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Now that we got an order of magnitude speed improvement, and somewhat consistent response times, we are ready to stand up a test harness to prove that mapPartitions() is faster than map() when the function we are calling produces negative results when call once per record instead of once per partition.  The wrapSingleWord() function is just going to add ">>" before each word in the RDD and slap on "<<" on the backside.  And to really make the point, I've snuck in a bogus method function that burns 10 millis of clock time for each function call which is my simulation of some arbitrary expensive operation.  Just paste in the following functions separately in the shell.

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In this tightly constrained Sandbox cluster, we are seeing about 0.15 secs to execute this completely.  Now, to get mapPartitions() to work we need another method function that does the same thing, but it has to allow the whole collection of elements to be passed into the function and it needs to return a whole collection on the way back.  The following is just a jazzed up version of the earlier methodfunction.

import java.util._
import scala.collection.JavaConversions._

def wrapMultiWords(words: Iterator[String]) : Iterator[String] = {
 simulateExpensiveObjectCreation()
  val sb = new StringBuilder()
  val wList = new ArrayList[String]()
  while( words.hasNext ) {
    sb.setLength(0)
    wList.add( sb.append(">>").append(words.next()).append("<<").toString() )
  }
  return wList.iterator()
}

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