Streaming and Online Algorithms for GraphX
GraphX is a resilient distributed graph processing framework on Apache Spark. It is designed for, and is good at, analysis of static graphs. However, it does not support analysis on time evolving graphs yet. In this talk, I will present graph processing research on streaming enhancements for GraphX, which may be used in both pure stream processing or lambda architectures. I will describe an architecture design, and demonstrate how it works with three machine learning algorithms, with detailed evaluation and analysis on performance and scalability.