# 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:

- 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.
- 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 ( ©myNoSQL)

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