Materialised view selection using randomised algorithms. (2015)

• Record Type: Journal Article
• Authors: Kumar, T.V. Vijay; Kumar, Santosh
• Is Part Of: International journal of business information systems. Volume 19:Number 2(2015)
• Page Start: 224
• Page End: 240
• Publication Date: 2015
• Subjects: data warehousing -- materialised view selection -- randomised algorithms -- iterative improvement -- simulated annealing -- randomised view selection -- optimisation -- multi–dimensional lattice; Information storage and retrieval systems -- Business -- Periodicals; Business -- Data processing -- Periodicals; Management information systems -- Periodicals; System design -- Periodicals; System analysis -- Periodicals; 651.8
• Languages: English
• ISSNs: 1746-0972

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.