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# 演示: PolarDB-X CDC 导入 Elasticsearch
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本示例我们通过演示 PolarDB-X 借助 Flink-CDC 将数据导入至 Elasticsearch 来介绍 PolarDB-X 的增量订阅能力，你可以前往:[PolarDB-X](https://github.com/ApsaraDB/galaxysql) 了解更多细节。
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### 准备教程所需要的组件
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我们假设你运行在一台 MacOS 或者 Linux 机器上，并且已经安装 docker.
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#### 配置并启动容器
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配置 `docker-compose.yml`。
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```yaml
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version: '2.1'
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services:
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polardbx:
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polardbx:
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image: polardbx/polardb-x:2.0.1
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container_name: polardbx
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ports:
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- "8527:8527"
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elasticsearch:
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image: 'elastic/elasticsearch:7.6.0'
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container_name: elasticsearch
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environment:
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- cluster.name=docker-cluster
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- bootstrap.memory_lock=true
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- ES_JAVA_OPTS=-Xms512m -Xmx512m
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- discovery.type=single-node
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ports:
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- '9200:9200'
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- '9300:9300'
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ulimits:
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memlock:
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soft: -1
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hard: -1
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nofile:
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soft: 65536
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hard: 65536
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kibana:
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image: 'elastic/kibana:7.6.0'
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container_name: kibana
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ports:
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- '5601:5601'
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volumes:
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- '/var/run/docker.sock:/var/run/docker.sock'
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```
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该 Docker Compose 中包含的容器有：
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- PolarDB-X: 商品表 `products` 和 订单表 `orders` 将存储在该数据库中， 这两张表将进行关联，得到一张包含更多信息的订单表 `enriched_orders`
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- Elasticsearch: 最终的订单表 `enriched_orders` 将写到 Elasticsearch
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- Kibana: 用来可视化 ElasticSearch 的数据
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在 `docker-compose.yml` 所在目录下执行下面的命令来启动本教程需要的组件：
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```shell
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docker-compose up -d
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```
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该命令将以 detached 模式自动启动 Docker Compose 配置中定义的所有容器。你可以通过 docker ps 来观察上述的容器是否正常启动了，也可以通过访问 [http://localhost:5601/](http://localhost:5601/) 来查看 Kibana 是否运行正常
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### 准备数据：
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使用已创建的用户名和密码进行登陆PolarDB-X。
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```shell
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mysql -h127.0.0.1 -P8527 -upolardbx_root -p"123456"
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```
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```sql
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CREATE DATABASE mydb;
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USE mydb;
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-- 创建一张产品表，并写入一些数据
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CREATE TABLE products (
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id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY,
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name VARCHAR(255) NOT NULL,
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description VARCHAR(512)
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) AUTO_INCREMENT = 101;
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INSERT INTO products
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VALUES (default,"scooter","Small 2-wheel scooter"),
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(default,"car battery","12V car battery"),
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(default,"12-pack drill bits","12-pack of drill bits with sizes ranging from #40 to #3"),
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(default,"hammer","12oz carpenter's hammer"),
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(default,"hammer","14oz carpenter's hammer"),
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(default,"hammer","16oz carpenter's hammer"),
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(default,"rocks","box of assorted rocks"),
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(default,"jacket","water resistent black wind breaker"),
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(default,"spare tire","24 inch spare tire");
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-- 创建一张订单表，并写入一些数据
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CREATE TABLE orders (
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order_id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY,
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order_date DATETIME NOT NULL,
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customer_name VARCHAR(255) NOT NULL,
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price DECIMAL(10, 5) NOT NULL,
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product_id INTEGER NOT NULL,
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order_status BOOLEAN NOT NULL -- Whether order has been placed
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) AUTO_INCREMENT = 10001;
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INSERT INTO orders
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VALUES (default, '2020-07-30 10:08:22', 'Jark', 50.50, 102, false),
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(default, '2020-07-30 10:11:09', 'Sally', 15.00, 105, false),
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(default, '2020-07-30 12:00:30', 'Edward', 25.25, 106, false);
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```
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### 下载 Flink 和所需要的依赖包
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1. 下载 [Flink 1.16.0](https://archive.apache.org/dist/flink/flink-1.16.0/flink-1.16.0-bin-scala_2.12.tgz) 并将其解压至目录 `flink-1.16.0`
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2. 下载下面列出的依赖包，并将它们放到目录 `flink-1.16.0/lib/` 下
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```下载链接只对已发布的版本有效, SNAPSHOT 版本需要本地编译```
