MR案例 之 重复数据处理

1 数据：

2 需求： 

使用MR 算法    将相同 手机号 的数据整理到一个文本中，文本 名称为 手机号。

3 代码实现 ：

package Test02;

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.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.MultipleOutputs;

import java.io.IOException;

public class MultipleOutputTest {

                 // map  类
	static class MyMapper extends Mapper<LongWritable,Text,Text,Text>{
		@Override
            // map  的 重写方法 
		protected void map(LongWritable key, Text value,Context context)throws IOException, InterruptedException {
            // 数据 分割 
			String[] fields = value.toString().split("\t");
            // 数据 输出
			context.write(new Text(fields[1]), value);
		}
	}
	
            //Reduce   类
	static class MyReducer extends Reducer<Text,Text,NullWritable,Text>{
		private MultipleOutputs<NullWritable, Text> multipleOutputs;
		
       
		protected void setup(Context context){
			multipleOutputs = new MultipleOutputs<NullWritable, Text>(context);
		}
		 // Reduce  重写方法
		@Override
		protected void reduce(Text key, Iterable<Text> values,Context context)throws IOException, InterruptedException {
			for (Text value : values) {
				multipleOutputs.write(NullWritable.get(), value, key.toString());
			}
		}
		
		protected void cleanup(Context context) throws IOException, InterruptedException{
			multipleOutputs.close();
		}
	}
	
	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
		Configuration conf = new Configuration();
		Job job = Job.getInstance(conf);
		job.setJarByClass(MultipleOutputTest.class);
		
		job.setJobName("MultipleOutputTest");
		
		job.setMapperClass(MyMapper.class);
		job.setReducerClass(MyReducer.class);

		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(Text.class);
		
		job.setOutputKeyClass(NullWritable.class);
		job.setOutputValueClass(Text.class);
		
		FileInputFormat.setInputPaths(job, new Path("D:\\HDFS001\\src\\data_flow3.1.txt"));
		FileOutputFormat.setOutputPath(job, new Path("G:\\phone"));
		
		job.waitForCompletion(true);
	}
}