Efficient external memory structures for range-aggregate queries

  • Authors:
  • Pankaj K. Agarwal;Lars Arge;Sathish Govindarajan;Jun Yang;Ke Yi

  • Affiliations:
  • Department of Computer Science, Duke University, Box 90129, Durham, NC 27708-0129, USA;MADALGO,11Center for Massive Data Algorithmics, a center of the Danish National Research Foundation. Department of Computer Science, Aarhus University, Aarhus, Denmark;CSA Department, Indian Institute of Science, Bangalore, India;Department of Computer Science, Duke University, Box 90129, Durham, NC 27708-0129, USA;Department of Computer Science and Engineering, HKUST, Hong Kong

  • Venue:
  • Computational Geometry: Theory and Applications
  • Year:
  • 2013

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Abstract

We present external memory data structures for efficiently answering range-aggregate queries. The range-aggregate problem is defined as follows: Given a set of weighted points in R^d, compute the aggregate of the weights of the points that lie inside a d-dimensional orthogonal query rectangle. The aggregates we consider in this paper include count, sum, and max. First, we develop a structure for answering two-dimensional range-count queries that uses O(N/B) disk blocks and answers a query in O(log"BN) I/Os, where N is the number of input points and B is the disk block size. The structure can be extended to obtain a near-linear-size structure for answering range-sum queries using O(log"BN) I/Os, and a linear-size structure for answering range-max queries in O(log"B^2N) I/Os. Our structures can be made dynamic and extended to higher dimensions.