Benchmarking spatial joins à la carte - Oliver Günther; Vincent Oria; Philippe Picouet; Jean-Marc Saglio; Michel Scholl (Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, 1997)
Spatial joins are join operations that involve spatial data types and operators. Spatial access methods are often used to speed up the computation of spatial joins. This paper addresses the issue of benchmarking spatial join operations. For this purpose, we first present a WWW-based tool to produce sets of rectangles. Experimentators can use a standard Web browser to specify the number of rectangles, as well as the statistical distributions of their sizes, shapes, and locations. Second, using the rectangle generator and a well-defined set of statistical models we defined several test suites to compare the performance of three spatial join algorithms: nested loop, scan-and-index, and synchronized tree traversal. We also added a real-life data set from the Sequoia 2000 storage benchmark. Our results confirm that the use of spatial indices leads to performance gains of several orders of magnitude. The tests also show that highly selective join predicates enjoy greater performance gains (and vice versa). All of the statistical models and algorithms are available on the Web, which allows for easy verification and modification of our experiments.
urn:nbn:de:kobv:11-10064291
Keywords: 330