| .. Licensed to the Apache Software Foundation (ASF) under one |
| or more contributor license agreements. See the NOTICE file |
| distributed with this work for additional information |
| regarding copyright ownership. The ASF licenses this file |
| to you under the Apache License, Version 2.0 (the |
| "License"); you may not use this file except in compliance |
| with the License. You may obtain a copy of the License at |
| |
| .. 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 Operators |
| ========================== |
| |
| `Amazon SageMaker <https://docs.aws.amazon.com/sagemaker>`__ is a fully managed |
| machine learning service. With Amazon SageMaker, data scientists and developers |
| can quickly build and train machine learning models, and then deploy them into a |
| production-ready hosted environment. |
| |
| Airflow provides operators to create and interact with SageMaker Jobs. |
| |
| Prerequisite Tasks |
| ------------------ |
| |
| .. include:: _partials/prerequisite_tasks.rst |
| |
| Manage Amazon SageMaker Jobs |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| |
| .. _howto/operator:SageMakerProcessingOperator: |
| |
| Create an Amazon SageMaker Processing Job |
| """"""""""""""""""""""""""""""""""""""""" |
| |
| To create an Amazon Sagemaker processing job to sanitize your dataset you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_processing] |
| :end-before: [END howto_operator_sagemaker_processing] |
| |
| |
| .. _howto/operator:SageMakerTrainingOperator: |
| |
| Create an Amazon SageMaker Training Job |
| """"""""""""""""""""""""""""""""""""""" |
| |
| To create an Amazon Sagemaker training job you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_training] |
| :end-before: [END howto_operator_sagemaker_training] |
| |
| .. _howto/operator:SageMakerModelOperator: |
| |
| Create an Amazon SageMaker Model |
| """""""""""""""""""""""""""""""" |
| |
| To create an Amazon Sagemaker model you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_model] |
| :end-before: [END howto_operator_sagemaker_model] |
| |
| .. _howto/operator:SageMakerTuningOperator: |
| |
| Start a Hyperparameter Tuning Job |
| """"""""""""""""""""""""""""""""" |
| |
| To start a hyperparameter tuning job for an Amazon Sagemaker model you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_tuning] |
| :end-before: [END howto_operator_sagemaker_tuning] |
| |
| .. _howto/operator:SageMakerDeleteModelOperator: |
| |
| Delete an Amazon SageMaker Model |
| """""""""""""""""""""""""""""""" |
| |
| To delete an Amazon Sagemaker model you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_delete_model] |
| :end-before: [END howto_operator_sagemaker_delete_model] |
| |
| .. _howto/operator:SageMakerTransformOperator: |
| |
| Create an Amazon SageMaker Transform Job |
| """""""""""""""""""""""""""""""""""""""" |
| |
| To create an Amazon Sagemaker transform job you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_transform] |
| :end-before: [END howto_operator_sagemaker_transform] |
| |
| .. _howto/operator:SageMakerEndpointConfigOperator: |
| |
| Create an Amazon SageMaker Endpoint Config Job |
| """""""""""""""""""""""""""""""""""""""""""""" |
| |
| To create an Amazon Sagemaker endpoint config job you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker_endpoint.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_endpoint_config] |
| :end-before: [END howto_operator_sagemaker_endpoint_config] |
| |
| .. _howto/operator:SageMakerEndpointOperator: |
| |
| Create an Amazon SageMaker Endpoint Job |
| """"""""""""""""""""""""""""""""""""""" |
| |
| To create an Amazon Sagemaker endpoint you can use |
| :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker_endpoint.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_endpoint] |
| :end-before: [END howto_operator_sagemaker_endpoint] |
| |
| |
| Amazon SageMaker Sensors |
| ^^^^^^^^^^^^^^^^^^^^^^^^ |
| |
| .. _howto/sensor:SageMakerTrainingSensor: |
| |
| Amazon SageMaker Training Sensor |
| """""""""""""""""""""""""""""""" |
| |
| To check the state of an Amazon Sagemaker training job until it reaches a terminal state |
| you can use :class:`~airflow.providers.amazon.aws.sensors.sagemaker.SageMakerTrainingSensor`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_training_sensor] |
| :end-before: [END howto_operator_sagemaker_training_sensor] |
| |
| .. _howto/sensor:SageMakerTransformSensor: |
| |
| Amazon SageMaker Transform Sensor |
| """"""""""""""""""""""""""""""""""" |
| |
| To check the state of an Amazon Sagemaker transform job until it reaches a terminal state |
| you can use :class:`~airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_transform_sensor] |
| :end-before: [END howto_operator_sagemaker_transform_sensor] |
| |
| .. _howto/sensor:SageMakerTuningSensor: |
| |
| Amazon SageMaker Tuning Sensor |
| """""""""""""""""""""""""""""" |
| |
| To check the state of an Amazon Sagemaker hyperparameter tuning job until it reaches a terminal state |
| you can use :class:`~airflow.providers.amazon.aws.sensors.sagemaker.SageMakerTuningSensor`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_tuning_sensor] |
| :end-before: [END howto_operator_sagemaker_tuning_sensor] |
| |
| .. _howto/sensor:SageMakerEndpointSensor: |
| |
| Amazon SageMaker Endpoint Sensor |
| """""""""""""""""""""""""""""""" |
| |
| To check the state of an Amazon Sagemaker hyperparameter tuning job until it reaches a terminal state |
| you can use :class:`~airflow.providers.amazon.aws.sensors.sagemaker.SageMakerEndpointSensor`. |
| |
| .. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_sagemaker_endpoint.py |
| :language: python |
| :dedent: 4 |
| :start-after: [START howto_operator_sagemaker_endpoint_sensor] |
| :end-before: [END howto_operator_sagemaker_endpoint_sensor] |
| |
| Reference |
| ^^^^^^^^^ |
| |
| For further information, look at: |
| |
| * `Boto3 Library Documentation for Sagemaker <https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html>`__ |
| * `Amazon SageMaker Developer Guide <https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html>`__ |