Airflow: error: unrecognized arguments: --yes

Question

我喜欢重新运行或运行来自作曲家的 DAG，下面的命令是我用过的，但我遇到了一些像这样的例外情况

kubeconfig entry generated for europe-west1-leo-stage-bi-db7ea92f-gke.
Executing within the following Kubernetes cluster namespace: composer-1-7-7-airflow-1-10-1-db7ea92f
command terminated with exit code 2
[2020-07-14 12:44:34,472] {settings.py:176} INFO - setting.configure_orm(): Using pool settings. pool_size=5, pool_recycle=1800
[2020-07-14 12:44:35,624] {default_celery.py:80} WARNING - You have configured a result_backend of redis://airflow-redis-service.default.svc.cluster.local:6379/0, it is highly recommended to use an alternative result_backend (i.e. a database).
[2020-07-14 12:44:35,628] {__init__.py:51} INFO - Using executor CeleryExecutor
[2020-07-14 12:44:35,860] {app.py:51} WARNING - Using default Composer Environment Variables. Overrides have not been applied.
[2020-07-14 12:44:35,867] {configuration.py:516} INFO - Reading the config from /etc/airflow/airflow.cfg
[2020-07-14 12:44:35,895] {configuration.py:516} INFO - Reading the config from /etc/airflow/airflow.cfg
usage: airflow [-h]
               {backfill,list_tasks,clear,pause,unpause,trigger_dag,delete_dag,pool,variables,kerberos,render,run,initdb,list_dags,dag_state,task_failed_deps,task_state,serve_logs,test,webserver,resetdb,upgradedb,scheduler,worker,flower,version,connections,create_user}
               ...
airflow: error: unrecognized arguments: --yes

ERROR: (gcloud.composer.environments.run) kubectl returned non-zero status code.

这是我的命令，第二行我指定了参数，有人可以帮忙吗？谢谢

 gcloud composer environments run leo-stage-bi     --location=europe-west1 backfill -- regulatory_spain_monthly  -s 20190701     -e 20190702 -t  "regulatory_spain_rud_monthly_materialization"  --reset_dagruns


gcloud composer environments run project-name     --location=europe-west1 backfill -- DAG name  -s start date     -e end date -t  task in the DAG --reset_dagruns

Answer 1

要触发手动运行，您可以使用 trigger_dag 参数：

gcloud composer environments run <COMPOSER_INSTANCE_NAME> --location <LOCATION> trigger_dag -- <DAG_NAME>

Answer 2

我已经检查了 Google Cloud SDK 300.0.0 工具集中的 gcloud 实用程序中的 Airflow backfill 子命令功能，并且我已经完成了测试尝试运行 backfill 具有相同错误的操作：

airflow: error: unrecognized arguments: --yes

深入研究这个问题并为 gcloud composer environments run 命令启动 --verbosity=debug，我发现了延迟的原因：

gcloud composer environments run <ENVIRONMENT> --location=<LOCATION> --verbosity=debug backfill -- <DAG> -s <start_date> -e <end_date> -t "task_id" --reset_dagruns

DEBUG: Executing command: ['/usr/bin/kubectl', '--namespace', '', 'exec', 'airflow-worker-*', '--stdin', '--tty', '--container', 'airflow-worker', '--', 'airflow', 'backfill', '', '-s', '<start_date>', '-e', '<end_date>', '-t', 'task_id', '--reset_dagruns', '--yes']

以上输出反映了 gcloud 如何解耦命令行参数，将它们分派给 kubectl 命令继承者的方式。说到这里，我假设 --yes argument 出于未知原因被传播，甚至更错误地定位了其余参数。

寻找解决方法我正在编写对特定 Airflow worker Pod 的相关 kubectl 命令调用，手动调度 Airflow 命令行参数：

kubectl -it exec $(kubectl get po -l run=airflow-worker -o jsonpath='{.items[0].metadata.name}' \
    -n $(kubectl get ns| grep composer*| awk '{print }')) -n $(kubectl get ns| grep composer*| awk '{print }') \
    -c airflow-worker -- airflow backfill <DAG> -s <start_date> -e <end_date> -t "task_id" --reset_dagruns

到目前为止，airflow backfill 命令成功且没有抛出任何错误。

Airflow: error: unrecognized arguments: --yes

Airflow: error: unrecognized arguments: --yes

google-cloud-platform

airflow

google-cloud-composer