Optimizing Queries Using a Materialized View in a Data Warehoue

Abstract

A data warehouse is a user-centered environment for data analysis and decision support. To support decision maker in making decisions quickly and accurately, using materialized views can provide significant improvements in query processing time. The problem of answering queries using views is to find efficient methods of answering a query using a set of previously materialized views over the database, rather than accessing the database relations. The known algorithms, the bucket algorithm, the inverse-rules algorithm have been used to rewrite queries using views before executing the queries. The bucket algorithm, predominantly used to rewrite queries, generates a candidate rewriting to a query using views then checks that the rewriting is contained in the original query. However, we show same deficiencies in the bucket algorithm then describe the containment bucket algorithm and give an optimal method to solve this problem. We present an experiment comparing the performance of both algorithms.