fix scala 2.13

mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala

@@ -176,23 +176,18 @@ class Imputer @Since("2.2.0") (@Since("2.2.0") override val uid: String)
           .map(_.headOption.getOrElse(Double.NaN))
 
       case Imputer.mode =>
+        // Keep in line with sklearn.impute.SimpleImputer (using scipy.stats.mode).
+        // If there is more than one mode, choose the smallest one.
         val modes = dataset.select(cols: _*).rdd.flatMap { row =>
           Iterator.range(0, numCols).flatMap { i =>
             // Ignore null.
             if (row.isNullAt(i)) Iterator.empty else Iterator.single((i, row.getDouble(i)), 1L)
           }
-        }.reduceByKey(_ + _).map { case ((i, v), c) => (i, (v, c))
-        }.reduceByKey { case ((v1, c1), (v2, c2)) =>
-          if (c1 > c2) {
-            (v1, c1)
-          } else if (c1 < c2) {
-            (v2, c2)
-          } else {
-            // Keep in line with sklearn.impute.SimpleImputer (using scipy.stats.mode).
-            // If there is more than one mode, choose the smallest one.
-            (math.min(v1, v2), c1)
-          }
-        }.mapValues(_._1).collectAsMap()
+        }.reduceByKey(_ + _).map { case ((i, v), c) =>
+          // negative value to apply the default ranking of [Long, Double]
+          (i, (c, -v))
+        }.reduceByKey(Ordering.apply[(Long, Double)].max
+        ).mapValues(-_._2).collectAsMap()
         Array.tabulate(numCols)(i => modes.getOrElse(i, Double.NaN))
     }