antonlin1 opened a new pull request, #57832:
URL: https://github.com/apache/airflow/pull/57832
Executor parallelism limit reached due to task leak in CeleryExecutor.
Addition of `celery.task_pending_timeout` to fix this.
Scenario as follows:
1. our deployment sees celery executor route a given task to team specific
celery queue, with dedicated worker
2. in my company we have scheduler along with dags deployed in many
different dcs and it happens that a specific team + their dedicated workers are
not setup in a given dc
3. thus we're in a situation where we can have dags that sends tasks to team
specific celery queue for which workers do not exist to consume said tasks
4. these tasks are not evicted from `celery_executor.running` in memory
state during scheduler lifetime. They remain indefinitely in
`celery_state.PENDING` (task instance state `RUNNING`) til' scheduler is
restarted. Thus slowly leaking tasks until executor.parallelism limit reached
- note that heartbeat nor dagrun timeout removes associated tasks from
celery_executor.running
The idea is to add a `celery.task_pending_timeout` configuration such that a
task in `celery_state.PENDING` will time out one it reaches the configured
`celery.task_pending_timeout`. This way freeing up the executor slot it was
holding.
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