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Certainly! Installing Apache Airflow with Celery as the executor can provide a scalable and distributed way to execute your Airflow tasks. In this tutorial, we'll guide you through the process of installing Apache Airflow and configuring it to use Celery as the executor.
Create a file named airflow.cfg in your Airflow home directory (by default, it's ~/airflow). Add the following configurations to use Celery:
Make sure to adjust the broker_url and result_backend based on your Celery broker and result backend preferences. In this example, we're using Redis as the broker and PostgreSQL as the result backend.
Now, you should be able to access the Airflow web UI at http://localhost:8080 and see that the Celery worker is connected.
Create a simple example DAG to test the configuration. Create a file named example_dag.py in the ~/airflow/dags directory:
Go to the Airflow web UI, locate the "example_dag," and trigger it manually. Monitor the progress in the Airflow web UI and Celery worker logs.
Congratulations! You've successfully installed Apache Airflow with Celery as the executor and executed a simple DAG. You can now build more complex workflows using Airflow and scale your task execution with Celery.
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