shuiqiangchen commented on a change in pull request #16:
URL: https://github.com/apache/flink-playgrounds/pull/16#discussion_r493545356



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File path: pyflink-walkthrough/README.md
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+# pyflink-walkthrough
+
+## Background
+
+In this playground, you will learn how to build and run an end-to-end PyFlink 
pipeline for data analytics, covering the following steps:
+
+* Reading data from a Kafka source;
+* Creating data using a 
[UDF](https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/python/table-api-users-guide/udfs/python_udfs.html);
+* Performing a simple aggregation over the source data;
+* Writing the results to Elasticsearch and visualizing them in Kibana.
+
+The environment is based on Docker Compose, so the only requirement is that 
you have [Docker](https://docs.docker.com/get-docker/) 
+installed in your machine.
+
+### Kafka
+You will be using Kafka to store sample input data about payment transactions. 
A simple data generator 
[generate_source_data.py](generator/generate_source_data.py) is provided to

Review comment:
       Here I would like to use `H3` header for each component (Kafka, PyFlink, 
Elaticsearch, Kibana) introduction to make them more recognizable.




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