title: Spark: Merge columns of the same dataframe without creating additional dataframes
body: <p>I have the following data frame</p>
  <pre><code>+--------------------+-------------------+-------------+
  |                uid2|               uid1|    timestamp|
  +--------------------+-------------------+-------------+
  |a                   |b                  |1589505008851|
  |c                   |d                  |1589505012502|
  |e                   |f                  |1589505016153|
  +--------------------+-------------------+-------------+
  </code></pre>
  <p>and I want to create something like that</p>
  <pre><code>+--------------------+-------------------+
  |                uids|          timestamp|
  +--------------------+-------------------+
  |a                   |1589505008851      |
  |c                   |1589505012502      |
  |e                   |1589505016153      |
  |b                   |1589505008851      |
  |d                   |1589505012502      |
  |f                   |1589505016153      |
  +--------------------+-------------------+
  </code></pre>
  <p>so I would like to merge the <code>uid1</code> and <code>uid2</code> columns into one column. The columns have the exact same length and they are of the same data type. Can I do this without creating an additional dataframe and &quot;unioning&quot; the two? Just by referencing the columns?</p>