title: Mapping Spark DataSet row values into new hash column
body: <p>Given the following <code>DataSet</code> values as <code>inputData</code>:</p>
  
  <pre><code>column0 column1 column2 column3
  A       88      text    99
  Z       12      test    200
  T       120     foo     12
  </code></pre>
  
  <p>In Spark, what is an efficient way to compute a new <code>hash</code> column, and append it to a new <code>DataSet</code>, <code>hashedData</code>, where <code>hash</code> is defined as the application of <code>MurmurHash3</code> over each row value of <code>inputData</code>.</p>
  
  <p>Specifically, <code>hashedData</code> as:</p>
  
  <pre><code>column0 column1 column2 column3 hash
  A       88      text    99      MurmurHash3.arrayHash(Array("A", 88, "text", 99))
  Z       12      test    200     MurmurHash3.arrayHash(Array("Z", 12, "test", 200))
  T       120     foo     12      MurmurHash3.arrayHash(Array("T", 120, "foo", 12))
  </code></pre>
  
  <p>Please let me know if any more specifics are necessary.</p>
  
  <p>Any help is appreciated. Thanks!</p>