Data structures for range-aggregate extent queries

被引:8
|
作者
Gupta, Prosenjit [1 ,2 ]
Janardan, Ravi [3 ]
Kumar, Yokesh [3 ]
Smid, Michiel [4 ]
机构
[1] Mentor Graph Corp, Hyderabad 5000082, Andhra Pradesh, India
[2] Int Inst Informat Technol, Hyderabad 500032, Andhra Pradesh, India
[3] Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN 55455 USA
[4] Carleton Univ, Sch Comp Sci, Ottawa, ON K1S 5B6, Canada
来源
关键词
Computational geometry; Data structures; Closest pair; Diameter; Width;
D O I
10.1016/j.comgeo.2009.08.001
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A fundamental and well-studied problem in computational geometry is range searching, where the goal is to preprocess a set, S, of geometric objects (e.g., points in the plane) so that the subset S' c S that is contained in a query range (e.g., an axes-parallel rectangle) can be reported efficiently. However, in many situations, what is of interest is to generate a more informative "summary" of the output, obtained by applying a suitable aggregation function on S'. Examples of such aggregation functions include count, sum, min, max, mean, median, mode, and top-k that are usually computed on a set of weights defined suitably on the objects. Such range-aggregate query problems have been the subject of much recent research in both the database and the computational geometry communities. In this paper, we further generalize this line of work by considering aggregation functions on point-sets that measure the extent or "spread" of the objects in the retrieved set S'. The functions considered here include closest pair, diameter, and width. The challenge here is that these aggregation functions (unlike, say, count) are not efficiently decomposable in the sense that the answer to S' cannot be inferred easily from answers to subsets that induce a partition of S'. Nevertheless, we have been able to obtain space- and query-time-efficient solutions to several such problems including: closest pair queries with axes-parallel rectangles on point sets in the plane and on random point-sets in R-d (d >= 2), closest pair queries with disks on random point-sets in the plane, diameter queries on point-sets in the plane, and guaranteed-quality approximations for diameter and width queries in the plane. Our results are based on a combination of geometric techniques, including multilevel range trees, Voronoi Diagrams, Euclidean Minimum Spanning Trees, sparse representations of candidate outputs, and proofs of (expected) upper bounds on the sizes of such representations. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:329 / 347
页数:19
相关论文
共 50 条
  • [1] Efficient external memory structures for range-aggregate queries
    Agarwal, Pankaj K.
    Arge, Lars
    Govindarajan, Sathish
    Yang, Jun
    Yi, Ke
    COMPUTATIONAL GEOMETRY-THEORY AND APPLICATIONS, 2013, 46 (03): : 358 - 370
  • [2] Answering Range-Aggregate Queries over Objects Generating Data Streams
    Gorawski, Marcin
    Malczok, Rafal
    DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, PT II, PROCEEDINGS, 2010, 5982 : 436 - 439
  • [3] FastRAQ: A Fast Approach to Range-Aggregate Queries in Big Data Environments
    Yun, Xiaochun
    Wu, Guangjun
    Zhang, Guangyan
    Li, Keqin
    Wang, Shupeng
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2015, 3 (02) : 206 - 218
  • [4] Range-Aggregate Queries Involving Geometric Aggregation Operations
    Rahul, Saladi
    Das, Ananda Swarup
    Rajan, K. S.
    Srinathan, Kannan
    WALCOM: ALGORITHMS AND COMPUTATION, 2011, 6552 : 122 - 133
  • [5] Colored top-K range-aggregate queries
    Sanyal, Biswajit
    Gupta, Prosenjit
    Majumder, Subhashis
    INFORMATION PROCESSING LETTERS, 2013, 113 (19-21) : 777 - 784
  • [6] CRB-tree: An efficient indexing scheme for range-aggregate queries
    Govindarajan, S
    Agarwal, PK
    Arge, L
    DATABASE THEORY ICDT 2003, PROCEEDINGS, 2003, 2572 : 143 - 157
  • [7] MARS: Enabling Verifiable Range-Aggregate Queries in Multi-Source Environments
    Liu, Qin
    Peng, Yu
    Xu, Qian
    Jiang, Hongbo
    Wu, Jie
    Wang, Tian
    Peng, Tao
    Wang, Guojun
    Zhang, Shaobo
    IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2024, 21 (04) : 1994 - 2011
  • [8] Opportunistic data structures for range queries
    Poon, CK
    Yiu, WK
    COMPUTING AND COMBINATORICS, PROCEEDINGS, 2005, 3595 : 560 - 569
  • [9] Opportunistic data structures for range queries
    Chung Keung Poon
    Wai Keung Yiu
    Journal of Combinatorial Optimization, 2006, 11 : 145 - 154
  • [10] Opportunistic data structures for range queries
    Poon, CK
    Yiu, WK
    JOURNAL OF COMBINATORIAL OPTIMIZATION, 2006, 11 (02) : 145 - 154