[SPARK-21638][ML] Fix RF/GBT Warning message error

## What changes were proposed in this pull request?

When train RF model, there are many warning messages like this:

> WARN  RandomForest: Tree learning is using approximately 268492800 bytes per iteration, which exceeds requested limit maxMemoryUsage=268435456. This allows splitting 2622 nodes in this iteration.

This warning message is unnecessary and the data is not accurate.

Actually, if all the nodes cannot split in one iteration, it will show this warning. For most of the case, all the nodes cannot split just in one iteration, so for most of the case, it will show this warning for each iteration.

## How was this patch tested?
The existing UT

Author: Peng Meng <[email protected]>

Closes apache#18868 from mpjlu/fixRFwarning.

Author: Peng Meng

mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala

@@ -1089,7 +1089,8 @@ private[spark] object RandomForest extends Logging {
     var numNodesInGroup = 0
     // If maxMemoryInMB is set very small, we want to still try to split 1 node,
     // so we allow one iteration if memUsage == 0.
-    while (nodeStack.nonEmpty && (memUsage < maxMemoryUsage || memUsage == 0)) {
+    var groupDone = false
+    while (nodeStack.nonEmpty && !groupDone) {
       val (treeIndex, node) = nodeStack.top
       // Choose subset of features for node (if subsampling).
       val featureSubset: Option[Array[Int]] = if (metadata.subsamplingFeatures) {
@@ -1107,9 +1108,11 @@ private[spark] object RandomForest extends Logging {
         mutableTreeToNodeToIndexInfo
           .getOrElseUpdate(treeIndex, new mutable.HashMap[Int, NodeIndexInfo]())(node.id)
           = new NodeIndexInfo(numNodesInGroup, featureSubset)
+        numNodesInGroup += 1
+        memUsage += nodeMemUsage
+      } else {
+        groupDone = true
       }
-      numNodesInGroup += 1
-      memUsage += nodeMemUsage
     }
     if (memUsage > maxMemoryUsage) {
       // If maxMemoryUsage is 0, we should still allow splitting 1 node.