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.. http://www.apache.org/licenses/LICENSE-2.0

.. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

=============================== Amazon SageMaker Unified Studio

Amazon SageMaker Unified Studio <https://aws.amazon.com/sagemaker/unified-studio/>__ is a unified development experience that brings together AWS data, analytics, artificial intelligence (AI), and machine learning (ML) services. It provides a place to build, deploy, execute, and monitor end-to-end workflows from a single interface. This helps drive collaboration across teams and facilitate agile development.

Airflow provides different operators for running artifacts in SageMaker Unified Studio. Read the descriptions below to understand which operator is best suited for your use case.

Prerequisite Tasks

To use these operators, you must do a few things:

Create a SageMaker Unified Studio domain and project, following the instruction in AWS documentation <https://docs.aws.amazon.com/sagemaker-unified-studio/latest/userguide/getting-started.html>__.
If the domain is an IdC domain, navigate to the "Compute > Workflow environments" tab, and click "Create" to create a new MWAA environment.
Create a Jupyter notebook, querybook, Visual ETL job, or SageMaker Unified Studio notebook and save it to your project.

Operators

.. _howto/operator:SageMakerNotebookOperator:

Run Jupyter notebooks, Querybooks, and Visual ETL jobs

Use :class:~airflow.providers.amazon.aws.operators.sagemaker_unified_studio.SageMakerNotebookOperator to execute Jupyter notebooks, querybooks, and visual ETL jobs. This operator relies on the sagemaker_studio Python library to execute these artifacts.

The artifact is identified by its relative file path within the project (e.g. test_notebook.ipynb).

.. exampleinclude:: /../../amazon/tests/system/amazon/aws/example_sagemaker_unified_studio.py :language: python :dedent: 4 :start-after: [START howto_operator_sagemaker_unified_studio_notebook] :end-before: [END howto_operator_sagemaker_unified_studio_notebook]

The following example adds domain ID, project ID, and domain name as operator parameters.

.. exampleinclude:: /../../amazon/tests/system/amazon/aws/example_sagemaker_unified_studio.py :language: python :dedent: 4 :start-after: [START howto_operator_sagemaker_unified_studio_notebook_explicit_params] :end-before: [END howto_operator_sagemaker_unified_studio_notebook_explicit_params]

.. _howto/operator:SageMakerUnifiedStudioNotebookOperator:

Run SageMaker Unified Studio notebooks

Use :class:~airflow.providers.amazon.aws.operators.sagemaker_unified_studio_notebook.SageMakerUnifiedStudioNotebookOperator to execute SageMaker Unified Studio notebooks through the DataZone StartNotebookRun API.

The notebook is identified by its notebook ID (e.g. nb-1234567890), along with the domain ID and project ID where the notebook resides.

.. exampleinclude:: /../../amazon/tests/system/amazon/aws/example_sagemaker_unified_studio_notebook.py :language: python :dedent: 4 :start-after: [START howto_operator_sagemaker_unified_studio_notebook] :end-before: [END howto_operator_sagemaker_unified_studio_notebook]

Notebooks can produce output variables that are automatically pushed to XCom when the run completes. Downstream tasks can consume these outputs via Jinja templating in notebook_parameters.

In this example, Notebook A produces outputs (e.g., name and age). Notebook B receives those values as parameters using Jinja templates like {{ task_instance.xcom_pull(task_ids='notebook-a-task', key='name') }}.

.. exampleinclude:: /../../amazon/tests/system/amazon/aws/example_sagemaker_unified_studio_notebook.py :language: python :dedent: 4 :start-after: [START howto_operator_sagemaker_unified_studio_notebook_pass_outputs] :end-before: [END howto_operator_sagemaker_unified_studio_notebook_pass_outputs]

Reference

What is Amazon SageMaker Unified Studio <https://docs.aws.amazon.com/sagemaker-unified-studio/latest/userguide/what-is-sagemaker-unified-studio.html>__