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A Query Answering Greedy Algorithm for Selecting Materialized Views

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6422))

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Abstract

Materialized views aim to improve the response time of analytical queries posed on a data warehouse. This entails that they contain information that provides answers to most future queries. The selection of such information from the data warehouse is referred to as view selection. View selection deals with selection of appropriate sets of views to improve the query response time. Several view selection algorithms exist in literature, most of them being greedy based. The greedy algorithm HRUA, which selects top-k views from a multidimensional lattice, is considered the most fundamental greedy based algorithm. It selects views having the highest benefit, computed in terms of size, for materialization. Though the views selected using HRUA are beneficial with respect to size, they may not account for a large number of future queries and may hence become an unnecessary overhead. This problem is addressed by the Query Answering Greedy Algorithm (QAGA) proposed in this paper. QAGA uses both the size of the view, and the frequency of previously posed queries answered by each view, to compute the profits of all views in each iteration. Thereafter it selects, from among them, the most profitable view for materialization. QAGA is able to select views which are beneficial with respect to size and have a greater likelihood of answering future queries. Further, experimental results show that QAGA, as compared to HRUA, is able to select views capable of answering greater number of queries. Though HRUA incurs a lower total cost of evaluating all the views, QAGA has a lower total cost of answering all the queries leading to an improvement in the average query response time. This in turn facilitates decision making.

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Authors and Affiliations

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

    T. V. Vijay Kumar & Mohammad Haider

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

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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Kumar, T.V.V., Haider, M. (2010). A Query Answering Greedy Algorithm for Selecting Materialized Views. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16732-4_17

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  • DOI: https://doi.org/10.1007/978-3-642-16732-4_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16731-7

  • Online ISBN: 978-3-642-16732-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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