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Proceedings Paper

A data skew handling method based on the minimum spatial proximity for parallel spatial database
Author(s): Yan Zhou; Qing Zhu; Yeting Zhang
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Paper Abstract

Data skew is one of most important reasons to deteriorate the performance of parallel spatial database. This paper studies the issues of handling data skew in shared nothing parallel spatial database system architecture. A novel data skew handling method is proposed, which fulfill spatial data distribution balancing based on the spatial proximity of data fragments. The minimum spatial proximity is used to be the principle of moving data fragments among different network parallel nodes. Our experimental results show that the proposed data skew handling method can achieve dynamic data load balancing and offer significant improvement for reducing response time of parallel spatial queries.

Paper Details

Date Published: 15 October 2009
PDF: 7 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74921G (15 October 2009); doi: 10.1117/12.837521
Show Author Affiliations
Yan Zhou, Univ. of Electronic Science and Technology of China (China)
Qing Zhu, Wuhan Univ. (China)
Yeting Zhang, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

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