使用mapreduce去除某些数字

解答2017年10月大数据行赛一题

数据：data.txt里面有500W个1-1000的整数

[root@master ~]# head data.txt 
851,944,745,729,855,954,179,124,753
710,990,349,777,36,970,688,463,450
385,178,816,361,797,792,960,708,459
840,128,997,610,722,180,887,635,205
840,623,804,327,645,379,986,489,420
210,181,356,411,909,498,654,59,288
568,828,352,420,829,629,183,993,308
858,118,598,561,227,828,158,38,203
96,187,22,654,300,194,97,990,509
508,728,10,569,726,588,822,219,571

生成数据的方法

[root@master ~]# cat genNum.sh 
count=0
for k in $(seq 1 555556)
do
    for j in $(seq 1 8)
    do
        num=$(($RANDOM%1000+1))
        echo -e "$num,\c" >> ./data.txt
        count=$((count+1))
        if [ $count -eq 5000000 ]; then break; fi
    done
    if [ $count -eq 5000000 ]; then break; fi
    num=$(($RANDOM%1000+1))
    echo "$num" >> ./data.txt
    count=$((count+1))
done

要求：使用mapreduce程序去除data.txt中所有的以2开头的数字

WordMapper.java

package com.jsit;

import java.io.IOException;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
 
 
public class WordMapper extends Mapper {
 
    @Override
    protected void map(LongWritable key, Text value, Mapper.Context context)
            throws IOException, InterruptedException {
        String line = value.toString();
        String[] words = line.split(" ");
        for(String word : words) {
            context.write(new Text(word), new IntWritable(1));
        }
    }
     
}

Reducer.java

package com.jsit;

import java.io.IOException;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
 
public class WordReducer extends Reducer {
 
    @Override
    protected void reduce(Text key, Iterable values,
            Reducer.Context context) throws IOException, InterruptedException {
        long count = 0;
        for(IntWritable v : values) {
            count += v.get();
        }
        context.write(key, new LongWritable(count));
    }
}

Test.java

package com.jsit;

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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 
 
public class Test {
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
                         
        Job job = Job.getInstance(conf);
         
        job.setMapperClass(WordMapper.class);
        job.setReducerClass(WordReducer.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);
         
        FileInputFormat.setInputPaths(job, "e:/temp/test.txt");
        FileOutputFormat.setOutputPath(job, new Path("e:/temp/out/"));
         
        job.waitForCompletion(true);
    }
}