Community Forums

Hey everyone,

This topic is dedicated to sharing common errors encountered while working with Apache Airflow and discussing effective troubleshooting strategies. Let's build a collective knowledge base to help each other overcome these challenges.

Here are a few common issues I've seen:

• Task exited with status '1': Often indicates an issue within the task's execution environment or the script itself.
• Lost connection to worker: Could be network issues, worker resource exhaustion, or scheduler misconfiguration.
• DAG validation errors: Syntax errors, incorrect imports, or issues with Airflow version compatibility.

What are your go-to methods for debugging Airflow problems?

Great initiative, AirflowGuru!

For the Task exited with status '1' error, I usually start by checking the task logs directly from the Airflow UI. The detailed output there often points to the specific Python traceback or command-line error. If the logs aren't informative enough, I'll try running the command or script locally in a similar environment to isolate the issue.

Another common one for me is Executor not picking up tasks. This can sometimes be resolved by restarting the worker or scheduler, but often it's a deeper issue with the executor's configuration or communication with the metadata database.

Echoing DataScientist on checking task logs. It's crucial. I also use `airflow dags list-imports --dag-id ` to quickly check for import errors before even running a task.

One trick for debugging connection issues (like Lost connection to worker) is to ensure the worker's network access to the scheduler and metadata DB is solid. Sometimes firewalls or security groups block necessary ports.

Also, keep an eye on resource utilization on your workers. If a task is memory-intensive, it can crash the worker process, leading to lost connections.

Here's an example of how I might structure a debugging step:

# In the task code
try:
    # Your task logic here
    result = perform_operation()
    print("Operation successful!")
except Exception as e:
    print(f"An error occurred: {e}")
    # Re-raise the exception to ensure Airflow marks the task as failed
    raise