We present BGS (Big Graph Surfer), a scalable graph visualization tool that creates hierarchical structure from original graphs and provide interactive navigation along the hierarchy by expanding or collapsing clusters when visualizing large-scale graphs. A distributed computing framework-Spark provides the backend for BGS on clustering and visualization. This architecture makes it capable of visualizing a graph bigger than 1 billion nodes or edges in real-time after preprocessing. In addition, BGS provides a series of hierarchy and graph exploration methods, such as hierarchy view, hierarchy navigation, hierarchy search, graph view, graph navigation, graph search, and other useful interactions. These functionalities facilitate the exploration of very large-scale graphs. To evaluate the effectiveness of BGS, we apply BGS to several large-scale graph datasets, and discuss its scalability, usability, and flexibility.
Keywords: BIG DATA; CLUSTERING; GRAPH HIERARCHY; GRAPH VISUALIZATION