title: eqNullSafe function raises error in spark 2.4.1
body: <p>I need to perform a left join in Spark 2.4.1 that keeps the Null values. </p>
  
  <p>While researching I found this solution: <a href="https://stackoverflow.com/questions/41728762/including-null-values-in-an-apache-spark-join/41729359">Including null values in an Apache Spark Join</a> which seems to be it. Everytime I call eqNullSafe however I get the error "'Column' object is not callable"</p>
  
  <p>I have tried the example provided under the link: </p>
  
  <pre><code>numbers_df = sc.parallelize([
      ("123", ), ("456", ), (None, ), ("", )
  ]).toDF(["numbers"])
  
  letters_df = sc.parallelize([
      ("123", "abc"), ("456", "def"), (None, "zzz"), ("", "hhh")
  ]).toDF(["numbers", "letters"])
  
  numbers_df.join(letters_df, numbers_df.numbers.eqNullSafe(letters_df.numbers))
  </code></pre>
  
  <p>Any idea why this code would raise these issues? I am using a SageMaker notebook on a AWS Glue developer endpoint. Might it be due to missing import? </p>
  
  <p>These are the imports I do aside from those specific to glue: </p>
  
  <pre><code>from pyspark.sql import *
  from pyspark.sql import functions as F
  </code></pre>