hussein-awala commented on issue #31147:
URL: https://github.com/apache/airflow/issues/31147#issuecomment-1554239929
By reading the task log, we can say that there there could be a default
timeout of 2 hours in the BigQuery client, which is not mentioned in the client
doc.
Since your job duration is less than 3 hours, can you try to set the
result_timeout parameter to 3h?
```python
insert_data = BigQueryInsertParametrizedJobOperator(
task_id=CommonTaskIds.INSERT_DATA_AND_UPDATE_VALID_DATES,
task_group=self.task_group,
gcp_conn_id=self.gcp_conn_id,
force_rerun=False,
reattach_states={"PENDING", "RUNNING", "DONE"},
job_id=kwargs.pop("job_id"),
configuration=config,
pool=self.pool,
trigger_rule=TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS,
result_timeout=3*60*60,
**kwargs,
)
```
An alternative solution can be providing a retry strategy through the
parameter `result_retry`, where the default strategy doesn't retry the query
for timeout exception.
Source code from GCP doc:
```python
def _should_retry(exc):
"""Predicate for determining when to retry.
We retry if and only if the 'reason' is 'backendError'
or 'rateLimitExceeded'.
"""
if not hasattr(exc, 'errors'):
return False
if len(exc.errors) == 0:
return False
reason = exc.errors[0]['reason']
return reason == 'backendError' or reason == 'rateLimitExceeded'
DEFAULT_RETRY = retry.Retry(predicate=_should_retry)
```
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