练习：Flink 自定义 process 和 source

package com;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@AllArgsConstructor
@NoArgsConstructor
public class Sensor {
    private String sensorId;
    private Long sensorTime;
    private Double sensorTemp;
}

package com;


import org.apache.flink.streaming.api.functions.source.SourceFunction;
import java.util.HashMap;
import java.util.Random;

public class MySource implements SourceFunction<Sensor> {
    
    //基础温度
    private Integer base;
    //构造
    public MySource(Integer base){
        this.base=base;
    }
    
    //开关
    private Boolean running = true;
    //随机数
    private Random random = new Random();
    
    @Override
    public void run(SourceContext<Sensor> sourceContext) throws Exception {
        //stmap<sensorId,temperature>
        HashMap<String, Double> stmap = new HashMap<>();
        //10个一组,初始化
        for (int i = 0; i < 10; i++) {
            stmap.put("sensor_"+(i+1),base*1.0) ;
        }

        while (running){
            for (String id : stmap.keySet()) {
                //重新生成随机温度，满足正态分布
                double newTemp = stmap.get(id) + random.nextGaussian()*20;
                stmap.put(id,newTemp);
                //封装成传感器对象
                Sensor sensor = new Sensor(id, System.currentTimeMillis(), newTemp);
                //进流
                sourceContext.collect(sensor);
                //每秒1个
                Thread.sleep(1000);
            }
        }
    }

    @Override
    public void cancel() {
        //关停
        running = false;

    }
}

package com;

import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;
import org.apache.flink.util.OutputTag;

//自定义process算子
public class MyProcess extends ProcessFunction<Sensor,Sensor> {

    //分流依据
    private Double temperature;
    public  MyProcess(Double temperature){
        this.temperature=temperature;
    }

    @Override
    public void processElement(Sensor sensor, Context context, Collector<Sensor> collector) throws Exception {
        if (sensor.getSensorTemp()>temperature){
            //主流
            collector.collect(sensor);
        }else {
            //存入侧输出标签
            context.output(new OutputTag<Sensor>("low"){},sensor);
        }

    }
}

package com;

import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.timestamps.BoundedOutOfOrdernessTimestampExtractor;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.OutputTag;
//测试类
public class MyTest {
    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        //获取自定义类数据源，以60度正态分布
        DataStream<Sensor> data = env.addSource(new MySource(60));
        //水位线允许1s延迟
        SingleOutputStreamOperator<Sensor> datas = data.assignTimestampsAndWatermarks(new BoundedOutOfOrdernessTimestampExtractor<Sensor>(Time.seconds(1)) {
            @Override
            public long extractTimestamp(Sensor sensor) {
                return sensor.getSensorTime() * 1000;
            }
        });
        //自定义process,分流判断依据60.0摄氏度
        SingleOutputStreamOperator<Sensor> res = datas.process(new MyProcess(60.0));
        //根据id:low获得侧输出流
        DataStream<Sensor> sideOutput = res.getSideOutput(new OutputTag<Sensor>("low") {});
        //主流输出
        res.print("high");
        //侧流输出
        sideOutput.print("low");

        try {
            env.execute();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}