要将Flink中的MySQL数据同步到PostgreSQL中，可以使用Flink CDC（Change Data Capture）功能和Flink JDBC连接器。
安装Flink CDC插件：在Flink安装目录下的lib文件夹中添加flink-connector-mysql-cdc.jar包，并重启Flink。
在Flink作业中配置MySQL CDC Source，将MySQL表的更改捕获为流式数据。示例代码如下：
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(1);
Properties properties = new Properties();
properties.setProperty("scan.startup.mode", "initial");
properties.setProperty("database.server.name", "mysql-server");
properties.setProperty("database.hostname", "localhost");
properties.setProperty("database.port", "3306");
properties.setProperty("database.user", "user");
properties.setProperty("database.password", "password");
properties.setProperty("database.whitelist", "db.table");
DataStreamSource<RowData> mysqlSource = env.addSource(new MySqlCdcSourceFunction(properties), "mysql-source");
- 将MySQL CDC Source输出的流式数据写入PostgreSQL。示例代码如下：
String postgresqlJdbcUrl = "jdbc:postgresql://localhost:5432/postgres?user=postgres&password=password";
JdbcConnectionOptions jdbcConnectionOptions = JdbcConnectionOptions.builder()
.withDriverName("org.postgresql.Driver")
.withUrl(postgresqlJdbcUrl)
.build();
JdbcOutputFormat jdbcOutputFormat = JdbcOutputFormat.buildJdbcOutputFormat()
.setOptions(jdbcConnectionOptions)
.setQuery("INSERT INTO public.table (id, name) VALUES (?, ?)")
.finish();
mysqlSource
.map(new MapFunction<RowData, Tuple2<String, String>>() {
@Override
public Tuple2<String, String> map(RowData rowData) throws Exception {
return new Tuple2(rowData.getString(0), rowData.getString(1));
}
})
.name("map to tuple")
.returns(Types.TUPLE(Types.STRING, Types.STRING))
.addSink(jdbcOutputFormat)
.name("postgresql-output");
env.execute("mysql-to-postgresql");
注意：上述示例代码仅供参考，具体实现需要根据业务需求进行调整和优化。
