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Further Results on Colored Range Searching

Authors Timothy M. Chan , Qizheng He, Yakov Nekrich

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Author Details

Timothy M. Chan
  • Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA
Qizheng He
  • Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA
Yakov Nekrich
  • Department of Computer Science, Michigan Technological University, Houghton, MI, USA

Funding

  • Chan, Timothy M.: Supported in part by NSF Grant CCF-1814026.

Cite AsGet BibTex

Timothy M. Chan, Qizheng He, and Yakov Nekrich. Further Results on Colored Range Searching. In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 28:1-28:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.SoCG.2020.28

Abstract

We present a number of new results about range searching for colored (or "categorical") data: 1) For a set of n colored points in three dimensions, we describe randomized data structures with O(n polylog n) space that can report the distinct colors in any query orthogonal range (axis-aligned box) in O(k polyloglog n) expected time, where k is the number of distinct colors in the range, assuming that coordinates are in {1,…,n}. Previous data structures require O((log n)/(log log n) + k) query time. Our result also implies improvements in higher constant dimensions. 2) Our data structures can be adapted to halfspace ranges in three dimensions (or circular ranges in two dimensions), achieving O(k log n) expected query time. Previous data structures require O(k log²n) query time. 3) For a set of n colored points in two dimensions, we describe a data structure with O(n polylog n) space that can answer colored "type-2" range counting queries: report the number of occurrences of every distinct color in a query orthogonal range. The query time is O((log n)/(log log n) + k log log n), where k is the number of distinct colors in the range. Naively performing k uncolored range counting queries would require O(k (log n)/(log log n)) time. Our data structures are designed using a variety of techniques, including colored variants of randomized incremental construction (which may be of independent interest), colored variants of shallow cuttings, and bit-packing tricks.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Data structures design and analysis
Keywords
  • Range searching
  • geometric data structures
  • randomized incremental construction
  • random sampling
  • word RAM

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