wjddn279 opened a new pull request, #55589:
URL: https://github.com/apache/airflow/pull/55589
## Description
Hello,
While testing Airflow 3.0.6 on Kubernetes, I observed that the dag-processor
keeps restarting.
Upon checking the pod logs, I found the following error:
```
sqlalchemy.exc.OperationalError: (MySQLdb.OperationalError) (1038, 'Out of
sort memory, consider increasing server sort buffer size')
[SQL: SELECT serialized_dag.data, serialized_dag.data_compressed,
serialized_dag.id, serialized_dag.dag_id, serialized_dag.created_at,
serialized_dag.last_updated, serialized_dag.dag_hash,
serialized_dag.dag_version_id
FROM serialized_dag
WHERE serialized_dag.dag_id = %s ORDER BY serialized_dag.created_at DESC
LIMIT %s]
[parameters: ('my_dag', 1)]
(Background on this error at: https://sqlalche.me/e/14/e3q8)
```
After investigating the root cause, I found that some rows in serialized_dag
contained data values exceeding 1MB
<img width="360" height="57" alt="image"
src="https://github.com/user-attachments/assets/5748f845-8484-44bf-9ec0-a49949fffc51";
/>
Since MySQL’s default sort_buffer_size is 256KB, any row where
serialized_dag.data exceeds this size cannot fit into the buffer. As a result,
the query fails with the “Out of sort memory” error and it makes pod restart.
There are three ways to solve this problem.
- User adjusts sort buffer size (increase)
- Add index to created_at
- Modify Queries
No. 1 requires the user to change arbitrarily, and it is difficult to figure
out what side effects No. 2 will have on the system. Therefore, we propose to
change the existing query in the following way.
```
SELECT serialized_dag.data, serialized_dag.data_compressed,
serialized_dag.id, serialized_dag.dag_id, serialized_dag.created_at,
serialized_dag.last_updated, serialized_dag.dag_hash,
serialized_dag.dag_version_id
FROM serialized_dag
WHERE serialized_dag.id = (
SELECT serialized_dag.id
FROM serialized_dag
WHERE serialized_dag.dag_id = 'my_dag'
ORDER BY serialized_dag.created_at DESC
LIMIT 1
)
```
The corresponding pr is the pr that contains the change point.
Since the modified query produces the same result as the original one, no
additional test cases or changes to existing tests are required.
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