Two-Stage Stochastic View Selection for Data-Analysis Queries

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 186)


We consider the problem of selecting an optimal set of views to answer a given collection of queries at the present time (stage 1) as well as several collections of queries in the future (stage 2), with a given probability of occurrence associated with each collection, so as to minimize the expected value of the corresponding query response time, while keeping the total size of the views within a given limit. We formulate this problem as a two-stage stochastic programming problem. We show that this model is equivalent to an integer programming (IP) model that can be solved via various commercial IP solvers. We also study the relationship between the queries and the views in this context and use this relationship to reduce the size of the corresponding IP model, hence increase the scalability of our proposed approach.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Operations Research ProgramNC State UniversityRaleighUSA
  2. 2.Computer Science DepartmentNC State UniversityRaleighUSA

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