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by Daniel C. Zilio, Anant Jhingran, Sriram Padmanabhan
IBM Research Report RC
http://www.db.toronto.edu/~zilio/pub/cfgv1.ps
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Abstract:
A shared nothing database system which tries to leverage the knowledge of partitioning attributes of relations can outperform a system where such knowledge is either not available or not used. The performance improvements are typically obtained by function shipping more database operations (joins, aggregates etc.), thus minimizing the communication overhead. In such a system, it is critical that the correct partitioning keys are selected so that the query workload is optimized. Previous research has ignored the importance of selecting the partitioning keys and have mostly focused on the degree of declustering. In this study we show that by following a systematic methodology, especially for the partitioning key selection and associated relation grouping issues, the entire data placement strategy for a given database schema and workload can be determined in a very efficient manner. We describe different flavors of this methodology and demonstrate the performance improvements resulting from them. 1
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