Just a girl in Tech

Hadoop and BigData have been two tremendous hot topic lately. Although many people want to dig into Hadoop and enjoy the benefits of Big Data, most of them don't know exactly how to do it or where to start it. This is where BigInsights is most beneficial. BigInsights is the Apache Hadoop related software from IBM , and its many built-in features and capabilities leverage your start point. First, besides having all Hadoop  ecosystem components (Hadoop, Hbase, Hive, Pig, Oozie, Zookeeper, Flume, Avro and Lucene) already working together and tested, it has a very easy-to-use install utility. If you have ever downloaded and installed Hadoop and all its components, and tried to make sure everything was working, you should know how much time a automatic installer can save. The principal value brought by BigInsights is, in my opinion, the friendly web-interface of the Hadoop tools. You don't have to program on "vim" or create MapReduce Java applications. You c...

I already talked about the Open Source Apache Mahout here , and now I'll show a dummy dummy first example of how to use its recommender system. It is a basic Java example that I used to try out Mahout. Hope it helps people starting to work with it. package myexample; import org.apache.mahout.cf.taste.common.TasteException; import org.apache.mahout.cf.taste.impl.model.XmlFile; import org.apache.mahout.cf.taste.impl.recommender.CachingRecommender; import org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender; import org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity; import org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender; import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity; import org.apache.mahout.cf.taste.similarity.ItemSimilarity; import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood; import org.apache.mahout.cf.taste.similarity.UserSimilarity; import org.apache.mahout.cf.taste....