Design and Implementation of Algorithms for Materialized View Selection and Maintenance in Data Warehousing Environment

Abstract

Data warehousing, data mining and online analytical processing represents some of the latest trends in computing environments and information technology application to large scale processing and analysis of data. Data warehousing technology is becoming essential for the effective business strategy formulation and implementation. For the success of any data warehouse, accurate and timely consolidated information along with quick and effective query response times is the basic fundamental requirement. The materialization of all views is practically impossible because of the materialized view storage space and maintenance cost constraint thus proper materialized views selection is one of the intelligent decisions in designing a data warehouse to get optimal efficiency. In this paper, we present a framework for selecting best materialized view so as to achieve the effective combination of good query response time, low query processing cost and low view maintenance cost in a specified storage space constraint. The framework implementation parameter includes query frequency cost, query storage cost and query processing cost. The framework select the best cost effective materialize views to optimize the query processing time thereby resulting efficient data warehousing system.