title: Why number of splits are different for the same Hadoop example for Java example vs Hadoop streaming with python example from Definitive Guide
body: <p>I am executing maximum temperature example from chapter 2 of Hadoop Definitive Guide and I noticed that number of splits for Java example is different over Hadoop Streaming with Python. Can someone help me understand the reasoning behind this difference ?</p>
  
  <p>Output for Java example:</p>
  
  <pre><code>Job Counters 
                  Launched map tasks=1
                  Launched reduce tasks=1
                  Rack-local map tasks=1
                  Total time spent by all maps in occupied slots (ms)=7007
                  Total time spent by all reduces in occupied slots (ms)=5760
                  Total time spent by all map tasks (ms)=7007
                  Total time spent by all reduce tasks (ms)=5760
                  Total vcore-seconds taken by all map tasks=7007
                  Total vcore-seconds taken by all reduce tasks=5760
                  Total megabyte-seconds taken by all map tasks=7175168
                  Total megabyte-seconds taken by all reduce tasks=5898240
  </code></pre>
  
  <p>Output for Hadoop streaming with Python example:</p>
  
  <pre><code>Job Counters 
          Launched map tasks=2
          Launched reduce tasks=1
          Rack-local map tasks=2
          Total time spent by all maps in occupied slots (ms)=16730
          Total time spent by all reduces in occupied slots (ms)=4673
          Total time spent by all map tasks (ms)=16730
          Total time spent by all reduce tasks (ms)=4673
          Total vcore-seconds taken by all map tasks=16730
          Total vcore-seconds taken by all reduce tasks=4673
          Total megabyte-seconds taken by all map tasks=17131520
          Total megabyte-seconds taken by all reduce tasks=4785152
  </code></pre>