Github user jkbradley commented on a diff in the pull request:

    https://github.com/apache/spark/pull/12023#discussion_r57674670
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala ---
    @@ -238,3 +238,128 @@ private[ml] object DecisionTreeModelReadWrite {
         finalNodes.head
       }
     }
    +
    +private[ml] object RandomForestModelReadWrite {
    +
    +  /**
    +    * Info for a [[org.apache.spark.ml.tree.Split]]
    +    *
    +    * @param featureIndex  Index of feature split on
    +    * @param leftCategoriesOrThreshold  For categorical feature, set of 
leftCategories.
    +    *                                   For continuous feature, threshold.
    +    * @param numCategories  For categorical feature, number of categories.
    +    *                       For continuous feature, -1.
    +    */
    +  case class SplitData(
    +                        featureIndex: Int,
    +                        leftCategoriesOrThreshold: Array[Double],
    +                        numCategories: Int) {
    +
    +    def getSplit: Split = {
    +      if (numCategories != -1) {
    +        new CategoricalSplit(featureIndex, leftCategoriesOrThreshold, 
numCategories)
    +      } else {
    +        assert(leftCategoriesOrThreshold.length == 1, s"DecisionTree split 
data expected" +
    +          s" 1 threshold for ContinuousSplit, but found thresholds: " +
    +          leftCategoriesOrThreshold.mkString(", "))
    +        new ContinuousSplit(featureIndex, leftCategoriesOrThreshold(0))
    +      }
    +    }
    +  }
    +
    +  object SplitData {
    +    def apply(split: Split): SplitData = split match {
    +      case s: CategoricalSplit =>
    +        SplitData(s.featureIndex, s.leftCategories, s.numCategories)
    +      case s: ContinuousSplit =>
    +        SplitData(s.featureIndex, Array(s.threshold), -1)
    +    }
    +  }
    +
    +  /**
    +    * Info for a [[Node]]
    +    *
    +    * @param treeID  Index used for tree identification in RandomForest
    +    * @param id  Index used for tree reconstruction.  Indices follow a 
pre-order traversal.
    +    * @param impurityStats  Stats array.  Impurity type is stored in 
metadata.
    +    * @param gain  Gain, or arbitrary value if leaf node.
    +    * @param leftChild  Left child index, or arbitrary value if leaf node.
    +    * @param rightChild  Right child index, or arbitrary value if leaf 
node.
    +    * @param split  Split info, or arbitrary value if leaf node.
    +    */
    +  case class NodeData(
    --- End diff --
    
    Ditto for NodeData.  You can create a new class for ensembles if needed:
    ```
    case class EnsembleNodeData(treeID: Int, node: NodeData)
    ```


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