Distributed Processing Method of Hotspot Spatial Analysis Based on Hadoop and Spark 


Vol. 45,  No. 2, pp. 99-105, Feb.  2018
10.5626/JOK.2018.45.2.99


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  Abstract

One of the spatial statistical analysis, hotspot analysis is one of easy method of see spatial patterns. It is based on the concept that "Adjacent ones are more relevant than those that are far away". However, in hotspot analysis is spatial adjacency must be considered, Therefore, distributed processing is not easy. In this paper, we proposed a distributed algorithm design for hotspot spatial analysis. Its performance was compared to standalone system and Hadoop, Spark based processing. As a result, it is compare to standalone system, Performance improvement rate of Hadoop at 625.89% and Spark at 870.14%. Furthermore, performance improvement rate is high at Spark processing than Hadoop at as more large data set.


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  Cite this article

[IEEE Style]

C. Kim, J. Lee, K. Hwang, H. Sung, "Distributed Processing Method of Hotspot Spatial Analysis Based on Hadoop and Spark," Journal of KIISE, JOK, vol. 45, no. 2, pp. 99-105, 2018. DOI: 10.5626/JOK.2018.45.2.99.


[ACM Style]

Changsoo Kim, Joosub Lee, KyuMoon Hwang, and Hyojin Sung. 2018. Distributed Processing Method of Hotspot Spatial Analysis Based on Hadoop and Spark. Journal of KIISE, JOK, 45, 2, (2018), 99-105. DOI: 10.5626/JOK.2018.45.2.99.


[KCI Style]

김창수, 이주섭, 황규문, 성효진, "하둡 및 Spark 기반 공간 통계 핫스팟 분석의 분산처리 방안 연구," 한국정보과학회 논문지, 제45권, 제2호, 99~105쪽, 2018. DOI: 10.5626/JOK.2018.45.2.99.


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