Clustering_with_Hadoop

• The Map-Reduce paradigmhttp://cacm.acm.org/magazines/2010/1/.../fulltext was explored for knowledge discovery from nuclear reactor simulation data, as it is imminent that this data will quickly become large-scale. Hadoop[<http://hadoop.apache.org/>], which is an open-source implementation of Map-Reduce, was used for this study.
• For preliminary investigation, kmeans clusteringhttp://nlp.stanford.edu/IR-book/html/.../k-means-1.html available from mahout[<http://mahout.apache.org/>] was employed. The results were similar to the ones we published in the paper - "Knowledge Discovery from Nuclear Reactor Simulation Data".
• A few important resources to learn Map-Reduce are:
  • Book Chapter 2 in Mining of Massive Datasets by Anand Rajaraman and Jeffrey David Ullmanhttp://infolab.stanford.edu/~ullman/m.../ch2.pdf.
  • The seminal paper http://cacm.acm.org/magazines/2010/1/.../fulltext] and the wiki article [<http://en.wikipedia.org/wiki/MapReduce>].
• A few important resources for Hadoop are:
  • The tutorial at http://hadoop.apache.org/docs/r1.0.4/mapred_tutorial.html....
  • The hadoop website at [<http://hadoop.apache.org/>].
• Some resources for learning mahout are:
  • The mahout website [<http://mahout.apache.org/>].
  • As we used the kmeans clustering in mahout, https://cwiki.apache.org/confluence/d.../K-Means+Clustering gives a good introduction.
• Here are the steps for