For example, task metadata, dates, model accuracy, or single value query results are all ideal data to use with XCom. XComs should be used to pass small amounts of data between tasks. You can view your XComs in the Airflow UI by going to Admin > XComs. Similarly, xcom_pull() can be used in a task to receive an XCom. Tasks can also be configured to push XComs by calling the xcom_push() method. Any time a task returns a value (for example, when your Python callable for your PythonOperator has a return), that value is automatically pushed to XCom. When an XCom is pushed, it is stored in the Airflow metadata database and made available to all other tasks. XComs can be "pushed", meaning sent by a task, or "pulled", meaning received by a task. They are defined by a key, value, and timestamp. XComs allow tasks to exchange task metadata or small amounts of data. The first method for passing data between Airflow tasks is to use XCom, which is a key Airflow feature for sharing task data. Large data sets require a method making use of intermediate storage and possibly utilizing an external processing framework. As you'll learn, XComs are one method of passing data between tasks, but they are only appropriate for small amounts of data. Knowing the size of the data you are passing between Airflow tasks is important when deciding which implementation method to use. This helps with recovery and ensures no data is lost if a failure occurs. When designing a DAG that passes data between tasks, it's important that you ensure that each task is idempotent. If every task in your DAG is idempotent, your full DAG is idempotent as well. However, this concept also applies to tasks within your DAG. If you execute the same DAGRun multiple times, you will get the same result. This concept is often associated with your entire DAG. This is the property whereby an operation can be applied multiple times without changing the result. Ensure idempotency Īn important concept for any data pipeline, including an Airflow DAG, is idempotency. See DAG writing best practices in Apache Airflow.īefore you dive into the specifics, there are a couple of important concepts to understand before you write DAGs that pass data between tasks. To get the most out of this guide, you should have an understanding of: All code in this guide can be found in the Github repo. SELECT value FROM xcom WHERE dag_id='' AND task_id='' AND. Xcom_values: List = list(map(lambda xcom: xcom.value, xcoms))ĭo note that since it is importing airflow packages, it still requires working airflow installation on python classpath (as well as connection to backend-db), but here we are not creating any tasks or dags (this snippet can be run in a standalone python file)įor this snippet, I have referred to views.py which is my favorite place to peek into Airflow's SQLAlchemy magicĭirectly query Airflow's SQLAlchemy backend meta-db XCom.execution_date = execution_date).all() XCom.dag_id = dag_id, XCom.task_id = task_id, Xcoms: List = session.query(XCom).filter( :param session: Airflow's SQLAlchemy Session (this param must not be passed, it will be automatically supplied decorator) Session: Optional) -> List:įunction that reads and returns 'values' of XCOMs with given filters Here's an untested code snippet for referenceįrom import provide_sessionįrom pendulum import read_xcom_values(dag_id: str, (without having to create a task or DAG). So you want to access XCOM outside Airflow (probably a different project / module, without creating any Airflow DAGs / tasks)?Īirflow uses SQLAlchemy for mapping all it's models (including XCOM) to corresponding SQLAlchemy backend (meta-db) tables Now I would like to pass this value to some python function sql_file_template without using PythonOperator.Īs per Airflow documentation xcom can be accessed only between tasks. The output of stored proc is a string which is captured using xcom. Task_instance.xcom_push(key='query_string', value=result) Query = query.format(kwargs,kwargs ,kwargs,kwargs,kwargs) Query = """CALL `.dataset_name.store_proc`( I have a stored XCom value that I wanted to pass to another python function which is not called using PythonOperator.
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