2 files changed, 17 insertions, 3 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala
index 1cd6f2a896..377326f873 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala
@@ -35,6 +35,7 @@ import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.{Loader, Saveable}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.SparkSession
+import org.apache.spark.RangePartitioner
 
 /**
  * Regression model for isotonic regression.
@@ -408,9 +409,11 @@ class IsotonicRegression private (private var isotonic: Boolean) extends Seriali
    */
   private def parallelPoolAdjacentViolators(
       input: RDD[(Double, Double, Double)]): Array[(Double, Double, Double)] = {
-    val parallelStepResult = input
-      .sortBy(x => (x._2, x._1))
-      .glom()
+    val keyedInput = input.keyBy(_._2)
+    val parallelStepResult = keyedInput
+      .partitionBy(new RangePartitioner(keyedInput.getNumPartitions, keyedInput))
+      .values
+      .mapPartitions(p => Iterator(p.toArray.sortBy(x => (x._2, x._1))))
       .flatMap(poolAdjacentViolators)
       .collect()
       .sortBy(x => (x._2, x._1)) // Sort again because collect() doesn't promise ordering.
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala
index ea4f286575..94da626d92 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala
@@ -176,6 +176,17 @@ class IsotonicRegressionSuite extends SparkFunSuite with MLlibTestSparkContext w
     assert(model.predictions === Array(1, 2, 2))
   }
 
+  test("SPARK-16426 isotonic regression with duplicate features that produce NaNs") {
+    val trainRDD = sc.parallelize(Seq[(Double, Double, Double)]((2, 1, 1), (1, 1, 1), (0, 2, 1),
+                                                                (1, 2, 1), (0.5, 3, 1), (0, 3, 1)),
+                                  2)
+
+    val model = new IsotonicRegression().run(trainRDD)
+
+    assert(model.boundaries === Array(1.0, 3.0))
+    assert(model.predictions === Array(0.75, 0.75))
+  }
+
   test("isotonic regression prediction") {
     val model = runIsotonicRegression(Seq(1, 2, 7, 1, 2), true)