DAG performance tracking in Apache Airflow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the Airflow DAG class.

Apache Airflow

from airflow.[1] import DAG

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

Ahooks

Boperators

Cmodels

Dutils

Attempts:

3 left

💡 Hint

Common Mistakes

Importing DAG from operators or hooks instead of models.

Using incorrect module names.

The DAG class is imported from the airflow.models module.

2fill in blank

medium

Complete the code to set the start date for a DAG.

Apache Airflow

from datetime import datetime

dag = DAG('example_dag', start_date=[1](2024, 1, 1))

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

Adate

Btime

Ctimedelta

Ddatetime

Attempts:

3 left

💡 Hint

Common Mistakes

Using date instead of datetime which lacks time info.

Using timedelta which is for durations, not points in time.

The start_date requires a datetime object to specify when the DAG should start running.

3fill in blank

hard

Fix the error in the code to correctly set the DAG schedule interval.

Apache Airflow

dag = DAG('example_dag', schedule_interval=[1])

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

A'@daily'

Bdaily

Ctimedelta(days=1)

D'daily'

Attempts:

3 left

💡 Hint

Common Mistakes

Using unquoted words like daily which cause syntax errors.

Using timedelta objects directly which is not accepted here.

The schedule_interval accepts cron presets as strings like '@daily'. The option daily without quotes is invalid.

4fill in blank

hard

Fill both blanks to create a task that tracks execution time using the PythonOperator.

Apache Airflow

from airflow.operators.python import PythonOperator

def track_time():
    print('Tracking execution time')

task = PythonOperator(task_id=[1], python_callable=[2], dag=dag)

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

A'track_time_task'

Btrack_time

C'execution_time'

Dprint_time

Attempts:

3 left

💡 Hint

Common Mistakes

Using a function name as task_id without quotes.

Passing a string as python_callable instead of a function reference.

The task_id must be a string identifier, here 'track_time_task'. The python_callable is the function track_time that runs when the task executes.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that tracks task durations longer than 5 minutes.

Apache Airflow

durations = {task_id: duration for task_id, duration in task_durations.items() if duration [1] [2] and task_id [3] 'task_1'}

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

A>

B300

C!=

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' causing wrong filtering.

Using '==' instead of '!=' to exclude the task.

This comprehension filters tasks with duration greater than 300 seconds (5 minutes) and excludes the task with ID 'task_1'.