Tonglin Li, Chaoqi Ma, Jiabao Li, Xiaobing Zhou, Ke Wang, Dongfang Zhao, Iman Sadooghi, I. Raicu
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GRAPH/Z: A Key-Value Store Based Scalable Graph Processing System
The emerging applications in big data and social networks issue rapidly increasing demands on graph processing. Graph query operations that involve a large number of vertices and edges can be tremendously slow on traditional databases. The state-of-the-art graph processing systems and databases usually adopt master/slave architecture that potentially impairs their The contributions of this paper are as follows: scalability. This work describes the design and implementation of a new graph processing system based on Bulk Synchronous Parallel model. Our system is built on top of ZHT, a scalable distributed key-value store, which benefits the graph processing in terms of scalability, performance and persistency. The experiment results imply excellent scalability.