Improving Min / Max Aggregation over Spatial

We examine the problem of computing MIN/MAX aggregate queries over a collection of spatial objects. Each spatial object is associated with a weight (value), for example, the average temperature or rainfall over the area covered by the object. Given a query rectangle, the MIN/MAX problem computes the minimum/maximum weight among all objects intersecting the query rectangle. Traditionally such queries have been performed as range search queries. Assuming that the objects are indexed by a spatial access method, the MIN/MAX is computed as objects are retrieved. This requires eeort proportional to the number of objects intersecting the query interval , which may be large. A better approach is to maintain aggregate information among the index nodes of the spatial access method; then various index paths can be eliminated during the range search. In this paper we propose four optimizations that further improve the performance of MIN/MAX queries. Our experiments show that the proposed optimizations ooer drastic performance improvement over previous approaches. Moreover, as a by-product of this work we present a dynamic version of the MSB-tree, an index that has been proposed for the MIN/MAX computation over 1-dimensional interval objects.