T2: A Customizable Parallel Database For Multi-dimensional Data
Chialin Chang
Anurag Acharya
Alan Sussman
Joel Saltz
SIGMOD Record, March 1998
Abstract:
In this paper, we present {\em T2}, a customizable parallel database
that integrates storage, retrieval and processing of multi-dimensional
datasets. T2 provides support for common operations including
index generation, data retrieval, memory management, scheduling of
processing across a parallel machine and user interaction. It
achieves its primary advantage from the ability to seamlessly
integrate data retrieval and processing for a wide variety of
applications and from the ability to maintain and jointly process
multiple datasets with different underlying grids. Most other systems
for multi-dimensional data have focused on uniformly distributed
datasets, such as images, maps, and dense multi-dimensional arrays.
Many real datasets, however, are non-uniform or unstructured.
For example, satellite data consists of a two dimensional strip that
is embedded in a three dimensional space; water contamination studies use
unstructured meshes to selectively simulate regions and so on. T2 can
handle both uniform and non-uniform datasets.
Postscript
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Soon to be available as UCSB TRCS98-05.