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Using the Airbyte Operator to orchestrate Airbyte Core

docs/platform/operator-guides/using-the-airflow-airbyte-operator.md

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Using the Airbyte Operator to orchestrate Airbyte Core

Airbyte is an official community provider for the Apache Airflow project. The Airbyte operator allows you to trigger Airbyte self-managed synchronization jobs from Apache Airflow, and this article walks you through configuring your Airflow DAG to do so.

:::note For historic reasons, the Airbyte operator is designed to work with the internal Config API rather than the newer Airbyte API and is therefore not intended or designed for orchestrating Airbyte Cloud. As an alternative, it is possible to make use of Airflow's HTTP operators with both Airbyte self-managed and Cloud. This approach is described in Using the new Airbyte API to orchestrate Airbyte Cloud with Airflow. :::

The Airbyte Provider documentation on Airflow project can be found here.

1. Set up the tools

First, make sure you have Docker installed. (We'll be using the docker-compose command, so your install should contain docker-compose.)

Start Airbyte

If this is your first time using Airbyte, we suggest going through our Basic Tutorial. This tutorial will use the Connection set up in the basic tutorial.

For the purposes of this tutorial, set your Connection's sync frequency to manual. Airflow will be responsible for manually triggering the Airbyte job.

Start Apache Airflow

If you don't have an Airflow instance, we recommend following this guide to set one up. Additionally, you will need to install the apache-airflow-providers-airbyte package to use Airbyte Operator on Apache Airflow. You can read more about it here

2. Create a DAG in Apache Airflow to trigger your Airbyte job

Create an Airbyte connection in Apache Airflow

Once Airflow starts, navigate to Airflow's Connections page as seen below. The Airflow UI can be accessed at http://localhost:8080/.

Airflow will use the Airbyte API to execute our actions. The Airbyte API uses HTTP, so we'll need to create a HTTP Connection. Airbyte is typically hosted at localhost:8001. Configure Airflow's HTTP connection accordingly - we've provided a screenshot example.

Don't forget to click save!

Retrieving the Airbyte Connection ID

Get the Airbyte Connection ID so your Airflow DAG knows which Airbyte Connection to trigger.

  1. Open Airbyte.

  2. Click Connections > your connection.

  3. Get the connection ID from the URL. The URL looks like the following example, and your connection ID appears near the end: https://<YOUR_DOMAIN>/workspaces/<YOUR_WORKSPACE_ID>/connections/<YOUR_CONNECTION_ID>/status.

Creating a simple Airflow DAG to run an Airbyte Sync Job

Place the following file inside the /dags directory. Name this file dag_airbyte_example.py.

python
from airflow import DAG
from airflow.utils.dates import days_ago
from airflow.providers.airbyte.operators.airbyte import AirbyteTriggerSyncOperator

with DAG(dag_id='trigger_airbyte_job_example',
         default_args={'owner': 'airflow'},
         schedule_interval='@daily',
         start_date=days_ago(1)
    ) as dag:

    money_to_json = AirbyteTriggerSyncOperator(
        task_id='airbyte_money_json_example',
        airbyte_conn_id='airbyte_conn_example',
        connection_id='1e3b5a72-7bfd-4808-a13c-204505490110',
        asynchronous=False,
        timeout=3600,
        wait_seconds=3
    )

The Airbyte Airflow Operator accepts the following parameters:

  • airbyte_conn_id: Name of the Airflow HTTP Connection pointing at the Airbyte API. Tells Airflow where the Airbyte API is located.
  • connection_id: The ID of the Airbyte Connection to be triggered by Airflow.
  • asynchronous: Determines how the Airbyte Operator executes. When true, Airflow will monitor the Airbyte Job using an AirbyteJobSensor. Default value is false.
  • timeout: Maximum time Airflow will wait for the Airbyte job to complete. Only valid when asynchronous=False. Default value is 3600 seconds.
  • wait_seconds: The amount of time to wait between checks. Only valid when asynchronous=False. Default value is 3 seconds.

This code will produce the following simple DAG in the Airbyte UI: airbyte_money_json_example.

Our DAG will show up in the Airflow UI shortly after we place our DAG file, and be automatically triggered shortly after.

Check the Timeline tab to see if the job started syncing.

Using the asynchronous parameter

If your Airflow instance has limited resources and/or is under load, setting the asynchronous=True can help. Sensors do not occupy an Airflow worker slot, so this is helps reduce Airflow load.

python
from airflow import DAG
from airflow.utils.dates import days_ago
from airflow.providers.airbyte.operators.airbyte import AirbyteTriggerSyncOperator
from airflow.providers.airbyte.sensors.airbyte import AirbyteJobSensor

with DAG(dag_id='airbyte_trigger_job_example_async',
         default_args={'owner': 'airflow'},
         schedule_interval='@daily',
         start_date=days_ago(1)
    ) as dag:

    async_money_to_json = AirbyteTriggerSyncOperator(
        task_id='airbyte_async_money_json_example',
        airbyte_conn_id='airbyte_conn_example',
        connection_id='1e3b5a72-7bfd-4808-a13c-204505490110',
        asynchronous=True,
    )

    airbyte_sensor = AirbyteJobSensor(
        task_id='airbyte_sensor_money_json_example',
        airbyte_conn_id='airbyte_conn_example',
        airbyte_job_id=async_money_to_json.output
    )

    async_money_to_json >> airbyte_sensor

That's it!

Don't be fooled by our simple example of only one Airflow task. Airbyte is a powerful data integration platform supporting many sources and destinations. The Airbyte Airflow Operator means Airbyte can now be easily used with the Airflow ecosystem - give it a shot!

For additional information about using the Airflow and Airbyte together, see the following: