Spatial query processing in an object-oriented database system
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The author describes an efficient data structure called the G-tree (or grid tree) for organizing multidimensional data. The data structure combines the features of grids and B-trees in a novel manner. It also exploits an ordering property that numbers the partitions in such a way that partitions that are spatially close to one another in a multidimensional space are also close in terms of their partition numbers. This structure adapts well to dynamic data spaces with a high frequency of insertions and deletions, and to nonuniform distributions of data. We demonstrate that it is possible to perform insertion, retrieval, and deletion operations, and to run various range queries efficiently using this structure. A comparison with the BD tree, zkdb tree and the KDB tree is carried out, and the advantages of the G-tree over the other structures are discussed. The simulated bucket utilization rates for the G-tree are also reported.