How to join two streams of data in Java using Flink's Table API for Confluent Cloud

Prerequisites

• A Confluent Cloud account
• The Confluent CLI installed on your machine
• Python 3.8 or later
• Java 21, e.g., follow the OpenJDK installation instructions here if you don't have Java. Validate that java -version shows version 21. Note: Java is required since the Flink Python API uses Py4J to communicate with the JVM under the hood.
• 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

Provision Confluent Cloud infrastructure

If you already have the Confluent Cloud resources required to populate a Table API client configuration file, e.g., from running a different tutorial, you may skip to the next step after creating or copying the properties file as documented here to joining-stream-stream/flink_table_api_python/cloud.properties within the top-level tutorials directory.

If you need to create the Confluent Cloud infrastructure needed to run this tutorial, the confluent-flink-quickstart CLI plugin creates the resources that you need to get started with Confluent Cloud for Apache Flink. Install it by running:

confluent plugin install confluent-flink-quickstart

Run the plugin as follows to create the Confluent Cloud resources needed for this tutorial and generate a Table API client configuration file. 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 flink region list --cloud <CLOUD>.

confluent flink quickstart \
    --name flink_table_api_tutorials \
    --max-cfu 10 \
    --region us-east-1 \
    --cloud aws \
    --table-api-client-config-file ./joining-stream-stream/flink_table_api_python/cloud.properties

The plugin should complete in under a minute and will generate a properties file as documented here.

Inspect the code

Take a look at the source code in joining-stream-stream/flink_table_api_python/joining-stream-stream.py. These two lines instantiate a table environment for executing Table API programs against Confluent Cloud:

settings = ConfluentSettings.from_file("./cloud.properties")
env = TableEnvironment.create(settings)

Let's join two of Confluent Cloud's example tables: orders and customers. You can find these tables in the read-only marketplace database of the examples catalog. The source code in this example uses the Table API's Table.join method to join these tables on the common customer_id key. Note that we must rename one table's customer_id field since the field names of the two joined tables can't overlap. We also add a condition that the row time of the order must be greater than or equal to the row time of the customer row.

table_result = orders_table \
    .join(customers_table, col('order_time') >= col('customer_time')
                           and col('order_customer_id') == col('customer_id')) \
    .select(
        col('order_id'),
        col('product_id'),
        col('name'),
        col('order_time'),
        col('customer_time')
    ) \
    .execute()

Given the table result, we can then materialize (in memory) the rows in the resulting stream by calling ConfluentTools.collect_materialized_limit or ConfluentTools.print_materialized_limit. This line materializes and prints 5 rows from the table result:

ConfluentTools.print_materialized_limit(table_result, 5)

Run the program

In order to run the program, first create a Python virtual environment in which to install the required dependencies. E.g., run the following commands to use the venv module. Note: use python3 and pip3 in the following commands if python and pip refer to Python 2 on your system.

cd joining-stream-stream/flink_table_api_python/
python -m venv venv; source ./venv/bin/activate;

Install the confluent-flink-table-api-python-plugin package:

pip install confluent-flink-table-api-python-plugin

You can run the example program directly in your IDE by opening the project located at joining-stream-stream/flink_table_api_python/, or via the command line:

python joining-stream-stream.py

The program will output 5 rows materialized via print_materialized_limit. The output will look like this:

+--------------------------------+------------+----------------------+-------------------------+-------------------------+
|                       order_id | product_id |                 name |              order_time |           customer_time |
+--------------------------------+------------+----------------------+-------------------------+-------------------------+
| ba98cd10-e1fc-45cd-99d1-e06... |       1220 |        Alonso Stokes | 2025-03-18 11:37:14.194 | 2025-03-18 11:37:13.698 |
| abdcc320-7d8c-47f7-970d-bba... |       1381 |         Emilia Huels | 2025-03-18 11:37:13.935 | 2025-03-18 11:37:13.698 |
| cfb0147c-5ce1-4bf9-8bd9-7ca... |       1196 | Miss Stephan Ruecker | 2025-03-18 11:37:13.895 | 2025-03-18 11:37:13.796 |
| 36f1e707-fed4-4c8e-92a5-b55... |       1365 | Miss Stephan Ruecker | 2025-03-18 11:37:13.995 | 2025-03-18 11:37:13.796 |
| 109dd8f8-293b-4a98-a972-fea... |       1393 |        Alease Russel | 2025-03-18 11:37:13.697 | 2025-03-18 11:37:13.994 |
+--------------------------------+------------+----------------------+-------------------------+-------------------------+
5 rows in set

Tear down Confluent Cloud infrastructure

When you are done, be sure to clean up any Confluent Cloud resources created for this tutorial. Since you created all resources in a Confluent Cloud environment, you can simply delete the environment and most of the resources created for this tutorial (e.g., the Kafka cluster and Flink compute pool) will be deleted. Run the following command in your terminal to get the environment ID of the form env-123456 corresponding to the environment named flink_table_api_tutorials_environment:

confluent environment list

Delete the environment:

confluent environment delete <ENVIRONMENT_ID>

Next, delete the Flink API key. This API key isn't associated with the deleted environment so it needs to be deleted separately. Find the key:

confluent api-key list --resource flink --current-user

And then copy the 16-character alphanumeric key and delete it:

confluent api-key delete <KEY>

Finally, for the sake of housekeeping, delete the Table API client configuration file:

rm joining-stream-stream/flink_table_api_python/cloud.properties