# 中文教程 1. 下载 `docker-compose.yml` ``` version: '2.1' services: postgres: image: debezium/example-postgres:1.1 ports: - "5432:5432" environment: - POSTGRES_PASSWORD=1234 - POSTGRES_DB=postgres - POSTGRES_USER=postgres - POSTGRES_PASSWORD=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" zookeeper: image: wurstmeister/zookeeper:3.4.6 ports: - "2181:2181" kafka: image: wurstmeister/kafka:2.12-2.2.1 ports: - "9092:9092" - "9094:9094" depends_on: - zookeeper environment: - KAFKA_ADVERTISED_LISTENERS=INSIDE://:9094,OUTSIDE://localhost:9092 - KAFKA_LISTENERS=INSIDE://:9094,OUTSIDE://:9092 - KAFKA_LISTENER_SECURITY_PROTOCOL_MAP=INSIDE:PLAINTEXT,OUTSIDE:PLAINTEXT - KAFKA_INTER_BROKER_LISTENER_NAME=INSIDE - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 - KAFKA_CREATE_TOPICS="user_behavior:1:1" volumes: - /var/run/docker.sock:/var/run/docker.sock ``` 2. 进入 mysql 容器,初始化数据: ``` docker-compose exec mysql mysql -uroot -p123456 ``` ```sql -- MySQL CREATE DATABASE mydb; USE mydb; CREATE TABLE products ( id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY, name VARCHAR(255) NOT NULL, description VARCHAR(512) ); ALTER TABLE products AUTO_INCREMENT = 101; INSERT INTO products VALUES (default,"scooter","Small 2-wheel scooter"), (default,"car battery","12V car battery"), (default,"12-pack drill bits","12-pack of drill bits with sizes ranging from #40 to #3"), (default,"hammer","12oz carpenter's hammer"), (default,"hammer","14oz carpenter's hammer"), (default,"hammer","16oz carpenter's hammer"), (default,"rocks","box of assorted rocks"), (default,"jacket","water resistent black wind breaker"), (default,"spare tire","24 inch spare tire"); CREATE TABLE orders ( order_id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY, order_date DATETIME NOT NULL, customer_name VARCHAR(255) NOT NULL, price DECIMAL(10, 5) NOT NULL, product_id INTEGER NOT NULL, order_status BOOLEAN NOT NULL -- 是否下单 ) AUTO_INCREMENT = 10001; INSERT INTO orders VALUES (default, '2020-07-30 10:08:22', 'Jark', 50.50, 102, false), (default, '2020-07-30 10:11:09', 'Sally', 15.00, 105, false), (default, '2020-07-30 12:00:30', 'Edward', 25.25, 106, false); ``` 3. 进入postgres 容器,初始化数据: ``` docker-compose exec postgres psql -h localhost -U postgres ``` ```sql -- PG CREATE TABLE shipments ( shipment_id SERIAL NOT NULL PRIMARY KEY, order_id SERIAL NOT NULL, origin VARCHAR(255) NOT NULL, destination VARCHAR(255) NOT NULL, is_arrived BOOLEAN NOT NULL ); ALTER SEQUENCE public.shipments_shipment_id_seq RESTART WITH 1001; ALTER TABLE public.shipments REPLICA IDENTITY FULL; INSERT INTO shipments VALUES (default,10001,'Beijing','Shanghai',false), (default,10002,'Hangzhou','Shanghai',false), (default,10003,'Shanghai','Hangzhou',false); ``` 4. 下载以下 jar 包到 `/lib/`: - [flink-sql-connector-elasticsearch7_2.11-1.11.1.jar](https://repo.maven.apache.org/maven2/org/apache/flink/flink-sql-connector-elasticsearch7_2.11/1.11.1/flink-sql-connector-elasticsearch7_2.11-1.11.1.jar) - [flink-sql-connector-mysql-cdc-1.0.0.jar](https://repo1.maven.org/maven2/com/alibaba/ververica/flink-sql-connector-mysql-cdc/1.0.0/flink-sql-connector-mysql-cdc-1.0.0.jar) - [flink-sql-connector-postgres-cdc-1.0.0.jar](https://repo1.maven.org/maven2/com/alibaba/ververica/flink-sql-connector-postgres-cdc/1.0.0/flink-sql-connector-postgres-cdc-1.0.0.jar) 5. 然后启动 Flink 集群,再启动 SQL CLI. ```sql --FlinkSQL CREATE TABLE products ( id INT, name STRING, description STRING ) 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 ) WITH ( 'connector' = 'mysql-cdc', 'hostname' = 'localhost', 'port' = '3306', 'username' = 'root', 'password' = '123456', 'database-name' = 'mydb', 'table-name' = 'orders' ); CREATE TABLE shipments ( shipment_id INT, order_id INT, origin STRING, destination STRING, is_arrived BOOLEAN ) 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' ); 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. 修改 mysql 和 postgres 里面的数据,观察 elasticsearch 里的结果。 ```sql --MySQL INSERT INTO orders VALUES (default, '2020-07-30 15:22:00', 'Jark', 29.71, 104, false); --PG INSERT INTO shipments VALUES (default,10004,'Shanghai','Beijing',false); --MySQL UPDATE orders SET order_status = true WHERE order_id = 10004; --PG UPDATE shipments SET is_arrived = true WHERE shipment_id = 1004; --MySQL DELETE FROM orders WHERE order_id = 10004; ``` 7. Kafka changelog json format 在 SQL CLI 中: ```sql --Flink SQL CREATE TABLE kafka_gmv ( day_str STRING, gmv DECIMAL(10, 5) ) WITH ( 'connector' = 'kafka', 'topic' = 'kafka_gmv', 'scan.startup.mode' = 'earliest-offset', 'properties.bootstrap.servers' = 'localhost:9092', 'format' = 'changelog-json' ); INSERT INTO kafka_gmv SELECT DATE_FORMAT(order_date, 'yyyy-MM-dd') as day_str, SUM(price) as gmv FROM orders WHERE order_status = true GROUP BY DATE_FORMAT(order_date, 'yyyy-MM-dd'); -- 读取 Kafka 的 changelog 数据,观察 materialize 后的结果 SELECT * FROM kafka_gmv; ``` 观察 kafka 的输出: ``` docker-compose exec kafka bash -c 'kafka-console-consumer.sh --topic kafka_gmv --bootstrap-server kafka:9094 --from-beginning' ``` 更新 orders 数据,观察SQL CLI 和 kafka console 的输出 ```sql -- MySQL UPDATE orders SET order_status = true WHERE order_id = 10001; UPDATE orders SET order_status = true WHERE order_id = 10002; UPDATE orders SET order_status = true WHERE order_id = 10003; INSERT INTO orders VALUES (default, '2020-07-30 17:33:00', 'Timo', 50.00, 104, true); UPDATE orders SET price = 40.00 WHERE order_id = 10005; DELETE FROM orders WHERE order_id = 10005; ```