title: Streaming or custom Jar in Hadoop
body: <p>I'm running a streaming job in Hadoop (on Amazon's EMR) with the mapper and reducer written in Python. I want to know about the speed gains I would experience if I implement the same mapper and reducer in Java (or use Pig).</p>
  
  <p>In particular, I'm looking for people's experiences on migrating from streaming to custom jar deployments and/or Pig and also documents containing benchmark comparisons of these options. I found this <a href="https://stackoverflow.com/questions/1482282/java-vs-python-on-hadoop">question</a>, but the answers are not specific enough for me. I'm not looking for comparisons between Java and Python, but comparisons between custom jar deployment in Hadoop and Python-based streaming.</p>
  
  <p>My job is reading NGram counts from the Google Books NGgram dataset and computing aggregate measures. It seems like CPU utilization on the compute nodes are close to 100%. (I would like to hear your opinions about the differences of having CPU-bound or an IO-bound job, as well).</p>
  
  <p>Thanks!</p>
  
  <p>Amaç</p>