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How to join a stream and a table in ksqlDB

ksqlDBKafka Streams
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How to join a stream and a table in ksqlDB

Suppose that you have events in a Kafka topic and a table of reference data (also known as a lookup table). Let's see how you can join each event in the stream to attributes in the table based on a common key.

Setup

Let's use the example of a movie rating event stream. But the stream only contains the movie id, which isn't very descriptive, so you want to enrich it with some additional information. So you'll set up join between the stream and a table that contains fact or lookup data.

Here's the movie rating stream:

CREATE STREAM ratings (movie_id INT KEY, rating DOUBLE)
  WITH (KAFKA_TOPIC='ratings', 
        PARTITIONS=1, 
        VALUE_FORMAT='JSON');

And this is the table definition containing the movie reference data:

CREATE TABLE movies (id INT PRIMARY KEY, title VARCHAR, release_year INT)
    WITH (KAFKA_TOPIC='movies', 
          PARTITIONS=1, 
          VALUE_FORMAT='JSON');

Note that for a stream-table join to succeed, the primary key of the table must be the key of the stream. For example, the movies primary key id matches up with the ratings stream key of movie_id.

With your stream and table in place you can build a join like this:

CREATE STREAM rated_movies AS
    SELECT ratings.movie_id AS id, title, rating
    FROM ratings
    LEFT JOIN movies ON ratings.movie_id = movies.id;

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 ratings stream and movies table backed by Kafka running in Docker and populate them with test data.

CREATE STREAM ratings (movie_id INT KEY, rating DOUBLE)
  WITH (KAFKA_TOPIC='ratings', 
        PARTITIONS=1, 
        VALUE_FORMAT='JSON');
CREATE TABLE movies (id INT PRIMARY KEY, title VARCHAR, release_year INT)
    WITH (KAFKA_TOPIC='movies', 
          PARTITIONS=1, 
          VALUE_FORMAT='JSON');
INSERT INTO movies (id, title, release_year) VALUES (294, 'Twisters', 2024);
INSERT INTO movies (id, title, release_year) VALUES (354, 'Unfrosted', 2024);
INSERT INTO movies (id, title, release_year) VALUES (782, 'Family Switch', 2023);

INSERT INTO ratings (movie_id, rating) VALUES (294, 8.2);
INSERT INTO ratings (movie_id, rating) VALUES (294, 8.5);
INSERT INTO ratings (movie_id, rating) VALUES (354, 9.9);
INSERT INTO ratings (movie_id, rating) VALUES (354, 9.7);
INSERT INTO ratings (movie_id, rating) VALUES (782, 7.8);
INSERT INTO ratings (movie_id, rating) VALUES (782, 7.7);
INSERT INTO ratings (movie_id, rating) VALUES (782, 2.1);

Finally, run the stream-table join query and land the results in a new rated_movies stream. Note that we first tell ksqlDB to consume from the beginning of the streams.

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

CREATE STREAM rated_movies AS
    SELECT ratings.movie_id AS id, title, rating
    FROM ratings
    LEFT JOIN movies ON ratings.movie_id = movies.id
    EMIT CHANGES;

Query the new stream:

SELECT *
FROM rated_movies
EMIT CHANGES;

The query output should look like this:

+----------------------+----------------------+----------------------+
|ID                    |TITLE                 |RATING                |
+----------------------+----------------------+----------------------+
|294                   |Twisters              |8.2                   |
|294                   |Twisters              |8.5                   |
|354                   |Unfrosted             |9.9                   |
|354                   |Unfrosted             |9.7                   |
|782                   |Family Switch         |7.8                   |
|782                   |Family Switch         |7.7                   |
|782                   |Family Switch         |2.1                   |
+----------------------+----------------------+----------------------+

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 streams we create.

Enter the following statements in the editor and click Run query. This creates the ratings stream and movies table and populates them with test data.

CREATE STREAM ratings (movie_id INT KEY, rating DOUBLE)
  WITH (KAFKA_TOPIC='ratings', 
        PARTITIONS=1, 
        VALUE_FORMAT='JSON');

CREATE TABLE movies (id INT PRIMARY KEY, title VARCHAR, release_year INT)
    WITH (KAFKA_TOPIC='movies', 
          PARTITIONS=1, 
          VALUE_FORMAT='JSON');

INSERT INTO movies (id, title, release_year) VALUES (294, 'Twisters', 2024);
INSERT INTO movies (id, title, release_year) VALUES (354, 'Unfrosted', 2024);
INSERT INTO movies (id, title, release_year) VALUES (782, 'Family Switch', 2023);

INSERT INTO ratings (movie_id, rating) VALUES (294, 8.2);
INSERT INTO ratings (movie_id, rating) VALUES (294, 8.5);
INSERT INTO ratings (movie_id, rating) VALUES (354, 9.9);
INSERT INTO ratings (movie_id, rating) VALUES (354, 9.7);
INSERT INTO ratings (movie_id, rating) VALUES (782, 7.8);
INSERT INTO ratings (movie_id, rating) VALUES (782, 7.7);
INSERT INTO ratings (movie_id, rating) VALUES (782, 2.1);

Now, paste the stream-table join query in the editor and click Run query. This will land the results in a new rated_movies stream.

CREATE STREAM rated_movies AS
    SELECT ratings.movie_id AS id, title, rating
    FROM ratings
    LEFT JOIN movies ON ratings.movie_id = movies.id
    EMIT CHANGES;

Query the new stream:

SELECT *
FROM rated_movies
EMIT CHANGES;

The query output should look like this:

+----------------------+----------------------+----------------------+
|ID                    |TITLE                 |RATING                |
+----------------------+----------------------+----------------------+
|294                   |Twisters              |8.2                   |
|294                   |Twisters              |8.5                   |
|354                   |Unfrosted             |9.9                   |
|354                   |Unfrosted             |9.7                   |
|782                   |Family Switch         |7.8                   |
|782                   |Family Switch         |7.7                   |
|782                   |Family Switch         |2.1                   |
+----------------------+----------------------+----------------------+

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>