（6）FlinkSQL将kafka数据写入到mysql方式一

这里不展开zookeeper、kafka安装配置（1）首先需要启动zookeeper和kafka

（2）定义一个kafka生产者

package com.producers;

import com.alibaba.fastjson.JSONObject;
import com.pojo.Event;
import com.pojo.WaterSensor;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
import org.apache.kafka.common.serialization.StringSerializer;

import java.util.Properties;
import java.util.Random;

/**

• Created by lj on 2022-07-09.
  */

public class Kafaka_Producer {

public final static String bootstrapServers = "127.0.0.1:9092";

public static void main(String[] args) {
    Properties props = new Properties();
    //设置Kafka服务器地址
    props.put("bootstrap.servers", bootstrapServers);
    //设置数据key的序列化处理类
    props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
    //设置数据value的序列化处理类
    props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
    KafkaProducer producer = new KafkaProducer<>(props);

    try {
        int i = 0;
        Random r=new Random();   //不传入种子
        String[] lang = {"flink","spark","hadoop","hive","hbase","impala","presto","superset","nbi"};

        while(true) {
            Thread.sleep(2000);
            WaterSensor waterSensor = new WaterSensor(lang[r.nextInt(lang.length)],i,i);
            i++;

            String msg = JSONObject.toJSONString(waterSensor);
            System.out.println(msg);
            RecordMetadata recordMetadata = producer.send(new ProducerRecord<>("kafka_data_waterSensor", null, null,  msg)).get();

// System.out.println("recordMetadata: {"+ recordMetadata +"}");

        }

    } catch (Exception e) {
        System.out.println(e.getMessage());
    }
}

}

（3）定义一个消息对象
package com.pojo;

import java.io.Serializable;

/**

• Created by lj on 2022-07-05.
  */

public class WaterSensor implements Serializable {

private String id;
private long ts;
private int vc;

public WaterSensor(){

}

public WaterSensor(String id,long ts,int vc){
    this.id = id;
    this.ts = ts;
    this.vc = vc;
}

public int getVc() {
    return vc;
}

public void setVc(int vc) {
    this.vc = vc;
}

public String getId() {
    return id;
}

public void setId(String id) {
    this.id = id;
}

public long getTs() {
    return ts;
}

public void setTs(long ts) {
    this.ts = ts;
}

}

（4）从kafka接入数据，并写入到mysql

public static void main(String[] args) throws Exception {

    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(1);
    StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

    //读取kafka的数据
    Properties properties = new Properties();
    properties.setProperty("bootstrap.servers","127.0.0.1:9092");
    properties.setProperty("group.id", "consumer-group");
    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");

    DataStreamSource streamSource = env.addSource(
            new FlinkKafkaConsumer(
                    "kafka_waterSensor",
                    new SimpleStringSchema(),
                    properties)
    );

    SingleOutputStreamOperator waterDS = streamSource.map(new MapFunction() {
        @Override
        public WaterSensor map(String s) throws Exception {
            JSONObject json  = (JSONObject)JSONObject.parse(s);
            return new WaterSensor(json.getString("id"),json.getLong("ts"),json.getInteger("vc"));
        }
    });

    // 将流转化为表
    Table table = tableEnv.fromDataStream(waterDS,
            $("id"),
            $("ts"),
            $("vc"),
            $("pt").proctime());

    tableEnv.createTemporaryView("EventTable", table);


    tableEnv.executeSql("CREATE TABLE flinksink (" +
            "componentname STRING," +
            "componentcount BIGINT NOT NULL," +
            "componentsum BIGINT" +
            ") WITH (" +
            "'connector.type' = 'jdbc'," +
            "'connector.url' = 'jdbc:mysql://localhost:3306/testdb?characterEncoding=UTF-8&useUnicode=true&useSSL=false&tinyInt1isBit=false&allowPublicKeyRetrieval=true&serverTimezone=Asia/Shanghai'," +
            "'connector.table' = 'flinksink'," +
            "'connector.driver' =  'com.mysql.cj.jdbc.Driver'," +
            "'connector.username' = 'root'," +
            "'connector.password' = 'root'," +
            "'connector.write.flush.max-rows'='3'\r\n" +
            ")"
    );
    Table mysql_user = tableEnv.from("flinksink");
    mysql_user.printSchema();

    Table result = tableEnv.sqlQuery(
            "SELECT " +
                    "id as componentname, " +                //window_start, window_end,
                    "COUNT(ts) as componentcount ,SUM(ts) as componentsum " +
                    "FROM TABLE( " +
                    "TUMBLE( TABLE EventTable , " +
                    "DESCRIPTOR(pt), " +
                    "INTERVAL '10' SECOND)) " +
                    "GROUP BY id , window_start, window_end"
    );

    //方式一：写入数据库

// result.executeInsert("flinksink").print(); //;.insertInto("flinksink");

    //方式二：写入数据库
    tableEnv.createTemporaryView("ResultTable", result);
    tableEnv.executeSql("insert into flinksink SELECT * FROM ResultTable").print();

// tableEnv.toAppendStream(result, Row.class).print("toAppendStream"); //追加模式

    env.execute();

}

（5）效果演示