title: Can I read multiple files into a Spark Dataframe from S3, passing over nonexistent ones?
body: <p>I would like to read multiple parquet files into a dataframe from S3. Currently, I'm using the following method to do this:</p>
  
  <pre><code>files = ['s3a://dev/2017/01/03/data.parquet',
           's3a://dev/2017/01/02/data.parquet']
  df = session.read.parquet(*files)
  </code></pre>
  
  <p>This works if all of the files exist on S3, but I would like to ask for a list of files to be loaded into a dataframe without breaking when some of the files in the list don't exist. In other words, I would like for sparkSql to load as many of the files as it finds into the dataframe, and return this result without complaining. Is this possible?</p>