Task failure callbacks in Apache Airflow - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a task failure callback in Airflow?

A task failure callback is a function that runs automatically when a task fails. It helps you respond to failures, like sending alerts or cleaning up resources.

beginner

How do you define a task failure callback in an Airflow DAG?

You define a Python function and assign it to the task's on_failure_callback parameter. This function receives context about the failed task.

intermediate

What kind of information can you access inside a task failure callback function?

You can access the task instance, execution date, exception details, and other context data to understand why the task failed.

intermediate

Why use task failure callbacks instead of just checking logs?

Callbacks let you automate responses like sending emails or notifications immediately after failure, saving time and reducing manual checks.

beginner

Can you use the same failure callback for multiple tasks?

Yes, you can reuse the same failure callback function for many tasks to keep your code simple and consistent.

What parameter do you use to set a failure callback on an Airflow task?

A on_retry_callback

B on_success_callback

C on_failure_callback

D on_complete_callback

The on_failure_callback parameter is used to specify a function that runs when a task fails.

What does the failure callback function receive as input?

A The task context dictionary

B The task logs only

C The DAG definition

D The Airflow scheduler

The failure callback function receives a context dictionary with details about the task and failure.

Which of these is a common use for task failure callbacks?

A Updating Airflow version

B Sending alert emails

C Changing task priority

D Starting a new DAG run

Sending alert emails is a common way to respond immediately to task failures.

Can a failure callback stop the task from failing?

A No, it only runs before the task

B Yes, it can fix the error automatically

C Yes, it prevents failure if set

D No, it runs after failure happens

Failure callbacks run after the task has failed; they do not prevent failure.

Is it possible to share one failure callback function across multiple tasks?

A Yes, it promotes code reuse

B No, each task needs a unique callback

C Only if tasks are in the same DAG

D Only for tasks with the same operator

You can reuse the same failure callback function for many tasks to keep code simple.

Explain how to create and use a task failure callback in Airflow.

Think about what happens when a task fails and how you can respond automatically.

Describe why task failure callbacks are useful in managing Airflow workflows.

Consider how you handle problems in daily tasks and how automation helps.

Practice

1. What is the main purpose of on_failure_callback in an Airflow task?

easy

A. To run a function automatically when the task fails

B. To schedule the task to run at a specific time

C. To retry the task multiple times on failure

D. To log the task's successful completion

Solution

1. Step 1: Understand the role of on_failure_callback

   This parameter is designed to specify a function that runs automatically when a task fails.

2. Step 2: Differentiate from other task features

   Scheduling and retries are handled by other parameters, not on_failure_callback.

3. Final Answer:

   To run a function automatically when the task fails -> Option A

4. Quick Check:

   Failure callback = automatic function on failure [OK]

Hint: Failure callback runs code only when task fails [OK]

Common Mistakes:

• Confusing failure callback with scheduling
• Thinking it retries the task automatically
• Assuming it runs on task success

2. Which of the following is the correct way to assign a failure callback function named notify_failure to an Airflow task?

easy

A. task = PythonOperator(failure_callback=notify_failure, ...)

B. task = PythonOperator(on_failure_callback=notify_failure, ...)

C. task = PythonOperator(on_fail_callback=notify_failure, ...)

D. task = PythonOperator(callback_on_failure=notify_failure, ...)

Solution

1. Step 1: Recall the exact parameter name

   The correct parameter to assign a failure callback is on_failure_callback.

2. Step 2: Match the parameter with the options

   Only task = PythonOperator(on_failure_callback=notify_failure, ...) uses on_failure_callback correctly.

3. Final Answer:

   task = PythonOperator(on_failure_callback=notify_failure, ...) -> Option B

4. Quick Check:

   Correct parameter name = on_failure_callback [OK]

Hint: Use exact parameter name: on_failure_callback [OK]

Common Mistakes:

• Using incorrect parameter names like failure_callback
• Swapping words in the parameter name
• Misspelling the parameter

3. Given this code snippet, what will be printed if the task fails?

def alert(context):
    print(f"Task {context['task_instance'].task_id} failed")

task = PythonOperator(
    task_id='my_task',
    python_callable=lambda: 1/0,
    on_failure_callback=alert
)

medium

A. Task succeeded

B. ZeroDivisionError

C. No output, task succeeds

D. Task my_task failed

Solution

1. Step 1: Analyze the task's python_callable

   The lambda divides 1 by 0, causing a failure (ZeroDivisionError).

2. Step 2: Understand the failure callback behavior

   On failure, the alert function runs and prints the failure message with the task ID.

3. Final Answer:

   Task my_task failed -> Option D

4. Quick Check:

   Failure triggers alert print [OK]

Hint: Failure triggers callback print message [OK]

Common Mistakes:

• Expecting ZeroDivisionError to print directly
• Thinking task succeeds despite error
• Ignoring the callback print output

4. You wrote this failure callback function:

def fail_alert():
    print("Task failed")

task = PythonOperator(
    task_id='fail_task',
    python_callable=lambda: 1/0,
    on_failure_callback=fail_alert
)

Why does the callback not run when the task fails?

medium

A. The callback function must be decorated with @task

B. The callback function must return a value

C. The callback function must accept a context parameter

D. The callback function must be async

Solution

1. Step 1: Check callback function signature

   Failure callbacks receive a context dictionary argument; missing it causes errors.

2. Step 2: Understand Airflow callback requirements

   The callback must accept one parameter (context) to work properly.

3. Final Answer:

   The callback function must accept a context parameter -> Option C

4. Quick Check:

   Callback needs context argument [OK]

Hint: Callback must accept context argument [OK]

Common Mistakes:

• Defining callback without parameters
• Expecting return value from callback
• Making callback async unnecessarily

5. You want to send an email alert only when a task fails and the failure reason contains the word "timeout". How should you implement the on_failure_callback function?

hard

A. Define a function that checks context['exception'] for 'timeout' and sends email if true

B. Define a function that always sends email regardless of failure reason

C. Use on_failure_callback to retry the task on timeout

D. Set on_failure_callback to None and handle alerts elsewhere

Solution

1. Step 1: Understand the requirement

   Send email only if failure reason contains "timeout".

2. Step 2: Use context to check exception message

   The failure callback receives context with exception info; check if 'timeout' is in the exception string.

3. Step 3: Send email conditionally

   Send email alert only if the condition is met inside the callback function.

4. Final Answer:

   Define a function that checks context['exception'] for 'timeout' and sends email if true -> Option A

5. Quick Check:

   Check exception text in callback before alert [OK]

Hint: Check exception text in callback before alert [OK]

Common Mistakes:

• Sending email on all failures without filtering
• Trying to retry task in failure callback
• Ignoring exception details in context