Abstract
Let a tuple of n objects obeying a query graph (QG) be called the n-tuple. The “D distance -value” of this n-tuple is the value of a linear function of distances of the n objects that make up this n-tuple, according to the edges of the QG. This paper addresses the problem of finding the Kn-tuples between n spatial datasets that have the smallest D distance -values, the so-called K-Multi-Way Distance Join Query (K-MWDJQ), where each set is indexed by an R-tree-based structure. This query can be viewed as an extension of K-Closest-Pairs Query (K-CPQ) [4] for n inputs. In addition, a recursive non-incremental branch-and-bound algorithm following a Depth-First search for processing synchronously all inputs without producing any intermediate result is proposed. Enhanced pruning techniques are also applied to the n R-trees nodes in order to reduce the total response time of the query, and a global LRU buffer is used to reduce the number of disk accesses. Finally, an experimental study of the proposed algorithm using real spatial datasets is presented.
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Corral, A., Manolopoulos, Y., Theodoridis, Y., Vassilakopoulos, M. (2003). Distance Join Queries of Multiple Inputs in Spatial Databases. In: Kalinichenko, L., Manthey, R., Thalheim, B., Wloka, U. (eds) Advances in Databases and Information Systems. ADBIS 2003. Lecture Notes in Computer Science, vol 2798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39403-7_25
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DOI: https://doi.org/10.1007/978-3-540-39403-7_25
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