Hello Pradeep, the standard betweeness and closeness measures do not scale to large graphs per se, as they require computation of all shortest paths, where even the result is quadratic in the number of vertices and therefore intractable.
U Kang has done some interesting work on finding scalable substitutes for these measures: "Centralities in large graphs" http://www.cs.cmu.edu/~ukang/papers/CentralitySDM2011.pdf These algorithms should be relatively simple to implement in Giraph, we had some students prototype them in a university course last year. Best, Sebastian On 05.02.2013 20:23, pradeep kumar wrote: > Hi all, > > Actually we are working on finding centrality for nodes in a graph > (betweenness , closeness and in-out) so far we have just implemented for > in-out and currently working on implementation of brandes alg for finding > betweenness centrality which requires finding shortest path for each node > to every node. > > Actually right now problem we are facing is passing all-nodes list at > beginning for computation of shortest paths. > > 1) Is their a method availabe to achieve this. we are using giraph 1.0..(we > couldnt find method for support in file library) > > 2) Is it possible compute shortest path for node to every other in single > superstep > > 3) or can we use master compute for such computation > > And is there any other way we can compute betweeness for nodes efficiently > in giraph.. > > Any suggestion..and..Thanks for help in advance.. >
