performance, than disk I/O. We propose a novel framework, called OM to optimize the memory utilization and output rate of CQs. Our technique monitors input stream and query characteristics, and switches plans only at certain boundary conditions. Our approach is tunable to application requirements and enables a user to make the query performance versus optimization overhead trade-off. Experimental analysis shows that our approach has high fidelity in predicting correct plans and is promising in terms of minimizing query scheduling overhead.

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