A data structure for orthogonal range queries

G. S. Lueker
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引用次数: 227

Abstract

Given a set of points in a d-dimensional space, an orthogonal range query is a request for the number of points in a specified d-dimensional box. We present a data structure and algorithm which enable one to insert and delete points and to perform orthogonal range queries. The worstcase time complexity for n operations is O(n logd n); the space usea is O(n logd-1 n). (O-notation here is with respect to n; the constant is allowed to depend on d.) Next we briefly discuss decision tree bounds on the complexity of orthogonal range queries. We show that a decision tree of height O(dn log n) (Where the implied constant does not depend on d or n) can be constructed to process n operations in d dimensions. This suggests that the standard decision tree model will not provide a useful method for investigating the complexity of such problems.
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正交范围查询的数据结构
给定d维空间中的一组点,正交范围查询是对指定d维框中点的数量的请求。我们提出了一种数据结构和算法,使人们能够插入和删除点,并执行正交范围查询。n个操作的最坏情况下的时间复杂度是O(n logn);空间占用是O(n log - 1n)这里的O符号是关于n的;允许常数依赖于d。)接下来,我们简要地讨论了正交范围查询复杂性的决策树界。我们证明了可以构造一个高度为O(dn log n)的决策树(其中隐含常数不依赖于d或n)来处理d维中的n个操作。这表明标准的决策树模型不会为研究此类问题的复杂性提供有用的方法。
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