A Window Retrieval Algorithm for Spatial Databases Using Quadtrees

An algorithm is presented to answer window queries in a quadtree-based spatial database environment by retrieving the covering blocks in the underlying spatial database. It works by decomposing the window operation into sub-operations over smaller window partitions. These partitions are the quadtree blocks corresponding to the window. Although a block b in the underlying spatial database may cover several of the smaller window partitions, b is only retrieved once. As a result, the algorithm generates an optimal number of disk I/O requests to answer a window query (i.e., one request per covering block). The algorithm uses an auxiliary main-memory data structure, called the active border, which requires additional storage of O(n), for a window query of size n n. An analysis of the algorithm's execution time and space requirements are given, as are some experimental results. 1 Introduction Because of the large volume of spatial databases, spatial access methods are usually used to organize and speed up the retrieval of spatial objects. Several spatial access methods make use of a regular decomposition of space (such as that induced by a quadtree) in order to organize and store spatial data. We focus on a disjoint decomposition of space (i.e., features are not permitted to overlap). Some examples of spatial databases with disjoint features include crop coverage, road networks, topography, etc. The large volume of spatial data imposes the need to store it in disk les. However, indexing techniques based on disjoint decomposition enables spatial features to be ac-cessed quickly without having to search the entire database. On the other hand, as a result of decomposing the underlying space, a spatial feature gets partitioned into multiple smaller pieces, which needs special treatment both from the view points of the indexing method and the spatial operations. In this paper, our focus is on one of the very important spatial operations, namely the window retrieval operation.