[MINOR][ML][PYSPARK] ALS example cleanup

Cleans up ALS examples by removing unnecessary casts to double for `rating` and `prediction` columns, since `RegressionEvaluator` now supports `Double` & `Float` input types.

## How was this patch tested?

Manual compile and run with `run-example ml.ALSExample` and `spark-submit examples/src/main/python/ml/als_example.py`.

Author: Nick Pentreath <nickp@za.ibm.com>

Closes #12892 from MLnick/als-examples-cleanup.

1 files changed, 0 insertions, 6 deletions

diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
index 7c1cfe2937..6b151a622e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
@@ -23,10 +23,6 @@ import org.apache.spark.ml.evaluation.RegressionEvaluator
 import org.apache.spark.ml.recommendation.ALS
 // $example off$
 import org.apache.spark.sql.SparkSession
-// $example on$
-import org.apache.spark.sql.functions._
-import org.apache.spark.sql.types.DoubleType
-// $example off$
 
 object ALSExample {
 
@@ -65,8 +61,6 @@ object ALSExample {
 
     // Evaluate the model by computing the RMSE on the test data
     val predictions = model.transform(test)
-      .withColumn("rating", col("rating").cast(DoubleType))
-      .withColumn("prediction", col("prediction").cast(DoubleType))
 
     val evaluator = new RegressionEvaluator()
       .setMetricName("rmse")