title: How to add columns of 2 RDDs to from a single RDD and then do aggregation of rows based on date data in PySpark
body: <p>I have two <code>RDDs</code> in PySpark:</p>
  
  <p><strong>RDD1:</strong></p>
  
  <pre><code>[(u'2013-01-31 00:00:00', u'a', u'Pab', u'abc', u'd'),(u'2013-01-31 00:00:00', u'a', u'ab', u'abc', u'g'),.....]
  </code></pre>
  
  <p><strong>RDD2:</strong></p>
  
  <pre><code>[(u'41',u'42.0'),(u'24',u'98.0'),....]
  </code></pre>
  
  <p>Both <code>RDDs</code> have same number or rows. Now what I want to do is take all the columns in each row from RDD1(converted from <code>unicode</code> to normal <code>string</code>) and the 2nd column from each row in RDD2 (converted from <code>unicode string</code> to <code>float</code> ) and form a new RDD with that. So the new RDD will look like this:</p>
  
  <p><strong>RDD3:</strong></p>
  
  <pre><code>[('2013-01-31 00:00:00', 'a', 'Pab', 'abc', 'd',42.0),('2013-01-31 00:00:00', 'a', 'ab', u'abc', 'g',98.0),.....]
  </code></pre>
  
  <p>Once that is done then I want to do <code>aggregation</code> of last value in each row(the float value) in this new <code>RDD3</code> by the <code>date</code> value in 1st column. That mans all the rows where <code>date</code> is <code>2013-01-31 00:00:00</code>, their last numeric values should be added.</p>
  
  <p>How can I do this in PySpark?</p>