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- 用于订阅PolarDB-X Binlog: [flink-sql-connector-mysql-cdc-2.3.0.jar](https://repo1.maven.org/maven2/com/ververica/flink-sql-connector-mysql-cdc/2.3.0/flink-sql-connector-mysql-cdc-2.3.0.jar)
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- 用于写入Elasticsearch: [flink-sql-connector-elasticsearch7-1.16.0.jar](https://repo.maven.apache.org/maven2/org/apache/flink/flink-sql-connector-elasticsearch7/1.16.0/flink-sql-connector-elasticsearch7-1.16.0.jar)
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3. 启动flink服务:
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```shell
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./bin/start-cluster.sh
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```
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我们可以访问 [http://localhost:8081/](http://localhost:8081/) 看到Flink正常运行:
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4. 启动Flink SQL CLI:
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```shell
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./bin/sql-client.sh
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```
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### 在 Flink SQL CLI 中使用 Flink DDL 创建表
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```sql
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-- 设置间隔时间为3秒
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Flink SQL> SET execution.checkpointing.interval = 3s;
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-- 创建source1 -订单表
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Flink SQL> CREATE TABLE orders (
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order_id INT,
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order_date TIMESTAMP(0),
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customer_name STRING,
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price DECIMAL(10, 5),
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product_id INT,
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order_status BOOLEAN,
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PRIMARY KEY (order_id) NOT ENFORCED
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) WITH (
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'connector' = 'mysql-cdc',
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'hostname' = '127.0.0.1',
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'port' = '8527',
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'username' = 'polardbx_root',
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'password' = '123456',
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'database-name' = 'mydb',
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'table-name' = 'orders'
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);
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-- 创建source2 -产品表
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CREATE TABLE products (
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id INT,
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name STRING,
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description STRING,
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PRIMARY KEY (id) NOT ENFORCED
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) WITH (
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'connector' = 'mysql-cdc',
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'hostname' = '127.0.0.1',
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'port' = '8527',
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'username' = 'polardbx_root',
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'password' = '123456',
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'database-name' = 'mydb',
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'table-name' = 'products'
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);
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-- 创建sink - 关联后的结果表
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Flink SQL> CREATE TABLE enriched_orders (
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order_id INT,
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order_date TIMESTAMP(0),
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customer_name STRING,
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price DECIMAL(10, 5),
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product_id INT,
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order_status BOOLEAN,
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product_name STRING,
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product_description STRING,
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PRIMARY KEY (order_id) NOT ENFORCED
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) WITH (
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'connector' = 'elasticsearch-7',
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'hosts' = 'http://localhost:9200',
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'index' = 'enriched_orders'
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);
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-- 执行读取和写入
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Flink SQL> INSERT INTO enriched_orders
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SELECT o.order_id,
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o.order_date,
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o.customer_name,
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o.price,
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o.product_id,
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o.order_status,
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p.name,
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p.description
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FROM orders AS o
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LEFT JOIN products AS p ON o.product_id = p.id;
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```
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### 在 Kibana 中查看数据
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访问 [http://localhost:5601/app/kibana#/management/kibana/index_pattern](http://localhost:5601/app/kibana#/management/kibana/index_pattern)
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创建 index pattern `enriched_orders`，之后可以在 [http://localhost:5601/app/kibana#/discover](http://localhost:5601/app/kibana#/discover) 看到写入的数据了。
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### 修改监听表数据，查看增量数据变动
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在PolarDB-X中依次执行如下修改操作，每执行一步就刷新一次 Kibana，可以看到 Kibana 中显示的订单数据将实时更新。
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```sql
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INSERT INTO orders VALUES (default, '2020-07-30 15:22:00', 'Jark', 29.71, 104, false);
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UPDATE orders SET order_status = true WHERE order_id = 10004;
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DELETE FROM orders WHERE order_id = 10004;
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```
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### 环境清理
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在 `docker-compose.yml` 文件所在的目录下执行如下命令停止所有容器：
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```shell
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docker-compose down
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```
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进入Flink的部署目录，停止 Flink 集群：
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```shell
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./bin/stop-cluster.sh
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```
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