ACM Transactions on Database Systems (TODS)
A practical divide-and-conquer algorithm for the rectangle intersection problem
Information Sciences: an International Journal
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Linear clustering of objects with multiple attributes
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Efficient processing of spatial joins using R-trees
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Partition based spatial-merge join
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Multidimensional access methods
ACM Computing Surveys (CSUR)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The Design and Implementation of Seeded Trees: An Efficient Method for Spatial Joins
IEEE Transactions on Knowledge and Data Engineering
PROBE Spatial Data Modeling and Query Processing in an Image Database Application
IEEE Transactions on Software Engineering
Efficient Computation of Spatial Joins
Proceedings of the Ninth International Conference on Data Engineering
Spatial Joins Using R-trees: Breadth-First Traversal with Global Optimizations
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Scalable Sweeping-Based Spatial Join
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The Impact of Global Clustering on Spatial Database Systems
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Strategies for Optimizing the Use of Redundancy in Spatial Databases
SSD '89 Proceedings of the First Symposium on Design and Implementation of Large Spatial Databases
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
A Storage and Access Architecture for Efficient Query Processing in Spatial Database Systems
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
Optimal Redundancy in Spatial Database Systems
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Generating Seeded Trees from Data Sets
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
A Performance Evaluation of Spatial Join Processing Strategies
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
ACM Transactions on Database Systems (TODS)
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The filter-and-refine strategy is well-established as the basis for spatial join algorithms. In contrast to the filter step, the refinement step has received little attention, despite contributing significantly to the total cost of a join evaluation. This paper reports investigations of spatial join algorithms for z-ordering and R-trees, with particular emphasis on interactions between choices of algorithms for the filter, sequencing and refinement steps and on the effects of clustered and unclustered organization of full spatial descriptions of objects. Our experiments show that while it is in general desirable to introduce an additional housekeeping step to reduce I/O costs of the refinement step, it is not necessary in all cases. In addition, we propose a new caching strategy for spatial joins, called zig-zag, which outperforms its competitors in all but one case. These results suggest that spatial joins need caching strategies other than non-spatial ones. Furthermore, our experiments confirm that the choice of the sequencing strategy used is very important and that clustering has a significant influence on join performance.