Efficient Execution of Multiple Query Workloads in Data Analysis Applications
抄録
Applications 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)