Abstract
With the increasing emphasis on data warehouse systems, the efficiency of complex analytical queries in such systems has become an important issue. Such queries posed challenging performance problems that initiated the use of parallel database systems and parallel algorithms in data warehouse environments. Many of these have been proposed in recent years but a review of the literature to our knowledge has not revealed any literature describing parallel methods with detailed cost models for aggregate data cube queries in a data warehouse environment. This paper presents a detailed cost model based on parallel methods for aggregate data cube queries. The detailed cost model enables us to study the behaviour and evaluate the performance of the three methods and thus identify the efficient parallel methods for aggregate data cube queries.
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Tan, R.BN., Taniar, D., Lu, G. (2003). Efficient Execution of Parallel Aggregate Data Cube Queries in Data Warehouse Environments. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_95
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DOI: https://doi.org/10.1007/978-3-540-45080-1_95
Publisher Name: Springer, Berlin, Heidelberg
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