A challenge that goes along with storing these large graphs across multiple machines is that there will also be communication overhead between the machines, and most likely additional storage requirements due to the same information needing to be stored on several nodes(as in assignment 3)
Levy
GraphX on Spark is a good example of storing graph info in memory of cluster. It then allows easy computation on the distributed stored graph
A challenge that goes along with storing these large graphs across multiple machines is that there will also be communication overhead between the machines, and most likely additional storage requirements due to the same information needing to be stored on several nodes(as in assignment 3)
GraphX on Spark is a good example of storing graph info in memory of cluster. It then allows easy computation on the distributed stored graph