Segment Indexes: Dynamic Indexing Techniques for Multi-Dimensional Interval Data.
Curtis P. Kolovson, Michael Stonebraker:
Segment Indexes: Dynamic Indexing Techniques for Multi-Dimensional Interval Data.
SIGMOD Conference 1991: 138-147@inproceedings{DBLP:conf/sigmod/KolovsonS91,
author = {Curtis P. Kolovson and
Michael Stonebraker},
editor = {James Clifford and
Roger King},
title = {Segment Indexes: Dynamic Indexing Techniques for Multi-Dimensional
Interval Data},
booktitle = {Proceedings of the 1991 ACM SIGMOD International Conference on
Management of Data, Denver, Colorado, May 29-31, 1991},
publisher = {ACM Press},
year = {1991},
pages = {138-147},
ee = {http://doi.acm.org/10.1145/115790.115807, db/conf/sigmod/KolovsonS91.html},
crossref = {DBLP:conf/sigmod/91},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
We propose new indexing techniques for interval
data in K>=1 dimensions consisting of a set of extensions to a
class of database indexing structures. These techniques are useful
for improving index search performance for spatial data composed
of multi-dimensional intervals that have nonuniform
length distributions. Interval data collections having non-uniform
length distributions are likely to occur in practice, and may be
typical of historical data collections in which tuples represent
intervals in the time dimension. We present these indexing
techniques, illustrate how they may be applied to the R-Tree index,
and provide the results of performance experiments.
Copyright © 1991 by the ACM,
Inc., used by permission. Permission to make
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Printed Edition
James Clifford, Roger King (Eds.):
Proceedings of the 1991 ACM SIGMOD International Conference on Management of Data, Denver, Colorado, May 29-31, 1991.
ACM Press 1991 ,
SIGMOD Record 20(2),
June 1991
Contents
[Index Terms]
[Full Text in PDF Format, 992 KB]
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