Airflow UI overview - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to start the Airflow webserver.

Apache Airflow

airflow [1]

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

Awebserver

Bscheduler

Ctriggerer

Dworker

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'scheduler' instead of 'webserver' starts the background scheduler, not the UI.

Using 'worker' or 'triggerer' does not start the UI.

The webserver command starts the Airflow UI server where you can view DAGs and tasks.

2fill in blank

medium

Complete the URL to access the Airflow UI on the local machine.

Apache Airflow

http://localhost:[1]

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

A8080

B5000

C8000

D9000

Attempts:

3 left

💡 Hint

Common Mistakes

Using port 5000 or 8000 which are common for other web apps but not Airflow.

Using port 9000 which is unrelated.

By default, Airflow's webserver runs on port 8080, so the UI is accessed at http://localhost:8080.

3fill in blank

hard

Fix the error in the command to list all DAGs in Airflow.

Apache Airflow

airflow [1] list

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

Awebserver

Btasks

Cscheduler

Ddags

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'webserver' or 'scheduler' which are unrelated to listing DAGs.

Using 'tasks' which is for task operations, not DAG listing.

The correct command to list DAGs is airflow dags list.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps DAG ids to their owners if the owner is 'airflow'.

Apache Airflow

{dag.dag_id: dag.owner for dag in dags if dag.[1] [2] 'airflow'}

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

Aowner

B==

C!=

Ddag_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' instead of '==' causes filtering of wrong DAGs.

Using 'dag_id' instead of 'owner' in the condition.

This comprehension filters DAGs where the owner equals 'airflow' and maps their IDs to owners.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps DAG ids to their start dates if the start date is after 2023-01-01.

Apache Airflow

{dag.[1]: dag.[2] for dag in dags if dag.[3] > '2023-01-01'}

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

Adag_id

Bstart_date

Downer

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'owner' instead of 'start_date' for filtering or values.

Mixing up keys and values in the comprehension.

This comprehension creates a dictionary of DAG ids to their start dates, filtering only those starting after January 1, 2023.

Practice

1. What is the primary purpose of the Airflow UI?

easy

A. To store data files for workflows

B. To write Python code for tasks

C. To monitor and manage workflows visually

D. To configure network settings

Solution

1. Step 1: Understand Airflow UI role

   The Airflow UI is designed as a web interface to help users see and control workflows easily.

2. Step 2: Identify main function

   It shows task status, logs, and workflow structure, making monitoring and management simple.

3. Final Answer:

   To monitor and manage workflows visually -> Option C

4. Quick Check:

   Airflow UI = Monitor & Manage Workflows [OK]

Hint: Airflow UI is for watching workflows, not coding [OK]

Common Mistakes:

• Confusing UI with coding environment
• Thinking UI stores data files
• Assuming UI manages network

2. Which section in the Airflow UI shows the status of each task in a workflow?

easy

A. Admin panel

B. DAGs tab

C. Logs tab

D. Graph view

Solution

1. Step 1: Identify UI sections

   The Graph view in Airflow UI visually displays tasks and their statuses in a workflow.

2. Step 2: Compare other options

   DAGs tab lists workflows, Logs tab shows task logs, Admin panel manages users/settings.

3. Final Answer:

   Graph view -> Option D

4. Quick Check:

   Task status = Graph view [OK]

Hint: Task status is shown in Graph view, not Logs [OK]

Common Mistakes:

• Confusing Logs tab with task status
• Thinking DAGs tab shows task details
• Assuming Admin panel shows task status

3. If a task in Airflow UI shows a red color in the Graph view, what does it mean?

medium

A. Task failed

B. Task is running

C. Task succeeded

D. Task is skipped

Solution

1. Step 1: Understand color codes in Graph view

   In Airflow UI, red color indicates a failed task.

2. Step 2: Recall other colors meaning

   Green means success, yellow means running, grey means skipped.

3. Final Answer:

   Task failed -> Option A

4. Quick Check:

   Red = Failed task [OK]

Hint: Red means failure in Airflow UI Graph view [OK]

Common Mistakes:

• Mixing red with running or success
• Confusing skipped with failed
• Ignoring color legend in UI

4. You notice that the Logs tab in Airflow UI shows no logs for a task that ran. What is the likely cause?

medium

A. Task never started or failed before logging

B. Logs tab is broken and needs UI restart

C. Task succeeded without logs

D. Logs are stored in a different UI section

Solution

1. Step 1: Analyze missing logs scenario

   If no logs appear, usually the task did not start or failed before producing logs.

2. Step 2: Eliminate other options

   Logs tab usually works; success tasks still have logs; logs are not in other UI sections.

3. Final Answer:

   Task never started or failed before logging -> Option A

4. Quick Check:

   No logs = Task not started or early failure [OK]

Hint: No logs usually means task didn't start properly [OK]

Common Mistakes:

• Assuming UI bug without checking task status
• Thinking success tasks have no logs
• Looking for logs in wrong UI tabs

5. You want to quickly check the order of tasks and their dependencies in a DAG using the Airflow UI. Which view should you use and why?

hard

A. Tree view, because it shows tasks in a timeline with dependencies

B. Graph view, because it visually displays tasks and their dependencies

C. Calendar view, because it shows task schedules

D. Code view, because it shows the Python code defining tasks

Solution

1. Step 1: Identify views for task order and dependencies

   The Graph view visually shows tasks as nodes connected by arrows representing dependencies.

2. Step 2: Compare other views

   Tree view shows task runs over time, Code view shows code but not visual dependencies, Calendar shows schedules.

3. Final Answer:

   Graph view, because it visually displays tasks and their dependencies -> Option B

4. Quick Check:

   Task order & dependencies = Graph view [OK]

Hint: Use Graph view to see task dependencies clearly [OK]

Common Mistakes:

• Confusing Tree view with dependency graph
• Looking at code instead of visual graph
• Using Calendar view for dependencies