A Distributed Clustering with Intelligent Multi Agents System for Materialized Views Selection

Materialized views are the most common approach that can provide optimal performance in processing time, especially for

OLAP

queries known for their great complexity. Due to the large computation and storage limitation, materialization of all possible views is not possible. Therefore, the key issue is to choose an optimal set of views to materialize. However, this task is a very hard, especially in the data warehouses context, where a trade-of-between performance and view storage cost must be taken into account when deciding which views should be materialized. Addressing this problem, we propose a new approach with two main phases. The first involves pruning the search space to reduce the number of views candidates. In this order, we use a distributed clustering approach using multi agents system that can significantly reduces the complexity of the selection process The second phase uses also a multi agent’s architecture to capture the relationships between views candidates to select the final set of materialized views. This set minimizes the query processing cost and satisfy the storage constraint. We validate our proposed approach using an experimental evaluation.