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Apache airflow provider for managing Reverse ETL syncs and Profiles runs in RudderStack.

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RudderStack Airflow Provider

The RudderStack Airflow Provider lets you programmatically schedule and trigger your Reverse ETL syncs and Profiles runs outside RudderStack and integrate them with your existing Airflow workflows.

Installation

pip install rudderstack-airflow-provider

Usage

RudderstackRETLOperator

[!NOTE]
Use RudderstackRETLOperator for reverse ETL connections

A simple DAG for triggering syncs for a RudderStack Reverse ETL source:

with DAG(
    "rudderstack-retl-sample",
    default_args=default_args,
    description="A simple tutorial DAG for reverse etl",
    schedule_interval=timedelta(days=1),
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["rs-retl"],
) as dag:
    # retl_connection_id, sync_type are template fields
    rs_operator = RudderstackRETLOperator(
        retl_connection_id="connection_id",
        task_id="<replace task id>",
        connection_id="<rudderstack api airflow connection id>"
    )

For the complete code, refer to this example.

Mandatatory parameters for RudderstackRETLOperator:

  • retl_connection_id: This is the connection id for the sync job.
  • connection_id: The Airflow connection to use for connecting to the Rudderstack API. Default value is rudderstack_default.

RudderstackRETLOperator exposes other configurable parameters as well. Mostly default values for them would be recommended.

  • request_max_retries: The maximum number of times requests to the RudderStack API should be retried before failng.
  • request_retry_delay: Time (in seconds) to wait between each request retry.
  • request_timeout: Time (in seconds) after which the requests to RudderStack are declared timed out.
  • poll_interval: Time (in seconds) for polling status of triggered job.
  • poll_timeout: Time (in seconds) after which the polling for a triggered job is declared timed out.
  • wait_for_completion: Boolean if execution run should poll and wait till completion of sync. Default value is True.
  • sync_type: Type of sync to trigger incremental or full. Default is None as RudderStack will be deteriming sync type.

RudderstackProfilesOperator

RudderstackProfilesOperator can be used to trigger profiles run. A simple DAG for triggering profile runs for a profiles project.

with DAG(
    "rudderstack-profiles-sample",
    default_args=default_args,
    description="A simple tutorial DAG for profiles run.",
    schedule_interval=timedelta(days=1),
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["rs-profiles"],
) as dag:
    # profile_id is template field
    rs_operator = RudderstackProfilesOperator(
        profile_id="<profile_id>",
        task_id="<replace task id>",
        connection_id="<rudderstack api connection id>",
    )

Mandatatory parameters for RudderstackProfilesOperator:

  • profile_id: This is the profiles id for the profiles project to run.
  • connection_id: The Airflow connection to use for connecting to the Rudderstack API. Default value is rudderstack_default.

RudderstackRETLOperator exposes other configurable parameters as well. Mostly default values for them would be recommended.

  • request_max_retries: The maximum number of times requests to the RudderStack API should be retried before failng.
  • request_retry_delay: Time (in seconds) to wait between each request retry.
  • request_timeout: Time (in seconds) after which the requests to RudderStack are declared timed out.
  • poll_interval: Time (in seconds) for polling status of triggered job.
  • poll_timeout: Time (in seconds) after which the polling for a triggered job is declared timed out.
  • wait_for_completion: Boolean if execution run should poll and wait till completion of sync. Default value is True.

Contribute

We would love to see you contribute to this project. Get more information on how to contribute here.

License

The RudderStack Airflow Provider is released under the MIT License.

Contact Us

For more information or queries on this feature, you can contact us or start a conversation in our Slack community.

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