[jira] [Commented] (AIRFLOW-2524) Airflow integration with AWS Sagemaker

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/AIRFLOW-2524?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16564918#comment-16564918 ] 

ASF GitHub Bot commented on AIRFLOW-2524:
-----------------------------------------

Fokko commented on a change in pull request #3658: [AIRFLOW-2524] Add Amazon SageMaker Training
URL: https://github.com/apache/incubator-airflow/pull/3658#discussion_r206786344
 
 

 ##########
 File path: airflow/contrib/operators/sagemaker_create_training_job_operator.py
 ##########
 @@ -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
+#
+#   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.
+
+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 Keliang, thanks for explaining the Sagemaker process. I think it is very similar to for example the Druid hook that we have: https://github.com/apache/incubator-airflow/blob/master/airflow/hooks/druid_hook.py#L93
   
   This hook will kick of a job using a HTTP POST of a json document to the druid cluster, and make sure that it receives a http 200. And then it will continue to poll the job by invoking the API periodically.

----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
users@infra.apache.org


> Airflow integration with AWS Sagemaker
> --------------------------------------
>
>                 Key: AIRFLOW-2524
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-2524
>             Project: Apache Airflow
>          Issue Type: Improvement
>          Components: aws, contrib
>            Reporter: Rajeev Srinivasan
>            Assignee: Yang Yu
>            Priority: Major
>              Labels: AWS
>
> Would it be possible to orchestrate an end to end  AWS  Sagemaker job using Airflow.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)