# Scalable way to calculate betweenness centrality for a graph in spark

I have a use-case to calculate betweenness centrality of nodes. I have tried graphx with spark-betweenness but it is a very long running job. Has anyone successfully calculated betweenness centrality of a large network with around 10 million vertices and 100 million edges?

Sorry, I do not think you can compute the exact betweenness centrality of nodes in a graph this size, as its complexity is $$O(n\cdot m)$$ where $$n$$ is the number of nodes, $$m$$ the number of links.