Currently, there are two implementations of ALS available: ml.recommendation.ALS<http://spark.apache.org/docs/latest/api/python/pyspark.ml.html#module-pyspark.ml.recommendation> and mllib.recommendation.ALS<http://spark.apache.org/docs/latest/api/python/pyspark.mllib.html#module-pyspark.mllib.recommendation>
1. How do they differ in terms of performance? 2. Am I correct to assume ml.recommendation.ALS (unlike mllib) does not support key-value RDDs? If so, what is the reason? Thank you,
