JonLeonard-PriorityRTree - The Priority R-Tree A...

Info icon This preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
The Priority R-Tree: A Practically Efficient and Worst-Case Optimal R-Tree Lars Arge Department of Computer Science Duke University, Box 90129 Durham, NC 27708-0129 USA [email protected] Mark de Berg Department of Computer Science TU Eindhoven, P.O.Box 513 5600 MB Eindhoven The Netherlands [email protected] Herman J. Haverkort Institute of Information and Computing Sciences Utrecht University, PO Box 80 089 3508 TB Utrecht, The Netherlands [email protected] Ke Yi Department of Computer Science Duke University, Box 90129 Durham, NC 27708-0129, USA [email protected] ABSTRACT We present the Priority R-tree, or PR-tree, which is the first R-tree variant that always answers a window query using O (( N/B ) 1 1 /d + T/B ) I/Os, where N is the number of d - dimensional (hyper-) rectangles stored in the R-tree, B is the disk block size, and T is the output size. This is provably asymptotically optimal and significantly better than other R- tree variants, where a query may visit all N/B leaves in the tree even when T = 0 . We also present an extensive experimental study of the practical performance of the PR- tree using both real-life and synthetic data. This study shows that the PR-tree performs similar to the best known R-tree variants on real-life and relatively nicely distributed data, but outperforms them significantly on more extreme data. 1. INTRODUCTION Spatial data naturally arise in numerous applications, in- cluding geographical information systems, computer-aided design, computer vision and robotics. Therefore spatial database systems designed to store, manage, and manipulate spatial data have received considerable attention over the years. Since these databases often involve massive datasets, disk based index structures for spatial data have been re- searched extensively—see e.g. the survey by Gaede and G¨un- Supported in part by the National Science Foundation through RI grant EIA–9972879, CAREER grant CCR– 9984099, ITR grant EIA–0112849, and U.S.–Germany Co- operative Research Program grant INT–0129182. Supported by the Netherlands’ Organization for Scientific Research (NWO). Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage, and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. SIGMOD 2004 June 13-18, 2004, Paris, France. Copyright 2004 ACM 1-58113-859-8/04/06 . . . $ 5.00. ther [11]. Especially the R-tree [13] and its numerous vari- ants (see e.g. the recent survey by Manolopoulos et al. [19]) have emerged as practically efficient indexing methods. In this paper we present the Priority R-tree, or PR-tree , which is the first R-tree variant that is not only practically efficient but also provably asymptotically optimal.
Image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern