title: Derive multiple columns from a single column in a Spark DataFrame
body: <p>I have a DF with a huge parseable metadata as a single string column in a Dataframe, lets call it DFA, with ColmnA.</p>
  
  <p>I would like to break this column, ColmnA into multiple columns thru a function, ClassXYZ = Func1(ColmnA). This function returns a class ClassXYZ, with multiple variables, and each of these variables now has to be mapped to new Column, such a ColmnA1, ColmnA2 etc.</p>
  
  <p>How would I do such a transformation from 1 Dataframe to another with these additional columns by calling this Func1 just once, and not have to repeat-it to create all the columns.</p>
  
  <p>Its easy to solve if I were to call this huge function every time to add a new column, but that what I wish to avoid.</p>
  
  <p>Kindly please advise with a working or pseudo code.</p>
  
  <p>Thanks</p>
  
  <p>Sanjay</p>