title: transposing few columns to row in spark dataframe
body: <p>Let's take the below dataframe as an example</p>
  
  <pre><code>+--------+-----------------------------
  |id  | fee_amount   | discount_amount | 
  |1   | 10.00        | 5.0             |
  |2   | 20.0         | 3.0             |
  </code></pre>
  
  <p>I want to be able to convert the above dataframe to following</p>
  
  <pre><code>+--------+-----------------------------
  |id  | amount_type  | discount_amount |
  |1   | fee          |   10.0          |
  |1   | discount     |   5.0           |
  |2   | fee          |   20.0          |
  |2   | discount     |   3.0           |
  </code></pre>
  
  <p>I just double the number of rows and I'm ok with that.</p>
  
  <p>I only want one column where amount value is stored and another column where a type of amount is stored. In the above example, I am given names of columns i.e. <code>fee_amount</code>, <code>discount_amount</code> that needs to be transposed. Is this even possible to do in spark dataframe? </p>