[Spark] Collaborative Filtering, alternating least squares (ALS) practice

Collaborative Filtering - spark.mllib
http://spark.apache.org/docs/latest/mllib-collaborative-filtering.html#collaborative-filtering

In the following example we load rating data. Each row consists of a user, a product and a rating. We use the default ALS.train() method which assumes ratings are explicit. We evaluate the recommendation model by measuring the Mean Squared Error of rating prediction.

Result :
Mean Squared Error = 5.491294660658085E-6



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ERROR : taskSchedulerImpl: Initial job has not accepted any resources
http://www.datastax.com/dev/blog/common-spark-troubleshooting

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ALS
http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.mllib.recommendation.ALS$

ALS.scala
https://github.com/apache/spark/blob/v1.6.1/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala

Movie Recommendations with MLlib
https://databricks-training.s3.amazonaws.com/movie-recommendation-with-mllib.html

Dataset - MovieLens 1M Dataset
http://grouplens.org/datasets/movielens/