(Enter summary)
Abstract: Reuse is a powerful method for improving system
performance. In this paper, we examine functional decomposition
for improving data reuse, and therefore
overall query execution performance, in the context
of data analysis applications. Additionally, we look
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.
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BibTeX entry: (Update)
H. Andrade, T. Kurc, A. Sussman, and J. Saltz. Exploiting functional decomposition for efficient parallel processing of multiple data analysis queries. In Proceedings of the 17th International Parallel & Distributed Processing Symposium. IEEE Computer Society Press, Apr. 2003. Also available as University of Maryland Technical Report CS-TR-4404 and UMIACS-TR-2002-84. http://citeseer.ist.psu.edu/andrade02exploiting.html More
@misc{ andrade03exploiting,
author = "H. Andrade and T. Kurc and A. Sussman and J. Saltz",
title = "Exploiting functional decomposition for efficient parallel processing of
multiple data analysis queries",
text = "H. Andrade, T. Kurc, A. Sussman, and J. Saltz. Exploiting functional decomposition
for efficient parallel processing of multiple data analysis queries. In
Proceedings of the 17th International Parallel & Distributed Processing
Symposium. IEEE Computer Society Press, Apr. 2003. Also available as University
of Maryland Technical Report CS-TR-4404 and UMIACS-TR-2002-84.",
year = "2003",
url = "citeseer.ist.psu.edu/andrade02exploiting.html" }
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