Exploiting Functional Decomposition for Efficient Parallel Processing of Multiple Data Analysis Queries
| dc.contributor.author | Andrade, Henrique | en_US |
| dc.contributor.author | Kurc, Tahsin | en_US |
| dc.contributor.author | Sussman, Alan | en_US |
| dc.contributor.author | Saltz, Joel | en_US |
| dc.date.accessioned | 2004-05-31T23:21:40Z | |
| dc.date.available | 2004-05-31T23:21:40Z | |
| dc.date.created | 2002-10 | en_US |
| dc.date.issued | 2002-10-25 | en_US |
| dc.description.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. A satellite data analysis application is used to experimentally show the performance benefits achieved using the techniques presented in the paper. UMIACS-TR-2002-84 | en_US |
| dc.format.extent | 1452269 bytes | |
| dc.format.mimetype | application/postscript | |
| dc.identifier.uri | http://hdl.handle.net/1903/1229 | |
| dc.language.iso | en_US | |
| dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_US |
| dc.relation.isAvailableAt | University of Maryland (College Park, Md.) | en_US |
| dc.relation.isAvailableAt | Tech Reports in Computer Science and Engineering | en_US |
| dc.relation.isAvailableAt | UMIACS Technical Reports | en_US |
| dc.relation.ispartofseries | UM Computer Science Department; CS-TR-4404 | en_US |
| dc.relation.ispartofseries | UMIACS; UMIACS-TR-2002-84 | en_US |
| dc.title | Exploiting Functional Decomposition for Efficient Parallel Processing of Multiple Data Analysis Queries | en_US |
| dc.type | Technical Report | en_US |