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Subject [GitHub] yangaws commented on a change in pull request #3658: [AIRFLOW-2524] Add Amazon SageMaker Training
Date Wed, 01 Aug 2018 23:06:48 GMT
yangaws commented on a change in pull request #3658: [AIRFLOW-2524] Add Amazon SageMaker Training

 File path: airflow/contrib/operators/
 @@ -0,0 +1,98 @@
+# -*- coding: utf-8 -*-
+# 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
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from airflow.contrib.hooks.sagemaker_hook import SageMakerHook
+from airflow.models import BaseOperator
+from airflow.utils import apply_defaults
+from airflow.exceptions import AirflowException
+class SageMakerCreateTrainingJobOperator(BaseOperator):
+    """
+       Initiate a SageMaker training
+       This operator returns The ARN of the model created in Amazon SageMaker
+       :param training_job_config:
+       The configuration necessary to start a training job (templated)
+       :type training_job_config: dict
+       :param region_name: The AWS region_name
+       :type region_name: string
+       :param sagemaker_conn_id: The SageMaker connection ID to use.
+       :type aws_conn_id: string
 Review comment:
   Hi @Fokko 
   I totally agree with what @srrajeev-aws mentioned here. And as a developer and maintainer
of SageMaker sdk, I can confirm that a lot users will use SageMaker on data with large size
which causes
   1. Training is time-consuming.
   2. Users may run parallel training jobs
   3. Users may want to manage ongoing training jobs. 
   So an asynchronous way of training would be preferred than a blocking one.

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