[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, 1 insertions, 5 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
index 4b13ba6f9c..7f568f4e0d 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
@@ -29,7 +29,6 @@ import org.apache.spark.api.java.function.Function;
 import org.apache.spark.ml.evaluation.RegressionEvaluator;
 import org.apache.spark.ml.recommendation.ALS;
 import org.apache.spark.ml.recommendation.ALSModel;
-import org.apache.spark.sql.types.DataTypes;
 // $example off$
 
 public class JavaALSExample {
@@ -109,10 +108,7 @@ public class JavaALSExample {
     ALSModel model = als.fit(training);
 
     // Evaluate the model by computing the RMSE on the test data
-    Dataset<Row> rawPredictions = model.transform(test);
-    Dataset<Row> predictions = rawPredictions
-      .withColumn("rating", rawPredictions.col("rating").cast(DataTypes.DoubleType))
-      .withColumn("prediction", rawPredictions.col("prediction").cast(DataTypes.DoubleType));
+    Dataset<Row> predictions = model.transform(test);
 
     RegressionEvaluator evaluator = new RegressionEvaluator()
       .setMetricName("rmse")