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Airflow DAGs

In Airflow, a pipeline is represented as a Directed Acyclic Graph or DAG. The nodes of the graph represent tasks that are executed. The directed connections between nodes represent dependencies between the tasks.

Representing a data pipeline as a DAG makes much sense, as some tasks need to finish before others can start. You could compare this to an assembly line in a car factory. The tasks build up, and each task can depend on previous tasks being finished. A fictional DAG could look something like this:

Example DAG

Assembling the frame happens first, then the body and tires and finally you paint. Let's reproduce the example above in code.

Bu egzersiz

Introduction to Data Engineering

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Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Create the DAG object
dag = DAG(dag_id="car_factory_simulation",
          default_args={"owner": "airflow","start_date": airflow.utils.dates.days_ago(2)},
          schedule_interval="____")
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