[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/93597.98741acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
Article
Free access

The R*-tree: an efficient and robust access method for points and rectangles

Published: 01 May 1990 Publication History

Abstract

The R-tree, one of the most popular access methods for rectangles, is based on the heuristic optimization of the area of the enclosing rectangle in each inner node. By running numerous experiments in a standardized testbed under highly varying data, queries and operations, we were able to design the R*-tree which incorporates a combined optimization of area, margin and overlap of each enclosing rectangle in the directory. Using our standardized testbed in an exhaustive performance comparison, it turned out that the R*-tree clearly outperforms the existing R-tree variants. Guttman's linear and quadratic R-tree and Greene's variant of the R-tree. This superiority of the R*-tree holds for different types of queries and operations, such as map overlay, for both rectangles and multidimensional points in all experiments. From a practical point of view the R*-tree is very attractive because of the following two reasons 1 it efficiently supports point and spatial data at the same time and 2 its implementation cost is only slightly higher than that of other R-trees.

References

[1]
D Greene 'An implementation and Performance Analysis of Spatial Data Access Methods', Proc 5th I n t Conf on Data Engineering, 606-615, 1989
[2]
A Guttman 'R-trees a dynamic index structure for spatial searching', Proc ACM SIGMOD Int Conf on Management of Data, 47-57, 1984
[3]
K Hlnrlchs 'The grid file system ~mplementatlon and case studies for appl~catxons', D~ssertat~on No 7734, Eldgen6sslsche Technlsche Hochschule (ETH), Zuench, 1985
[4]
D Knuth 'The art of computer programming', Vol 3 sorting and searclung, Addison-Wesley Publ C o, Reading, Mass, 1973
[5]
H P Krlegel, M Schlwletz, R Schneider, B Seeger 'Performance comparison of point and spatlal access methods', Proc Syrup on the Design and Implementation of Large Spatial Databases', Santa Barbara, 1989, Lecture Notes m Computer Science
[6]
J Nlevergelt, H Hmterberger, K C Sevcd< 'The grid file an adaptable, symmetric mult~ey file structure', ACM Trans on Database Systems, Vol 9, 1, 38- 71, 1984
[7]
N Roussopoulos, D Lelfker 'Direct spatial search on plctonal databases using packed R-trees', Proc ACM SIGMOD Int Conf on Managment of Data, 17-31, 1985
[8]
B Seeger, H P Krlegel 'Design and implementation of spatial access methods', Proc 14th Int Conf on Very Large Databases, 360-371, 1988
[9]
B Seeger, HP Krlegel 'The design and implementation of the buddy tree', Computer Science Techmcal Report 3/90, Umverslty of Bremen, submitted for pubhcatlon, 1990

Cited By

View all
  • (2025)Learning Road Network Index Structure for Efficient Map MatchingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348519537:1(423-437)Online publication date: Jan-2025
  • (2025)A Comparative Study of Rapidly-exploring Random Tree Algorithms Applied to Ship Trajectory Planning and Behavior GenerationJournal of Intelligent & Robotic Systems10.1007/s10846-025-02222-7111:1Online publication date: 11-Jan-2025
  • (2025)An update-intensive LSM-based R-tree indexThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-024-00876-734:1Online publication date: 1-Jan-2025
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
SIGMOD '90: Proceedings of the 1990 ACM SIGMOD international conference on Management of data
May 1990
398 pages
ISBN:0897913655
DOI:10.1145/93597
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. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 1990

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Article

Conference

SIGMOD 90
Sponsor:
SIGMOD 90: SIGMOD'90
May 23 - 26, 1990
New Jersey, Atlantic City, USA

Acceptance Rates

Overall Acceptance Rate 785 of 4,003 submissions, 20%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1,128
  • Downloads (Last 6 weeks)154
Reflects downloads up to 15 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2025)Learning Road Network Index Structure for Efficient Map MatchingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348519537:1(423-437)Online publication date: Jan-2025
  • (2025)A Comparative Study of Rapidly-exploring Random Tree Algorithms Applied to Ship Trajectory Planning and Behavior GenerationJournal of Intelligent & Robotic Systems10.1007/s10846-025-02222-7111:1Online publication date: 11-Jan-2025
  • (2025)An update-intensive LSM-based R-tree indexThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-024-00876-734:1Online publication date: 1-Jan-2025
  • (2024)Efficient Parallel Processing of R-Tree on GPUsMathematics10.3390/math1213211512:13(2115)Online publication date: 5-Jul-2024
  • (2024)Large Language Model-Driven Structured Output: A Comprehensive Benchmark and Spatial Data Generation FrameworkISPRS International Journal of Geo-Information10.3390/ijgi1311040513:11(405)Online publication date: 10-Nov-2024
  • (2024)SGIR-Tree: Integrating R-Tree Spatial Indexing as Subgraphs in Graph Database Management SystemsISPRS International Journal of Geo-Information10.3390/ijgi1310034613:10(346)Online publication date: 27-Sep-2024
  • (2024)Integrating NoSQL, Hilbert Curve, and R*-Tree to Efficiently Manage Mobile LiDAR Point Cloud DataISPRS International Journal of Geo-Information10.3390/ijgi1307025313:7(253)Online publication date: 14-Jul-2024
  • (2024)Hierarchical Indexing and Compression Method with AI-Enhanced Restoration for Scientific Data ServiceApplied Sciences10.3390/app1413552814:13(5528)Online publication date: 25-Jun-2024
  • (2024)A computation-aware shape loss function for point cloud completionProceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v38i7.28558(7287-7295)Online publication date: 20-Feb-2024
  • (2024)Spatial Index Including Non-Spatial AttributesThe Journal of Korean Institute of Information Technology10.14801/jkiit.2024.22.1.7122:1(71-76)Online publication date: 31-Jan-2024
  • Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media