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Composer - GCP




the DAG files are stored within a "dags" folder, which resides inside of a Cloud Storage bucket, that is created when a Cloud Composer environment is created.




inside the DAG file there will be the default py file for orchestration.

you can create the number of DAG files and upload into this folder to create the workflow

if you click on the files, it will lead to airflow monitoring under graph you can see DAG and operator (task) , and under code ,you can see the code for orchestration 



if the DAG is yellow in color that means it's not working properly then we have to debug if its in green color its works properly .


from airflow import DAG
from airflow.operators.bash import BashOperator
from datetime import datetime, timedelta

default_args = {
    'owner': 'your_name',
    'start_date': datetime(2023, 10, 26),
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
    'dagrun_timeout': timedelta(hours=2),
}

with DAG(
    dag_id='my_data_pipeline',  # DAG Name
    schedule_interval='@daily',  # Schedule interval
    default_args=default_args,
    catchup=False, The catchup parameter determines whether Airflow should "catch up" on past scheduled runs that were missed.
) as dag:
    task1 = BashOperator(
        task_id='extract_data',  # Task ID
        bash_command='echo "Extracting data..."',
    )

    task2 = BashOperator(
        task_id='transform_data',  # Task ID
        bash_command='echo "Transforming data..."',
    )

    task1 >> task2  # Define task dependencies, >> operator defines the order in which tasks should be executed

Key Points:

  • DAG parameters control the overall behavior of the workflow.
  • Operator parameters define the individual steps within the workflow.
  • task_id values must be unique within a DAG.
  • The dag_id must be unique across all dags inside of the airflow environment.
  • The schedule_interval is what tells airflow when to run the dag.
  • The dagrun_timeout is a safety net.

I hope this helps clarify these important Airflow concepts.

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