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Two-Stage Stochastic View Selection for Data-Analysis Queries

  • Conference paper
Advances in Databases and Information Systems

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

Abstract

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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Author information

Authors and Affiliations

  1. Operations Research Program, NC State University, Raleigh, NC, 27695, USA

    Rong Huang & Yahya Fathi

  2. Computer Science Department, NC State University, Raleigh, NC, 27695, USA

    Rada Chirkova

Authors
  1. Rong Huang
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  2. Rada Chirkova
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  3. Yahya Fathi
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Corresponding author

Correspondence to Rong Huang .

Editor information

Editors and Affiliations

  1. Institute of Computing Science, Poznan University of Technology, ul. Piotrowo 3a, Poznan, 60-965, Poland

    Tadeusz Morzy

  2. , Dept. of Computer Science, University of Kaiserslautern, Kaiserslautern, 67653, Germany

    Theo Härder

  3. Institute of Computing Science, Faculty of Computing, Poznań University of Technology, Piotrowo 2, Poznań, 60-965, Poland

    Robert Wrembel

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Huang, R., Chirkova, R., Fathi, Y. (2013). Two-Stage Stochastic View Selection for Data-Analysis Queries. In: Morzy, T., Härder, T., Wrembel, R. (eds) Advances in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 186. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32741-4_11

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  • DOI: https://doi.org/10.1007/978-3-642-32741-4_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32740-7

  • Online ISBN: 978-3-642-32741-4

  • eBook Packages: EngineeringEngineering (R0)

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