GraphX is a new component in Spark for graphs and graph-parallel computation. At a high level, GraphX extends the Spark RDD by introducing a new Graph abstraction: a directed multigraph with properties attached to each vertex and edge. To support graph computation, GraphX exposes a set of fundamental operators (e.g., subgraph, joinVertices, and aggregateMessages) as well as an optimized variant of the Pregel API. In addition, GraphX includes a growing collection of graph algorithms and builders to simplify graph analytics tasks.
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- Meng, Xiangrui; Bradley, Joseph; Yavuz, Burak; Sparks, Evan; Venkataraman, Shivaram; Liu, Davies; Freeman, Jeremy; Tsai, Db; Amde, Manish; Owen, Sean; Xin, Doris; Xin, Reynold; Franklin, Michael J.; Zadeh, Reza; Zaharia, Matei; Talwalkar, Ameet: MLlib: machine learning in Apache Spark (2016)