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Spatial query processing in an object-oriented database system

Author:

Jack A. OrensteinAuthors Info & Claims

ACM SIGMOD Record, Volume 15, Issue 2

Pages 326 - 336

https://doi.org/10.1145/16856.16886

Published: 15 June 1986 Publication History

Abstract

DBMSs must offer spatial query processing capabilities to meet the needs of applications such as cartography, geographic information processing and CAD. Many data structures and algorithms that process grid representations of spatial data have appeared in the literature. We unify much of this work by identifying common principles and distilling them into a small set of constructs. (Published data structures and algorithms can be derived as special cases.) We show how these constructs can be supported with only minor modifications to current DBMS implementations. The ideas are demonstrated in the context of the range query problem. Analytical and experimental evidence indicates that performance of the derived solution is very good (e.g., comparable to performance of the kd tree.)

References

[1]

D. J. Abel, J. L. Smlth. k data structure and algorlthm based on a hnear key for a rectangle retrieval problem. Computer Y#s#on, Graphics and Image Processing 27, 1 (1983), 19-31.

[2]

J. L. Bentley. Multldlmenmonal binary search trees used for assoemtlve searching. Comm ACM 18, 9 (1975), 509-517.

Digital Library

[3]

J. L. Bentley, J. H. Fr#edman. Data structures for range searching. ACM Comp. Surv. //, 4 (1979), 397-410.

Digital Library

[4]

W.A. Burkhard. Interpolation-based index maintenance. Proc. 2nd ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, (1983), 76-89.

Digital Library

[5]

N. 8. Chang, K. S. Fu. Picture query languages for p#ctorml database systems. COMPUTER 14# 11 (1981), 23-33.

[6]

$. K. Chang et al. A relatlonal database system for pictures. Proe. IEEE Workshop on Picture Data Description and Management (1977).

[7]

M. Chock et al. Database structure and mampulatlon capabilities of a p#cture database management system (PICDMS). IEEE Trans on Pattern Analy# and Machine Intelhgence 6, 4 (1984), 484-492.

[8]

U. Dayal et sl. PROBE - a research project m knowledge-oriented database systems: prehmmary analys}s. Technical Report CCA-85-03 (1985), Computer Corporation of America.

[9]

I. Gsrgantm}. An effective way to represent quadtrees. Comm. ACM 25, 12 (1982), 905-910.

Digital Library

[10]

R. L. Haskm, R. A. Lorle. On extending the functions of a relational database system. Proc. ACM SIGMOD (1982), 207-212.

Digital Library

[11]

Y. E. Lien, D. F. Utter Jr. Design of an Image database. Proe. IEEE Workshop on Picture Data Description and Management (1977).

[12]

J. H. Llou, S. B. Yao. Multldimenmonal elustertug for database orgamzation. {nformatmn Systems 2, 4 (19'/7), 187-198.

[13]

R. A. Lorle, W. Plouffe. Relatmnal databases for engineering data. IBM Research Report Rj 384'/(43914) 416/83 (1983).

[14]

M. Mantyla, M. Tammmen. Locahzed set operations for solid modehng.Computer Graphics 17, 3 (1983), 279-288.

Digital Library

[15]

T. H. Merrett. Mult#dlmenslonal paging for efficient database querying. Proe. Int'l Conference of Management of Data, Milan (1978), 2'/7-290.

[16]

T. H. Merrett, E.J. Otoo. Dynamle multipaging: a storage structure for large shared databases. Proe. 2rid Int'l Conference on Databsses# Improwng Usability and Responsiveness, Jerusalem (1982).

[17]

T. H. Merrett. Relational Information Systems, Reston Pubhshmg, Reston, Virginia (1984).

Digital Library

[18]

J N1evergelt, H. Hmterberger, K. C. Sevc}k. The grid file" an adaptable, symmetrlc multikey file structure. ACM TODS 9, 1 (1984), 38- 71.

Digital Library

[19]

J. A. Orenstem. Multidimensional tries used for assocmhve searching. Information Processmg Letters 14, 4 (1982), 150-15'/.

[20]

J. A. Orenstem. Algorlthms and data structures for the implementahon of a relatmnal database. Ph.D. thesm, McGfll Unlverslty, (1983). Also available as Techmcal Report SOCS-82-17 (1982), School of Computer Science, McGfll Umversity.

Digital Library

[21]

J A. Orenstem, T. H. Merrett. A class of data structures for assocmt}ve searching. Proc. 3rd ACM SIGACT-SIGMOD Symposmm on Principles of Database Systems (1984), 181-190.

