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From GitBox <...@apache.org>
Subject [GitHub] [flink-playgrounds] alpinegizmo commented on a change in pull request #16: [FLINK-19145][walkthroughs] Add PyFlink-walkthrough to Flink playground.
Date Wed, 23 Sep 2020 04:31:38 GMT

alpinegizmo commented on a change in pull request #16:
URL: https://github.com/apache/flink-playgrounds/pull/16#discussion_r492952901



##########
File path: pyflink-walkthrough/README.md
##########
@@ -102,6 +106,24 @@ $ docker-compose exec jobmanager ./bin/flink run -py /opt/pyflink-walkthrough/pa
 
 3. Stop the PyFlink job:
 
-Visit the Flink Web UI at [http://localhost:8081/#/overview](http://localhost:8081/#/overview)
, select the job and click `Cancle` on the upper right side.
+Visit the Flink Web UI at [http://localhost:8081/#/overview](http://localhost:8081/#/overview)
, select the job and click `Cancel` on the upper right side.
 
 ![image](pic/cancel.png)
+
+## Extension
+
+You are able to edit the [payment_msg_processing.py](payment_msg_proccessing.py) or create
new PyFlink 
+projects to perform more complex processing logic locally on your operating system under
the `pyflink-walkthrough` 
+directory since it is mounted on the `jobmanager` docker container. Such as:
+* Creating a new Kafka source table;
+* Creating a new index for the Elasticsearch sink;
+* Calculating the amount of transactions grouped by a 1 minute tumble window and payPlatforms.
+
+After the modification, you can submit the new job by executing the same command mentioned
at 
+[Running the PyFlink Job](#running-the-pyflink-job)
+```shell script
+$ docker-compose exec jobmanager ./bin/flink run -py /opt/pyflink-walkthrough/payment_msg_proccessing.py
-d
+```
+
+Furthermore, you can also [create new kibana dashboards](https://www.elastic.co/guide/en/kibana/7.8/dashboard-create-new-dashboard.html)

+to visualize more charts of various dimension based on the persistent indexes in Elasticsearch.

Review comment:
       ```suggestion
   ## Further Explorations
   
   If you would like to explore this example more deeply, you can edit [payment_msg_processing.py](payment_msg_proccessing.py)
or create new PyFlink 
   projects that perform more complex processing. You can do this locally under the `pyflink-walkthrough`

   directory, since it is mounted on the `jobmanager` docker container. 
   
   Ideas:
   * Add your own Kafka source table;
   * Create a new index for the Elasticsearch sink;
   * Count the number of transactions, grouped by a 1 minute tumbling windows, and by payPlatform.
   
   After making a modification, you can submit the new job by executing the same command mentioned
at 
   [Running the PyFlink Job](#running-the-pyflink-job)
   ```bash
   $ docker-compose exec jobmanager ./bin/flink run -py /opt/pyflink-walkthrough/payment_msg_proccessing.py
-d
   ```
   
   Furthermore, you can also [create new kibana dashboards](https://www.elastic.co/guide/en/kibana/7.8/dashboard-create-new-dashboard.html)

   that visualize other aspects of the data in the Elasticsearch.
   ```




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