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.
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Velinov, G., Jakimovski, B., Cerepnalkoski, D., Kon-Popovska, M. (2008). Improvement of Data Warehouse Optimization Process by Workflow Gridification. In: Atzeni, P., Caplinskas, A., Jaakkola, H. (eds) Advances in Databases and Information Systems. ADBIS 2008. Lecture Notes in Computer Science, vol 5207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85713-6_21
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DOI: https://doi.org/10.1007/978-3-540-85713-6_21
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