简介

综合资源包

方法 / 步骤

一: 部署Flink

• 添加Flink 到环境变量

#flink
export FLINK_HOME=/usr/local/flink/flink-1.15.0/
export PATH=$FLINK_HOME/bin:$PATH

# 重载环境变量配置
source /etc/profile
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• Flink 配置

# 开启外网访问
rest.bind-address: 0.0.0.0
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• 启动Flink

# 启动Flink集群
./start-cluster.sh

# 停止Flink集群
#./stop-cluster.sh

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启动成功以后访问 服务的8081端口，可看到Flink Web UI 界面：

二: 配置同步插件Flink_CDC并配置Demo

2.1 上传Flink_CDC驱动包和MySQL驱动包：放到主文件的lib目录下

elasticsearch连接器-后面的是flink的版本，要保证和flink版本一致。
ES SQL驱动包

2.2流式ETL作业demo

# 校验是否开启binlog 如果显示OFF则代表未开启
show variables like 'log_bin';
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如果没有开启,找到配置文件添加配置

[mysqld]
#开启binlog
log-bin = mysql-bin

#选择row模式
binlog-format = ROW

#配置mysql replication需要定义,不能喝canal的slaveId重复
server_id = 1 
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2.2.1 MySQL创建数据库和表 products，orders，并插入数据

-- MySQL
CREATE DATABASE flinkcdc;
USE flinkcdc;
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 -- Whether order has been placed
) 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);
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三: 创建Flink_CDC虚拟表

3.1 启动Flink SQL CLI

./bin/sql-client.sh
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• 开启 checkpoint，每隔3秒做一次 checkpoint

Flink SQL> SET execution.checkpointing.interval = 3s;
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3.2 控制台创建CDC虚拟表

• 使用 Flink SQL CLI 创建对应的表，用于同步这些底层数据库表的数据：

CREATE TABLE products (
    id INT,
    name STRING,
    description STRING,
    PRIMARY KEY (id) NOT ENFORCED
  ) WITH (
    'connector' = 'mysql-cdc',
    'hostname' = '192.168.3.23',
    'port' = '3307',
    'username' = 'root',
    'password' = 'My123456',
    'database-name' = 'flinkcdc',
    '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',
    'hostname' = '192.168.3.23',
    'port' = '3307',
    'username' = 'root',
    'password' = 'My123456',
    'database-name' = 'flinkcdc',
    'table-name' = 'orders'
  );


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• 查询是否添加成功

select * from orders;
select * from products;
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四: Flink_CDC创建ES数据

4.1 创建ES数据

• 创建 enriched_orders 表， 用来将关联后的订单数据写入 Elasticsearch 中

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,
   PRIMARY KEY (order_id) NOT ENFORCED
 ) WITH (
     'connector' = 'elasticsearch-7',
     'hosts' = 'http://192.168.1.71:9200',
     'index' = 'enriched_orders'
 );
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• 创建 enriched_orders 表， 用来将关联后的订单数据写入 Elasticsearch 中

insert into enriched_orders
select 
	o.order_id      as order_id,
	o.order_date    as order_date,
	o.customer_name as customer_name,
	o.price         as price,
	o.product_id    as product_id,
	o.order_status  as order_status,
	p.name          as product_name,
	p.description   as product_description
from orders as o
left join products as p on o.product_id=p.id;
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4.2 访问 Kibana 可看到订单宽表的数据：

接下来，修改 MySQL 和 Postgres 数据库中表的数据，Kibana中显示的订单数据也将实时更新：

参考资料 & 致谢

[1] [GitHub仓库] flink
[2] [GitHub仓库] link-cdc-connectors
[3] [FlinkCDC实时同步MySQL数据到ES
[4] 从 MySQL 到 ElasticSearch