Learning-Based Query Performance Modeling and Prediction

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Provided by: Brown University
Topic: Big Data
Format: PDF
Accurate Query Performance Prediction (QPP) is central to effective resource management, query optimization and query scheduling. Analytical cost models, used in current generation of query optimizers, have been successful in comparing the costs of alternative query plans, but they are poor predictors of execution latency. As a more promising approach to QPP, this paper studies the practicality and utility of sophisticated learning-based models, which have recently been applied to a variety of predictive tasks with great success, in both static and dynamic query workloads.
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