Abstract

Particular and timely unified information along with quick and effective query response times is the basicfundamental requirement for the success of any collection of independent data marts (data warehouse) which formsFact Constellation Schema or Galaxy Schema. Because of the materialized view storage area, the materialization ofall views is practically impossible thus suitable Materialized Views (MVs) picking is one of the intelligent decisions indesigning a Fact Constellation Schema to get optimal efficiency. This paper presents a framework for picking bestmaterializedview using Quantum Particle Swarm Optimization (QPSO) algorithm where it is one of the stochasticalgorithms in order to achieve the effective combination of good query response time and low query handling cost.The results reveal that the proposed method for picking best- materialized view using QPSO algorithm is betterthan other techniques via computing the ratio of query response time and compare it to the response time of thesame queries on the MVs. Ratio of implementing the query on the base table takes five times more time than thequery implementation on the MVs. Where the response time of queries through MVs access 0.084 seconds while bydirect access queries 0.422 seconds. This outlines that the performance of query through MVs access is 402.38%better than those directly access via data warehouse-logical.

Keywords

The article was added to IASJ on 2020-05-07

131 Total full text downloads since the date of addition