Flink Getting Started Guide¶

There are four different approaches to deploy and run Apache Flink / Confluent Flink:

1. Local Binary Installation
2. Docker-based local deployment
3. Kubernetes Deployment Colima, AKS, EKS, GKS, King or minicube
4. Confluent Cloud Managed Service

Prerequisites¶

Before getting started, ensure you have:

1. Java 11 or higher installed (OpenJDK)
2. Docker Engine and Docker CLI (for Docker and Kubernetes deployments)
3. kubectl and Helm (for Kubernetes deployment)
4. Confluent Cloud account (for Confluent Cloud deployment)
5. Confluent cli installed
6. Git clone this repository.

1. Open Source Apache Flink Local Binary Installation¶

This approach is ideal for development and testing on a single machine.

Installation Steps¶

1. Download and extract Flink binary

   # Using the provided script
   ./deployment/product-tar/install-local.sh
   
   # Or manually
   curl https://dlcdn.apache.org/flink/flink-1.20.1/flink-1.20.1-bin-scala_2.12.tgz --output flink-1.20.1-bin-scala_2.12.tgz
   tar -xzf flink-1.20.1-bin-scala_2.12.tgz
   

2. Download and extract Kafka binary See download versions

   curl https://downloads.apache.org/kafka/3.9.0/kafka_2.13-3.9.0.tgz  --output kafka_2.13-3.9.0.tgz 
   tar -xvf kafka_2.13-3.9.0.tgz
   cd kafka_2.13-3.9.0
   KAFKA_CLUSTER_ID="$(bin/kafka-storage.sh random-uuid)"
   bin/kafka-storage.sh format -t $KAFKA_CLUSTER_ID -c config/kraft/server.properties
   

3. Set environment variables:

   export FLINK_HOME=$(pwd)/flink-1.20.1
   export KAFKA_HOME=$(pwd)/kafka_2.13-3.9.0
   export PATH=$PATH:$FLINK_HOME/bin:$KAFKA_HOME/bin
   

4. Start the Flink cluster:

   $FLINK_HOME/bin/start-cluster.sh
   

5. Access the Web UI at http://localhost:8081

6. Submit a job (Java application)

   ./bin/flink run ./examples/streaming/TopSpeedWindowing.jar
   ./bin/flink list
   ./bin/flink cancel <id> 
   

7. Download needed SQL connector for Kafka

   cd flink-1.20.1
   mkdir sql-lib
   cd sql-lib
   curl https://repo.maven.apache.org/maven2/org/apache/flink/flink-sql-connector-kafka/3.4.0-1.20/flink-sql-connector-kafka-3.4.0-1.20.jar --output flink-sql-connector-kafka-3.4.0-1.20.jar
   

8. Stop the cluster:

   $FLINK_HOME/bin/stop-cluster.sh
   

Running a simple SQL application¶

1. Start Kafka cluster and create topics

   $KAFKA_HOME/bin/kafka-server-start.sh $KAFKA_HOME/config/kraft/server.properties
   $KAFKA_HOME/bin/kafka-topics.sh --create --topic flink-input --bootstrap-server localhost:9092
   $KAFKA_HOME/bin/kafka-topics.sh --create --topic message-count --bootstrap-server localhost:9092
   

2. Use the Flink SQL Shell:

   $FLINK_HOME/bin/sql-client.sh --library $FLINK_HOME/sql-lib
   

   • Create a table using Kafka connector:

     CREATE TABLE flinkInput (
        `raw` STRING,
        `ts` TIMESTAMP(3) METADATA FROM 'timestamp'
     ) WITH (
        'connector' = 'kafka',
        'topic' = 'flink-input',
        'properties.bootstrap.servers' = 'localhost:9092',
        'properties.group.id' = 'j9rGroup',
        'scan.startup.mode' = 'earliest-offset',
        'format' = 'raw'
     );
     

   • Create an output table in a debezium format so we can see the before and after data:

     CREATE TABLE msgCount (
        `count` BIGINT NOT NULL
     ) WITH (
        'connector' = 'kafka',
        'topic' = 'message-count',
        'properties.bootstrap.servers' = 'localhost:9092',
        'properties.group.id' = 'j9rGroup',
        'scan.startup.mode' = 'earliest-offset',
        'format' = 'debezium-json'
     );
     

   • Make the simplest flink processing by counting the messages:

     INSERT INTO msgCount SELECT COUNT(*) as `count` FROM flinkInput;
     

     The result will look like:

     [INFO] Submitting SQL update statement to the cluster...
     [INFO] SQL update statement has been successfully submitted to the cluster:
     Job ID: 2be58d7f7f67c5362618b607da8265d7
     

