期刊名称：International Journal of Electronics Communication and Computer Technology
印刷版ISSN：2249-7838
出版年度：2015
卷号：5
期号：Special
出版社：International Journal of Electronics Communication and Computer Technology
摘要：Map Reduce is a widely used parallel programming model and computing platform. With Map Reduce, it is very easy to develop scalable parallel programs to process data-intensive applications on clusters. Spatial Databases such as postgreSQL, Oracle have been extensively in use to perform spatial data analysis using SQL Query manipulation. But spatial database on a single machine has its limitations with respect to the size of the datasets it can process. Some instances, Spatial Queries need to perform Spatial joins between two large data tables may take huge timespans to generate the entire set of results. In this paper, we propose a distributed approach to spatial data analysis of large data sets. We evaluated the performance and efficiency of spatial operation in Hadoop environment. It demonstrates the applicability of cloud computing technology in computing- intensive spatial applications and compared the performance with that of single spatial databases
