K-means Parallelization Algorithm Based on MapReduce

Abstract

Spatial Cluster analysis is another important technique in the field of spatial data mining, especially the K-Means spatial clustering method, which can deal with spatial objects with geographical location and attribute. However, with the development of the information society, the spatial data grows explosively, but the serial algorithm has low computing efficiency and is difficult to process massive spatial data. Aiming at spatial with a double meaning of location and attribute, the paper designed and implemented KMeans spatial clustering parallel algorithm on Hadoop. Using Yahoo Weibo user data is to do clustering analysis. Finally, the visualization of clustering results was implemented by Google Map.