Distance Join Queries of Multiple Inputs in Spatial Databases

Let a tuple of n objects obeying a query graph (QG) be called the n-tuple. The “Ddistance-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 K n-tuples between n spatial datasets that have the smallest Ddistance-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 ...

• Type: Conference
• Year: 2003
• Where: ADBIS
• Authors: Antonio Corral, Yannis Manolopoulos, Yannis Theodoridis, Michael Vassilakopoulos
• Keywords: ADBIS 2003, Database, Distance Join Query, Query Graph, Spatial Datasets