A Metaheuristic Based Approach for Solving the Index Selection Problem in Data Warehouses - Bahache, Anwar Nour Eddine (FACULTE Mathématique et Informatique DEPARTEMENT D’ Informatique, 2018)
Analytical queries defined on a star schema modeled data warehouse are very complex and time consuming due to the join operations between the fact and dimension tables. Several techniques to reduce the cost and response time has been emerged in the past decades such as indexes. Binary Join Indexes (BJI) are one of the well-known indexes and its selection is considered as a problem itself (noted Index Selection Problem: ISP). this problem is crucial in data warehousing physical design. To solve this problem two approaches exists statistics-based approach and metaheuristic-based approach. In this dissertation we propose a new metaheuristic-basedapproach. This approach is based on the improved version of the artificial fish swarm algorithm for solving the binary join index selection problem. This approach aims to select the optimal set of BJI based on a mathematical cost model. This method was tested against a datamining constraint-based method and proved its effectiveness and even its superiority to the datamining constraint method.
Keywords: Keywords: Analytical queries, Data warehouse, Binary join index, Artificial fish swarm algorithm.