== 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.
Although contrived, this type of use cases are pretty common in the industry where some organizations want to track the statistics of some entities over a time window.
In essence, the application receives product information from input topic and count the interested products in a configurable time window and report that in an output topic.
This sample uses lambda expressions and thus requires Java 8+.
=== Running the app:
Go to the root of the repository and do:
`docker-compose up -d`
`./mvnw clean package`
`java -jar target/kafka-streams-product-tracker-0.0.1-SNAPSHOT.jar --app.product.tracker.productIds=123,124,125`
The above command will track products with ID's 123,124 and 125 every 30 seconds with the counts from the last minute.
In other words, every 30 seconds a new 1 minute window is started.
Issue the following commands:
`docker exec -it kafka-prod-tracker /opt/kafka/bin/kafka-console-producer.sh --broker-list 127.0.0.1:9092 --topic products`
On another terminal:
`docker exec -it kafka-prod-tracker /opt/kafka/bin/kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --key-deserializer org.apache.kafka.common.serialization.IntegerDeserializer --property print.key=true --topic product-counts`
Enter the following in the console producer (one line at a time) and watch the output on the console consumer:
```
{"id":"123"}
{"id":"124"}
{"id":"125"}
{"id":"123"}
{"id":"123"}
{"id":"123"}
```
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