ExternalTaskSensor for cross-DAG dependencies in Apache Airflow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the ExternalTaskSensor from Airflow sensors.

Apache Airflow

from airflow.sensors.external_task import [1]

Drag options to blanks, or click blank then click option'

AExternalTaskSensor

BExternalSensorTask

CTaskSensorExternal

DExternalTask

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong class names like ExternalSensorTask or ExternalTask.

The correct import is ExternalTaskSensor from airflow.sensors.external_task.

2fill in blank

medium

Complete the ExternalTaskSensor to wait for a task named 'task_b' in DAG 'dag_b'.

Apache Airflow

wait_for_task = ExternalTaskSensor(
    task_id='wait_for_task_b',
    external_dag_id='[1]',
    external_task_id='task_b',
    mode='reschedule'
)

Drag options to blanks, or click blank then click option'

Atask_a

Bdag_a

Cdag_b

Dtask_b

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing external_dag_id with external_task_id.

The external_dag_id should be the DAG where the task to wait for lives, which is 'dag_b'.

3fill in blank

hard

Fix the error in the ExternalTaskSensor mode parameter to avoid blocking the worker.

Apache Airflow

wait_for_task = ExternalTaskSensor(
    task_id='wait_for_task_c',
    external_dag_id='dag_c',
    external_task_id='task_c',
    mode='[1]'
)

Drag options to blanks, or click blank then click option'

Apoke

Breschedule

Cblock

Dwait

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'poke' mode which blocks the worker.

Using mode='reschedule' allows the sensor to free the worker slot while waiting, preventing blocking.

4fill in blank

hard

Fill both blanks to create an ExternalTaskSensor that waits for 'task_x' in 'dag_x' with a 600 seconds timeout.

Apache Airflow

wait_task = ExternalTaskSensor(
    task_id='wait_task_x',
    external_dag_id='[1]',
    external_task_id='[2]',
    timeout=600
)

Drag options to blanks, or click blank then click option'

Adag_x

Btask_x

Cdag_y

Dtask_y

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping DAG and task names.

The sensor waits for task_x in dag_x, so those values fill the blanks.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps task ids to their ExternalTaskSensor instances for tasks 'task1' and 'task2' in 'dag_main'.

Apache Airflow

sensors = {
    '[1]': ExternalTaskSensor(
        task_id='wait_[1]',
        external_dag_id='[2]',
        external_task_id='[1]'
    )
    for [3] in ['task1', 'task2']
}

Drag options to blanks, or click blank then click option'

Atask

Bdag_main

Ctask_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inconsistently.

The variable name for iteration is 'task' (option D), the DAG id is 'dag_main' (option B), and the dictionary keys and sensor task ids use the iteration variable 'task'.

Practice

1. What is the main purpose of the ExternalTaskSensor in Airflow?

easy

A. To wait for a task in another DAG to complete before proceeding

B. To trigger a DAG run manually

C. To schedule DAGs at specific intervals

D. To monitor system resource usage

Solution

1. Step 1: Understand the role of ExternalTaskSensor

   The ExternalTaskSensor is designed to pause a task until a specified task in a different DAG finishes successfully.

2. Step 2: Compare with other options

   Triggering DAGs, scheduling, and monitoring resources are handled by other components, not ExternalTaskSensor.

3. Final Answer:

   To wait for a task in another DAG to complete before proceeding -> Option A

4. Quick Check:

   ExternalTaskSensor waits for cross-DAG task completion [OK]

Hint: ExternalTaskSensor waits for tasks in other DAGs [OK]

Common Mistakes:

• Confusing ExternalTaskSensor with DAG trigger
• Thinking it schedules DAGs
• Assuming it monitors system resources

2. Which of the following is the correct way to instantiate an ExternalTaskSensor to wait for task 'task_a' in DAG 'dag_1'?

easy

A. ExternalTaskSensor(task_id='wait_task', dag='dag_1', task='task_a')

B. ExternalTaskSensor(task_id='wait_task', dag_id='dag_1', task_id='task_a')

C. ExternalTaskSensor(task_id='wait_task', external_dag='dag_1', external_task='task_a')

D. ExternalTaskSensor(task_id='wait_task', external_dag_id='dag_1', external_task_id='task_a')

Solution

1. Step 1: Identify correct parameter names

   The ExternalTaskSensor requires external_dag_id and external_task_id to specify the DAG and task it waits for.

