title: Multiple consecutive join with pyspark
body: <p>I'm trying to join multiple DF together. Because how join work, I got the same column name duplicated all over. </p>
  
  <blockquote>
    <p>When called on datasets of type (K, V) and (K, W), returns a dataset
    of (K, (V, W)) pairs with all pairs of elements for each key.</p>
  </blockquote>
  
  <pre><code># Join Min and Max to S1
  joinned_s1 = (minTime.join(maxTime, minTime["UserId"] == maxTime["UserId"]))
  
  # Join S1 and sum to s2
  joinned_s2 = (joinned_s1.join(sumTime, joinned_s1["UserId"] == sumTime["UserId"]))
  </code></pre>
  
  <p>I got this error: ""Reference 'UserId' is ambiguous, could be: UserId#1578, UserId#3014.;" </p>
  
  <p>What is the proper way of removing W from my dataset once successfully joined? </p>