Research on Graph Processing Systems on a Single Machine

With the rapid development of technologies such as cloud computing, the increasingly popularity of social network and other Internet applications, the data scale that human can access is growing at an unprecedented rate. Recently, technological changes associated with big data are hot in academy and industrial, and it’s meaningful to dig out the potential information in massive data. Many real-world problems can be represented as graphs, such as supply chain analysis, genealogy, web graphs, etc. Large graphs demand efficiently processing technologies to derive valuable knowledge and many graph processing engines have been developed. This paper first introduces concepts of graphs and categories of graph processing engine on a single machine. Thereafter, it focuses on analyzing and summarizing current researches about key techniques on graph processing, including data structure, parallel programing, and partitioning strategies. Finally, current research work about graph processing engine on a single machine is summarized and further research directions are pointed out.