Unless you are able to visualize the output, the decision tree rules can get difficult to interpret. Unless you implement the decision tree in the Scala language (which has a tree visualization method using the databricks Display command), some of your options are:
First parse the Spark output object to JSON format and then input using D3.js to visualize the tree. There are some prebuilt packages on Github, which can assist you in doing this.
Write the RDD you create to a file, input the RDD in Scala, and run DecisionTreeClassifier(). Then, fit the model and use the databricks display command on the model to display the tree.