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Doc: Add Callbacks Section to Logging & Monitoring (#18842)
Airflow users often ask for an easy way to monitor the success or failure of tasks and/or DAGs. The use of callbacks, such as on_success_callback, helps users monitor DAG runs in an easily configurable way. This document provides an overview of available callbacks, linked to the relevant section in the Tasks document. It also provides a simple example of calling a function on any task failure in the DAG, as well as a separate function that is called upon the success of the last task in the DAG.
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.. Licensed to the Apache Software Foundation (ASF) under one | ||
or more contributor license agreements. See the NOTICE file | ||
distributed with this work for additional information | ||
regarding copyright ownership. The ASF licenses this file | ||
to you under the Apache License, Version 2.0 (the | ||
"License"); you may not use this file except in compliance | ||
with the License. You may obtain a copy of the License at | ||
.. http://www.apache.org/licenses/LICENSE-2.0 | ||
.. Unless required by applicable law or agreed to in writing, | ||
software distributed under the License is distributed on an | ||
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
KIND, either express or implied. See the License for the | ||
specific language governing permissions and limitations | ||
under the License. | ||
Callbacks | ||
========= | ||
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A valuable component of logging and monitoring is the use of task callbacks to act upon changes in state of a given task, or across all tasks in a given DAG. | ||
For example, you may wish to alert when certain tasks have failed, or have the last task in your DAG invoke a callback when it succeeds. | ||
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.. note:: | ||
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Callback functions are only invoked when the task state changes due to execution by a worker. | ||
As such, task changes set by the command line interface (:doc:`CLI <../usage-cli>`) or user interface (:doc:`UI <../ui>`) do not | ||
execute callback functions. | ||
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Callback Types | ||
-------------- | ||
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There are four types of task events that can trigger a callback: | ||
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=========================================== ================================================================ | ||
Name Description | ||
=========================================== ================================================================ | ||
``on_success_callback`` Invoked when the task :ref:`succeeds <concepts:task-instances>` | ||
``on_failure_callback`` Invoked when the task :ref:`fails <concepts:task-instances>` | ||
``sla_miss_callback`` Invoked when a task misses its defined :ref:`SLA <concepts:slas>` | ||
``on_retry_callback`` Invoked when the task is :ref:`up for retry <concepts:task-instances>` | ||
=========================================== ================================================================ | ||
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Example | ||
------- | ||
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In the following example, failures in any task call the ``task_failure_alert`` function, and success in the last task calls the ``dag_success_alert`` function: | ||
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.. code-block:: python | ||
from datetime import datetime, timedelta | ||
from airflow import DAG | ||
from airflow.operators.dummy import DummyOperator | ||
def task_failure_alert(context): | ||
print(f"Task has failed, task_instance_key_str: {context['task_instance_key_str']}") | ||
def dag_success_alert(context): | ||
print(f"DAG has succeeded, run_id: {context['run_id']}") | ||
with DAG( | ||
dag_id="example_callback", | ||
schedule_interval=None, | ||
start_date=datetime(2021, 1, 1), | ||
dagrun_timeout=timedelta(minutes=60), | ||
catchup=False, | ||
on_success_callback=None, | ||
on_failure_callback=task_failure_alert, | ||
tags=["example"], | ||
) as dag: | ||
task1 = DummyOperator(task_id="task1") | ||
task2 = DummyOperator(task_id="task2") | ||
task3 = DummyOperator(task_id="task3", on_success_callback=dag_success_alert) | ||
task1 >> task2 >> task3 |
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