Ginga: a self-adaptive query processing system
Proceedings of the eleventh international conference on Information and knowledge management
Adaptive Query Processing: A Survey
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
Distributed query adaptation and its trade-offs
Proceedings of the 2003 ACM symposium on Applied computing
Query Processing and Optimization on the Web
Distributed and Parallel Databases
Composable XML integration grammars
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Self-monitoring query execution for adaptive query processing
Data & Knowledge Engineering
Design of an embedded cost model for mobile queries
UbiMob '04 Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing
Distributed and Parallel Databases
A monitoring service for large-scale dynamic query optimisation in a grid environment
International Journal of Web and Grid Services
A strategy to develop adaptive and interactive query brokers
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
Dynamic query optimisation: towards decentralised methods
International Journal of Intelligent Information and Database Systems
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Execution plans produced by traditional query optimizers for data integration queries may yield poor performance for several reasons. The cost estimates may be inaccurate, the memory available at run-time may be insufficient, or data delivery rate can be unpredictable. In this paper, we address the problem of unpredictable data arrival rate. We propose to dynamically schedule queries in order to deal with irregular data delivery rate and gracefully adapt to the available memory. Our approach performs careful step-by-step scheduling of several query fragments and processes these fragments based on data arrivals. We describe a performance evaluation that shows important performance gains in several configurations.