How to count the number of events in a Kafka topic with Kafka Streams

An aggregation in Kafka Streams is a stateful operation used to perform a "clustering" or "grouping" of values with the same key. An aggregation in Kafka Streams may return a different type than the input value. In our example here we're going to use the count() method to perform a count on the number of tickets sold.

 builder.stream(INPUT_TOPIC, Consumed.with(Serdes.String(), ticketSaleSerde))
        .map((k, v) -> new KeyValue<>(v.title(), v.ticketTotalValue()))
        .groupByKey(Grouped.with(Serdes.String(), Serdes.Integer()))
        .count()
        .toStream().mapValues(v -> v.toString() + " tickets sold")
        .to(OUTPUT_TOPIC, Produced.with(Serdes.String(), Serdes.String()));

Let's review the key points in this example

    map((key, value) -> new KeyValue<>(v.title(), v.ticketTotalValue()))

Aggregations must group records by key. Since the stream source topic doesn't define any, the code has a map operation which creates new key-value pairs setting the key of the stream to the TicketSale.title field.

        groupByKey(Grouped.with(Serdes.String(), Serdes.Integer()))

Since you've changed the key, under the covers Kafka Streams performs a repartition immediately before it performs the grouping.
Repartitioning is simply producing records to an internal topic and consuming them back into the application. By producing the records the updated keys land on the correct partition. Additionally, since the key-value types have changed you need to provide updated Serde objects, via the Grouped configuration object to Kafka Streams for the (de)serialization process for the repartitioning.

count()

The count() operator is a convenience aggregation method. Under the covers it works like any other aggregation in Kafka Streams i.e. it requires an Initializer, Aggregator and a Materialized to set the Serde for the value since it's a long. But since the result of this aggregation is a simple count, Kafka Streams handles all those details for you.

                .toStream().mapValues(v -> v + " tickets sold")
                .to(OUTPUT_TOPIC, Produced.with(Serdes.String(), Serdes.String()));

Aggregations in Kafka Streams return a KTable instance, so it's converted to a KStream then mapValues appends a string to the count to give it some context on the meaning of the number.

The following steps use Confluent Cloud. To run the tutorial locally with Docker, skip to the Docker instructions section at the bottom.

Prerequisites

• A Confluent Cloud account
• The Confluent CLI installed on your machine
• Apache Kafka or Confluent Platform (both include the Kafka Streams application reset tool)
• Clone the confluentinc/tutorials repository and navigate into its top-level directory:

  git clone git@github.com:confluentinc/tutorials.git
  cd tutorials

Create Confluent Cloud resources

Login to your Confluent Cloud account:

confluent login --prompt --save

Install a CLI plugin that will streamline the creation of resources in Confluent Cloud:

confluent plugin install confluent-quickstart

Run the plugin from the top-level directory of the tutorials repository to create the Confluent Cloud resources needed for this tutorial. Note that you may specify a different cloud provider (gcp or azure) or region. You can find supported regions in a given cloud provider by running confluent kafka region list --cloud <CLOUD>.

confluent quickstart \
  --environment-name kafka-streams-aggregating-sum-env \
  --kafka-cluster-name kafka-streams-aggregating-sum-cluster \
  --create-kafka-key \
  --kafka-java-properties-file ./aggregating-sum/kstreams/src/main/resources/cloud.properties

The plugin should complete in under a minute.

Create topics

Create the input and output topics for the application:

confluent kafka topic create aggregation-sum-input
confluent kafka topic create aggregation-sum-output

Start a console producer:

confluent kafka topic produce aggregation-sum-input

Enter a few JSON-formatted ticket sales:

{"title":"Guardians of the Galaxy", "ticketTotalValue":15}
{"title":"Doctor Strange", "ticketTotalValue":15}
{"title":"Guardians of the Galaxy", "ticketTotalValue":15}

Enter Ctrl+C to exit the console producer.

Compile and run the application

Compile the application from the top-level tutorials repository directory:

./gradlew aggregating-sum:kstreams:shadowJar

Navigate into the application's home directory:

cd aggregating-sum/kstreams

Run the application, passing the Kafka client configuration file generated when you created Confluent Cloud resources:

java -cp ./build/libs/aggregating-sum-standalone.jar \
    io.confluent.developer.KafkaStreamsAggregatingCount \
    ./src/main/resources/cloud.properties

Validate that you see the correct ticket sale counts per title in the aggregation-sum-output topic.

confluent kafka topic consume aggregation-sum-output -b --print-key --delimiter :

You should see:

Guardians of the Galaxy:2 tickets sold
Doctor Strange:1 tickets sold

Clean up

When you are finished, delete the kafka-streams-aggregating-sum-env environment by first getting the environment ID of the form env-123456 corresponding to it:

confluent environment list

Delete the environment, including all resources created for this tutorial:

confluent environment delete <ENVIRONMENT ID>

docker compose -f ./docker/docker-compose-kafka.yml up -d

docker exec -it broker /bin/bash

kafka-topics --bootstrap-server localhost:9092 --create --topic aggregation-sum-input
kafka-topics --bootstrap-server localhost:9092 --create --topic aggregation-sum-output

kafka-console-producer --bootstrap-server localhost:9092 --topic aggregation-sum-input

{"title":"Guardians of the Galaxy", "ticketTotalValue":15}
{"title":"Doctor Strange", "ticketTotalValue":15}
{"title":"Guardians of the Galaxy", "ticketTotalValue":15}

./gradlew aggregating-sum:kstreams:shadowJar

cd aggregating-sum/kstreams

java -cp ./build/libs/aggregating-sum-standalone.jar \
    io.confluent.developer.KafkaStreamsAggregatingCount \
    ./src/main/resources/local.properties

kafka-console-consumer --bootstrap-server localhost:9092 --topic aggregation-sum-output --from-beginning --property "print.key=true" --property "key.separator=:"

Doctor Strange:1 tickets sold
Guardians of the Galaxy:2 tickets sold

docker compose -f ./docker/docker-compose-kafka.yml down