Hadoop之MapReduce （排序3）

今天我们还是统计最热门的前四电影。用Combiner

import com.sort2.UserRateTop;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;

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.apache.htrace.fasterxml.jackson.databind.ObjectMapper;
import org.apache.log4j.BasicConfigurator;

import java.io.IOException;
import java.util.Comparator;
import java.util.Map;
import java.util.TreeMap;

public class RateHot {
    public static class RateHotMap extends Mapper<LongWritable, Text,Text, IntWritable>{
        ObjectMapper objectMapper = new ObjectMapper();
        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            //处理json数据，获取字段
            String line = value.toString();
            UserRateTop userRateTop = objectMapper.readValue(line, UserRateTop.class);
            String movie = userRateTop.getMovie();
            //传给RateHotCombiner类的Reduce  统计个数，在传给RateHotReduce
            //此方法是在map阶段求和，以前写的都是在Reduce阶段求和
            context.write(new Text(movie),new IntWritable(1));

        }
    }


    public static class RateHotReduce extends Reducer<Text, IntWritable,Text,IntWritable> {
        TreeMap<IntWritable, Text> map;

        @Override
        //匿名内部类
        protected void setup(Context context) throws IOException, InterruptedException {

            map = new TreeMap<>(new Comparator<IntWritable>() {
                @Override
                public int compare(IntWritable o1, IntWritable o2) {
                    //排序
                    return o2.compareTo(o1);
                }
            });

        }


        @Override
        protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            Integer count = 0;
            for (IntWritable value : values) {

                count = count + value.get();
            }
            //将统计完的数据放到map里  排序
            map.put(new IntWritable(count), new Text(key));
        }

        @Override
        protected void cleanup(Context context) throws IOException, InterruptedException {


            Configuration conf = context.getConfiguration();
            //在这里定义取出多少
            int suibian = conf.getInt("suibian", 3);

            for (int i = 0; i < suibian; i++) {
                Map.Entry<IntWritable, Text> entry = map.pollFirstEntry();
                IntWritable count = entry.getKey();
                Text movie = entry.getValue();
                context.write(movie, count);
            }
        }

    }
    public static void main(String[] args) throws InterruptedException, IOException, ClassNotFoundException {
        BasicConfigurator.configure();//自动快速使用缺省log4j的环境
        Configuration conf = new Configuration();
        conf.setInt("suibian",Integer.parseInt(args[0]));
        Job job = Job.getInstance(conf);
//        conf.set("yarn.resorcemanager.hostname","192.168.72.110");
//        conf.set("fs.deafutFS", "hdfs://192.168.72.110:9000/");

        job.setCombinerClass(RateHotCombiner.class);
        job.setJarByClass(RateHot.class);
        job.setMapperClass(RateHotMap.class);
        job.setReducerClass(RateHotReduce.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

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

//        FileInputFormat.setInputPaths(job,new Path(args[1]));
//        FileOutputFormat.setOutputPath(job,new Path(args[1]));
        FileInputFormat.setInputPaths(job,new Path("D:/eclipse/wc/input/rating.json"));
        FileOutputFormat.setOutputPath(job,new Path("D:/eclipse/wc/output"));

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

Combiner类

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class RateHotCombiner extends Reducer<Text, IntWritable,Text,IntWritable> {
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        Integer count = 0;
        for (IntWritable value:values) {
            count++;

        }
        context.write(key,new IntWritable(count));
    }
}

结果

注意 ： conf.setInt("suibian",Integer.parseInt(args[0]));里面的参数传递。