Complex Networks on Hadoop Map Reduce

Brief Introduction

JUNG is a social network API which can compute many centrality measures to study networks. Some of them include

  • Betweenness Centrality
  • degree centrality
  • Clustering Co-efficient / Transitivity
  • Closeness Centrality
  • Graph Density
  • Geodesic Distance
  • Weighted /Unweighted shortest path

If there are large number of networks, with hundreds of vertices in each network, then it would be best to process each network in parallel. I have placed the JUNG process code in the reducer. Mapper will pass different networks into separate reducers in process them in parallel.

map_reduce