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hadoop MultipleOutputs

时间:2015-05-01 13:16:48      阅读:90      评论:0      收藏:0      [点我收藏+]

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MultipleOutputs: 

  write data to multiple files with customized name, can be used for both map and reduce phase.

http://www.lichun.cc/blog/2013/11/how-to-use-hadoop-multipleoutputs/

public static class MyMap extends
            Mapper<LongWritable, Text, Text, DoubleWritable> {
        MultipleOutputs<Text, DoubleWritable> mos;

        public void map(LongWritable inKey, Text inValue, Context context)
                throws IOException, InterruptedException {

            mos.write(map_out_file, NullWritable.get(), new Text(name));

        }

        @Override
        public void setup(Context context) {
            mos = new MultipleOutputs<Text, DoubleWritable>(context);
        }

        @Override
        protected void cleanup(Context context) throws IOException,
                InterruptedException {
            mos.close();
        }

    }

example

package a5p2;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.RawComparator;
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.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.MultipleOutputs;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class ClassAvg2 {
    public static final String map_out_file = "mapOutFileIndividualStudentAverage";
    public static final String reduce_out_file = "reduceOutFileClassAverage";

    public static class AvgMap extends
            Mapper<LongWritable, Text, Text, DoubleWritable> {
        MultipleOutputs<Text, DoubleWritable> mos;

        public void map(LongWritable inKey, Text inValue, Context context)
                throws IOException, InterruptedException {

            String line = inValue.toString();
            StringTokenizer myToken = new StringTokenizer(line);
            String name = myToken.nextToken();
            int cnt = 0;
            double sum = 0;
            double avg;
            while (myToken.hasMoreTokens()) {
                sum += Float.parseFloat(myToken.nextToken());
                cnt++;
            }
            avg = sum / cnt;
            context.write(new Text(name), new DoubleWritable(avg));
            mos.write(map_out_file, NullWritable.get(), new Text(name + " "
                    + avg));

        }

        @Override
        public void setup(Context context) {
            mos = new MultipleOutputs<Text, DoubleWritable>(context);
        }

        @Override
        protected void cleanup(Context context) throws IOException,
                InterruptedException {
            mos.close();
        }

    }

    public static class AvgReduce extends
            Reducer<Text, DoubleWritable, Text, DoubleWritable> {
        MultipleOutputs<Text, DoubleWritable> mos;

        public void reduce(Text key, Iterable<DoubleWritable> inValues,
                Context context) throws IOException, InterruptedException {

            double classSum = 0;
            int cnt = 0;
            for (DoubleWritable dw : inValues) {
                classSum += dw.get();
                cnt++;
            }
            double classAvg = classSum / cnt;
            mos.write(reduce_out_file, NullWritable.get(), new Text(
                    "Class average: " + classAvg));
            // context.write(new Text("class average"), new DoubleWritable(
            // classAvg));

        }

        @Override
        public void setup(Context context) {
            mos = new MultipleOutputs<Text, DoubleWritable>(context);
        }

        @Override
        protected void cleanup(Context context) throws IOException,
                InterruptedException {
            mos.close();
        }

    }

    public static class AvgGroupComparator implements RawComparator<Text> {

        public int compare(Text t1, Text t2) {
            return 0;
        }

        public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2) {
            return 0;
        }
    }

    public static void main(String[] args) throws IOException,
            ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        Job job = new Job(conf, "class avg");
        job.setJarByClass(ClassAvg2.class);

        // mapper
        job.setMapperClass(AvgMap.class);
        job.setGroupingComparatorClass(AvgGroupComparator.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(DoubleWritable.class);

        // reducer
        job.setReducerClass(AvgReduce.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(DoubleWritable.class);

        // input and output
        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        MultipleOutputs.addNamedOutput(job, map_out_file,
                TextOutputFormat.class, NullWritable.class, Text.class);
        MultipleOutputs.addNamedOutput(job, reduce_out_file,
                TextOutputFormat.class, NullWritable.class, Text.class);

        System.exit(job.waitForCompletion(true) ? 0 : 1);

    }

}

 

hadoop MultipleOutputs

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原文地址:http://www.cnblogs.com/phoenix13suns/p/4470529.html

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