Benchmarking Spatial Join Operations with Spatial Output
Erik G. Hoel, Hanan Samet · 1995
The spatial join operation is benchmarked using variants of well-known spatial data structures such as the R-tree, R-tree, R +-tree, and the PMR quadtree. The focus is on a spatial join with spatial output because the result of the spatial join frequently serves as input to subsequent spatial operations (i.e., a cascaded spatial join as would be common in a spatial spreadsheet). Thus, in addition to the time required to perform the spatial join itself (whose output is not always required to be spatial), the time to build the spatial data structure also plays an important role in the benchmark. The studied quantities are the time to build the data structure and the time to do the spatial join in an application domain consisting of planar line segment data. Experiments reveal that spatial data structures based on a disjoint decomposition of space and bounding boxes (i.e., the R +-tree and the PMR quadtree with bounding boxes) outperform the other structures that are based upon a non-disjoint decomposition (i.e., the R-tree and R-tree). As the size of the output of the spatial join increases with respect to the larger of the two inputs, the advantage of the bounding boxes used in methods based on a disjoint non-regular decomposition is no longer a factor and