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Query Prioritization for View Selection

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Progress in Intelligent Computing Techniques: Theory, Practice, and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 518))

Abstract

Selection of best set of views that can minimize answering cost of queries under space or maintenance cost bounds is a problem of view selection in data warehouse. Various solutions have been provided by minimizing/maximizing cost functions using various frameworks such as lattice, MVPP. Parameters that have been considered in the cost functions for view selection include view size, query frequency, view update cost, view sharing cost, etc. However, queries also have a priority value indicating the level of importance in generating its results. Some queries require immediate response time, while some can wait. Thus, if views needed by highly prioritized queries are pre-materialized, their response time can be faster. Query priority can help in selection of better set of views by which higher priority views can be selected before lower priority views. Thus, we introduce query priority and cube priority for view selection in data warehouse.

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Authors and Affiliations

  1. USICT, GGSIPU, New Delhi, India

    Anjana Gosain &  Heena Madaan

Authors
  1. Anjana Gosain
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  2. Heena Madaan
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Corresponding author

Correspondence to Heena Madaan .

Editor information

Editors and Affiliations

  1. National Institute of Technology, Dept. of Computer Science & Engineering National Institute of Technology, Rourkela, Odisha, India

    Pankaj Kumar Sa

  2. National Institute of Technology, Dept. of Computer Science & Engineering National Institute of Technology, Rourkela, Odisha, India

    Manmath Narayan Sahoo

  3. Universiti Malaysia Perlis (UniMAP), School of Mecahtronics Engineering Universiti Malaysia Perlis (UniMAP), Arau, Perlis, Malaysia

    M. Murugappan

  4. The University of Exeter, Lecturer The University of Exeter, Exeter, Devon, United Kingdom

    Yulei Wu

  5. National Institute of Technology, Dept. of Computer Science & Engineering National Institute of Technology, Rourkela, Odisha, India

    Banshidhar Majhi

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© 2018 Springer Nature Singapore Pte Ltd.

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Gosain, A., Heena Madaan (2018). Query Prioritization for View Selection. In: Sa, P., Sahoo, M., Murugappan, M., Wu, Y., Majhi, B. (eds) Progress in Intelligent Computing Techniques: Theory, Practice, and Applications. Advances in Intelligent Systems and Computing, vol 518. Springer, Singapore. https://doi.org/10.1007/978-981-10-3373-5_40

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  • DOI: https://doi.org/10.1007/978-981-10-3373-5_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3372-8

  • Online ISBN: 978-981-10-3373-5

  • eBook Packages: EngineeringEngineering (R0)

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