OpenMetadata/openmetadata-airflow-apis
Imri Paran d91273a30d
Fix 20325: Trigger external apps with config (#20397)
* wip

* feat: trigger external apps with override config

- Added in openmetadata-airflow-apis functionality to trigger DAG with feature.
- Modified openmetadata-airflow-apis application runner to accept override config from params.
- Added overloaded runPipeline with `Map<String,Object> config` to allow triggering apps with configuration. We might want to expand this to all ingestion pipelines. For now its just for apps.
- Implemented an example external app that can be used to test functionality of external apps. The app can be enabled by setting the `ENABLE_APP_HelloPipelines=true` environment variable.

* fix class doc for application

* fixed README for airflow apis

* fixes

* set HelloPipelines to disabeld by default

* fixed basedpywright errros

* fixed app schema

* reduced airflow client runPipeline to an overload with null config
removed duplicate call to runPipeline in AppResource

* Update openmetadata-docs/content/v1.7.x-SNAPSHOT/developers/applications/index.md

Co-authored-by: Matias Puerta <matias@getcollate.io>

* deleted documentation file

---------

Co-authored-by: Matias Puerta <matias@getcollate.io>
2025-05-06 17:41:24 +07:00
..

OpenMetadata Airflow Managed DAGS Api

This is a plugin for Apache Airflow >= 1.10 and Airflow >=2.x that exposes REST APIs to deploy an OpenMetadata workflow definition and manage DAGS and tasks.

Development

The file development/airflow/airflow.cfg contains configuration which runs based on the airflow server deployed by the quick-start and development compose files.

You ca run the following command to start the development environment:

export AIRFLOW_HOME=$(pwd)/openmetadata-airflow-managed-api/development/airflow
airflow webserver

Requirements

First, make sure that Airflow is properly installed with the latest version 2.3.3. From the docs:

Then, install following packages in your scheduler and webserver python env.

pip install openmetadata-airflow-managed-apis       

Configuration

Add the following section to airflow.cfg

[openmetadata_airflow_apis]
dag_generated_configs = {AIRFLOW_HOME}/dag_generated_configs

substitute AIRFLOW_HOME with your airflow installation home

Deploy

pip install "apache-airflow==2.3.3" --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.3.3/constraints-3.9.txt"
  1. Install the package

  2. mkdir -p {AIRFLOW_HOME}/dag_generated_configs

  3. (re)start the airflow webserver and scheduler

    airflow webserver
    airflow scheduler
    

Validate

You can check that the plugin is correctly loaded by going to http://{AIRFLOW_HOST}:{AIRFLOW_PORT}/restapi, or accessing the REST_API_PLUGIN view through the Admin dropdown.

APIs

Enable JWT Auth tokens

Plugin enables JWT Token based authentication for Airflow versions 1.10.4 or higher when RBAC support is enabled.

Generating the JWT access token
curl -XPOST http://localhost:8080/api/v1/security/login -H "Content-Type: application/json" -d '{"username":"admin", "password":"admin", "refresh":true, "provider": "db"}'
Examples:
curl -X POST http://localhost:8080/api/v1/security/login -H "Content-Type: application/json" -d '{"username":"admin", "password":"admin", "refresh":true, "provider": "db"}'
Sample response which includes access_token and refresh_token.
{
 "access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE2MDQyMTc4MzgsIm5iZiI6MTYwNDIxNzgzOCwianRpIjoiMTI4ZDE2OGQtMTZiOC00NzU0LWJiY2EtMTEyN2E2ZTNmZWRlIiwiZXhwIjoxNjA0MjE4NzM4LCJpZGVudGl0eSI6MSwiZnJlc2giOnRydWUsInR5cGUiOiJhY2Nlc3MifQ.xSWIE4lR-_0Qcu58OiSy-X0XBxuCd_59ic-9TB7cP9Y",
 "refresh_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE2MDQyMTc4MzgsIm5iZiI6MTYwNDIxNzgzOCwianRpIjoiZjA5NTNkODEtNWY4Ni00YjY0LThkMzAtYzg5NTYzMmFkMTkyIiwiZXhwIjoxNjA2ODA5ODM4LCJpZGVudGl0eSI6MSwidHlwZSI6InJlZnJlc2gifQ.VsiRr8_ulCoQ-3eAbcFz4dQm-y6732QR6OmYXsy4HLk"
}

By default, JWT access token is valid for 15 mins and refresh token is valid for 30 days. You can renew the access token with the help of refresh token as shown below.

