Metric indexing to improve distance joints
Niels J. Nes, C.W. Quak, Martin L. Kersten · UvA-DARE (University of Amsterdam) · 1998
Database applications using large vector data are often supported by spatial index structures to locate spatially related objects. An important query class deals with finding related object pairs under a distance function. %, i.e. those %spatially close to a given point. , like nearest neighbors. In this paper we demonstrate that a light-weight indexing structure, based on the metric properties derived from the distance function, is often sufficient to support this important class. It is of particular importance as a temporary search accelerator while processing complex queries. Moreover, it can be used to speed up point and region queries for low selectivities and, presumably, highly-skewed spaces.