我有一个气流DAG,它有两个任务:
他们自己工作得很好。我故意在熊猫数据栏中创建了一个错误,以了解on_failure_callback是如何工作的,并查看它是否被触发。从日志上看,它似乎没有:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1197, in handle_failure
task.on_failure_callback(context)
TypeError: on_failure_callback() takes 0 positional arguments but 1 was given为什么on_failure_callback不能工作?
以下是DAG的可视化表示:

以下是代码:
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
# ===========================================================================发布于 2021-01-30 13:14:04
您需要为您的函数指定一个参数,该参数可以接收上下文,这是由于气流如何触发回调。
def on_failure_callback(context):
print("Fail works ! ")请注意,对于您的实现,您无法从消息中判断哪个任务失败了,因此您可能希望在错误消息中添加以下任务详细信息:
def on_failure_callback(context):
ti = context['task_instance']
print(f"task {ti.task_id } failed in dag { ti.dag_id } ")https://stackoverflow.com/questions/65967548
复制相似问题