WordCount 分析

WordCount程序中Map和Reduce过程分析

Map过程：

（1）文件的拆分，测试用的文件较小，每个文件为一个split，并将文件按行分成<key,value>对，如下图，这一步是由框架完成：

（2）将分割好的<key ,value>对交给用户定义的map方法进行处理，生成新的<key,value>对，如下图，这一步是由用户的map函数完成的，其中的每一行对应一个map进程,总共需要四个map进程：

（3）得到map方法输出的<key,value>后，框架会按照key值进行排序，并执行Combine过程，将相同的key值进行累加，这一步是由框架完成，如下图：

Reduce 过程：

Reducer 先对从Mapper接收的数据进行排序，再交由用户定义的Reduce方法处理，得到新的<key,value>对，如下图，由四个reduce进程完成：

import java.io.IOException;
import java.net.URI;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
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.Reducer.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;


public class WordCount {

	/**
	 * @param args
	 * @author nwpulisz
	 * @date:2016.3.29
	 */
	static final String INPUT_PATH="hdfs://192.168.255.132:9000/INPUT";
	static final String OUTPUT_PATH="hdfs://192.168.255.132:9000/OUTPUT";
	
	public static void main(String[] args) throws Throwable {
		// TODO Auto-generated method stub
		Configuration conf = new Configuration();
		Path outPut_path= new Path(OUTPUT_PATH);
		Job job = new Job(conf, "WordCount");
		
		//如果输出路径是存在的，则提前删除输出路径
		FileSystem fileSystem = FileSystem.get(new URI(OUTPUT_PATH), conf);
		if(fileSystem.exists(outPut_path))
		{
			fileSystem.delete(outPut_path,true);
		}
		
		FileInputFormat.setInputPaths(job, INPUT_PATH);
		FileOutputFormat.setOutputPath(job, outPut_path);
		
		job.setMapperClass(MyMapper.class);
		job.setReducerClass(MyReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(LongWritable.class);
		job.waitForCompletion(true);
	}
	
	static class MyMapper extends Mapper<LongWritable, Text, Text, LongWritable>{

		protected void map(LongWritable key, Text value, 
                Context context) throws IOException, InterruptedException {
			String[] splits = value.toString().split("\\W+");
			for (String word : splits) {
				context.write(new Text(word), new LongWritable(1));
			}
		}
		
	}
	
	static class MyReducer extends Reducer<Text, LongWritable, Text, LongWritable>{

		protected void reduce(Text key, Iterable<LongWritable> values, Context context
                ) throws IOException, InterruptedException {
			long times = 0L;
			for(LongWritable value: values) {
					times+=value.get();
			}
			context.write(new Text(key),new LongWritable(times));
			}		
	}
	
}

输入：