title: How to get rows from DF that contain value None in pyspark (spark)
body: <p>In below example <code>df.a == 1</code> predicate returns correct result but <code>df.a == None</code> returns 0 when it should return 1.</p>
  
  <pre><code>l = [[1], [1], [2], [2], [None]]
  df = sc.parallelize(l).toDF(['a'])
  df    # DataFrame[a: bigint]
  df.collect()    # [Row(a=1), Row(a=1), Row(a=2), Row(a=2), Row(a=None)]
  df.where(df.a == 1).count()   # 2L
  df.where(df.a == None).count()   # 0L
  </code></pre>
  
  <p>Using Spark 1.3.1</p>