DataWarehousing and Knowledge Discovery

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Abstract

DataWarehouse applications use a large number of materialized views to assist a Data Warehouse to perform well. But how to select views to be materialized is challenging. Several heuristic algorithms have been proposed in the past to tackle with this problem. In this paper, we propose a completely different approach, Genetic Algorithm, to choose materialized views and demonstrate that it is practical and effective compared with heuristic approaches.

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Mohania, M., & Tjoa, A. M. (Eds.). (1999). DataWarehousing and Knowledge Discovery (Vol. 1676). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-48298-9

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