确定所有日期内所有住房单元的最大每小时耗电量。您的处理应生成一个值。
我有这个样本数据

LOG_ID     HOUSE_ID CONDATE     CONHOUR ENERGY_READING  FLAG

3682572 16  2019-01-01   05:21:50   11143.735496    0

3682573 16  2019-01-01  05:22:00    11143.738274    0

3682574 16  2019-01-01  05:22:10    11143.741052    0

3682575 16  2019-01-01  05:22:20    11143.74383 0

3682576 16  2019-01-01  05:22:30    11143.746608    0

3682577 16  2019-01-01  05:22:40    11143.749386    0

3682578 16  2019-01-01  05:22:50    11143.752164    0

3682579 16  2019-01-01  05:23:00    11143.754942    0

3682580 16  2019-01-01  05:23:10    11143.75772 0

3682581 16  2019-01-01  05:23:20    11143.760498    0

3682582 16  2019-01-01  05:23:30    11143.763276    0

3682583 16  2019-01-01  05:23:40    11143.766054    0

3682584 16  2019-01-01  05:23:50    11143.768832    0

这是样本数据。其中能量消耗是累积的。所以在这里我想找到每天的最大小时消耗。
我试过了：Map器类

import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;

public class EnergyMapper
        extends Mapper<LongWritable, Text, Text, FloatWritable> {
    @Override
    protected void map(LongWritable key, Text value, Mapper.Context context) throws IOException, InterruptedException {
        String[] values = value.toString().split("\\s+");
        String date;

        int houseId;
        String time;
        double energyReading;
        EnergyValues ev;

        try {
            date = values[2];
            houseId = Integer.parseInt(values[1]);
            time = values[3];
            energyReading = Double.parseDouble(values[4]);
            ev = new EnergyValues(houseId,time,energyReading,date);
        }
        catch (Exception e){
            date = "NA";
            ev = new EnergyValues();
        }
        context.write(new Text(date), ev);
    }
}

异径管等级

import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Calendar;
import java.util.Date;
import java.io.IOException;

public class EnergyReducer extends Reducer<Text, EnergyValues, Text, EnergyValues> {
    @Override
    protected void reduce(Text key, Iterable<EnergyValues> sales, Context context)
            throws IOException, InterruptedException {
        String Data = "";
     //   int i = 0;
        double  Consumption = 0.0D;
        double  minConsumption = 0.0D;
        double  MaxConsumption = 0.0D;

        for (EnergyValues amount: sales) {

            //maxConsumption =

            try {
                minConsumption = getHourlyComp(key,sales,amount.getTime());
            } catch (ParseException e) {
                throw new RuntimeException(e);
            }

            Consumption = minConsumption - amount.getEnergyReading() ;
            System.out.println("outside function +++++++++++++++++++++++++");
            System.out.println(amount.getEnergyReading() );

            MaxConsumption = Math.max(MaxConsumption, Consumption);

            Data =  amount.getHouseId()+","+ ","+ amount.getTime() + "," + amount.getEnergyReading();
        }

        context.write(new Text(String.valueOf(MaxConsumption)), new EnergyValues(Data));

    }

    public double getHourlyComp(Text key, Iterable<EnergyValues> sales, String time)throws ParseException{

        float maxConsumption = 0.0F;

        for (EnergyValues amount: sales) {

               // String hours = time.substring(0, 2);

               // if (hours != "23"){
                    if (key.toString() == amount.getDate()) {

                        String myTime = time;
                        SimpleDateFormat df = new SimpleDateFormat("HH:MM:SS");
                        Date d = df.parse(myTime);
                        Calendar cal = Calendar.getInstance();
                        cal.setTime(d);
                        cal.add(Calendar.HOUR, 1);
                        String newTime = df.format(cal.getTime());

                        if (newTime == amount.getTime()) {
                            System.out.println("Inside function ----------------------");
                            System.out.println(amount.getEnergyReading() );
                            return amount.getEnergyReading();
                        }
                    }
          //  }

        }
        return 0;
    }
}

能源价值类

import org.apache.hadoop.io.Writable;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

public class EnergyValues implements Writable {
    int houseId;
    String time;
    double energyReading;
    String date;

    String data;

    public EnergyValues(){
        this.houseId = 0;
        this.time = "";
        this.energyReading =0.0;
        this.date = "";
    }
    public EnergyValues( String value2) {
        this.data = value2;
        }
    public EnergyValues(int val1, String val2, double val3,String val4) {
        this.houseId = val1;
        this.time = val2;
        this.energyReading = val3;
        this.date =val4;
    }

    public int getHouseId() {
        return houseId;
    }

    public String getTime() {return time; }

    public double getEnergyReading(){return energyReading;}

    public String getDate(){return date;}

    @Override
    public void write(DataOutput dataOutput) throws IOException {
        dataOutput.writeInt(houseId);
        dataOutput.writeChars(time);
        dataOutput.writeDouble(energyReading);
        dataOutput.writeChars(date);
    }

    @Override
    public void readFields(DataInput dataInput) throws IOException {
        houseId = dataInput.readInt();
        time = String.valueOf(dataInput.readChar());
        energyReading = dataInput.readDouble();
        date = String.valueOf(dataInput.readChar());
    }

}

但是当我运行这个程序时，我得到的结果是

0.0     EnergyValues@f79a760

0.0     EnergyValues@14f5da2c

0.0     EnergyValues@239b0f9d

0.0     EnergyValues@619bfe29

0.0     EnergyValues@1eb6749b

0.0     EnergyValues@652a7737

0.0     EnergyValues@2bef51f2

0.0     EnergyValues@650eab8