 Materialised view selection using randomised algorithmsT.V. Vijay Kumar and Santosh Kumar International Journal of Business Information Systems, 2015, vol. 19, issue 2, 224-240 Abstract: A data warehouse stores historical data for the purpose of answering decision making queries. Such queries are usually exploratory and complex in nature and have a high response time when processed against a continuously growing data warehouse. This response time can be reduced by materialising the views in a data warehouse. All views cannot be materialised due to space constraints. Also, optimal view selection is an NP-complete problem. This paper proposes a randomised view selection two phase optimisation algorithm (VS2POA) that selects the top-T views from a multi-dimensional lattice. VS2POA selects views in two phases wherein, in the first phase, iterative improvement is used to select the best local optimised top-T views. These become the initial set of top-T views for the next phase, which is based on simulated annealing. VS2POA, in comparison to the well known greedy algorithm HRUA, selects comparatively better quality views for higher dimensional datasets. Keywords: data warehousing; materialised view selection; randomised algorithms; iterative improvement; simulated annealing; randomised view selection; optimisation; multi-dimensional lattice. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:19:y:2015:i:2:p:224-240 Access Statistics for this article More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd |
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