   • Start a producer in one terminal

      bin/kafka-console-producer.sh --topic flink-input --bootstrap-server localhost:9092
     

   • Verify result in a second terminal

     bin/kafka-console-consumer.sh -topic message-count  --bootstrap-server localhost:9092
     

     The results will be a list of debezium records like

     {"before":null,"after":{"count":1},"op":"c"}
     {"before":{"count":1},"after":null,"op":"d"}
     {"before":null,"after":{"count":2},"op":"c"}
     {"before":{"count":2},"after":null,"op":"d"}
     {"before":null,"after":{"count":3},"op":"c"}
     {"before":{"count":3},"after":null,"op":"d"}
     {"before":null,"after":{"count":4},"op":"c"}
     

3. [Optional] Start SQL Gateway for concurrent SQL queries:

   $FLINK_HOME/bin/sql-gateway.sh start -Dsql-gateway.endpoint.rest.address=localhost
   

See product documentation for different examples. To do some Python Table API demonstrations see this chapter.

Troubleshooting¶

• If port 8081 is already in use, modify $FLINK_HOME/conf/flink-conf.yaml
• Check logs in $FLINK_HOME/log directory
• Ensure Java 11+ is installed and JAVA_HOME is set correctly

2. Docker-based Deployment¶

This approach provides containerized deployment using Docker Compose.

Quick Start¶

1. Build a custom Apache Flink image with your own connectors. Verify current docker image tag then use the Dockerfile:

   cd deployment/custom-flink-image
   docker build -t jbcodeforce/myflink .
   

2. Start Flink session cluster:

   cd deployment/docker
   docker compose up -d
   

Docker Compose with Kafka¶

To run Flink with Kafka:

cd deployment/docker
docker compose -f kafka-docker-compose.yaml up -d

Customization¶

• Modify deployment/custom-flink-image/Dockerfile to add required connectors
• Update deployment/docker/flink-oss-docker-compose.yaml for configuration changes

During development, we can use docker-compose to start a simple Flink session cluster or a standalone job manager to execute one unique job, which has the application jar mounted inside the docker image. We can use this same environment to do SQL based Flink apps.

As Task manager will execute the job, it is important that the container running the flink code has access to the jars needed to connect to external sources like Kafka or other tools like FlinkFaker. Therefore, in deployment/custom-flink-image, there is a Dockerfile to get the needed jars to build a custom Flink image that may be used for Taskmanager and SQL client. Always update the jar version with new Flink version.

3. Kubernetes Deployment¶

This approach provides scalable, production-ready deployment using Kubernetes.

Apache Flink¶

See the K8S deployment deeper dive chapter and the lab readme for details.

Confluent Platform Manager for Flink on Kubernetes¶

See Kubernetes deployment chapter for detailed instructions, and the deployment folder and readme. See also the Confluent operator documentation, submit Flink SQL Statement with Confluent Manager for Apache Flink:

For Confluent Platform deployment:

1. Install Confluent Flink Operator (see CMF product get started):

   make deploy_cp_flink_operator
   

2. Deploy Confluent Platform Kafka cluster:

   make deploy_cp_cluster
   

3. Deploy Confluent Manager for Flink (cmf)

4. Deploy Flink applications

5. Work with SQL

4. Confluent Cloud Deployment¶

This approach provides a fully managed Flink service.

1. Create a Flink compute pool:

   confluent flink compute-pool create my-pool --cloud aws --region us-west-2
   

2. Start SQL client:

   confluent flink shell
   

3. Submit SQL statements:

   CREATE TABLE my_table (
     id INT,
     name STRING
   ) WITH (
     'connector' = 'kafka',
     'topic' = 'my-topic',
     'properties.bootstrap.servers' = 'pkc-xxxxx.region.provider.confluent.cloud:9092',
     'properties.security.protocol' = 'SASL_SSL',
     'properties.sasl.mechanism' = 'PLAIN',
     'properties.sasl.jaas.config' = 'org.apache.kafka.common.security.plain.PlainLoginModule required username="<API_KEY>" password="<API_SECRET>";',
     'format' = 'json'
   );
   

See Confluent Cloud Flink documentation for more details.

See the Shift Left project to manage bigger Flink project with a dedicated CLI.

Choosing the Right Deployment Approach¶

Additional Resources¶

• Apache Flink Documentation
• Confluent Cloud Documentation
• Flink Kubernetes Operator
• Docker Hub Flink Images
• Shift Left project to manage Flink project at scale.