Minor Description
I am trying to use the SparkListener interface to hook up some custom monitoring for some of our critical jobs. Among the first metrics I would like is an output row count & size metric. I'm using PySpark and the Py4J interface to implement the listener.
I am able to see the recordsRead and bytesRead metrics via the taskEnd.taskMetrics().inputMetrics().recordsRead() and .bytesRead() methods. taskEnd.taskMetrics().outputMetrics().recordsWritten() and .bytesWritten() are always 0. I see similar output if I use the stageCompleted event instead.
To trigger execution, I am using df.write.parquet(path). If I use df.rdd.saveAsTextFile(path) instead, the counts and bytes are correct.
Another clue that this bug is deeper in Spark SQL is that the Spark Application Master doesn't show the Output Size / Records column with df.write.parquet or df.write.text, but does with df.rdd.saveAsTextFile. Since the Spark Application Master also gets its output via the Listener interface, this would seem related.
There is a related PR: https://issues.apache.org/jira/browse/SPARK-21882, but I believe this to be a distinct issue.