Renewing the Access Token
curl -X POST "http://{AIRFLOW_HOST}:{AIRFLOW_PORT}/api/v1/security/refresh" -H 'Authorization: Bearer <refresh_token>'
Examples:
curl -X POST "http://localhost:8080/api/v1/security/refresh" -H 'Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE2MDQyMTc4MzgsIm5iZiI6MTYwNDIxNzgzOCwianRpIjoiZjA5NTNkODEtNWY4Ni00YjY0LThkMzAtYzg5NTYzMmFkMTkyIiwiZXhwIjoxNjA2ODA5ODM4LCJpZGVudGl0eSI6MSwidHlwZSI6InJlZnJlc2gifQ.VsiRr8_ulCoQ-3eAbcFz4dQm-y6732QR6OmYXsy4HLk'
sample response returns the renewed access token as shown below.
{
 "access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE2MDQyODQ2OTksIm5iZiI6MTYwNDI4NDY5OSwianRpIjoiZDhhN2IzMmYtMWE5Zi00Y2E5LWFhM2ItNDEwMmU3ZmMyMzliIiwiZXhwIjoxNjA0Mjg1NTk5LCJpZGVudGl0eSI6MSwiZnJlc2giOmZhbHNlLCJ0eXBlIjoiYWNjZXNzIn0.qY2e-bNSgOY-YboinOoGqLfKX9aQkdRjo025mZwBadA"
}

Enable API requests with JWT

If the Authorization header is not added in the api requestresponse error:
{"msg":"Missing Authorization Header"}
Pass the additional Authorization:Bearer <access_token> header in the rest API request.

Examples:

curl -X GET -H 'Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE2MDQyODQ2OTksIm5iZiI6MTYwNDI4NDY5OSwianRpIjoiZDhhN2IzMmYtMWE5Zi00Y2E5LWFhM2ItNDEwMmU3ZmMyMzliIiwiZXhwIjoxNjA0Mjg1NTk5LCJpZGVudGl0eSI6MSwiZnJlc2giOmZhbHNlLCJ0eXBlIjoiYWNjZXNzIn0.qY2e-bNSgOY-YboinOoGqLfKX9aQkdRjo025mZwBadA' http://localhost:8080/rest_api/api\?api\=dag_state\&dag_id\=dag_test\&run_id\=manual__2020-10-28T17%3A36%3A28.838356%2B00%3A00

Using the API

Once you deploy the plugin and restart the webserver, you can start to use the REST API. Bellow you will see the endpoints that are supported.

Note: If enable RBAC, http://{AIRFLOW_HOST}:{AIRFLOW_PORT}/rest_api/
This web page will show the Endpoints supported and provide a form for you to test submitting to them.

deploy_dag

Description:
  • Deploy a new dag, and refresh dag to session.
Endpoint:
http://{AIRFLOW_HOST}:{AIRFLOW_PORT}/rest_api/api?api=deploy_dag
Method:
  • POST
POST request Arguments:
{
	"workflow": {
		"name": "test_ingestion_x_35",
		"force": "true",
		"pause": "false",
		"unpause": "true",
		"dag_config": {
			"test_ingestion_x_35": {
				"default_args": {
					"owner": "harsha",
					"start_date": "2021-10-29T00:00:00.000Z",
					"end_date": "2021-11-05T00:00:00.000Z",
					"retries": 1,
					"retry_delay_sec": 300
				},
				"schedule_interval": "0 3 * * *",
				"concurrency": 1,
				"max_active_runs": 1,
				"dagrun_timeout_sec": 60,
				"default_view": "tree",
				"orientation": "LR",
				"description": "this is an example dag!",
				"tasks": {
					"task_1": {
						"operator": "airflow.operators.python_operator.PythonOperator",
						"python_callable_name": "metadata_ingestion_workflow",
						"python_callable_file": "metadata_ingestion.py",
						"op_kwargs": {
							"workflow_config": {
								"metadata_server": {
									"config": {
										"api_endpoint": "http://localhost:8585/api",
										"auth_provider_type": "no-auth"
									},
									"type": "metadata-server"
								},
								"sink": {
									"config": {
										"es_host": "localhost",
										"es_port": 9200,
										"index_dashboards": "true",
										"index_tables": "true",
										"index_topics": "true"
									},
									"type": "elasticsearch"
								},
								"source": {
									"config": {
										"include_dashboards": "true",
										"include_tables": "true",
										"include_topics": "true",
										"limit_records": 10
									},
									"type": "metadata"
								}
							}
						}
					}
				}
			}
		}
	}
}
Examples:
curl -H  'Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE2MzU2NTE1MDAsIm5iZiI6MTYzNTY1MTUwMCwianRpIjoiNWQyZTM3ZDYtNjdiYS00NGZmLThjOWYtMDM0ZTQyNGE3MTZiIiwiZXhwIjoxNjM1NjUyNDAwLCJpZGVudGl0eSI6MSwiZnJlc2giOnRydWUsInR5cGUiOiJhY2Nlc3MifQ.DRUYCAiMh5h2pk1MZZJ4asyVFC20pu35DuAANQ5GxGw' -H 'Content-Type: application/json' -d "@test_ingestion_config.json" -X POST http://localhost:8080/rest_api/api\?api\=deploy_dag```
##### response:
```json
{"message": "Workflow [test_ingestion_x_35] has been created", "status": "success"}

delete_dag

Description:
  • Delete dag based on dag_id.
Endpoint:
http://{AIRFLOW_HOST}:{AIRFLOW_PORT}/rest_api/api?api=delete_dag&dag_id=value
Method:
  • GET
GET request Arguments:
  • dag_id - string - The id of dag.
Examples:
curl -X GET http://localhost:8080/rest_api/api?api=delete_dag&dag_id=dag_test
response:
{
  "message": "DAG [dag_test] deleted",
  "status": "success"
}