Kafka Streams for Low Code Environments

Go to the KSML repository Clone the repository with GIT, or download a ZIP file using the Code button If you've downloaded a zip file, extract it to a working directory.

Open the repository in your favorite editor. We will be working in the root and the examples directory of the project. The other directories contain the source code of KSML. You can take a look if you're interested.

Open the `docker-compose.yml` file in the root directory.

This file start a Kafka environment with Schema Registry and a data generator for the examples

Perform a `docker-compose up -d` in the root directory to start the environment in the background

Docker has recently introduced an alternative command `docker compose up -d`

Perform a `docker-compose logs -d example-producer`. By looking at your console you should see the data generator in action, you should see produce messages appear.

The service can fail several times while waiting for the Kafka topics to be created.

Docker has recently introduced an alternative command `docker compose logs -d example-producer`

The next step is to build a KSML definition that is going to process the data. Below you will find 3 simple examples that help you to understand the KSML syntax better and see what it is capable of.

Example 1

Inspecting topic data

Create a file `sensor-inspect.yaml` in the folder `/examples` with the following contents

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It's time to start a KSML Runner with your KSML definition.

Open the file `ksml-runner.yml` in the `examples` directory.

Replace the reference to `1-demo-inspect.yaml` with `sensor-inspect.yaml`

Execute the `run.sh` script in the examples directory

If everything goes well, you should see the AVRO sensordata being written to STDOUT.

Now that your setup works fine and you have successfully launched the first KSML app, let's add some more. In the list below you will find some example definitions for various operations. Click "expand" to see the code for every example and repeat "step 3" for each of them.