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

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

Suppose you have a topic with events that represent ticket sales for movies. In this tutorial, we will use ksqlDB to calculate the total number of tickets sold per movie.

Setup

Let's assume the following DDL for our base movie_ticket_sales stream:

CREATE STREAM movie_ticket_sales (title VARCHAR, sale_ts VARCHAR, ticket_total_value INT)
    WITH (KAFKA_TOPIC='movie-ticket-sales',
          PARTITIONS=1,
          VALUE_FORMAT='AVRO');

Compute the count

Given the movie_ticket_sales stream definition above, we can figure out the total number of tickets sold per movie using the following COUNT aggregation:

SELECT title,
       COUNT(*) AS tickets_sold
FROM movie_ticket_sales
GROUP BY title
EMIT CHANGES;

Running the example

You can run the example backing this tutorial in one of two ways: locally with the ksql CLI against Kafka and ksqlDB running in Docker, or with Confluent Cloud.

Local With Docker

Prerequisites

Run the commands

Clone the confluentinc/tutorials GitHub repository (if you haven't already) and navigate to the tutorials directory:

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

Start ksqlDB and Kafka:

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

Next, open the ksqlDB CLI:

docker exec -it ksqldb-cli ksql http://ksqldb-server:8088

Run the following SQL statements to create the movie_ticket_sales stream backed by Kafka running in Docker and populate it with test data.

CREATE STREAM movie_ticket_sales (title VARCHAR, sale_ts VARCHAR, ticket_total_value INT)
    WITH (KAFKA_TOPIC='movie-ticket-sales',
          PARTITIONS=1,
          VALUE_FORMAT='AVRO');
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Unfrosted', '2024-09-18T10:00:00Z', 10);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Family Switch', '2024-09-18T10:00:00Z', 12);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Family Switch', '2024-09-18T10:01:00Z', 12);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T10:01:31Z', 12);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Family Switch', '2024-09-18T10:01:36Z', 24);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T10:02:00Z', 18);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T11:40:00Z', 36);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T11:40:09Z', 18);

Finally, run the aggregating count query. Note that we first tell ksqlDB to consume from the beginning of the stream, and we also configure the query to use caching so that we only get a single output record per key (movie title).

SET 'auto.offset.reset'='earliest';
SET 'ksql.streams.cache.max.bytes.buffering' = '10000000';

SELECT title,
       COUNT(*) AS tickets_sold
FROM movie_ticket_sales
GROUP BY title
EMIT CHANGES;

The query output should look like this:

+----------------------------------+----------------------------------+
|TITLE                             |TICKETS_SOLD                      |
+----------------------------------+----------------------------------+
|Unfrosted                         |1                                 |
|Family Switch                     |3                                 |
|Twisters                          |4                                 |
+----------------------------------+----------------------------------+

When you are finished, exit the ksqlDB CLI by entering CTRL-D and clean up the containers used for this tutorial by running:

docker compose -f ./docker/docker-compose-ksqldb.yml down
Confluent Cloud

Prerequisites

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-cloud_kickstart

Run the following command to create a Confluent Cloud environment and Kafka cluster. This will create resources in AWS region us-west-2 by default, but you may override these choices by passing the --cloud argument with a value of aws, gcp, or azure, and the --region argument that is one of the cloud provider's supported regions, which you can list by running confluent kafka region list --cloud <CLOUD PROVIDER>

confluent cloud-kickstart --name ksqldb-tutorial \
  --environment-name ksqldb-tutorial \
  --output-format stdout

Now, create a ksqlDB cluster by first getting your user ID of the form u-123456 when you run this command:

confluent iam user list

And then create a ksqlDB cluster called ksqldb-tutorial with access linked to your user account:

confluent ksql cluster create ksqldb-tutorial \
  --credential-identity <USER ID>

Run the commands

Login to the Confluent Cloud Console. Select Environments in the lefthand navigation, and then click the ksqldb-tutorial environment tile. Click the ksqldb-tutorial Kafka cluster tile, and then select ksqlDB in the lefthand navigation.

The cluster may take a few minutes to be provisioned. Once its status is Up, click the cluster name and scroll down to the editor.

In the query properties section at the bottom, change the value for auto.offset.reset to Earliest so that ksqlDB will consume from the beginning of the stream we create. Then click Add another field and add a property cache.max.bytes.buffering with value 10000000. This configures the count query to use caching so that we only get a single output record per key (movie title).

Enter the following statements in the editor and click Run query. This creates the movie_ticket_sales stream and populates it with test data.

CREATE STREAM movie_ticket_sales (title VARCHAR, sale_ts VARCHAR, ticket_total_value INT)
    WITH (KAFKA_TOPIC='movie-ticket-sales',
          PARTITIONS=1,
          VALUE_FORMAT='AVRO');

INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Unfrosted', '2024-09-18T10:00:00Z', 10);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Family Switch', '2024-09-18T10:00:00Z', 12);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Family Switch', '2024-09-18T10:01:00Z', 12);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T10:01:31Z', 12);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Family Switch', '2024-09-18T10:01:36Z', 24);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T10:02:00Z', 18);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T11:40:00Z', 36);
INSERT INTO movie_ticket_sales (title, sale_ts, ticket_total_value) VALUES ('Twisters', '2024-09-18T11:40:09Z', 18);

Now paste the aggregating count query in the editor and click Run query:

SELECT title,
       COUNT(*) AS tickets_sold
FROM movie_ticket_sales
GROUP BY title
EMIT CHANGES;

The query output should look like this (order may vary):

+----------------------------------+----------------------------------+
|TITLE                             |TICKETS_SOLD                      |
+----------------------------------+----------------------------------+
|Unfrosted                         |1                                 |
|Family Switch                     |3                                 |
|Twisters                          |4                                 |
+----------------------------------+----------------------------------+

Clean up

When you are finished, delete the ksqldb-tutorial 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>