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How to update the number of partitions of a Kafka topic with ksqlDB

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How to update the number of partitions of a Kafka topic with ksqlDB

Imagine you want to change the partitions of your Kafka topic. You can use a streaming transformation to automatically stream all the messages from the original topic into a new Kafka topic that has the desired number of partitions.

Setup

To accomplish this transformation, first create a stream based on the original topic:

CREATE STREAM s1 (k VARCHAR KEY, v VARCHAR)
    WITH (KAFKA_TOPIC='topic',
          VALUE_FORMAT='JSON');

Then, create a second stream that reads everything from the original topic and puts into a new topic with the desired number of partitions:

CREATE STREAM s2
    WITH (KAFKA_TOPIC='topic2',
          VALUE_FORMAT='JSON',
          PARTITIONS=2) AS
    SELECT *
    FROM s1
    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 s1 stream backed by Kafka running in Docker and populate it with test data.

CREATE STREAM s1 (k VARCHAR KEY, v VARCHAR)
    WITH (KAFKA_TOPIC='topic',
          PARTITIONS=1,
          VALUE_FORMAT='JSON');
INSERT INTO s1 (k, v) VALUES ('hello', 'world');
INSERT INTO s1 (k, v) VALUES ('foo', 'bar');
INSERT INTO s1 (k, v) VALUES ('bar', 'baz');

Next, run the CREATE STREAM AS SELECT query to populate a new topic, topic2 with the same events in topic but having 2 partitions.

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

CREATE STREAM s2
    WITH (KAFKA_TOPIC='topic2',
          VALUE_FORMAT='JSON',
          PARTITIONS=2) AS
    SELECT *
    FROM s1
    EMIT CHANGES;

Observe the expected number of partitions when you run the kafka-topics command in the broker container:

docker exec -it broker kafka-topics --bootstrap-server localhost:29092 --describe --topic topic1
docker exec -it broker kafka-topics --bootstrap-server localhost:29092 --describe --topic topic2

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.

Enter the following statements in the editor and click Run query. This creates the s1 stream and populates it with test data.

CREATE STREAM s1 (k VARCHAR KEY, v VARCHAR)
    WITH (KAFKA_TOPIC='topic',
          PARTITIONS=1,
          VALUE_FORMAT='JSON');

INSERT INTO s1 (k, v) VALUES ('hello', 'world');
INSERT INTO s1 (k, v) VALUES ('foo', 'bar');
INSERT INTO s1 (k, v) VALUES ('bar', 'baz');

Now paste the CREATE STREAM AS SELECT query to populate a new topic, topic2 with the same events in topic but having 2 partitions.

CREATE STREAM s2
    WITH (KAFKA_TOPIC='topic2',
          VALUE_FORMAT='JSON',
          PARTITIONS=2) AS
    SELECT *
    FROM s1
    EMIT CHANGES;

Observe the expected number of partitions for the topic and topic2 topics when you navigate to Topics in the lefthand navigation of the Confluent Cloud Console.

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>