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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/156
Title: Integration of spatial join algorithms for processing multiple inputs
Authors: Mamoulis, Nikos
Papadias, Dimitris
Keywords: Spatial joins
Spatial query processing
Query optimization
Issue Date: 1999
Citation: 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
Abstract: 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.
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
URI: http://hdl.handle.net/1783.1/156
Appears in Collections:CSE Conference Papers

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