Hadoop之MapReduce （排序）

今天我们将json数据以用户排序，取出每个用户评分最高的前三个。

UserRateTop 类

import org.apache.hadoop.io.WritableComparable;

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

public class UserRateTop implements WritableComparable<UserRateTop> {
     
    private String movie;
    private String timeStamp;
    private Integer rate;
    private String uid;


    public String getMovie() {
     
        return movie;
    }

    public void setMovie(String movie) {
     
        this.movie = movie;
    }

    public String getTimeStamp() {
     
        return timeStamp;
    }

    public void setTimeStamp(String timeStamp) {
     
        this.timeStamp = timeStamp;
    }

    public Integer getRate() {
     
        return rate;
    }

    public void setRate(Integer rate) {
     
        this.rate = rate;
    }

    public String getUid() {
     
        return uid;
    }

    public void setUid(String uid) {
     
        this.uid = uid;
    }

    @Override
    public String toString() {
     
        return "UserRateTop{" +
                "movie='" + movie + '\'' +
                ", timeStamp='" + timeStamp + '\'' +
                ", rate=" + rate +
                ", uid='" + uid + '\'' +
                '}';
    }

    @Override
    public int compareTo(UserRateTop o) {
     
        return o.getRate().compareTo(this.rate);
    }

    @Override
    public void write(DataOutput dataOutput) throws IOException {
     

        dataOutput.writeUTF(this.movie);
        dataOutput.writeInt(this.rate);
        dataOutput.writeUTF(this.timeStamp);
        dataOutput.writeUTF(this.uid);
    }

    @Override
    public void readFields(DataInput dataInput) throws IOException {
     
        this.movie = dataInput.readUTF();
        this.rate = dataInput.readInt();
        this.timeStamp = dataInput.readUTF();
        this.uid = dataInput.readUTF();
    }
}

MapReduce类

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.codehaus.jackson.map.ObjectMapper;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;

public class UserRateSort {
     
    public static class UserMap extends Mapper<LongWritable, Text,Text, UserRateTop>{
     
        ObjectMapper objectMapper = new ObjectMapper();
        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
     
            String line = value.toString();
            UserRateTop userRateTop = objectMapper.readValue(line,UserRateTop.class);
            context.write(new Text(userRateTop.getUid()),userRateTop);
        }
    }
    public static class UserReduce extends Reducer<Text,UserRateTop,UserRateTop, NullWritable>{
     
        @Override
        protected void reduce(Text key, Iterable<UserRateTop> values, Context context) throws IOException, InterruptedException {
     
            ArrayList<UserRateTop> userRateTops = new ArrayList<UserRateTop>();
            for (UserRateTop value: values) {
     
            //在这里要在创建个UserRateTop对象，获取里面的属性。如果不获取，每次循环都会将
            //前面的数据覆盖掉。即都是用户评分的最后一行数据。
                UserRateTop top = new UserRateTop();
                top.setMovie(value.getMovie());
                top.setRate(value.getRate());
                top.setTimeStamp(value.getTimeStamp());
                top.setUid(value.getUid());
                userRateTops.add(top);
            }
            Collections.sort(userRateTops);
            for (int i = 0; i < 3; i++) {
     
                context.write(userRateTops.get(i),NullWritable.get());
            }
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
     
        Configuration conf = new Configuration();


        Job job = Job.getInstance();
        conf.set("yarn.resorcemanager.hostname","192.168.72.110");
        conf.set("fs.deafutFS", "hdfs://192.168.72.110:9000/");


        job.setJarByClass(UserRateSort.class);
        job.setMapperClass(UserMap.class);
        job.setReducerClass(UserReduce.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(UserRateTop.class);
        job.setOutputKeyClass(UserRateTop.class);
        job.setOutputValueClass(NullWritable.class);

        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);

        FileInputFormat.setInputPaths(job,new Path(args[0]));
        FileOutputFormat.setOutputPath(job,new Path(args[1]));

        job.submit();
        boolean b = job.waitForCompletion(true);
        System.exit(b ? 0:1);
    }
}

将其打包上传到虚拟机执行，结果如下。