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Exploiting Functional Decomposition for Efficient Parallel Processing of Multiple Data Analysis Queries

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parallel processing

Overview Reuse is a powerful method for improving system performance. This paper examines functional decomposition for improving data reuse, and therefore overall query execution performance, in the context of data analysis applications. Additionally, the paper looks at the performance effects of using various projection primitives that make it possible to transform intermediate results generated during the execution of a previous query so that they can be reused by a new query. A satellite data analysis application is used to experimentally show the performance benefits achieved using the techniques presented in the paper.

Further White Paper Details
Publisher	Ohio State University	File Format	PDF
Date Published	September 2006
Format	White Papers
Topics	Parallel Processing, Data Mining - Analysis

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