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Time and Space Optimization for Processing Groups of Multi-Dimensional Scientific Queries

dc.contributor.authorAryangat, Sureshen_US
dc.contributor.authorAndrade, Henriqueen_US
dc.contributor.authorSussman, Alanen_US
dc.description.abstractData analysis applications in areas as diverse as remote sensing and telepathology require operating on and processing very large datasets. For such applications to execute efficiently, careful attention must be paid to the storage, retrieval, and manipulation of the datasets. This paper addresses the optimizations performed by a high performance database system that processes groups of data analysis requests for these applications, which we call queries. The system performs end-to-end processing of the requests, formulated as PostgreSQL declarative queries. The queries are converted into imperative descriptions, multiple imperative descriptions are merged into a single execution plan, the plan is optimized to decrease execution time via common compiler optimization techniques, and, finally, the plan is optimized to decrease memory consumption. The last two steps effectively reduce both the time and space to execute query groups, as shown in the experimental results. (UMIACS-TR-2004-14)en_US
dc.format.extent485160 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4569en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2004-14en_US
dc.titleTime and Space Optimization for Processing Groups of Multi-Dimensional Scientific Queriesen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US

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