Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/156

Integration of Spatial Join Algorithms for Processing Multiple Inputs

Authors Mamoulis, N.
Papadias, D.
Issue Date 1999
Source SIGMOD Record (ACM Special Interest Group on Management of Data) , v. 28, (2), 1999, p. 1-12
Summary Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined inputs, while others treat datasets with no index, providing solutions for the case where at least one input comes as an intermediate result of another database operator. In this paper we analyze previous work on spatial joins and propose a novel algorithm, called slot index spatial join (SISJ), that efficiently computes the spatial join between two inputs, only one of which is indexed by an R-tree. Going one step further, we show how SISJ and other spatial join algorithms can be implemented as operators in a database environment that joins more than two spatial datasets. We study the differences between relational and spatial multiway joins, and propose a dynamic programming algorithm that optimizes the execution of complex spatial queries.
Subjects
ISSN 0163-5808
ISBN 1-58113-084-8
Rights © ACM, 1999. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings / ACM-SIGMOD International Conference on Management of Data, Philadelphia, PA, USA, 1-3 June, 1999, ACM Press, New York, USA, 1999, p. 1-12
Language English
Format Article
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