Creating a basic DAG file in Apache Airflow - Practice Exercises

Challenge - 5 Problems

💻 Command Output

intermediate

Output of a simple Airflow DAG run

Given this Airflow DAG code, what will be the output when the task runs successfully?

Apache Airflow

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime

def greet():
    print('Hello from Airflow!')

default_args = {
    'start_date': datetime(2024, 1, 1)
}

dag = DAG('greet_dag', default_args=default_args, schedule_interval='@daily')

task = PythonOperator(
    task_id='greet_task',
    python_callable=greet,
    dag=dag
)

A Hello from Airflow!

B Task greet_task failed

C SyntaxError: invalid syntax

D No output because DAG is paused

💡 Hint

The PythonOperator runs the greet function which prints a message.

The greet function prints 'Hello from Airflow!' when the task runs successfully.

🧠 Conceptual

intermediate

Understanding DAG schedule_interval

What does the schedule_interval='@hourly' mean in an Airflow DAG?

A The DAG runs once every minute

B The DAG runs once every day

C The DAG runs once every hour

D The DAG runs only once at start_date

💡 Hint

Think about how often '@hourly' triggers the DAG.

'@hourly' is a preset that schedules the DAG to run once every hour.

❓ Configuration

advanced

Correct DAG default_args configuration

Which option correctly sets the default_args for an Airflow DAG with a start date of January 1, 2024, and retries set to 3?

A {'start_date': datetime(2024, 1, 1), 'retries': 3}

B {'start_date': '2024-01-01', 'retries': '3'}

C {start_date: datetime(2024, 1, 1), retries: 3}

D {'start_date': datetime(2024, 1, 1), retries: 'three'}

💡 Hint

Check the types of values and syntax for dictionary keys and values.

Option A uses correct Python dictionary syntax with proper types for start_date and retries.

❓ Troubleshoot

advanced

Identifying error in DAG task definition

What error will occur with this task definition in an Airflow DAG? from airflow.operators.python import PythonOperator task = PythonOperator( task_id='task1' python_callable=lambda: print('Hi') dag=dag )

A NameError: name 'dag' is not defined

B SyntaxError: missing comma between arguments

C TypeError: python_callable must be a function

D No error, task will run successfully

💡 Hint

Look carefully at the commas separating arguments in the function call.

The task definition is missing commas between arguments, causing a SyntaxError.

🔀 Workflow

expert

Order of steps to create and run a basic Airflow DAG

What is the correct order of steps to create and run a basic Airflow DAG?

A 1,3,2,4

B 3,2,1,4

C 2,1,3,4

D 1,2,3,4

💡 Hint

Think about writing code first, then placing it, then starting services, then running.

You first write the DAG file, then place it in the DAGs folder, start Airflow services, then trigger the DAG.

Practice

1. What is the main purpose of a DAG file in Apache Airflow?

easy

A. To configure the Airflow webserver settings

B. To store logs generated by tasks

C. To install Python packages required by tasks

D. To define tasks and their schedule for workflow automation

Solution

1. Step 1: Understand what a DAG file represents

   A DAG file in Airflow is a Python script that defines a Directed Acyclic Graph, which represents tasks and their dependencies.

2. Step 2: Identify the role of the DAG file

   The DAG file schedules and organizes tasks to automate workflows, not for logging, configuration, or package installation.

3. Final Answer:

   To define tasks and their schedule for workflow automation -> Option D

4. Quick Check:

   DAG file purpose = Define tasks and schedule [OK]

Hint: DAG files define workflows, not configs or logs [OK]

Common Mistakes:

• Confusing DAG file with Airflow config files
• Thinking DAG files store logs
• Assuming DAG files install packages

2. Which of the following is the correct way to import the DAG class in an Airflow DAG file?

easy

A. import DAG from airflow.models

B. import airflow.DAG

C. from airflow.models import DAG

D. from airflow import DAG

Solution

1. Step 1: Recall the correct import syntax in Python

   Python imports use 'from module import class' syntax for specific classes.

2. Step 2: Match with Airflow's module structure

   The recommended import used in official Airflow documentation is 'from airflow.models import DAG'.

