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

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-11578?focusedWorklogId=772131&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-772131 ]

ASF GitHub Bot logged work on BEAM-11578:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 18/May/22 21:14
            Start Date: 18/May/22 21:14
    Worklog Time Spent: 10m 
      Work Description: asf-ci commented on PR #17706:
URL: https://github.com/apache/beam/pull/17706#issuecomment-1130559029

   Can one of the admins verify this patch?




Issue Time Tracking
-------------------

    Worklog Id:     (was: 772131)
    Time Spent: 20m  (was: 10m)

> `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: Yi Hu
>            Priority: P1
>          Time Spent: 20m
>  Remaining Estimate: 0h
>
> 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`)



--
This message was sent by Atlassian Jira
(v8.20.7#820007)