Improvement of Data Warehouse Optimization Process by Workflow Gridification

  • Authors:
  • Goran Velinov;Boro Jakimovski;Darko Cerepnalkoski;Margita Kon-Popovska

  • Affiliations:
  • Institute of Informatics, Faculty of Science and Mathematics, Ss.Cyril and Methodius University, Skopje, Macedonia;Institute of Informatics, Faculty of Science and Mathematics, Ss.Cyril and Methodius University, Skopje, Macedonia;Institute of Informatics, Faculty of Science and Mathematics, Ss.Cyril and Methodius University, Skopje, Macedonia;Institute of Informatics, Faculty of Science and Mathematics, Ss.Cyril and Methodius University, Skopje, Macedonia

  • Venue:
  • ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
  • Year:
  • 2008

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Abstract

Generalized problem optimization of the relational data warehouses ,i.e., selection of the optimal set of views, their optimal fragmentation and their optimal set of indexes is very complex and still a challenging problem. Therefore, choice of optimization method and improvements of optimization process are essential. Our previous research was focused on utilization of Genetic Algorithms for problem optimization. In this paper we further optimize our solution by applying our novel Java Gid framework for Genetic Algorithms (GGA) in the process of relational data warehouses optimization. Obtained experimental results have shown, that for different input parameters, GGA dramatically improves efficiency of the optimization process.