title: Join multiple spark dfs, combine array column with union of all values
body: <p>Let's say my dfs have two cols: id (int), and names (array[string])</p>
  
  <pre><code>df1: 
  1 []
  3 ['alice']
  4 ['bob']
  
  df2: 
  1 ['jack']
  2 ['breanna']
  3 []
  
  df3: 
  1 ['anna']
  3 ['rob', 'jerry']
  4 []
  </code></pre>
  
  <p>I want to combine them all into:</p>
  
  <pre><code>df_union: 
  1 ['jack', 'anna']
  2 ['breanna']
  3 ['alice','rob','jerry']
  4 ['bob']
  </code></pre>
  
  <p>This is a udf I made to help: </p>
  
  <pre><code>def appendReasonUdf =
  udf((names: Seq[String], newNames: Seq[String]) =&gt; names ++ newNames)
  </code></pre>
  
  <p>Not sure what the next best course of action is. </p>
  
  <p><code>df1.union(df2) * insert code to special handle the names col ??? *</code></p>