[jira] [Commented] (AIRFLOW-7014) Operator for Apache Kylin

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

    [ https://issues.apache.org/jira/browse/AIRFLOW-7014?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17126367#comment-17126367 ] 

ASF GitHub Bot commented on AIRFLOW-7014:
-----------------------------------------

boring-cyborg[bot] commented on pull request #9149:
URL: https://github.com/apache/airflow/pull/9149#issuecomment-639246295


   Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contribution Guide (https://github.com/apache/airflow/blob/master/CONTRIBUTING.rst)
   Here are some useful points:
   - Pay attention to the quality of your code (flake8, pylint and type annotations). Our [pre-commits]( https://github.com/apache/airflow/blob/master/STATIC_CODE_CHECKS.rst#prerequisites-for-pre-commit-hooks) will help you with that.
   - In case of a new feature add useful documentation (in docstrings or in `docs/` directory). Adding a new operator? Check this short [guide](https://github.com/apache/airflow/blob/master/docs/howto/custom-operator.rst) Consider adding an example DAG that shows how users should use it.
   - Consider using [Breeze environment](https://github.com/apache/airflow/blob/master/BREEZE.rst) for testing locally, it’s a heavy docker but it ships with a working Airflow and a lot of integrations.
   - Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
   - Be sure to read the [Airflow Coding style]( https://github.com/apache/airflow/blob/master/CONTRIBUTING.rst#coding-style-and-best-practices).
   Apache Airflow is a community-driven project and together we are making it better 🚀.
   In case of doubts contact the developers at:
   Mailing List: dev@airflow.apache.org
   Slack: https://apache-airflow-slack.herokuapp.com/
   


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> Operator for Apache Kylin 
> --------------------------
>
>                 Key: AIRFLOW-7014
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-7014
>             Project: Apache Airflow
>          Issue Type: Improvement
>          Components: executors, operators
>    Affects Versions: 1.10.0
>            Reporter: Shao Feng Shi
>            Assignee: liuyongheng
>            Priority: Major
>
> Apache Kylin is an analytial data warehouse for big data. Kylin provides a set of RESTful API for user to trigger the data loading, and also run SQL queries against the OLAP cubes in sub-seconds latency. We developed a KylinOperator within Airflow, so that user can easily trigger Kylin with other tasks (hive, spark, etc), and plan to contribute into Airflow.



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