Introduction

This quick start page describes how to run the hadoop based recommendation jobs of Mahout Taste on a Hadoop cluster.

Steps

Testing it on one single machine w/o cluster

In the examples directory type:

 
mvn -q exec:java -Dexec.mainClass="org.apache.mahout.cf.taste.hadoop.SlopeOneDiffsAveragesJob" -Dexec.args="<OPTIONS>" 
mvn -q exec:java -Dexec.mainClass="org.apache.mahout.cf.taste.hadoop.SlopeOnePrefsToDiffsJob" -Dexec.args="<OPTIONS>" 
mvn -q exec:java -Dexec.mainClass="org.apache.mahout.cf.taste.hadoop.RecommenderJob" -Dexec.args="<OPTIONS>"

Running it on the cluster

In $MAHOUT_HOME/, build the jar containing the job (mvn install) The job will be generated in $MAHOUT_HOME/core/target/ and it's name will contain the Mahout version number. For example, when using Mahout 0.1 release, the job will be mahout-core-0.1.jar
(Optional) 1 Start up Hadoop: $HADOOP_HOME/bin/start-all.sh
Put the data: $HADOOP_HOME/bin/hadoop fs -put <PATH TO DATA> testdata
Run the Job: $HADOOP_HOME/bin/hadoop jar $MAHOUT_HOME/core/target/mahout-core-<MAHOUT VERSION>.job org.apache.mahout.cf.taste.hadoop.<JOB> <OPTIONS>
Get the data out of HDFS and have a look. Use bin/hadoop fs -lsr output to view all outputs.

Command line options

 
Usage:
SlopeOneDiffsAveragesJob and SlopeOnePrefsToDiffsJob [--input <input> --output <output> --help]                                     
Options                                                                         
  --input (-i) input      The Path for input preferences file.                  
  --output (-o) output    The directory pathname for output.             
  --help (-h)             Print out help.


Usage:                                                                          
Recommender [--recommenderClassName <recommenderClassName> --userRec <userRec> --userIdFile <userIdFile> --dataModelFile <dataModelFile> --output <output> --help]                                                                         
Options                                                                         
  --recommenderClassName (-r) recommenderClassName    Name of recommender class to use.
  --userRec (-n) userRec                              Desired number of recommendations per user.
  --userIdFile (-f) userIdFile                        File containing user ids.
  --dataModelFile (-m) dataModelFile                  File containing data model.
  --output (-o) output                                The directory pathname for output.
  --help (-h)                                         Print out help.