Apache Spark 2.x Cookbook

How to do it...

1. Start Spark shell or Scala shell in Databricks Cloud:

        $ spark-shell

2. Import the Alternating Least Squares (ALS) and rating classes:

        scala> import org.apache.spark.ml.recommendation.ALS         scala> import           org.apache.spark.ml.evaluation.RegressionEvaluator

3. Create a Rating case class:

        scala> case class Rating(userId: Int, movieId: Int, rating: Double, timestamp: Long)

4. Load the ratings data as a Rating dataset:

        scala> val ratings = spark.read.option("header","true").option("inferschema","true").csv("s3a://sparkcookbook/moviedata/ratings.csv").as[Rating].cache

5. Split into test and training dataset:

        scala> val Array(training, test) = ratings.randomSplit(Array(0.7, 0.3))

6. Initialize ALS() function:

        scala> val ...