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KubernetesExecutor: Task stuck in queued state when using deprecated `executor_config` dict format

apache/airflow#67643·46930·Python·115 天未动·3 条评论·上游最近活跃 ·池内状态:可认领
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上游 issue 正文

### Under which category would you file this issue? Providers ### Apache Airflow version 3.3 ### What happened and how to reproduce it? When we try to run a dag with `executor_config={"KubernetesExecutor": {"config_file": "/some/path/kubeconfig.yaml"}}`, the task gets stuck in a `Queued` state on the UI for a long time and often takes over 40 minutes to fail. Further inspecting the scheduler logs shows the below: ``` → export KUBECONFIG=/Users/81045729/Documents/constant_variables/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.30.13/.kubeconfig && kubectl logs -n airflow airflow-scheduler-58dcc9f6cf-qnbvj -c scheduler 2>&1 | grep -i "Invalid executor_config\|TypeError\|error.*executor\|execute_async\|run_next\|Cannot convert\|failed\|Error\|Failed" | tail -200000 2026-05-28T12:18:23.173735Z [error ] Invalid executor_config for TaskInstanceKey(dag_id='test_k8s_executor_config_legacy', task_id='check_for_failure', run_id='manual__2026-05-28T12:18:22.589053+00:00', try_number=1, map_index=-1). Executor_config: {'KubernetesExecutor': {'config_file': '/some/path/kubeconfig.yaml'}} [airflow.providers.cncf.kubernetes.executors.kubernetes_executor.KubernetesExecutor] loc=kubernetes_executor.py:221 2026-05-28T12:18:23.174607Z [info ] Received executor event with state failed for task instance TaskInstanceKey(dag_id='test_k8s_executor_config_legacy', task_id='check_for_failure', run_id='manual__2026-05-28T12:18:22.589053+00:00', try_number=1, map_index=-1) [airflow.jobs.scheduler_job_runner.SchedulerJobRunner] loc=scheduler_job_runner.py:1251 2026-05-28T12:18:23.179662Z [info ] TaskInstance Finished: dag_id=test_k8s_executor_config_legacy, task_id=check_for_failure, run_id=manual__2026-05-28T12:18:22.589053+00:00, map_index=-1, ti_id=019e6e85-7d17-7605-aac9-7506f0cea68b, run_start_date=None, run_end_date=None, run_duration=None, state=queued, executor=KubernetesExecutor(parallelism=32), executor_state=failed, try_number=1, max_tries=0, pool=default_pool, queue…
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