【问题标题】:Airflow on_failure_callback气流 on_failure_callback
【发布时间】:2021-05-04 03:28:23
【问题描述】:

你好希望你们一切都好我想问一个问题 最近我一直在尝试使用 airfow 并在这里玩它是一切正常的情况我有两个任务

  • read_csv
  • 进程文件

他们工作得很好我故意在 pandas Datframe 中创建了一个错字,以了解失败回调的工作原理,并查看是否触发了它似乎从日志中看出来它没有

''' 回溯(最近一次通话最后): 文件“/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py”,第 1197 行,在 handle_failure task.on_failure_callback(上下文) TypeError: on_failure_callback() 接受 0 个位置参数,但给出了 1 个 '''

这里是代码

try:

    from datetime import timedelta
    from airflow import DAG
    from airflow.operators.python_operator import PythonOperator
    from datetime import datetime
    import pandas as pd

    # Setting up Triggers
    from airflow.utils.trigger_rule import TriggerRule

    # for Getting Variables from airlfow
    from airflow.models import Variable

    print("All Dag modules are ok ......")
except Exception as e:
    print("Error  {} ".format(e))


def read_csv(**context):
    data = [{"name":"Soumil","title":"Full Stack Software Engineer"}, { "name":"Nitin","title":"Full Stack Software Engineer"},]
    df = pd.DataFramee(data=data)

    dag_config = Variable.get("VAR1")
    print("VAR 1 is : {} ".format(dag_config))
    context['ti'].xcom_push(key='mykey', value=df)


def process_file(**context):
    instance = context.get("ti").xcom_pull(key='mykey')
    print(instance.head(2))
    return "Process complete "


def on_failure_callback(**context):
    print("Fail works  !  ")



with DAG(dag_id="invoices_dag",
         schedule_interval="@once",
         default_args={
             "owner": "airflow",
             "start_date": datetime(2020, 11, 1),
             "retries": 1,
             "retry_delay": timedelta(minutes=1),
             'on_failure_callback': on_failure_callback,
         },
         catchup=False) as dag:

    read_csv = PythonOperator(
        task_id="read_csv",
        python_callable=read_csv,
        op_kwargs={'filename': "Soumil.csv"},
        provide_context=True
    )

    process_file = PythonOperator(
        task_id="process_file",
        python_callable=process_file,
        provide_context=True
    )




read_csv >> process_file





# ====================================Notes====================================

# all_success           -> triggers when all tasks arecomplete
# one_success           -> trigger when one task is complete
# all_done              -> Trigger when all Tasks are Done
# all_failed            -> Trigger when all task Failed
# one_failed            -> one task is failed
# none_failed           -> No Task Failed

# ==============================================================================



# ============================== Executor====================================

# There are Three main  types of executor
# -> Sequential Executor  run single task in linear fashion wih no parllelism default Dev
# -> Local Exector  run each task in seperate process
# -> Celery Executor Run each worker node within multi node architecture Most scalable

# ===========================================================================

【问题讨论】:

    标签: airflow


    【解决方案1】:

    你需要为你的函数指定一个参数来接收上下文,这是由于 Airflow 如何触发on_failure_callback

    def on_failure_callback(context):
        print("Fail works  !  ")
    

    请注意,在您的实施中,您无法从消息中判断哪个任务失败,因此您可能希望在错误消息中添加任务详细信息,例如:

    def on_failure_callback(context):
        ti = context['task_instance']
        print(f"task {ti.task_id } failed in dag { ti.dag_id } ")
    

    【讨论】:

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