== Spring Cloud Stream Kafka Streams Interactive Query (basic)
This sample demonstrates a Spring Cloud Stream processor using Kafka Streams basic state store query support.
=== Application
The app is based on a contrived use case of tracking products by interactively querying their status. The program accepts product ID's and tracks their counts hitherto by interactively querying the underlying store.
[[build-app]]
=== Building
To build the app simply execute the following command:
[source,bash]
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./mvnw clean install
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=== Running
==== Ensure these pre-requisites
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* The app has been built by following the <<build-app>> steps
* Apache Kafka broker available at `localhost:9092`
[#kafka_tools]
TIP: The included xref:../../../tools/kafka/docker-compose/README.adoc#run_kafka_cluster[Kafka tools] can be used to easily start a broker at the required coordinates
****
==== Start the streams app
[source,bash]
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java -jar target/kafka-streams-interactive-query-basic-4.0.0-SNAPSHOT.jar --app.product.tracker.product-ids=123,124,125
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The above command will track products with ID's `123`,`124` and `125` and print their counts seen so far every 30 seconds.
===== Send input messages
Leverage the Kafka command line tool `kafka-console-producer` to send messges (products) to the input topic.
Issue the following command on a separate terminal:
[source,bash]
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docker exec -it broker1 /bin/kafka-console-producer --broker-list broker1:29091 --topic products
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NOTE: The command reference `broker1` and `broker1:29091` as they assume the aforementioned <<kafka_tools,Kafka Tools>> are used to create the cluster. If you start up your own cluster you will need to adjust the coordinates accordingly. Also note that the port is `29091` as that is the internal port configured on the cluster (rather than the expected `9091`)
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.
[source,bash]
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{"id":"123"}
{"id":"124"}
{"id":"125"}
{"id":"123"}
{"id":"123"}
{"id":"123"}
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The output should look something like the following:
[source,bash]
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Product ID: 123 Count: 4
Product ID: 124 Count: 1
Product ID: 125 Count: 1
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