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Efficient Execution of Multiple Query Workloads in Data Analysis Applications

dc.contributor.authorAndrade, Henriqueen_US
dc.contributor.authorKurc, Tahsinen_US
dc.contributor.authorSussman, Alanen_US
dc.contributor.authorSaltz, Joelen_US
dc.description.abstractApplications that analyze, mine, and visualize large datasets is considered an important class of applications in many areas of science, engineering and business. Queries commonly executed in data analysis applications often involve user-defined processing of data and application-specific data structures. If data analysis is employed in a collaborative environment, the data server should execute multiple such queries simultaneously to minimize the response time to the clients of the data analysis application. In a multi-client environment, there may be a large number of overlapping regions of interest and common processing requirements among the clients. Thus, better performance can be achieved if commonalities among multiple queries can be exploited. In this paper we present the design of a runtime system for executing multiple query workloads on a shared-memory machine. We describe initial experimental results using an application for browsing digitized microscopy images. (Cross-referenced as UMIACS-TR-2001-35)en_US
dc.format.extent3550577 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4250en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2001-35en_US
dc.titleEfficient Execution of Multiple Query Workloads in Data Analysis Applicationsen_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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