== What is this app?
This is an example of a Spring Cloud Stream processor using Kafka Streams support.
The example is based on a contrived use case of tracking products by interactively querying their status.
The program accepts product ID's and track their counts hitherto by interactively querying the underlying store. \
This sample uses lambda expressions and thus requires Java 8+.
==== Starting Kafka in a docker container
* Skip steps 1-3 if you already have a non-Docker Kafka environment.
1. Go to the docker directory in this repo and invoke the command `docker-compose up -d`.
2. Ensure that in the docker directory and then invoke the script `start-kafka-shell.sh`
3. cd $KAFKA_HOME
4. Start the console producer: +
Assuming that you are running kafka on a docker container on mac osx. Change the zookeeper IP address accordingly otherwise. +
`bin/kafka-console-producer.sh --broker-list 192.168.99.100:9092 --topic products`
=== Running the app:
Go to the root of the repository and do:
`./mvnw clean package`
`java -jar target/kstream-interactive-query-0.0.1-SNAPSHOT.jar --kstream.product.tracker.productIds=123,124,125`
The above command will track products with ID's 123,124 and 125 and print their counts seen so far every 30 seconds.
* By default we use the docker container IP (mac osx specific) in the `application.yml` for Kafka broker and zookeeper.
Change it in `application.yml` (which requires a rebuild) or pass them as runtime arguments as below.
`spring.cloud.stream.kstream.binder.brokers=<Broker IP Address>` +
`spring.cloud.stream.kstream.binder.zkNodes=<Zookeeper IP Address>`
Enter the following in the console producer (one line at a time) and watch the output on the console (or IDE) where the application is running.
```
{"id":"123"}
{"id":"124"}
{"id":"125"}
{"id":"123"}
{"id":"123"}
{"id":"123"}
```
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