Authors: T.V. Vijay Kumar; Mohammad Haider
Addresses: School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi-110067, India ' School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi-110067, India
Abstract: A data warehouse is designed for answering decision making queries. These queries are usually long, complex and exploratory in nature and involve aggregates over a large number of dimensions. As a result, the processing time for such queries, against a continuously growing data warehouse, is high. This problem can be addressed by materialising views over a data warehouse. This paper presents a query answering view selection algorithm (QAVSA) that considers the size and query answering capability of views to select the top-K views for materialisation from a multi-dimensional lattice. The views selected using QAVSA are likely to be beneficial both with respect to their size and their ability to answer decision making queries. Further, experimental results show that QAVSA, in comparison to the well known greedy algorithm HRUA, is able to efficiently select views that can provide answers to greater number of queries. This in turn would facilitate decision making.
Keywords: data warehouses; materialised view selection; greedy algorithms; query answering; decision making queries.
International Journal of Business Information Systems, 2015 Vol.18 No.3, pp.338 - 353
Published online: 28 Mar 2015 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article