Large scale spatial temporal data visualization based on spark and 3D volume rendering

Abstract

In this paper, we presented a spark based analysis framework for large scale spatial temporal data such as trajectories, LBS, Noise distribution and so on. With spark, spatial temporal data can be processed, mined and the results can be saved in parallel. Then these results will be imported into spatial-indexed databases for further applications. Finally, we studied the volume rendering methods to improve the visualization for the spatial temporal analysis results. We tested our algorithm on a spark cluster. The experimental results indicate that the proposed method is efficient to process and illustrate the spatial temporal big data.