Mining information for constructing materialised views

  • Authors:

  • T.V. Vijay Kumar;Anurag Goel;Neeraj Jain

  • Affiliations:

  • School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi-110067, India.;Mahanagar Telephone Nigam Limited, CB&CRM Data Centre, Jawaharlal Nehru Marg, New Delhi--110002, India.;Indian Oil Corporation Limited, Research and Development Centre, Faridabad, Haryana-121007, India

  • Venue:
  • International Journal of Information and Communication Technology
  • Year:
  • 2010

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Abstract

A materialised view is constructed to improve response time for complex analytical queries posed on a large data warehouse. Most existing approaches use all the queries posed on the data warehouse for constructing materialised views. It is generally observed that, among all the queries posed on the data warehouse in the past, queries that are similar and more frequently posed have high likelihood of being posed again in future and are therefore, appropriate for constructing materialised views. The approach presented in this paper, attempts to select such frequently posed queries from among all the queries posed on the data warehouse. Further, since the materialised views are required to fit within the available storage space, the approach selects a subset of profitable frequent queries that conforms to the space constraint. The information accessed by these queries has high likelihood of being accessed again by future queries. Furthermore, it is experimentally shown that use of this information for constructing materialised views reduces query response time. This in turn would facilitate decision-making.