Calculating a Graph's Degree Distribution Using R MapReduce over Hadoop

Marko Rodriguez is experimenting with R on Hadoop and one of his exercises is calculating a graph’s degree distribution. I confess I had to use Wikipedia for reminding what’s the definition of a node degree:

1. The degree of a node in a network (sometimes referred to incorrectly as the connectivity) is the number of connections or edges the node has to other nodes. The degree distribution P(k) of a network is then defined to be the fraction of nodes in the network with degree k.
2. The degree distribution is very important in studying both real networks, such as the Internet and social networks, and theoretical networks.

As an imagination exercise think of a graph database that’s actively maintaining an internal degree distribution and uses it to suggest or partition the graph. Would that work?

Original title and link: Calculating a Graph’s Degree Distribution Using R MapReduce over Hadoop (NoSQL database©myNoSQL)

via: http://groups.google.com/group/gremlin-users/browse_thread/thread/db50a72f92a26e06