Digital Library

[22]

J. A. Orenstem. Spatial query processing in PROBE. Working paper. To appear as a Teehmcal Report, Computer Corporation of America.

[23]

M. Ouksel, P. Scheuermann. Storage mappings for multidimensional hnear dynamic hashing. Proe. 2rid ACM SIGACT-SIGMOD Symposmm on Principles of Database Systems, (1983), 90-105.

Digital Library

[24]

J. T. Robinson. The K-D-B tree: a search structure for large multidimensional dynamic indexes. Proc. ACM SIGMOD (1981), 10-18.

Digital Library

[25]

P. Scheuermann, M. Ouksel. Multidimensional B-trees for associative searching m database systems lnformatzon Systems 7, 2 (1982), 123- 137.

[26]

J. D. Smith. The apphcatmn of data base management systems to spatial data handhng. Project report, Department of Landscape Architecture and Regional Planning, Umvermty of Massachusetts, Amherst (1984).

[27]

M. Stonebraker et al. Apphcation of abstract data types and abstract indices to CAD data. Proe. ACM SIGMOD conference on engineering design applications (1983).

[28]

M. Stonebraker. Ineluszon of new types in relational data base systems. Memorandum No. UCB/ERL M85/67, Eleetromcs Research Laboratory, College of Engineering, University of Califorma, Berkeley (1985).

[29]

H. Samet. The quadtree and related hlerarehical data structures. ACAI Comp. Surv. 16, 2 (1984), 187-260.

Digital Library

[30]

H. Samet, M. Tammmen. Bmtrees, CSG trees and time. SIGGRAPH (1985).

Digital Library

[31]

M. Samet, M. TammInen. Computing geometrm propert}es of images represented by linear quadtrees. IEEE Trans. on Pattern Analys#a and Machine Intelhgence 7, 2 (1985), 229-239.

[32]

M. Tammmen. The EXCELL method for effmlent geometrle access to data. Acta Polytechmca Scandmawca, Mathematics and Computer Selenee Series No. 34 (1981).

[33]

M. Tammmen, R. Sulonen. The EXCELL method for efflc}ent geometrle access to data. Proc 19th ACM Design Automation Conf. (1982), 345-351.

Digital Library

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Spatial query processing in an object-oriented database system
SIGMOD '86: Proceedings of the 1986 ACM SIGMOD international conference on Management of data

DBMSs must offer spatial query processing capabilities to meet the needs of applications such as cartography, geographic information processing and CAD. Many data structures and algorithms that process grid representations of spatial data have appeared ...
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Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database ...
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Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 15, Issue 2

June 1986

407 pages

ISSN:0163-5808

DOI:10.1145/16856

Editor:
Carlo Zaniolo

Issue’s Table of Contents

SIGMOD '86: Proceedings of the 1986 ACM SIGMOD international conference on Management of data
June 1986
407 pages
ISBN:0897911911
DOI:10.1145/16894
Editor:
Carlo Zaniolo

Copyright © 1986 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: 15 June 1986

Published in SIGMOD Volume 15, Issue 2

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Sung M(2023)Visibility-Based Fast Collision Detection of a Large Number of Moving Objects on GPUIEEE Access10.1109/ACCESS.2023.327719811(49456-49463)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3277198
Chen WZhu XChen GYu B(2022)Efficient Point Cloud Analysis Using Hilbert CurveComputer Vision – ECCV 202210.1007/978-3-031-20086-1_42(730-747)Online publication date: 11-Nov-2022
https://doi.org/10.1007/978-3-031-20086-1_42
Chaudhry NYousaf M(2019)Spatial querying of mineral resources using PostGIS2019 2nd International Conference on Advancements in Computational Sciences (ICACS)10.23919/ICACS.2019.8688999(1-6)Online publication date: Feb-2019
https://doi.org/10.23919/ICACS.2019.8688999
Mu WTong D(2019) On solving large p -median problems Environment and Planning B: Urban Analytics and City Science10.1177/239980831989259847:6(981-996)Online publication date: 9-Dec-2019
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Mamoulis N(2018)Spatial JoinEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_356(3598-3606)Online publication date: 7-Dec-2018
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Mokbel MAref W(2018)Space-Filling Curves for Query ProcessingEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_350(3548-3554)Online publication date: 7-Dec-2018
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Huang WZhang WZhang DMeng L(2017)Elastic Spatial Query Processing in OpenStack Cloud Computing Environment for Time-Constraint Data AnalysisISPRS International Journal of Geo-Information10.3390/ijgi60300846:3(84)Online publication date: 15-Mar-2017
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Mamoulis N(2017)Spatial JoinEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_356-2(1-9)Online publication date: 13-Jan-2017
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