[jira] [Created] (SPARK-22605) OutputMetrics empty for DataFrame writes

["Jason White (JIRA)" <ji...@apache.org>]

Jason White created SPARK-22605:
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             Summary: OutputMetrics empty for DataFrame writes
                 Key: SPARK-22605
                 URL: https://issues.apache.org/jira/browse/SPARK-22605
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.2.0
            Reporter: Jason White
            Priority: Minor


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.



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