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Efficient processing of spatial joins using R-trees

Authors:

Thomas Brinkhoff,

Hans-Peter Kriegel,

Bernhard SeegerAuthors Info & Claims

ACM SIGMOD Record, Volume 22, Issue 2

Pages 237 - 246

https://doi.org/10.1145/170036.170075

Published: 01 June 1993 Publication History

Abstract

Spatial joins are one of the most important operations for combining spatial objects of several relations. The efficient processing of a spatial join is extremely important since its execution time is superlinear in the number of spatial objects of the participating relations, and this number of objects may be very high. In this paper, we present a first detailed study of spatial join processing using R-trees, particularly R*-trees. R-trees are very suitable for supporting spatial queries and the R*-tree is one of the most efficient members of the R-tree family. Starting from a straightforward approach, we present several techniques for improving its execution time with respect to both, CPU- and I/O-time. Eventually, we end up with an algorithm whose total execution time is improved over the first approach by an order of magnitude. Using a buffer of reasonable size, I/O-time is almost optimal, i.e. it almost corresponds to the time for reading each required page of the relations exactly once. The performance of the various approaches is investigated in an experimental performance comparison where several large data sets from real applications are used.

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Papamichalopoulos MPapadakis GMandilaras GSiampou MMamoulis NKoubarakis M(2024)Three-dimensional Geospatial Interlinking with JedAI-spatialJournal of Web Semantics10.1016/j.websem.2024.100817(100817)Online publication date: Mar-2024
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Efficient processing of spatial joins using R-trees

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SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data

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Information

Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 22, Issue 2

June 1, 1993

558 pages

ISSN:0163-5808

DOI:10.1145/170036

Editors:
Peter Buneman
Univ. of Pennsylvania
,
Sushil Jajodia,
Won Kim
UniSQL, Inc., Austin, TX

Issue’s Table of Contents

SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data
June 1993
566 pages
ISBN:0897915925
DOI:10.1145/170035
Editors:
Peter Buneman
Univ. of Pennsylvania
,
Sushil Jajodia

Copyright © 1993 ACM.

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]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 1993

Published in SIGMOD Volume 22, Issue 2

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Cited By

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https://doi.org/10.3390/ijgi13100346
Papamichalopoulos MPapadakis GMandilaras GSiampou MMamoulis NKoubarakis M(2024)Three-dimensional Geospatial Interlinking with JedAI-spatialJournal of Web Semantics10.1016/j.websem.2024.100817(100817)Online publication date: Mar-2024
https://doi.org/10.1016/j.websem.2024.100817
Wei BGuo XLi XWu ZZhao JZou Q(2024)Construct and Query A Fine-Grained Geospatial Knowledge GraphData Science and Engineering10.1007/s41019-023-00237-49:2(152-176)Online publication date: 22-Jan-2024
https://doi.org/10.1007/s41019-023-00237-4
Lee JKwon TJung S(2024)An effective spatial join method for blockchain-based geospatial data using hierarchical quadrant spatial LSM+ treeThe Journal of Supercomputing10.1007/s11227-024-06134-580:12(17492-17523)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s11227-024-06134-5
Huang YLee C(2024)Efficient processing of all neighboring object group queries with budget range constraint in road networksComputing10.1007/s00607-024-01260-7106:5(1359-1393)Online publication date: 16-Feb-2024
https://doi.org/10.1007/s00607-024-01260-7
Ukey NYang ZLi BZhang GHu YZhang W(2023)Survey on Exact kNN Queries over High-Dimensional Data SpaceSensors10.3390/s2302062923:2(629)Online publication date: 5-Jan-2023
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Vajiac CLee MKulshrestha ALevy SPark NOlligschlaeger AJones CRabbany RFaloutsos C(2023)DeltaShield: Information Theory for Human- Trafficking DetectionACM Transactions on Knowledge Discovery from Data10.1145/356304017:2(1-27)Online publication date: 30-Mar-2023
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Bhandari AHamandawana PAttique MCho HChung T(2023)ParSCL: A Parallel and Distributed Framework to Process All Nearest Neighbor Queries on a Road NetworkIEEE Access10.1109/ACCESS.2023.330868411(94043-94056)Online publication date: 2023
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Teng DBaig FPeng ZKong JWang F(2023)Efficient spatial queries over complex polygons with hybrid representationsGeoInformatica10.1007/s10707-023-00508-228:3(459-497)Online publication date: 27-Dec-2023
https://doi.org/10.1007/s10707-023-00508-2
Hu XSintos SGao JAgarwal PYang JIves ZBonifati AEl Abbadi A(2022)Computing Complex Temporal Join Queries EfficientlyProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3517893(2076-2090)Online publication date: 10-Jun-2022
https://dl.acm.org/doi/10.1145/3514221.3517893
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