Logo of Humboldt-Universität zu BerlinLogo of Humboldt-Universität zu Berlin
edoc-Server
Open-Access-Publikationsserver der Humboldt-Universität
de|en
Header image: facade of Humboldt-Universität zu Berlin
View Item 
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
View Item 
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
2006-06-02Buch DOI: 10.18452/3827
Benchmarking Spatial Joins À La Carte
Günther, Oliver
Oria, Vincent
Picouet, Philippe
Saglio, Jean-Marc
Scholl, Michel
Spatial joins are join operations that involve spatial data types and operators. Spatial access methods are often used to speed up the computation of spatial joins. This paper addresses the issue of benchmarking spatial join operations. For this purpose, we first present a WWW-based tool to produce sets of rectangles. Experimentators can use a standard Web browser to specify the number of rectangles, as well as the statistical distributions of their sizes, shapes, and locations. Second, using the rectangle generator and a well-defined set of statistical models we defined several test suites to compare the performance of three spatial join algorithms: nested loop, scan-and-index, and synchronized tree traversal. We also added a real-life data set from the Sequoia 2000 storage benchmark. Our results confirm that the use of spatial indices leads to performance gains of several orders of magnitude. The tests also show that highly selective join predicates enjoy greater performance gains (and vice versa). All of the statistical models and algorithms are available on the Web, which allows for easy verification and modification of our experiments.
Files in this item
Thumbnail
50.pdf — Adobe PDF — 329.1 Kb
MD5: 8a52ea901ebf093b4e11e847f9075d60
Cite
BibTeX
EndNote
RIS
InCopyright
Details
DINI-Zertifikat 2019OpenAIRE validatedORCID Consortium
Imprint Policy Contact Data Privacy Statement
A service of University Library and Computer and Media Service
© Humboldt-Universität zu Berlin
 
DOI
10.18452/3827
Permanent URL
https://doi.org/10.18452/3827
HTML
<a href="https://doi.org/10.18452/3827">https://doi.org/10.18452/3827</a>