Hi, I'm using the Java Api for Dataframe api for Spark-Mllib. Should I be using the RDD api instead as I'm not sure if this functionality has been ported over to dataframes, correct me if I'm wrong.
My goal is to evaluate spark's recommendation capabilities. I'm looking at this example: http://spark.apache.org/docs/latest/ml-collaborative-filtering.html Looking at the java docs I can see there is a method: http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.html "public RDD <http://spark.apache.org/docs/latest/api/java/org/apache/spark/rdd/RDD.html><scala.Tuple2<Object,Rating <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/recommendation/Rating.html>[]>> recommendUsersForProducts(int num)" For some reason the recommendProductsForUsers method isn't available in the java api: model.recommendProductsForUsers Is there something I'm missing here: I've posted my code here on this gist. I am using the dataframe api for mllib. I know there may be work to port over functionality from RDD's. https://gist.github.com/zmhassan/6ccdda8b4ad86f9b1924477c65ed5d45 Thanks, Zak
