Windows MapReduce 开发环境搭建以及运行实战_windows配置mapreduce环境

package com.cakin.mapreduce.wc;
import java.io.IOException;
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.Mapper.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class WordcountApp {
     public static class MyMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
         /**
          * map阶段的业务逻辑处理就写在map()方法中
          * maptask会对每一行输入数据调用一次我们自定义的map()方法
          * @throws InterruptedException
          */
         private Text word = new Text();
         private IntWritable one = new IntWritable(1);
           @Override
         protected void map(LongWritable key,Text value,Context context) throws IOException, InterruptedException{
             //将maptask传递给我们的文本内容先转换成string
             String line=value.toString();
             //按照空格行切割单词
             String[] words=line.split(" ");
             //将单词输出为<单词，1>
             for(String w:words) {
                 word.set(w);
                //将单词作为key，将次数1作为Value，以便于后续的数据分发，可以根据单词分发，以便于相同单词会到相同的reduce task
                 context.write(word,one);
             }
         }
     }
     public static class MyReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
         /**
          * <angel,1> <angel,1> <angel,1> <angel,1> <angel,1>
          * <hello,1> <hello,1> <hello,1> <hello,1> <hello,1> <hello,1>
          * <banana,1> <banana,1> <banana,1> <banana,1> <banana,1> <banana,1>
          * 入参key：是一组单词的kv对应的key,将相同单词的一组传递，如此时key是hello，那么参数二是一个迭代器，一组数
          * @throws InterruptedException
          * @throws IOException
          */
         private IntWritable sum= new IntWritable();
           @Override
         protected void reduce(Text key,Iterable<IntWritable> values ,Context context) throws IOException, InterruptedException {
             int count=0;
     /**
             Iterator<IntWritable> iterator=values.iterator();
             while(iterator.hasNext()) {
                 count+=iterator.next().get();
             }
     */
             for(IntWritable value:values) {
                 count+=value.get();
             }
             sum.set(count);
             context.write(key, sum);
         }   
     }
     
     public static void main(String[] args) throws IllegalArgumentException, IOException, ClassNotFoundException, InterruptedException {
        if(args.length <2)
        {
           args= new String[]{
                     "hdfs://192.168.0.102:8020/input",
                     "hdfs://192.168.0.102:8020/output1"
           };
           
           
        }
           Configuration conf=new Configuration();
        /*
         * 集群中节点都有配置文件
        conf.set("mapreduce.framework.name.", "yarn");
        conf.set("yarn.resourcemanager.hostname", "mini1");
        */
        Job job=Job.getInstance(conf);
        //jar包在哪里,现在在客户端，传递参数
        //任意运行，类加载器知道这个类的路径，就可以知道jar包所在的本地路径
        job.setJarByClass(WordcountApp.class);
        //指定本业务job要使用的mapper/Reducer业务类
        job.setMapperClass(MyMapper.class);
        job.setReducerClass(MyReducer.class);
        //指定mapper输出数据的kv类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        //指定最终输出的数据kv类型
        job.setOutputKeyClass(Text.class);
        job.setOutputKeyClass(IntWritable.class);
        //指定job的输入原始文件所在目录
        FileInputFormat.setInputPaths(job, new Path(args[0]));
        //指定job的输出结果所在目录
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        //将job中配置的相关参数及job所用的java类在的jar包，提交给yarn去运行
        //提交之后，此时客户端代码就执行完毕，退出
        //job.submit();
        //等集群返回结果在退出
        boolean res=job.waitForCompletion(true);
        System.exit(res?0:1);
        //类似于shell中的$？
    }
}