Materialised view selection using randomised algorithms

摘要: A data warehouse stores historical for the purpose of answering decision making queries. Such queries are usually exploratory and complex in nature have a high response time when processed against continuously growing warehouse. This can be reduced by materialising views All cannot materialised due to space constraints. Also, optimal view selection is an NP-complete problem. paper proposes randomised two phase optimisation algorithm VS2POA that selects top-T from multi-dimensional lattice. phases wherein, first phase, iterative improvement used select best local optimised views. These become initial set next which based on simulated annealing. VS2POA, comparison well known greedy HRUA, comparatively better quality higher dimensional datasets.