Time and Space Optimization for Processing Groups of Multi-Dimensional Scientific Queries
Time and Space Optimization for Processing Groups of Multi-Dimensional Scientific Queries
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Date
2004-04-19
Authors
Aryangat, Suresh
Andrade, Henrique
Sussman, Alan
Advisor
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Abstract
Data 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)