求大神详解，不太懂

Question

package com.zkpk.us;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;class UserMapper extends Mapper<LongWritable, Text, Text, IntWritable> { protected void map( LongWritable key, Text value, org.apache.hadoop.mapreduce.Mapper<LongWritable, Text, Text, IntWritable>.Context context) throws java.io.IOException, InterruptedException { IntWritable one = new IntWritable(1); String[] columns = value.toString().split("\t"); if (columns != null && columns.length == 6) { Text uid = new Text(columns[1]); context.write(uid, one); } };}class UserReducer extends Reducer<Text, IntWritable, Text, IntWritable> { protected void reduce( Text key, java.lang.Iterable<IntWritable> values, org.apache.hadoop.mapreduce.Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws java.io.IOException, InterruptedException { int sum = 0; for(IntWritable value : values){ sum += value.get(); } context.write(key, new IntWritable(sum)); };}public class UserCount { /** * @param args */ public static void main(String[] args)throws Exception { Configuration conf = new Configuration(); Job job = new Job(conf, "UserUid"); job.setJarByClass(UserCount.class); job.setInputFormatClass(TextInputFormat.class); job.setOutputFormatClass(TextOutputFormat.class); job.setMapperClass(UserMapper.class); job.setReducerClass(UserReducer.class); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); job.setOutputKeyClass(Text.class); job.setOutputValueClass(IntWritable.class); job.waitForCompletion(true); }}

Answer 1

这是hadoop的wordCount程序啊，对input文件下的文档单词分类计数，你在hadoop output 文件夹下可以看到，每个单词出现的频数

Answer 2

这是MapReduce程序，是Hadoop处理数据的核心。程序有三部分组成：

第一部分：Map。表示将数据进行分词处理，分隔符是制表键

第二部分：Reduce。将Map的输出进行汇总，得到最后的输出。

第三部分：主程序。将Map和Reduce组成一个任务job，来执行，数据的输入和输出都来至于HDFS。

有问题，可以再问我。呵呵

Answer 3

直接说 什么问题

    直接贴代码  不想看