title: Joining 2 Dataframes on multiple columns Pandas
body: <p>Consider 2 Dataframes and need to use joining of 2 dataframes by 2 unique columns (idA, idB) and compute sum of their col Distance 
  . By the way (idA,idB) is equal to (idB,idA), so their Distance has to be summed</p>
  
  <pre><code>In [1]: df1 = pd.DataFrame({'idA': ['1', '2', '3', '2'],
     ...:                     'idB': ['1', '4', '8', '1'],
     ...:                     'Distance': ['0.727273', '0.827273', '0.127273', '0.927273']},
     ...:                     index=[0, 1, 2, 3])
     ...: 
  
  In [2]: df2 = pd.DataFrame({'idA': ['1', '5', '2', '5'],
     ...:                     'idB': ['2', '1', '4', '7'],
     ...:                     'Distance': ['0.11', '0.1', '3.0', '0.8']},
     ...:                      index=[4, 5, 6, 7])
  </code></pre>
  
  <p>The output has to be this way: </p>
  
  <pre><code>    Sum_Distance    idA idB
    0  0.727273       1   1
    1  3.827273       2   4  &lt;-- 2,4 = 3.0 + 2,4 = 0.827273
    2  0.127273       3   8
    3  1.037273       2   1  &lt;-- 2,1 = 0.927273 + 1,2 = 0.11
    4  0.1            5   1
    5  0.8            5   7
  </code></pre>
  
  <p>Help find the way how to do it using Pandas/Spark.</p>