Apache Spark ALS collaborative filtering results. They don't make sense

Question

I wanted to try out Spark for collaborative filtering using MLlib as explained in this tutorial: https://databricks-training.s3.amazonaws.com/movie-recommendation-with-mllib.htm

Answer 1

I have tried using the same dataset and following this Spark tutorial, I get the same (subjectively bad) results.

However, using a simpler method - for instance based on Pearson Correlation as a similarity measure - instead of matrix factorization, I get much, much better results. This means I would mostly get kid movies with your input preferences and the same input ratings file.

Unless you really need the factorization (which has a lot of advantages, though), I would suggest using another recommendation method.