A systematic review on materialized view selection

Abstract

The purpose of materialized view selection is to minimize the cost of answering queries and fast query response time for timely access to information and decision support. Besides various research issues related to data warehouse evolution, materialized view selection is one of the most challenging ones. Various authors have given different methodologies, strategies and followed algorithms to solve this problem in an efficient manner. The main motivation behind this systematic review is to provide a path for future research scope in materialized view selection. Various techniques presented in the papers are identified, evaluated, and compared in terms of memory storage space, cost, and query processing time to find if any particular approach is superior to others. By means of a review of the available literature, the authors have drawn several conclusions about the status quo of materialized view selection and a future outlook is predicted on bridging the large gaps that were found in the existing methods.