You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@airflow.apache.org by "fat-catTW (via GitHub)" <gi...@apache.org> on 2026/08/07 16:25:52 UTC
[PR] Isolate scheduled DagRun creation failures with savepoints [airflow]
fat-catTW opened a new pull request, #71287:
URL: https://github.com/apache/airflow/pull/71287
<!-- SPDX-License-Identifier: Apache-2.0
https://www.apache.org/licenses/LICENSE-2.0 -->
<!--
Thank you for contributing!
Please provide above a brief description of the changes made in this pull request.
Write a good git commit message following this guide: https://chris.beams.io/posts/git-commit/
Please make sure that your code changes are covered with tests.
And in case of new features or big changes remember to adjust the documentation.
For user-facing UI changes, please attach before/after screenshots (or a short
screen recording) so reviewers can assess the visual impact.
Feel free to ping (in general) for the review if you do not see reaction for a few days
(72 Hours is the minimum reaction time you can expect from volunteers) - we sometimes miss notifications.
In case of an existing issue, reference it using one of the following:
* closes: #ISSUE
* related: #ISSUE
-->
##### Was generative AI tooling used to co-author this PR?
<!--
If generative AI tooling has been used in the process of authoring this PR, please
change below checkbox to `[X]` followed by the name of the tool, uncomment the "Generated-by".
-->
## Why
`SchedulerJobRunner._create_dag_runs` catches exceptions while creating scheduled DagRuns and then continues with the next Dag. This does not work reliably when the failure is caused by a database error, because the SQLAlchemy session can be left in a failed transaction state.
When that happens, one failing DagRun creation attempt can prevent the scheduler from creating DagRuns for other healthy Dags in the same batch.
## Solution
Wrap each scheduled DagRun creation attempt in a nested transaction/savepoint. If a database-level failure happens for one Dag, only that DagRun creation attempt is rolled back and the outer scheduler transaction remains usable.
The in-memory active run counter is updated only after the savepoint succeeds, keeping scheduler state aligned with the database transaction outcome.
A regression test covers a flush-time database failure for one Dag and verifies that another Dag in the same batch still creates its DagRun successfully.
relates: #59120
- `[X]` Yes (please specify the tool below)
Generated-by: [Codex] following [the guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#gen-ai-assisted-contributions)
---
* Read the **[Pull Request Guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#pull-request-guidelines)** for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
* For fundamental code changes, an Airflow Improvement Proposal ([AIP](https://cwiki.apache.org/confluence/display/AIRFLOW/Airflow+Improvement+Proposals)) is needed.
* When adding dependency, check compliance with the [ASF 3rd Party License Policy](https://www.apache.org/legal/resolved.html#category-x).
* For significant user-facing changes create newsfragment: `{pr_number}.significant.rst`, in [airflow-core/newsfragments](https://github.com/apache/airflow/tree/main/airflow-core/newsfragments). You can add this file in a follow-up commit after the PR is created so you know the PR number.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: commits-unsubscribe@airflow.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] Isolate scheduled DagRun creation failures with savepoints [airflow]
Posted by "fat-catTW (via GitHub)" <gi...@apache.org>.
fat-catTW commented on code in PR #71287:
URL: https://github.com/apache/airflow/pull/71287#discussion_r3764055572
##########
airflow-core/src/airflow/utils/sqlalchemy.py:
##########
@@ -635,10 +658,12 @@ class CommitProhibitorGuard:
def __init__(self, session: Session):
self.session = session
- def _validate_commit(self, _):
+ def _validate_commit(self, session):
if self.expected_commit:
self.expected_commit = False
return
+ if session.info.get(_EXPECTED_SAVEPOINT_COMMIT) and session.in_nested_transaction():
Review Comment:
Thanks for the review.
I added a short comment to make it explicit that the session-wide marker is only set around the synchronous savepoint release.
Thanks
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: commits-unsubscribe@airflow.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] Isolate scheduled DagRun creation failures with savepoints [airflow]
Posted by "potiuk (via GitHub)" <gi...@apache.org>.
potiuk commented on PR #71287:
URL: https://github.com/apache/airflow/pull/71287#issuecomment-5839240160
Hello @fat-catTW - thank you for your contributions to Apache Airflow!
The Airflow community has introduced a limit of **5 open pull requests at a time** for contributors without write access to the repository. You currently have 17 open pull requests, so - as a one-time step of introducing the limit - we closed the ones where maintainers have not engaged yet:
* #69482 - Clarify Task Instance terminal state reporting
* #69764 - Restrict asset state store access to registered tasks
* #70140 - Clean up stale KubernetesPodOperator pods
* #71112 - Skip maxed out queued DagRun candidates
* #71216 - Optimize scheduler backfill completion updates
* #71287 - Isolate scheduled DagRun creation failures with savepoints
* #71331 - Flush scheduled DagRun creation state promptly
* #71697 - Allow paused Dags to finish running DagRuns
* #72561 - Respect SMTP connection sender for task email alerts
* #72871 - Reduce XCom requests when resolving mapped task inputs
* #72917 - Handle Dag run clear errors in task SDK client
* #73037 - Deduplicate API response result conversions
These pull requests stay open because maintainers are already engaged in them - they count towards your limit:
* #71214 - Store executor callback DagRun references in the database
* #71546 - Limit Glue retry task UUID scan
* #71654 - Fix Dag run filtering for null start dates
* #72715 - Allow API clients to refresh Dag bundles
* #73169 - Add missing Amazon provider unit tests
This is **not** a judgement of you or of your changes. We never told contributors before that opening many pull requests at once was a problem, so there is nothing to feel bad about - and nothing is lost: your branches, commits and the review history stay where they are.
What we ask you to do is to make your **first prioritization decision**: choose which of the pull requests above matter most to you, and reopen them (up to 5 open at a time, including the ones still open) with the "Reopen pull request" button or `gh pr reopen <PR_NUMBER> --repo apache/airflow`. Reopen the ones you are ready to follow through - keep them rebased, respond to review comments and fix failing checks.
While your pull requests are waiting for review, the most valuable thing you can do is help in other ways - reviewing other contributors' pull requests, helping with issues, and taking part in the discussions on the devlist and Slack.
Why we introduced the limit, what it means for you and how to reopen or restore a pull request is explained in https://github.com/apache/airflow/blob/main/contributing-docs/32_open_pull_request_limit.rst.
---
Drafted-by: Claude Code (Opus 5); reviewed by @potiuk before posting
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: commits-unsubscribe@airflow.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] Isolate scheduled DagRun creation failures with savepoints [airflow]
Posted by "potiuk (via GitHub)" <gi...@apache.org>.
potiuk closed pull request #71287: Isolate scheduled DagRun creation failures with savepoints
URL: https://github.com/apache/airflow/pull/71287
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: commits-unsubscribe@airflow.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] Isolate scheduled DagRun creation failures with savepoints [airflow]
Posted by "steveahnahn (via GitHub)" <gi...@apache.org>.
steveahnahn commented on code in PR #71287:
URL: https://github.com/apache/airflow/pull/71287#discussion_r3762296105
##########
airflow-core/src/airflow/utils/sqlalchemy.py:
##########
@@ -635,10 +658,12 @@ class CommitProhibitorGuard:
def __init__(self, session: Session):
self.session = session
- def _validate_commit(self, _):
+ def _validate_commit(self, session):
if self.expected_commit:
self.expected_commit = False
return
+ if session.info.get(_EXPECTED_SAVEPOINT_COMMIT) and session.in_nested_transaction():
Review Comment:
_EXPECTED_SAVEPOINT_COMMIT is session-wide, so this exemption fires for any nested commit while it is set, not just the savepoint that set it. It's safe as written since it is only set across the synchronous savepoint.commit() on a single-threaded session but a one-line comment saying so would help, and it would need rethinking if nested savepoints ever land on this path.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: commits-unsubscribe@airflow.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org