Flink流处理api之sink_error:(15, 43) java: 无法访问org.apache.flink.api.conn

概述

Flink中没有类似mapreduce、spark中的foreach方法让用户进行迭代的操作，所以所有对外的输出操作都要利用sink来完成
通过这样的形式来完成任务的输出操作

stream.addSink(new MySink(xxxxxx));
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当然 Flink 官网也集成了一些sink的框架

• 其中官方的有
  
• 还有Apache Bahir 下面的
  

kafak sink （重点）

导入依赖

<dependency>
 <groupId>org.apache.flink</groupId>
 <artifactId>flink-connector-kafka-0.11_2.12</artifactId>
 <version>1.10.1</version>
</dependency>
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实例：从Kafka接收数据后sink到Kafka

import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011;

import java.util.Properties;

public class Sink_Kafka {
    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //kafka 配置
        Properties properties = new Properties();
        properties.setProperty("bootstrap.servers", "192.168.216.111:9092,192.168.216.112:9092,192.168.216.113:9092");
        properties.setProperty("group.id", "flink-kafka");
        properties.setProperty("key.deserializer",
                "org.apache.kafka.common.serialization.StringDeserializer");
        properties.setProperty("value.deserializer",
                "org.apache.kafka.common.serialization.StringDeserializer");
        properties.setProperty("auto.offset.reset", "latest");


        // 读取Kafka topic中的数据
        DataStreamSource<String> stream = env.addSource(new FlinkKafkaConsumer011<String>(
                "sensor",
                new SimpleStringSchema(),
                properties
        ));

        // 发送到kafka生产者
        String brokerlist = "192.168.216.111:9092,192.168.216.112:9092,192.168.216.113:9092";
        String topic = "flink-kafka-sink";
        stream.addSink(new FlinkKafkaProducer011<String>(brokerlist,topic,new SimpleStringSchema()));
    }
}
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redis sink

依赖

<dependency>
            <groupId>org.apache.bahir</groupId>
            <artifactId>flink-connector-redis_2.11</artifactId>
            <version>1.0</version>
 </dependency>
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ElasticSearch sink

依赖

<dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-elasticsearch6_2.12</artifactId>
            <version>1.10.1</version>
</dependency>
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自定义 sink （重点）

在实际生活中的场景下我们很多时候要自定义sink操作，Flink 内置了一些基本的数据源和接收器，可以方便的写出sink操作。但是数据一致性等一些问题还需要我们考虑
下面来自定义mysql sink

引入mysql连接器依赖

<dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.44</version>
</dependency>
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实现sink jdbc

import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;

public class Sink_Custom_MySQL {
    public static void main(String[] args) throws Exception
    {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        DataStreamSource<SensorReading> inputDataStream = env.addSource(new SourceFromCustom.CustomSource());
        inputDataStream.addSink(new CustomJdbcSink());
        env.execute();
    }

    // 自定义 jdbc SinkFunction<T> sinkFunction
    public static class CustomJdbcSink extends RichSinkFunction<SensorReading>{
        Connection conn = null;
        PreparedStatement insertStmt = null;
        PreparedStatement updateStmt = null;

        // open 创建连接
        @Override
        public void open(Configuration parameters) throws Exception
        {
            //数据库连接参数
            conn = DriverManager.getConnection("jdbc:mysql://localhost:3306/flinkstudy","root","123456");
            // 创建与编译器，占位符 可传参
            insertStmt = conn.prepareStatement("INSERT INTO sensor (id, temp) VALUES (?, ?)");
            updateStmt = conn.prepareStatement("UPDATE sensor SET temp = ? WHERE id = ?");
        }
        // 调用连接，执行 sql
        @Override
        public void invoke(SensorReading value, Context context) throws Exception
        {
            updateStmt.setDouble(1,value.getTemperature());
            updateStmt.setString(2,value.getId());
            updateStmt.execute();
            // 如果刚才update 语句没有更新，那么插入
            if (updateStmt.getUpdateCount() == 0){
                insertStmt.setString(1,value.getId());
                insertStmt.setDouble(2,value.getTemperature());
                insertStmt.execute();
            }

        }
        @Override
        public void close() throws Exception{
            insertStmt.close();
            updateStmt.close();
            conn.close();
        }

    }

}
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