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https://issues.apache.org/jira/browse/BEAM-11578?focusedWorklogId=773595&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-773595
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ASF GitHub Bot logged work on BEAM-11578:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 23/May/22 16:57
Start Date: 23/May/22 16:57
Worklog Time Spent: 10m
Work Description: codecov[bot] commented on PR #17706:
URL: https://github.com/apache/beam/pull/17706#issuecomment-1134920304
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+ Misses 22624 22622 -2
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------
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Issue Time Tracking
-------------------
Worklog Id: (was: 773595)
Time Spent: 1.5h (was: 1h 20m)
> `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: 1.5h
> 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`)
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