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by Hongjun Zhu, Jianwen Su, Oscar H. Ibarra
In Proc. Int. Conf. on Web-Age Information Management
http://www.cs.ucsb.edu/~hongjunz/waim00.ps
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Abstract:
Abstract. Spatial joins are very important but costly operations in spatial databases. A typical evaluation strategy of spatial joins is to perform the join on approximations of spatial objects and then evaluate the join of the real objects based on the results. The common approximation is the minimum bounding rectangle. Minimum bounding rectangles are coarse approximations of spatial objects and may cause a large number of "false hits". In this paper, we consider a more general form of approximation with rectilinear polygons for spatial objects in the context of spatial join evaluation. A naive approach is to decompose rectilinear polygons into rectangles and use an exisiting rectangle join algorithm. This may require additional cost for sorting, index construction, and decomposition and prohibits the join evaluation to be pipelined. The main contribution of the paper is a technique for extending plane sweeping based rectangle join algorithms to perform a spatial join on rectilinear polygons directly. We show that the join of two sets of rectilinear polygons can be computed in O(bN log b N b + #
Citations
|
270
|
Parallel processing of spatial joins using r-trees
– Brinkhoff, Kriegel, et al.
- 1996
|
|
174
|
Join Indices
– Valduriez
- 1987
|
|
170
|
Spatial query processing in an object-oriented database system
– Orenstein
- 1986
|
|
150
|
Partition based spatial-merge join
– Patel, DeWitt
- 1996
|
|
149
|
The buffer tree: A new technique for optimal I/O-algorithms
– Arge
- 1995
|
|
145
|
Fundamentals of spatial information systems
– Laurini, Thompson
- 1992
|
|
130
|
Multi-step processing of spatial joins
– Brinkhoff, Kriegel, et al.
- 1994
|
|
124
|
External-memory computational geometry
– Goodrich, Tsay, et al.
- 1993
|
|
107
|
Constraint Databases
– Benedikt, Libkin
- 2000
|
|
101
|
PROBE Spatial Data Modeling and Query Processing in an Image Database Application
– Orenstein, Manola
- 1988
|
|
93
|
Efficient computation of spatial joins
– Gunther
- 1993
|
|
90
|
Spatial joins using r-trees: Breadth-first traversal with global optimizations
– Huang, Jing, et al.
- 1997
|
|
89
|
Spatial hash-joins
– Lo, Ravishankar
- 1996
|
|
77
|
Spatial join indices
– Rotem
- 1991
|
|
69
|
Redundancy in spatial databases
– ORENSTEIN
- 1989
|
|
55
|
Scalable sweeping-based spatial join
– Arge, Procopiuc, et al.
- 1998
|
|
54
|
Solutions to Klee's rectangle problems
– Bentley
- 1977
|
|
43
|
The R*-tree: an ecient and robust access method for points and rectangles
– Beckmann, Kriegel, et al.
- 1990
|
|
36
|
A new algorithm for computing joins with grid files
– Becker, Hinrichs, et al.
- 1993
|
|
35
|
Geometric intersection problems
– Shamos, Hoey
- 1976
|
|
22
|
Hierarchical representations of collections of small rectangles
– Samet
- 1988
|
|
7
|
Filter trees for managing spatial data over a range of size granularities
– Sevcik, Koudas
- 1996
|
|
7
|
A Raster approximation for processing of spatial joins
– Zimbrao, Souza
- 1998
|
|
6
|
Minimal rectangular partition of digitized blobs
– Ferrari, Sklansky
- 1980
|
|
3
|
An index structure for spatial joins in linear constraint databases
– Zhu, Su, et al.
- 1999
|
|
1
|
Toward spatial joins for general polygons
– Zhu, Su, et al.
- 2000
|
