International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
194 Bayesian Optimization Algorithm for OLAP Data Cubes
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On-Line Analytical Processing (OLAP) tools are frequently used in business, science and health to extract useful knowledge from massive databases. An important and hard optimization problem in OLAP data warehouses is the view selection problem, consisting of selecting a set of aggregate views of the data for speeding up future query processing. We apply the Bayesian optimization algorithm (BOA)to view selection under a size constraint. Our emphasis is to determine the suitability of the combination of BOA with constraint handling to the view selection problem, compared to a widely used UMDA. The BOA are competitive with the UMDA on a variety of problem instances, often finding approximate optimal solutions in a reasonable amount of time.