XCom size limitations and alternatives in Apache Airflow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to push a small value to XCom in an Airflow task.

Apache Airflow

task_instance.xcom_push(key='my_key', value=[1])

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

Arange(1000)

Bopen('file.txt')

Clambda x: x+1

D'small_data'

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to push large objects like files or functions to XCom.

Only small, simple data like strings or numbers should be pushed to XCom due to size limits.

2fill in blank

medium

Complete the code to pull a value from XCom in an Airflow task.

Apache Airflow

value = task_instance.xcom_pull(task_ids=[1], key='my_key')

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

ANone

B'non_existing_task'

C'previous_task'

D123

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong or non-existing task IDs when pulling XCom values.

You must specify the task ID that pushed the XCom value to pull it correctly.

3fill in blank

hard

Fix the error in the code that tries to push a large file content to XCom.

Apache Airflow

with open('large_file.txt', 'r') as f:
    content = f.read()
task_instance.xcom_push(key='file_content', value=[1])

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

Alen(content)

Bcontent

Cf

D'content'

Attempts:

3 left

💡 Hint

Common Mistakes

Pushing entire large file content causing XCom size errors.

Large file content should not be pushed directly to XCom. Instead, push a small reference like file size or path.

4fill in blank

hard

Fill both blanks to store a large result outside XCom and push its path instead.

Apache Airflow

result_path = '/tmp/result.json'
with open(result_path, 'w') as f:
    json.dump([1], f)
task_instance.xcom_push(key='result_path', value=[2])

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

Alarge_result

Bresult_path

C'large_result'

D'result_path'

Attempts:

3 left

💡 Hint

Common Mistakes

Pushing large data directly to XCom instead of a file path.

Save large data to a file and push the file path to XCom as a small reference.

5fill in blank

hard

Fill all three blanks to read a large result from a file path pulled from XCom.

Apache Airflow

result_path = task_instance.xcom_pull(task_ids=[1], key=[2])
with open(result_path, [3]) as f:
    result = json.load(f)

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

A'previous_task'

B'result_path'

C'r'

D'my_key'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong keys or task IDs when pulling XCom data.

Opening the file in wrong mode.

Pull the file path from XCom using the correct task ID and key, then open the file in read mode.

Practice

1. What is the main reason to avoid storing large data directly in Airflow's XCom?

easy

A. Because XCom automatically deletes large data after one hour

B. Because Airflow does not support any data sharing between tasks

C. Because large data can slow down Airflow and cause stability issues

D. Because large data is encrypted and cannot be read by tasks

Solution

1. Step 1: Understand XCom's purpose

   XCom is designed for small data sharing between tasks, not large data storage.

2. Step 2: Recognize impact of large data in XCom

   Storing large data in XCom can slow down Airflow and cause stability problems.

3. Final Answer:

   Because large data can slow down Airflow and cause stability issues -> Option C

4. Quick Check:

   XCom size limits = Avoid large data [OK]

Hint: Remember: XCom is for small data only [OK]

Common Mistakes:

• Thinking XCom can handle large files safely
• Believing XCom auto-deletes large data quickly
• Assuming Airflow does not support task communication

2. Which of the following is the correct way to push a small value to XCom in an Airflow PythonOperator task?

easy

A. task_instance.push_xcom('result', 123)

B. task_instance.xcom_push(key='result', value=123)

C. xcom_push(task_instance, 'result', 123)

D. task_instance.xcom('result', 123)

Solution

1. Step 1: Recall XCom push method syntax

   The correct method to push data is task_instance.xcom_push(key, value).

2. Step 2: Match the correct syntax

   task_instance.xcom_push(key='result', value=123) uses the correct method and parameter names.

3. Final Answer:

   task_instance.xcom_push(key='result', value=123) -> Option B

4. Quick Check:

   XCom push method = xcom_push(key, value) [OK]

Hint: Use xcom_push with key and value parameters [OK]

Common Mistakes:

• Using incorrect method names like push_xcom
• Omitting key or value parameters
• Calling xcom as a method instead of xcom_push

3. Given the following code snippet in an Airflow task, what will be the output when retrieving the XCom value?

def push_func(ti):
    ti.xcom_push(key='data', value='small string')

def pull_func(ti):
    return ti.xcom_pull(key='data', task_ids='push_task')

# Assume push_func runs first and then pull_func runs
result = pull_func(ti)

medium

A. Empty string

B. None

C. KeyError

D. 'small string'

Solution

1. Step 1: Understand XCom push and pull sequence

   The first task pushes 'small string' with key 'data'. The second task pulls it using the same key and task id.

2. Step 2: Predict the pull result

   Since the key and task id match, the pull returns the pushed value 'small string'.

3. Final Answer:

   'small string' -> Option D

4. Quick Check:

   XCom pull returns pushed value if keys match [OK]

Hint: Pull returns pushed value if keys and task_ids match [OK]

Common Mistakes:

• Expecting None if tasks run in order
• Confusing key names or task_ids
• Assuming pull returns error if no data

4. You tried to push a large file content directly into XCom but Airflow throws an error. What is the best way to fix this issue?

medium

A. Store the large file in external storage and push only its reference in XCom

B. Increase Airflow's XCom size limit in the configuration file

C. Split the large file into many small pieces and push each piece separately in XCom

D. Disable XCom size checks in Airflow's source code

Solution

1. Step 1: Identify the cause of the error

   Airflow limits XCom size; pushing large files directly causes errors.

2. Step 2: Choose the best practice alternative

   Storing large data externally and pushing only a reference keeps Airflow stable and avoids errors.

3. Final Answer:

   Store the large file in external storage and push only its reference in XCom -> Option A

4. Quick Check:

   Large data in XCom? Use external storage reference [OK]

Hint: Use external storage for large data, push reference only [OK]

Common Mistakes:

• Trying to increase XCom size limit (not supported)
• Splitting data manually is complex and error-prone
• Modifying Airflow source code is risky and unnecessary

5. You have a DAG where a task generates a large JSON report. You want to pass this report to the next task without slowing down Airflow. Which approach is best?

hard

A. Save the JSON report to an S3 bucket and push the S3 path via XCom

B. Serialize the JSON report and push it directly in XCom

C. Convert the JSON to a string and push it in XCom without size check

D. Store the JSON report in Airflow variables and read it in the next task

Solution

1. Step 1: Recognize XCom size limits

   Large JSON data should not be pushed directly to XCom to avoid performance issues.

2. Step 2: Select best alternative for large data sharing

   Saving the report externally (e.g., S3) and pushing only the path keeps Airflow fast and stable.

3. Final Answer:

   Save the JSON report to an S3 bucket and push the S3 path via XCom -> Option A

4. Quick Check:

   Large data? Use external storage + XCom reference [OK]

Hint: Push large data externally, pass only reference in XCom [OK]

Common Mistakes:

• Pushing large JSON directly in XCom
• Ignoring Airflow variables size limits
• Assuming string conversion bypasses size limits