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Multi-objective materialized view selection using MOGA

Author

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  • Jay Prakash

    (Jawaharlal Nehru University)

  • T. V. Vijay Kumar

    (Jawaharlal Nehru University)

Abstract

Materialized views are used as an alternative means for reducing the response time of analytical queries posed against a data warehouse. Since all views cannot be materialized and since optimal view selection is an NP-Hard problem, there is a need to select an appropriate subset of views for materialization that reduce the response times for analytical queries. This problem, referred to as view selection, is a widely studied problem in data warehousing. Several materialized view selection (MVS) algorithms exist that address the view selection problem, as a single objective optimization problem where the objective is to minimize the total cost of evaluating all the views (TVEC). This cost comprises two costs, i.e. the total cost of evaluation due to materialized views and the total cost of evaluation due to non-materialized views. Minimization of these two costs simultaneously would lead to the minimization of TVEC. In this paper, this bi-objective optimization problem, where the two costs are minimized simultaneously, has been solved using the Multi-Objective Genetic Algorithm (MOGA). The proposed MOGA based MVS algorithm selects the Top-K views from a multidimensional lattice with the purpose of achieving an optimal trade-off between the two aforementioned objectives. Materializing these selected Top-K views would reduce the response times for analytical queries and thereby would result in effective and efficient decision making.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:2:d:10.1007_s13198-020-00947-2
    DOI: 10.1007/s13198-020-00947-2
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    References listed on IDEAS

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    1. Mohammad Haider Syed & T.V. Vijay Kumar, 2017. "Query Frequency based View Selection," International Journal of Business Analytics (IJBAN), IGI Global, vol. 4(1), pages 36-55, January.
    2. Biri Arun & T.V. Vijay Kumar, 2017. "Materialized View Selection using Artificial Bee Colony Optimization," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 13(1), pages 26-49, January.
    3. T.V. Vijay Kumar, 2013. "Answering query-based selection of materialised views," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 5(1), pages 103-116.
    4. Biri Arun & T.V. Vijay Kumar, 2015. "Materialized View Selection using Marriage in Honey Bees Optimization," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 5(3), pages 1-25, July.
    5. Biren Shah & Karthik Ramachandran & Vijay Raghavan, 2006. "A Hybrid Approach for Data Warehouse View Selection," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 2(2), pages 1-37, April.
    6. T.V. Vijay Kumar & Kalyani Devi, 2012. "Materialised view construction in data warehouse for decision making," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 11(4), pages 379-396.
    7. 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.
    8. T.V. Vijay Kumar & Biri Arun, 2016. "Materialised view selection using BCO," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 22(3), pages 280-301.
    9. 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.
    10. T.V. Vijay Kumar & Mohammad Haider, 2015. "Query answering-based view selection," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 18(3), pages 338-353.
    11. Biri Arun & T.V. Vijay Kumar, 2017. "Materialized View Selection Using Bumble Bee Mating Optimization," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 9(3), pages 1-27, July.
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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.

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