我在 KubernetesPodOperator 的 DAG 设置中做错了什么

我在这个中找到了以下Airflow DAG博客文章 https://kubernetes.io/blog/2018/06/28/airflow-on-kubernetes-part-1-a-different-kind-of-operator/:

from airflow import DAG
from datetime import datetime, timedelta
from airflow.contrib.operators.kubernetes_pod_operator import KubernetesPodOperator
from airflow.operators.dummy_operator import DummyOperator


default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'start_date': datetime.utcnow(),
    'email': ['[email protected] /cdn-cgi/l/email-protection'],
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 1,
    'retry_delay': timedelta(minutes=5)
}

dag = DAG(
    'kubernetes_sample', default_args=default_args, schedule_interval=timedelta(minutes=10))


start = DummyOperator(task_id='run_this_first', dag=dag)

passing = KubernetesPodOperator(namespace='default',
                          image="Python:3.6",
                          cmds=["Python","-c"],
                          arguments=["print('hello world')"],
                          labels={"foo": "bar"},
                          name="passing-test",
                          task_id="passing-task",
                          get_logs=True,
                          dag=dag
                          )

failing = KubernetesPodOperator(namespace='default',
                          image="ubuntu:1604",
                          cmds=["Python","-c"],
                          arguments=["print('hello world')"],
                          labels={"foo": "bar"},
                          name="fail",
                          task_id="failing-task",
                          get_logs=True,
                          dag=dag
                          )

passing.set_upstream(start)
failing.set_upstream(start)

在我尝试向其中添加任何自定义内容之前...尝试按原样运行它。但是，代码在我的气流环境中似乎超时。

根据文档here https://cloud.google.com/composer/docs/how-to/using/using-kubernetes-pod-operator我尝试设置startup_timeout_seconds到像 10m 这样荒谬的东西......但仍然收到文档中描述的超时消息：

[2019-01-04 11:13:33,360] {pod_launcher.py:112} INFO - Event: fail-7dd76b92 had an event of type Pending
Traceback (most recent call last):
  File "/usr/local/bin/airflow", line 6, in <module>
    exec(compile(open(__file__).read(), __file__, 'exec'))
  File "/usr/local/lib/airflow/airflow/bin/airflow", line 27, in <module>
    args.func(args)
  File "/usr/local/lib/airflow/airflow/bin/cli.py", line 392, in run
    pool=args.pool,
  File "/usr/local/lib/airflow/airflow/utils/db.py", line 50, in wrapper
    result = func(*args, **kwargs)
  File "/usr/local/lib/airflow/airflow/models.py", line 1492, in _run_raw_task
    result = task_copy.execute(context=context)
  File "/usr/local/lib/airflow/airflow/contrib/operators/kubernetes_pod_operator.py", line 123, in execute
    raise AirflowException('Pod Launching failed: {error}'.format(error=ex))
airflow.exceptions.AirflowException: Pod Launching failed: Pod took too long to start

任何意见将不胜感激。

由于此代码未使用完全合格的图像，这意味着 Airflow 正在从hub.docker.com https://hub.docker.com/, and "Python:3.6" and "ubuntu:1604"没有可用的 docker 镜像名称Python https://hub.docker.com/_/python or Ubuntu https://hub.docker.com/_/ubuntu in hub.docker.com https://hub.docker.com/.

另外，“Python”命令不应该大写。

具有有效 docker 映像名称的工作代码将是：

from airflow import DAG
from datetime import datetime, timedelta
from airflow.contrib.operators.kubernetes_pod_operator import KubernetesPodOperator
from airflow.operators.dummy_operator import DummyOperator


default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'start_date': datetime.utcnow(),
    'email': ['[email protected] /cdn-cgi/l/email-protection'],
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 1,
    'retry_delay': timedelta(minutes=5)
}

dag = DAG(
    'kubernetes_sample', default_args=default_args, schedule_interval=timedelta(minutes=10))


start = DummyOperator(task_id='run_this_first', dag=dag)

passing = KubernetesPodOperator(namespace='default',
                          image="python:3.6-stretch",
                          cmds=["python","-c"],
                          arguments=["print('hello world')"],
                          labels={"foo": "bar"},
                          name="passing-test",
                          task_id="passing-task",
                          get_logs=True,
                          dag=dag
                          )

failing = KubernetesPodOperator(namespace='default',
                          image="ubuntu:16.04",
                          cmds=["python","-c"],
                          arguments=["print('hello world')"],
                          labels={"foo": "bar"},
                          name="fail",
                          task_id="failing-task",
                          get_logs=True,
                          dag=dag
                          )

passing.set_upstream(start)
failing.set_upstream(start)