title: Spark-mllib retraining saved models
body: <p>I am trying to make a classification with spark-mllib, especially using RandomForestModel. </p>
  
  <p>I have taken a look on this example from spark (RandomForestClassificationExample.scala), but I need a somewhat expanded approach.</p>
  
  <p>I need to be able to train a model, save the model for future usage, but also to be able to load it and train further. Like, extend the dataset and train again.</p>