title: Drop partition columns when writing parquet in pyspark
body: <p>I have a dataframe with a date column.  I have parsed it into year, month, day columns.  I want to partition on these columns, but I do not want the columns to persist in the parquet files.</p>
  
  <p>Here is my approach to partitioning and writing the data:</p>
  
  <pre><code>df = df.withColumn('year', f.year(f.col('date_col'))).withColumn('month',f.month(f.col('date_col'))).withColumn('day',f.dayofmonth(f.col('date_col')))
  
  df.write.partitionBy('year','month', 'day').parquet('/mnt/test/test.parquet')
  </code></pre>
  
  <p>This properly creates the parquet files, including the nested folder structure.  However I do not want the year, month, or day columns in the parquet files.</p>