Scheduler crashes when unpausing some dags with: TypeError: '>' not supported between instances of 'NoneType' and 'int'
See original GitHub issueApache Airflow version: 2.0.0
Kubernetes version (if you are using kubernetes) (use kubectl version
):
1.15
Environment:
- Cloud provider or hardware configuration: GKE
- OS (e.g. from /etc/os-release): Ubuntu 18.04
What happened: I just migrated from 1.10.14 to 2.0.0. When I turn on some random dags, the scheduler crashes with the following error:
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1275, in _execute
self._run_scheduler_loop()
File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1377, in _run_scheduler_loop
num_queued_tis = self._do_scheduling(session)
File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1533, in _do_scheduling
num_queued_tis = self._critical_section_execute_task_instances(session=session)
File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1132, in _critical_section_execute_task_instances
queued_tis = self._executable_task_instances_to_queued(max_tis, session=session)
File "/usr/local/lib/python3.6/dist-packages/airflow/utils/session.py", line 62, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1034, in _executable_task_instances_to_queued
if task_instance.pool_slots > open_slots:
TypeError: '>' not supported between instances of 'NoneType' and 'int'
What you expected to happen:
I expected those dags would have their tasks scheduled without problems.
How to reproduce it:
Can’t reproduce it yet. Still trying to figure out if this happens only with specific dags or not.
Anything else we need to know:
I couldn’t find in which context task_instance.pool_slots
could be None
Issue Analytics
- State:
- Created 3 years ago
- Comments:17 (16 by maintainers)
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Another workaround is to run the following query in your metadata db:
i’m glad i found this before opening another issue 😂
Apache Airflow version: 2.0.1
What happened: