FrankYang0529 opened a new pull request, #72138:
URL: https://github.com/apache/airflow/pull/72138

   ## Why
   
   - With `[kafka_event_producer] dag_run_events_enabled = True`, the scheduler 
crashes with `sqlalchemy.orm.exc.DetachedInstanceError` when more than one Dag 
run is queued.
   - The DagRun listeners run inside the scheduler's own transaction. It moves 
queued Dag runs to RUNNING.
   - Building the Kafka producer resolves the Kafka connection. On the 
scheduler that means `MetastoreBackend.get_connection`, which is decorated with 
`@provide_session`. `create_session()` is thread-scoped, so on the scheduler's 
thread it reuses the scheduler's own session and closes it on exit.
   - The first Dag run in `_start_queued_dagruns` passes. the second crashes on 
`dag_run.dag_id`.
   
   ## How
   
   - Producer construction moves into `_build_producer`, which runs on a 
single-use `ThreadPoolExecutor`. `settings.Session` gives out one session per 
thread, so the connection lookup gets a session of its own and leaves the 
caller's transaction alone.
   
   ## Verification
   
   - `uv run --project providers/apache/kafka pytest 
providers/apache/kafka/tests/unit`
   - `breeze shell --integration kafka --backend postgres --db-reset`, then 
`pytest 
providers/apache/kafka/tests/integration/apache/kafka/plugins/test_event_producer.py
 --integration kafka`.
    <!-- 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".
   -->
   
   - [X] Yes - Claude Code
   
   <!--
   Generated-by: [Tool Name] 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: [email protected]

For queries about this service, please contact Infrastructure at:
[email protected]

Reply via email to