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by Matthias Gimbel, Bernhard Haumacher, Peter C. Lockemann, Walter F. Tichy
http://wwwipd.ira.uka.de/~gimbel/1999-1.ps.gz
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Abstract:
Abstract. The exploitation of hidden information from large datasets by means of data mining techniques suffers from long response times. We address this problem by using the processing power of workstation clusters and have studied the performance of OLAP queries as a first step towards a portable data mining platform. The results of our study suggest that with the availability of parallel workstation clusters that are equipped with high performance communication networks, fine-grained and communication-intensive parallelizations of queries are promising-- even though they are considered too costly in traditional database systems. The paper describes our Java framework for parallel OLAP-type query execution, necessary optimizations to the standard Java implementation, and analyzes the performance of non-standard parallel execution schemes on a workstation cluster. 1
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