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A View Recommendation Greedy Algorithm for Materialized Views Selection

  • Conference paper
Information Intelligence, Systems, Technology and Management (ICISTM 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 141))

Abstract

View selection is one of the key problems in view materialization. Several algorithms exist in literature for view selection, most of them are greedy based. The greedy algorithms, in each iteration, select the most beneficial view for materialization. Most of these algorithms are focused around algorithm HRUA. HRUA exhibits high run time complexity. As a result, it becomes infeasible to select views for higher dimensions. This scalability problem is addressed by the greedy algorithm VRGA proposed in this paper. Unlike HRUA, VRGA selects views from a smaller search space, comprising of recommended views, instead of all the views in the lattice. This enables VRGA to select views efficiently for higher dimensional data sets. Further, experimental results show that VRGA, in comparison to HRUA, requires significantly lesser benefit computations, view evaluation time and memory. Alternatively, HRUA has a slight edge over VRGA as regards to the total cost of evaluating all the views.

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Author information

Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    T. V. Vijay Kumar, Mohammad Haider & Santosh Kumar

  2. Mahatma Gandhi Mission’s College of Engineering and Technology, Noida, UP, 201301, India

    Mohammad Haider

  3. Krishna Institute of Engineering and Technology, Ghaziabad, UP, 201206, India

    Santosh Kumar

Authors
  1. T. V. Vijay Kumar
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  2. Mohammad Haider
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  3. Santosh Kumar
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Editor information

Editors and Affiliations

  1. Computer Science, College of Engineering and Science, Louisiana Tech University, 71272, Ruston, LA, USA

    Sumeet Dua

  2. CISE Department, CSE 301, University of Florida, 32611, Gainesville, FL, USA

    Sartaj Sahni

  3. Management Development Institute, 122 007, Sukhrali, Gurgaon, India

    D. P. Goyal

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Vijay Kumar, T.V., Haider, M., Kumar, S. (2011). A View Recommendation Greedy Algorithm for Materialized Views Selection. In: Dua, S., Sahni, S., Goyal, D.P. (eds) Information Intelligence, Systems, Technology and Management. ICISTM 2011. Communications in Computer and Information Science, vol 141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19423-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-19423-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19422-1

  • Online ISBN: 978-3-642-19423-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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