See also the stuff I did for build-asf-email.sh. Would be nice to add into that.

shell script to run parallel ALS on the netflix dataset

Integrated in Mahout-Quality #1164 (See https://builds.apache.org/job/Mahout-Quality/1164/)
MAHOUT-878 Provide better examples for the parallel ALS recommender code

ssc : http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1200366
Files :

• /mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/hadoop/als/FactorizationEvaluator.java
• /mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/hadoop/als/ParallelALSFactorizationJob.java
• /mahout/trunk/examples/bin/factorize-netflix.sh
• /mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/hadoop
• /mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/hadoop/example
• /mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/hadoop/example/als
• /mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/hadoop/example/als/netflix
• /mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/hadoop/example/als/netflix/NetflixDatasetConverter.java
• /mahout/trunk/math/src/main/java/org/apache/mahout/math/als/AlternatingLeastSquaresSolver.java

You might also do one for the Amazon product review data set at http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html That has 5.8M reviews. I've got some sequential preprocessing code that extracts out the items, converts ids to longs and gets the rating.

Would make a nice usecase but 5.8 million is a bit small for a hadoop based solution.

Sure, but most of are examples are meant to try out locally, too.

Ok. But we already have a small example using the 1 million movielens dataset for this algorithm.