Building a Real-Time MySQL and PostgreSQL Streaming ETL with Flink CDC

This tutorial demonstrates how to quickly build a streaming ETL pipeline that captures changes from MySQL and PostgreSQL using Flink CDC and writes enriched order data to Elasticsearch.

Prerequisites: Docker installed on a Linux or macOS machine.

1. Prepare components – a docker-compose.yml file starts MySQL, PostgreSQL, Elasticsearch, Kibana and Flink containers.

version: '2.1'
services:
  postgres:
    image: debezium/example-postgres:1.1
    ports:
      - "5432:5432"
    environment:
      - POSTGRES_PASSWORD=1234
      - POSTGRES_DB=postgres
      - POSTGRES_USER=postgres
  mysql:
    image: debezium/example-mysql:1.1
    ports:
      - "3306:3306"
    environment:
      - MYSQL_ROOT_PASSWORD=123456
      - MYSQL_USER=mysqluser
      - MYSQL_PASSWORD=mysqlpw
  elasticsearch:
    image: elastic/elasticsearch:7.6.0
    environment:
      - cluster.name=docker-cluster
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
      - discovery.type=single-node
    ports:
      - "9200:9200"
      - "9300:9300"
    ulimits:
      memlock:
        soft: -1
        hard: -1
      nofile:
        soft: 65536
        hard: 65536
  kibana:
    image: elastic/kibana:7.6.0
    ports:
      - "5601:5601"

2. Load sample data into MySQL (tables products and orders ) and PostgreSQL (table shipments ) using the SQL statements below.

-- MySQL
CREATE DATABASE mydb;
USE mydb;
CREATE TABLE products (
  id INT AUTO_INCREMENT PRIMARY KEY,
  name VARCHAR(255) NOT NULL,
  description VARCHAR(512)
);
INSERT INTO products VALUES
  (DEFAULT,'scooter','Small 2‑wheel scooter'),
  (DEFAULT,'car battery','12V car battery'),
  ...;

CREATE TABLE orders (
  order_id INT AUTO_INCREMENT PRIMARY KEY,
  order_date DATETIME NOT NULL,
  customer_name VARCHAR(255) NOT NULL,
  price DECIMAL(10,5) NOT NULL,
  product_id INT NOT NULL,
  order_status BOOLEAN NOT NULL
) AUTO_INCREMENT=10001;
INSERT INTO orders VALUES
  (DEFAULT,'2020-07-30 10:08:22','Jark',50.50,102,FALSE),
  ...;

-- PostgreSQL
CREATE TABLE shipments (
  shipment_id SERIAL PRIMARY KEY,
  order_id INT NOT NULL,
  origin VARCHAR(255) NOT NULL,
  destination VARCHAR(255) NOT NULL,
  is_arrived BOOLEAN NOT NULL
);
INSERT INTO shipments VALUES
  (DEFAULT,10001,'Beijing','Shanghai',FALSE),
  ...;

3. Start Flink – run ./bin/start-cluster.sh to launch the Flink cluster and then ./bin/sql-client.sh to open the Flink SQL CLI.

4. Create CDC source tables and Elasticsearch sink in the SQL CLI.

-- Flink SQL
CREATE TABLE products (
  id INT,
  name STRING,
  description STRING,
  PRIMARY KEY (id) NOT ENFORCED
) WITH (
  'connector' = 'mysql-cdc',
  'hostname' = 'localhost',
  'port' = '3306',
  'username' = 'root',
  'password' = '123456',
  'database-name' = 'mydb',
  'table-name' = 'products'
);

CREATE TABLE orders (
  order_id INT,
  order_date TIMESTAMP(0),
  customer_name STRING,
  price DECIMAL(10,5),
  product_id INT,
  order_status BOOLEAN,
  PRIMARY KEY (order_id) NOT ENFORCED
) WITH (
  'connector' = 'mysql-cdc',
  ...
);

CREATE TABLE shipments (
  shipment_id INT,
  order_id INT,
  origin STRING,
  destination STRING,
  is_arrived BOOLEAN,
  PRIMARY KEY (shipment_id) NOT ENFORCED
) WITH (
  'connector' = 'postgres-cdc',
  'hostname' = 'localhost',
  'port' = '5432',
  'username' = 'postgres',
  'password' = 'postgres',
  'database-name' = 'postgres',
  'schema-name' = 'public',
  'table-name' = 'shipments'
);

CREATE TABLE enriched_orders (
  order_id INT,
  order_date TIMESTAMP(0),
  customer_name STRING,
  price DECIMAL(10,5),
  product_id INT,
  order_status BOOLEAN,
  product_name STRING,
  product_description STRING,
  shipment_id INT,
  origin STRING,
  destination STRING,
  is_arrived BOOLEAN,
  PRIMARY KEY (order_id) NOT ENFORCED
) WITH (
  'connector' = 'elasticsearch-7',
  'hosts' = 'http://localhost:9200',
  'index' = 'enriched_orders'
);

5. Insert joined data into Elasticsearch using an INSERT‑SELECT statement.

INSERT INTO enriched_orders
SELECT o.*, p.name, p.description, s.shipment_id, s.origin, s.destination, s.is_arrived
FROM orders AS o
LEFT JOIN products AS p ON o.product_id = p.id
LEFT JOIN shipments AS s ON o.order_id = s.order_id;

6. Verify results in Kibana; the order view updates in real time as you modify the source tables (INSERT, UPDATE, DELETE examples are provided).

7. Clean up – stop all containers with docker-compose down and shut down the Flink cluster with ./bin/stop-cluster.sh .

Conclusion: The guide provides a hands‑on example of using Flink CDC for real‑time data integration across relational databases and a search engine, illustrating the end‑to‑end workflow from source capture to Elasticsearch visualization.