2. Step 2: Match parameters with options

   Only ExternalTaskSensor(task_id='wait_task', external_dag_id='dag_1', external_task_id='task_a') uses the correct parameter names and syntax.

3. Final Answer:

   ExternalTaskSensor(task_id='wait_task', external_dag_id='dag_1', external_task_id='task_a') -> Option D

4. Quick Check:

   Use external_dag_id and external_task_id parameters [OK]

Hint: Use external_dag_id and external_task_id parameters [OK]

Common Mistakes:

• Using wrong parameter names like dag_id or external_dag
• Confusing task_id with external_task_id
• Omitting required parameters

3. Given this snippet in DAG 'dag_2':

wait_for_task = ExternalTaskSensor(
    task_id='wait_for_task_a',
    external_dag_id='dag_1',
    external_task_id='task_a',
    mode='reschedule',
    poke_interval=30
)

wait_for_task.execute(context={})

What happens if task_a in dag_1 has not completed yet?

medium

A. The sensor waits and retries every 30 seconds without blocking a worker slot

B. The sensor immediately fails with an error

C. The sensor completes successfully without waiting

D. The sensor blocks a worker slot and retries every 30 seconds

Solution

1. Step 1: Understand mode='reschedule'

   In 'reschedule' mode, the sensor frees the worker slot between pokes, retrying after the poke_interval.

2. Step 2: Analyze behavior when task not complete

   The sensor will keep checking every 30 seconds without blocking a worker slot until the external task finishes.

3. Final Answer:

   The sensor waits and retries every 30 seconds without blocking a worker slot -> Option A

4. Quick Check:

   mode='reschedule' frees worker slot during wait [OK]

Hint: mode='reschedule' frees worker slot during wait [OK]

Common Mistakes:

• Confusing 'reschedule' with 'poke' mode
• Assuming immediate failure if task incomplete
• Thinking sensor completes without waiting

4. You wrote this ExternalTaskSensor:

wait_task = ExternalTaskSensor(
    task_id='wait_task',
    external_dag_id='dag_1',
    external_task_id='task_a',
    timeout=300
)

But the sensor never finishes even after task_a completes. What is the likely cause?

medium

A. The timeout is too high

B. The sensor's execution_date does not match the external task's execution date

C. The task_id is incorrect

D. The sensor is missing poke_interval

Solution

1. Step 1: Understand execution_date matching

   ExternalTaskSensor waits for the external task with the same execution_date by default.

2. Step 2: Identify mismatch issue

   If the sensor's execution_date differs from the external task's, it will wait forever even if the external task completed.

3. Final Answer:

   The sensor's execution_date does not match the external task's execution date -> Option B

4. Quick Check:

   Execution dates must match for ExternalTaskSensor to succeed [OK]

Hint: Check execution_date alignment between DAGs [OK]

Common Mistakes:

• Assuming timeout controls waiting for task completion
• Confusing task_id with external_task_id
• Thinking poke_interval absence causes hang

5. You want to create a cross-DAG dependency where task_b in dag_2 waits for task_a in dag_1 to succeed, but only for the same execution date. Which configuration ensures this behavior and avoids deadlocks?

hard

A. Use ExternalTaskSensor with external_dag_id='dag_1', external_task_id='task_a', and execution_date_fn=lambda x: x - timedelta(days=1)

B. Use ExternalTaskSensor with external_dag_id='dag_1', external_task_id='task_a', and execution_date_fn=lambda x: x

C. Use ExternalTaskSensor with external_dag_id='dag_1', external_task_id='task_a', and default execution_date matching

D. Use ExternalTaskSensor with external_dag_id='dag_1', external_task_id='task_a', and mode='poke' without execution_date control

Solution

1. Step 1: Understand default execution_date behavior

   By default, ExternalTaskSensor waits for the external task with the same execution_date, ensuring correct cross-DAG sync.

2. Step 2: Avoid execution_date shifts

   Using execution_date_fn to shift dates can cause deadlocks or missed dependencies.

3. Step 3: Consider mode

   mode='poke' works but does not affect execution_date matching; default is fine here.

4. Final Answer:

   Use ExternalTaskSensor with external_dag_id='dag_1', external_task_id='task_a', and default execution_date matching -> Option C

5. Quick Check:

   Default execution_date matching avoids deadlocks [OK]

Hint: Default execution_date matching avoids deadlocks [OK]

Common Mistakes:

• Shifting execution_date causing missed dependencies
• Ignoring execution_date alignment
• Misusing mode without fixing execution_date