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Orchestrating Large and Small Projects With Apache Airflow

The Real Python Podcast

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Airflow

The DAG factory would take in like a configuration file, like a YAML or a JSON configuration file that you would feed to it. It would generate this giant array of DAGs without the need for templates. This works great until you get to thousands. Once you get to those thousands, that's when the time months were happening and we just, it would take longer to generate that array of D AGs on Airflow. So what we actually ended up doing was converting our usage of DAG factories into smaller, segmented or sharded versions of those DAG factories because smaller versions of that can be held in memory.

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