Surrounding join query processing in spatial databases

Lingxiao Li, David Taniar, Maria Indrawan-Santiago, Zhou Shao

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

2 Citations (Scopus)

Abstract

Spatial join queries play an important role in spatial database, and mostly all the distance-based join queries are based on the range search and nearest neighbour (NN), namely range join query and kNN join query. In this paper, we propose a new join query which is called surrounding join query. Given two point datasets Q and P of multidimensional objects, the surrounding query retrieves for each point in Q its all surrounding points in P. As a new spatial join query, we propose algorithms that are able to process such query efficiently. Evaluation on multiple real world datasets illustrate that our approach achieves high performance.

Original languageEnglish
Title of host publicationDatabases Theory and Applications
Subtitle of host publication28th Australasian Database Conference, ADC 2017 Brisbane, QLD, Australia, September 25–28, 2017 Proceedings
EditorsZi Huang, Xiaokui Xiao, Xin Cao
Place of PublicationCham Switzerland
PublisherSpringer
Pages17-28
Number of pages12
ISBN (Electronic)9783319681559
ISBN (Print)9783319681542
DOIs
Publication statusPublished - 2017
EventAustralasian Database Conference 2017 - Brisbane, Australia
Duration: 25 Sep 201728 Sep 2017
Conference number: 28th
http://adc-conferences.org.au/adc2017/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10538
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceAustralasian Database Conference 2017
Abbreviated titleADC 2017
CountryAustralia
CityBrisbane
Period25/09/1728/09/17
Internet address

Keywords

  • Nearest neighbour
  • Spatial database
  • Spatial indexing
  • Spatial join

Cite this

Li, L., Taniar, D., Indrawan-Santiago, M., & Shao, Z. (2017). Surrounding join query processing in spatial databases. In Z. Huang, X. Xiao, & X. Cao (Eds.), Databases Theory and Applications: 28th Australasian Database Conference, ADC 2017 Brisbane, QLD, Australia, September 25–28, 2017 Proceedings (pp. 17-28). (Lecture Notes in Computer Science ; Vol. 10538 ). Cham Switzerland: Springer. https://doi.org/10.1007/978-3-319-68155-9_2
Li, Lingxiao ; Taniar, David ; Indrawan-Santiago, Maria ; Shao, Zhou. / Surrounding join query processing in spatial databases. Databases Theory and Applications: 28th Australasian Database Conference, ADC 2017 Brisbane, QLD, Australia, September 25–28, 2017 Proceedings. editor / Zi Huang ; Xiaokui Xiao ; Xin Cao. Cham Switzerland : Springer, 2017. pp. 17-28 (Lecture Notes in Computer Science ).
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abstract = "Spatial join queries play an important role in spatial database, and mostly all the distance-based join queries are based on the range search and nearest neighbour (NN), namely range join query and kNN join query. In this paper, we propose a new join query which is called surrounding join query. Given two point datasets Q and P of multidimensional objects, the surrounding query retrieves for each point in Q its all surrounding points in P. As a new spatial join query, we propose algorithms that are able to process such query efficiently. Evaluation on multiple real world datasets illustrate that our approach achieves high performance.",
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Li, L, Taniar, D, Indrawan-Santiago, M & Shao, Z 2017, Surrounding join query processing in spatial databases. in Z Huang, X Xiao & X Cao (eds), Databases Theory and Applications: 28th Australasian Database Conference, ADC 2017 Brisbane, QLD, Australia, September 25–28, 2017 Proceedings. Lecture Notes in Computer Science , vol. 10538 , Springer, Cham Switzerland, pp. 17-28, Australasian Database Conference 2017, Brisbane, Australia, 25/09/17. https://doi.org/10.1007/978-3-319-68155-9_2

Surrounding join query processing in spatial databases. / Li, Lingxiao; Taniar, David; Indrawan-Santiago, Maria; Shao, Zhou.

Databases Theory and Applications: 28th Australasian Database Conference, ADC 2017 Brisbane, QLD, Australia, September 25–28, 2017 Proceedings. ed. / Zi Huang; Xiaokui Xiao; Xin Cao. Cham Switzerland : Springer, 2017. p. 17-28 (Lecture Notes in Computer Science ; Vol. 10538 ).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

TY - GEN

T1 - Surrounding join query processing in spatial databases

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AU - Taniar, David

AU - Indrawan-Santiago, Maria

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N2 - Spatial join queries play an important role in spatial database, and mostly all the distance-based join queries are based on the range search and nearest neighbour (NN), namely range join query and kNN join query. In this paper, we propose a new join query which is called surrounding join query. Given two point datasets Q and P of multidimensional objects, the surrounding query retrieves for each point in Q its all surrounding points in P. As a new spatial join query, we propose algorithms that are able to process such query efficiently. Evaluation on multiple real world datasets illustrate that our approach achieves high performance.

AB - Spatial join queries play an important role in spatial database, and mostly all the distance-based join queries are based on the range search and nearest neighbour (NN), namely range join query and kNN join query. In this paper, we propose a new join query which is called surrounding join query. Given two point datasets Q and P of multidimensional objects, the surrounding query retrieves for each point in Q its all surrounding points in P. As a new spatial join query, we propose algorithms that are able to process such query efficiently. Evaluation on multiple real world datasets illustrate that our approach achieves high performance.

KW - Nearest neighbour

KW - Spatial database

KW - Spatial indexing

KW - Spatial join

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Li L, Taniar D, Indrawan-Santiago M, Shao Z. Surrounding join query processing in spatial databases. In Huang Z, Xiao X, Cao X, editors, Databases Theory and Applications: 28th Australasian Database Conference, ADC 2017 Brisbane, QLD, Australia, September 25–28, 2017 Proceedings. Cham Switzerland: Springer. 2017. p. 17-28. (Lecture Notes in Computer Science ). https://doi.org/10.1007/978-3-319-68155-9_2