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Materialised view selection using randomised algorithms

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  • T.V. Vijay Kumar
  • Santosh Kumar

Abstract

A data warehouse stores historical data for the purpose of answering decision making queries. Such queries are usually exploratory and complex in nature and have a high response time when processed against a continuously growing data warehouse. This response time can be reduced by materialising the views in a data warehouse. All views cannot be materialised due to space constraints. Also, optimal view selection is an NP-complete problem. This paper proposes a randomised view selection two phase optimisation algorithm (VS2POA) that selects the top-T views from a multi-dimensional lattice. VS2POA selects views in two phases wherein, in the first phase, iterative improvement is used to select the best local optimised top-T views. These become the initial set of top-T views for the next phase, which is based on simulated annealing. VS2POA, in comparison to the well known greedy algorithm HRUA, selects comparatively better quality views for higher dimensional datasets.

Suggested Citation

  • T.V. Vijay Kumar & Santosh Kumar, 2015. "Materialised view selection using randomised algorithms," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 19(2), pages 224-240.
    • Handle: RePEc:ids:ijbisy:v:19:y:2015:i:2:p:224-240
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    Citations

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    Cited by:

    1. Jay Prakash & T. V. Vijay Kumar, 2020. "Multi-objective materialized view selection using NSGA-II," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(5), pages 972-984, October.
    2. T. V. Vijay Kumar & Biri Arun, 2017. "Materialized view selection using HBMO," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 379-392, January.
    3. Anjana Gosain & Kavita Sachdeva, 2019. "Selection of materialized views using stochastic ranking based Backtracking Search Optimization Algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 801-810, August.
    4. Jay Prakash & T. V. Vijay Kumar, 2020. "Multi-objective materialized view selection using MOGA," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 220-231, July.

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