Spatial partitioning techniques in spatialhadoop

Ahmed Eldawy, Louai Alarabi, Mohamed Mokbel

Research output: Chapter in Book/Report/Conference proceedingChapter

53 Citations (Scopus)

Abstract

SpatialHadoop is an extended MapReduce framework that supports global indexing that spatial partitions the data across machines providing orders of magnitude speedup, compared to traditional Hadoop. In this paper, we describe seven alternative partitioning techniques and experimentally study their effect on the quality of the generated index and the performance of range and spatial join queries. We found that using a 1% sample is enough to produce high quality partitions. Also, we found that the total area of partitions is a reasonable measure of the quality of indexes when running spatial join. This study will assist researchers in choosing a good spatial partitioning technique in distributed environments.

Original languageEnglish
Title of host publicationProceedings of the VLDB Endowment
PublisherAssociation for Computing Machinery
Pages1602-1605
Number of pages4
Volume8
Edition12
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: 11 Sep 200611 Sep 2006

Other

Other3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
CountryKorea, Republic of
CitySeoul
Period11/9/0611/9/06

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

Cite this

Eldawy, A., Alarabi, L., & Mokbel, M. (2015). Spatial partitioning techniques in spatialhadoop. In Proceedings of the VLDB Endowment (12 ed., Vol. 8, pp. 1602-1605). Association for Computing Machinery. https://doi.org/10.14778/2824032.2824057

Spatial partitioning techniques in spatialhadoop. / Eldawy, Ahmed; Alarabi, Louai; Mokbel, Mohamed.

Proceedings of the VLDB Endowment. Vol. 8 12. ed. Association for Computing Machinery, 2015. p. 1602-1605.

Research output: Chapter in Book/Report/Conference proceedingChapter

Eldawy, A, Alarabi, L & Mokbel, M 2015, Spatial partitioning techniques in spatialhadoop. in Proceedings of the VLDB Endowment. 12 edn, vol. 8, Association for Computing Machinery, pp. 1602-1605, 3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006, Seoul, Korea, Republic of, 11/9/06. https://doi.org/10.14778/2824032.2824057
Eldawy A, Alarabi L, Mokbel M. Spatial partitioning techniques in spatialhadoop. In Proceedings of the VLDB Endowment. 12 ed. Vol. 8. Association for Computing Machinery. 2015. p. 1602-1605 https://doi.org/10.14778/2824032.2824057
Eldawy, Ahmed ; Alarabi, Louai ; Mokbel, Mohamed. / Spatial partitioning techniques in spatialhadoop. Proceedings of the VLDB Endowment. Vol. 8 12. ed. Association for Computing Machinery, 2015. pp. 1602-1605
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