3. Final Answer:

   from airflow.models import DAG -> Option C

4. Quick Check:

   Correct import syntax = from airflow.models import DAG [OK]

Hint: Use 'from airflow.models import DAG' to import DAG class [OK]

Common Mistakes:

• Using incorrect import syntax
• Trying to import DAG directly from airflow
• Using invalid Python import statements

3. Given the following DAG snippet, what will be the task_id of the BashOperator task?

from airflow import DAG
from airflow.operators.bash import BashOperator
from datetime import datetime

default_args = {'start_date': datetime(2024, 1, 1)}
with DAG('example_dag', default_args=default_args, schedule_interval='@daily') as dag:
    task = BashOperator(task_id='print_date', bash_command='date')

medium

A. print_date

B. task

C. example_dag

D. bash_command

Solution

1. Step 1: Identify the task_id parameter in BashOperator

   The BashOperator is created with task_id='print_date', which names the task.

2. Step 2: Understand task_id usage

   task_id is the unique identifier for the task in the DAG, so the task's id is 'print_date'.

3. Final Answer:

   print_date -> Option A

4. Quick Check:

   task_id value = print_date [OK]

Hint: Look for task_id argument in operator constructor [OK]

Common Mistakes:

• Confusing variable name with task_id
• Using DAG id as task_id
• Mistaking bash_command as task_id

4. Identify the error in this DAG file snippet:

from airflow import DAG
from airflow.operators.bash import BashOperator
from datetime import datetime

with DAG('my_dag', start_date=datetime(2024, 1, 1), schedule_interval='@daily') as dag:
    task1 = BashOperator(task_id='task1', bash_command='echo Hello')
    task2 = BashOperator(task_id='task2', bash_command='echo World')
    task1 >> task2

print('DAG created')

medium

A. No error, DAG is correctly defined

B. Missing default_args dictionary for start_date

C. Incorrect import of BashOperator

D. Using print statement inside DAG context

Solution

1. Step 1: Check imports and DAG definition

   Imports are correct, DAG is created with start_date and schedule_interval directly in constructor.

2. Step 2: Verify task creation and dependencies

   Tasks are created with valid task_ids and bash commands, and dependency is set with 'task1 >> task2'.

3. Step 3: Confirm print statement usage

   Print outside DAG context is allowed and does not affect DAG creation.

4. Final Answer:

   No error, DAG is correctly defined -> Option A

5. Quick Check:

   DAG syntax correct = No error [OK]

Hint: Check if DAG and tasks follow Airflow syntax rules [OK]

Common Mistakes:

• Assuming default_args is mandatory
• Thinking print inside DAG causes error
• Confusing import paths for operators

5. You want to create a DAG that runs a task every Monday at 7 AM starting from March 1, 2024. Which schedule_interval and start_date combination is correct in the DAG definition?

hard

A. schedule_interval='@weekly', start_date=datetime(2024, 3, 4)

B. schedule_interval='0 7 * * 1', start_date=datetime(2024, 3, 1)

C. schedule_interval='@daily', start_date=datetime(2024, 3, 1, 7, 0)

D. schedule_interval='0 7 * * 0', start_date=datetime(2024, 3, 1)

Solution

1. Step 1: Determine the cron expression for Monday 7 AM

   Cron '0 7 * * 1' runs every Monday at 7:00 AM (1=Monday).

2. Step 2: Validate start_date

   March 1, 2024 (Friday) is before the first Monday (March 4), so first run on March 4, 7 AM.

3. Step 3: Eliminate other options

   A: '@weekly'='0 0 * * 0' (Sunday midnight), wrong day/time. C: daily. D: Sunday (0).

4. Final Answer:

   schedule_interval='0 7 * * 1', start_date=datetime(2024, 3, 1) -> Option B

5. Quick Check:

   Monday 7AM cron = '0 7 * * 1' [OK]

Hint: Use cron '0 7 * * 1' for Mon 7AM [OK]

Common Mistakes:

• Setting start_date on wrong weekday
• Confusing cron day numbers (0=Sunday, 1=Monday)
• Using daily schedule for weekly task