syun64 opened a new pull request, #34126:
URL: https://github.com/apache/airflow/pull/34126
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related: https://github.com/apache/airflow/discussions/33677
Currently, Airflow supports clearing Dag runs in one of three ways:
REST API endpoint
[clear](https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/clear_dag_run)
UI button
[clearExistingTasks](https://github.com/apache/airflow/blob/9fa782f622ad9f6e568f0efcadf93595f67b8a20/airflow/www/static/js/dag/details/dagRun/ClearRun.tsx#L54)
[Task Clear cli
command](https://github.com/apache/airflow/blob/47682042a45501ab235d612580b8284a8957523e/airflow/cli/commands/task_command.py)
All three of these methods ultimately invoke [dag.clear
method](https://github.com/apache/airflow/blob/main/airflow/models/dag.py#L2129)
and put the DagRun back in a DagRunState.Queued state. Unfortunately there is
currently no way for the schedulers to know if the QUEUED DagRun is its
original scheduled run, or has been cleared from an already finished state.
The inability for Airflow or for users to distinguish between the original
scheduled DagRun, and a cleared DagRun leads to difficulty in inferring
meaningful information from reliability metrics. Some example reliability
metrics that can be used as meaningful indicators of the Airflow cluster
health, when monitoring periodic / scheduled Dags include:
[dagrun.schedule_delay](https://github.com/apache/airflow/blob/5dfbbbbf5adf70a9814121de8706a7c36f241836/airflow/jobs/scheduler_job_runner.py#L1341)
[dagrun.first_task_scheduling_delay](https://github.com/apache/airflow/blob/4037d79b5c3fe952b491a24ed99dea95c43e7666/airflow/models/dagrun.py#L954)
Each of these metrics help engineers understand if the Airflow is scheduling
DagRuns and tasks when they are meant to be scheduled. And if these metrics are
published in a reliable way, we empower engineers to be able to set up alarms
when these metrics spike. Unfortunately, these metrics spike in false-alarms
when the DagRuns are cleared.
This PR proposes that we persist the information that a DagRun was
**cleared** as a boolean attribute in the DagRun table, when the DagRun is
cleared to a 'QUEUED' state from a finished state ('SUCCESS' or 'FAILED').
Additional positive impact of introducing this boolean attribute, is that
this also exposes this information to users who may be using their own custom
operators to generate reliability metrics of their DagRuns/tasks. (e.g.
Deferrable Operators that measure SLAs as suggested in
https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-57+Refactor+SLA+Feature
and other discussions).
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