Space: Apache Lucene Mahout (http://cwiki.apache.org/confluence/display/MAHOUT)
Page: canopy-commandline
(http://cwiki.apache.org/confluence/display/MAHOUT/canopy-commandline)
Edited by Jeff Eastman:
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h1. Running Canopy Clustering from the Command Line
Mahout's Canopy clustering can be launched from the same command line
invocation whether you are running on a single machine in stand-alone mode or
on a larger Hadoop cluster. The difference is determined by the $HADOOP_HOME
and $HADOOP_CONF_DIR environment variables. If both are set to an operating
Hadoop cluster on the target machine then the invocation will run Canopy on
that cluster. If either of the environment variables are missing then the
stand-alone Hadoop configuration will be invoked instead.
{code}
./bin/mahout canopy <OPTIONS>
{code}
* 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 0.3 release, the job will be
mahout-core-0.3.job
h2. Testing it on one single machine w/o cluster
* Put the data: cp <PATH TO DATA> testdata
* Run the Job:
{code}
./bin/mahout canopy -i testdata -o output -dm
org.apache.mahout.common.distance.CosineDistanceMeasure -ow -t1 5 -t2 2
{code}
h2. Running it on the cluster
* (As needed) Start up Hadoop: $HADOOP_HOME/bin/start-all.sh
* Put the data: $HADOOP_HOME/bin/hadoop fs -put <PATH TO DATA> testdata
* Run the Job:
{code}
export HADOOP_HOME=<Hadoop Home Directory>
export HADOOP_CONF_DIR=$HADOOP_HOME/conf
./bin/mahout canopy -i testdata -o output -dm
org.apache.mahout.common.distance.CosineDistanceMeasure -ow -t1 5 -t2 2
{code}
* Get the data out of HDFS and have a look. Use bin/hadoop fs -lsr output to
view all outputs.
h1. Command line options
{code}
--input (-i) input Path to job input directory. Must
be a SequenceFile of
VectorWritable
--output (-o) output The directory pathname for output.
--overwrite (-ow) If present, overwrite the output
directory before running job
--distanceMeasure (-dm) distanceMeasure The classname of the
DistanceMeasure. Default is
SquaredEuclidean
--t1 (-t1) t1 T1 threshold value
--t2 (-t2) t2 T2 threshold value
--clustering (-cl) If present, run clustering after
the iterations have taken place
--help (-h) Print out help
{code}
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