title: Sum operation on PySpark DataFrame giving TypeError when type is fine
body: <p>I have such DataFrame in PySpark (this is the result of a take(3), the dataframe is very big):</p>
  
  <pre><code>sc = SparkContext()
  df = [Row(owner=u'u1', a_d=0.1), Row(owner=u'u2', a_d=0.0), Row(owner=u'u1', a_d=0.3)]
  </code></pre>
  
  <p>the same <em>owner</em> will have more rows. What I need to do is summing the values of the field a_d per owner, after grouping, as </p>
  
  <pre><code>b = df.groupBy('owner').agg(sum('a_d').alias('a_d_sum'))
  </code></pre>
  
  <p>but this throws error</p>
  
  <blockquote>
    <p>TypeError: unsupported operand type(s) for +: 'int' and 'str'</p>
  </blockquote>
  
  <p>However, the schema contains double values, not strings (this comes from a printSchema()):</p>
  
  <pre><code>root
  |-- owner: string (nullable = true)
  |-- a_d: double (nullable = true)
  </code></pre>
  
  <p>So what is happening here?</p>