[jira] [Commented] (BEAM-11578) `dataflow_metrics` (python) fails with TypeError (when int overflowing?)

["Beam JIRA Bot (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/BEAM-11578?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17323964#comment-17323964 ] 

Beam JIRA Bot commented on BEAM-11578:
--------------------------------------

This issue is assigned but has not received an update in 30 days so it has been labeled "stale-assigned". If you are still working on the issue, please give an update and remove the label. If you are no longer working on the issue, please unassign so someone else may work on it. In 7 days the issue will be automatically unassigned.

> `dataflow_metrics` (python) fails with TypeError (when int overflowing?)
> ------------------------------------------------------------------------
>
>                 Key: BEAM-11578
>                 URL: https://issues.apache.org/jira/browse/BEAM-11578
>             Project: Beam
>          Issue Type: Bug
>          Components: sdk-py-core
>    Affects Versions: 2.25.0
>            Reporter: Romain Yon
>            Assignee: Pablo Estrada
>            Priority: P1
>              Labels: stale-assigned
>
> Hi all,
> It seems like the python beam job I'm running is failing because of a bug in beam's metrics.
> The logic of the job appears to work and the final output is successfully being written on GCS, but the dataflow job throws and error and has a failed status:
> ```
> Traceback (most recent call last):
>  File "path/to/my/code.py", line 11, in <module>
>  MyJob().run()
>  File "/path/to/my/lib.py", line 173, in run
>  for c in result.metrics().query()["counters"]
>  File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/dataflow/dataflow_metrics.py", line 261, in query
>  self._populate_metrics(response, metric_results, user_metrics=True)
>  File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/dataflow/dataflow_metrics.py", line 188, in _populate_metrics
>  attempted = self._get_metric_value(metric['tentative'])
>  File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/dataflow/dataflow_metrics.py", line 224, in _get_metric_value
>  lambda x: x.key == 'sum').value.double_value)
> TypeError: int() argument must be a string, a bytes-like object or a number, not 'NoneType'
> ```
> Note that prior to this stacktrace, there is a logging entry:
> ```
> {"severity": "INFO", "message": "Distribution metric sum value seems to have overflowed integer_value range, the correctness of sum or mean value may not be guaranteed: <JsonValue\\n object_value: <JsonObject\\n properties: [<Property\\n key: \'count\'\\n value: <JsonValue\\n integer_value: 96>>, <Property\\n key: \'mean\'\\n value: <JsonValue\\n integer_value: 0>>, <Property\\n key: \'max\'\\n value: <JsonValue\\n integer_value: 0>>, <Property\\n key: \'min\'\\n value: <JsonValue\\n integer_value: 0>>, <Property\\n key: \'sum\'\\n value: <JsonValue\\n integer_value: 0>>]>>"}
> ```
> I guess there seems to be an issue while casting the overflowing int to a double.
> (Note: We don't really have control over the number of events being fired since the metrics are emitted by `tensorflow_transform.beam.TransformDataset`)



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