title: Spark: save DataFrame partitioned by "virtual" column
body: <p>I'm using PySpark to do classic ETL job (load dataset, process it, save it) and want to save my Dataframe as files/directory partitioned by a "virtual" column; what I mean by "virtual" is that I have a column Timestamp which is a string containing an ISO 8601 encoded date, and I'd want to partition by Year / Month / Day; but I don't actually have either a Year, Month or Day column in the DataFrame; I have this Timestamp from which I can derive these columns though, but I don't want my resultat items to have one of these columns serialized.</p>
  
  <p>File structure resulting from saving the DataFrame to disk should look like:</p>
  
  <pre><code>/ 
      year=2016/
          month=01/
              day=01/
                  part-****.gz
  </code></pre>
  
  <p>Is there a way to do what I want with Spark / Pyspark ?</p>