title: Strict partition an RDD into multiple RDDs in Spark
body: <p>I have an rdd with <code>n</code> partitions and I would like to split this rdd into <code>k</code> rdds in such a way that </p>
  
  <pre><code>rdd = rdd_1.union(rdd_2).union(rdd_3)...union(rdd_k)
  </code></pre>
  
  <p>So for example if <code>n=10</code> and <code>k=2</code> I would like to end up with 2 rdds where rdd1 is composed of 5 partitions and rdd2 is composed of the other 5 partitions.</p>
  
  <p>What is the most efficient way to do this in Spark?</p>