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How to count the number of messages in a topic with ksqlDB

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How to count the number of messages in a topic with ksqlDB

It can be useful to know how many messages are currently in a topic, but you cannot calculate this directly based on the offsets, because you need to consider the topic's retention policy, log compaction, and potential duplicate messages. In this example, we'll take a topic of pageview data and see how we can count all the messages in the topic. Note that the time complexity for this tutorial is O(n) (linear); processing time will depend on the number of messages in the topic, and large data sets will require long running times.

Setup

First, create a stream over the topic you're interested in counting the number of records.

CREATE STREAM pageviews (msg VARCHAR)
  WITH (KAFKA_TOPIC ='pageviews',
        VALUE_FORMAT='JSON');

Note that at this stage we’re just interested in counting the messages in their entirety, so we define the loosest schema possible, msg VARCHAR, for speed. Also, you'll need to configure ksqlDB to start from the beginning of the topic so that all messages are included in the count:

SET 'auto.offset.reset' = 'earliest';

Then COUNT the events in the pageviews stream:

SELECT COUNT(*) AS msg_count
FROM pageviews
EMIT CHANGES;

The query above will run continually until you cancel it.

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 pageviews stream backed by Kafka running in Docker and populate it with test data.

CREATE STREAM pageviews (msg VARCHAR)
  WITH (KAFKA_TOPIC ='pageviews',
        PARTITIONS=1,
        VALUE_FORMAT='JSON');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/home');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/search');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/home');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/products');

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 count result.

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

SELECT COUNT(*) AS msg_count
FROM pageviews
EMIT CHANGES;

The query output should look like this:

+----------------------------------------+
|MSG_COUNT                               |
+----------------------------------------+
|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 final count in this example as oppposed to updates for every event in the pageviews stream.

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

CREATE STREAM pageviews (msg VARCHAR)
  WITH (KAFKA_TOPIC ='pageviews',
        PARTITIONS=1,
        VALUE_FORMAT='JSON');

INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/home');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/search');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/home');
INSERT INTO pageviews (msg) VALUES ('https://www.acme.com/products');

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

SELECT COUNT(*) AS msg_count
FROM pageviews
EMIT CHANGES;

The query output should look like this:

+----------------------------------------+
|MSG_COUNT                               |
+----------------------------------------+
|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>