1 files changed, 3 insertions, 10 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java
index 2d12bdd2a6..03670383b7 100644
--- a/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java
@@ -21,7 +21,6 @@ package org.apache.spark.examples.mllib;
 import scala.Tuple2;
 
 import org.apache.spark.api.java.*;
-import org.apache.spark.api.java.function.Function;
 import org.apache.spark.mllib.classification.LogisticRegressionModel;
 import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS;
 import org.apache.spark.mllib.evaluation.MulticlassMetrics;
@@ -46,19 +45,13 @@ public class JavaMulticlassClassificationMetricsExample {
     JavaRDD<LabeledPoint> test = splits[1];
 
     // Run training algorithm to build the model.
-    final LogisticRegressionModel model = new LogisticRegressionWithLBFGS()
+    LogisticRegressionModel model = new LogisticRegressionWithLBFGS()
       .setNumClasses(3)
       .run(training.rdd());
 
     // Compute raw scores on the test set.
-    JavaRDD<Tuple2<Object, Object>> predictionAndLabels = test.map(
-      new Function<LabeledPoint, Tuple2<Object, Object>>() {
-        public Tuple2<Object, Object> call(LabeledPoint p) {
-          Double prediction = model.predict(p.features());
-          return new Tuple2<Object, Object>(prediction, p.label());
-        }
-      }
-    );
+    JavaPairRDD<Object, Object> predictionAndLabels = test.mapToPair(p ->
+      new Tuple2<>(model.predict(p.features()), p.label()));
 
     // Get evaluation metrics.
     MulticlassMetrics metrics = new MulticlassMetrics(predictionAndLabels.rdd());