title: Sum a column of SparseVectors in PySpark?
body: <p>I have a column of SparseVectors like this:</p>
  
  <pre><code>+--------------------+
  |      features_array|
  +--------------------+
  |(11,[1,2,3],[1.0,...|
  |(11,[1,2],[1.0,1.0])|
  |(11,[1,2],[1.0,1.0])|
  |(11,[1,4],[1.0,1.0])|
  |(11,[1,3,4],[1.0,...|
  +--------------------+
  </code></pre>
  
  <p>And just want to sum all the rows without converting to an RDD first. I should end up with just one sparse vector. I've tried a bunch of things but keep getting a bunch of schema mismatch errors.</p>
  
  <p>If I had dense vectors, the input and output would be like this:</p>
  
  <p>Input:</p>
  
  <pre><code>feature_array
  [1,2]
  [3,5] 
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>feature_array
  [4,7]
  </code></pre>