flink集成hikari

好的，以下是一个简单的 Flink 集成 Hikari 的示例代码：

// 导入必要的类
import org.apache.flink.api.common.functions.RuntimeContext;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.runtime.taskexecutor.TaskExecutor;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import org.apache.flink.streaming.api.scala.DataStream;
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment;

import java.sql.Connection;
import java.sql.PreparedStatement;
import java.sql.SQLException;

import com.zaxxer.hikari.HikariConfig;
import com.zaxxer.hikari.HikariDataSource;

// 创建 StreamExecutionEnvironment
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

// 创建一个包含数据的 DataStream
DataStream<String> dataStream = ...

// 配置 Hikari 连接池信息
HikariConfig config = new HikariConfig();
config.setJdbcUrl("your-jdbc-url");
config.setUsername("your-username");
config.setPassword("your-password");
config.addDataSourceProperty("cachePrepStmts", "true");
config.addDataSourceProperty("prepStmtCacheSize", "250");
config.addDataSourceProperty("prepStmtCacheSqlLimit", "2048");
HikariDataSource dataSource = new HikariDataSource(config);

// 创建一个用于写入数据库的 RichSinkFunction
RichSinkFunction<String> jdbcSink = new RichSinkFunction<String>() {
    private transient Connection connection;
    private transient PreparedStatement preparedStatement;

    @Override
    public void open(Configuration parameters) throws Exception {
        super.open(parameters);
        connection = dataSource.getConnection();
        preparedStatement = connection.prepareStatement("INSERT INTO your-table-name (name, count) VALUES (?, ?)");
    }

    @Override
    public void close() throws Exception {
        super.close();
        if (preparedStatement != null) {
            preparedStatement.close();
        }
        if (connection != null) {
            connection.close();
        }
    }

    @Override
    public void invoke(String value, Context context) throws Exception {
        String[] fields = value.split(",");
        preparedStatement.setString(1, fields[0]);
        preparedStatement.setInt(2, Integer.parseInt(fields[1]));
        preparedStatement.executeUpdate();
    }
};

// 将数据写入数据库
dataStream.addSink(jdbcSink);

// 执行 Flink 任务
env.execute("Flink Hikari Demo");

这段代码将数据流中的每个字符串对象解析为两个字段，然后插入到指定的表中。您可以根据需要修改此代码以符合您的数据格式和数据库结构。希望能帮助到您！