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| 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. |
| |
| |
| Yandex.Cloud Data Proc Operators |
| ================================ |
| |
| The `Yandex.Cloud Data Proc <https://cloud.yandex.com/services/data-proc>`__ is a service that helps to deploy Apache Hadoop®* and Apache Spark™ clusters in the Yandex.Cloud infrastructure. |
| |
| You can control the cluster size, node capacity, and set of Apache® services |
| (Spark, HDFS, YARN, Hive, HBase, Oozie, Sqoop, Flume, Tez, Zeppelin). |
| |
| Apache Hadoop is used for storing and analyzing structured and unstructured big data. |
| |
| Apache Spark is a tool for quick data-processing that can be integrated with Apache Hadoop as well as with other storage systems. |
| |
| Prerequisite Tasks |
| ^^^^^^^^^^^^^^^^^^ |
| #. Install the ``yandexcloud`` package first, like so: ``pip install 'apache-airflow[yandexcloud]'``. |
| #. Restart the Airflow webserver and scheduler. |
| #. Make sure the Yandex.Cloud connection type has been defined in Airflow. Open the connections list and look for a connection with 'yandexcloud' type. |
| #. Fill the required fields in Yandex.Cloud connection. |
| |
| Using the operators |
| ^^^^^^^^^^^^^^^^^^^^^ |
| See the usage examples in `example DAGs <https://github.com/apache/airflow/blob/master/airflow/providers/yandex/example_dags/example_yandexcloud_dataproc.py>`_ |