flink cdc 集成paimon样例

### Flink CDC 集成 Paimon 示例代码与教程 #### 使用 Flink CDC 连接器读取 MySQL 数据并写入 Paimon 表 为了实现这一目标，可以按照如下方式配置和编写代码： 1. **引入依赖** 在 `pom.xml` 文件中添加必要的 Maven 依赖项以支持 Flink CDC 和 Paimon。 ```xml <dependencies> <!-- Flink dependencies --> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.12</artifactId> <version>${flink.version}</version> </dependency> <!-- Flink CDC Connector for MySQL --> <dependency> <groupId>com.ververica</groupId> <artifactId>flink-connector-mysql-cdc</artifactId> <version>${cdc.connector.version}</version> </dependency> <!-- Apache Paimon Table Store --> <dependency> <groupId>org.apache.paimon</groupId> <artifactId>paimon-flink</artifactId> <version>${paimon.version}</version> </dependency> </dependencies> ``` 2. **创建表结构定义** 使用 SQL DDL 定义要同步到 Paimon 中的目标表。这里假设有一个名为 `orders` 的订单表。 ```sql CREATE TABLE orders ( order_id BIGINT NOT NULL, user_id BIGINT, product_name STRING, amount DOUBLE, PRIMARY KEY (order_id) NOT ENFORCED ) WITH ( 'connector' = 'paimon', 'warehouse.path' = 'file:///path/to/paimon/warehouse' ); ``` 3. **编写 Flink 应用程序** 下面是一个完整的 Java 实现例子，它展示了如何利用 Flink CDC 将来自 MySQL 的变更数据捕获并通过 Paimon 存储起来。 ```java import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; import com.alibaba.ververica.cdc.connectors.mysql.MySqlSource; import com.alibaba.ververica.cdc.debezium.DebeziumDeserializationSchema; import org.apache.flink.formats.json.JsonRowDataDeserializationSchema; import org.apache.flink.table.api.TableResult; import org.apache.flink.table.api.bridge.java.StreamTableEnvironment; public class MysqlToPaimonExample { public static void main(String[] args) throws Exception { final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); final StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env); MySqlSource<String> mySqlSource = MySqlSource.<String>builder() .hostname("localhost") .port(3306) .databaseList("test_db") // database name .tableList("test_db.orders") // table names, format is {database}.{table} .username("root") .password("your_password") .deserializer(new JsonRowDataDeserializationSchema()) // convert to JSON string .build(); tableEnv.executeSql(""" CREATE TABLE paimon_orders ( order_id BIGINT NOT NULL, user_id BIGINT, product_name STRING, amount DOUBLE, PRIMARY KEY(order_id) NOT ENFORCED ) WITH ( 'connector' = 'paimon', 'warehouse.path' = '/tmp/paimon_example' ) """); var cdcStream = env.fromSource(mySqlSource, WatermarkStrategy.noWatermarks(), "MySQL Source"); tableEnv.createTemporaryView("source_table", cdcStream.map(record -> record)); tableEnv.executeSql("INSERT INTO paimon_orders SELECT * FROM source_table").await(); } } ``` 此应用程序会持续监听 MySQL 数据库中的变化，并将这些更改实时地应用到指定路径下的 Paimon 表中[^1]。