环境：Windows8.1，Eclipse

用Hadoop自带的wordcount示例

hadoop2.7.0

hadoop-eclipse-plugin-2.7.0.jar //Eclipse的插件，需要对应Hadoop当前版本

 

基本步骤有很多博客已经提及，就不再赘述

1. 将hadoop-eclipse-plugin-2.7.0.jar放入Eclipse的plugins目录，启动Eclipse

2. 配置Eclipse的Hadoop location信息

 

3. 新建MapReduce Project

4. 将wordcount的代码拷贝进去

/** * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements.  See the NOTICE file * distributed with this work for additional information * regarding copyright ownership.  The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License.  You may obtain a copy of the License at * *     http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */package org.apache.hadoop.examples;import java.io.IOException;import java.util.StringTokenizer;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IntWritable;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.util.GenericOptionsParser;public class WordCount {  public static class TokenizerMapper        extends Mapper
     
      {        private final static IntWritable one = new IntWritable(1);    private Text word = new Text();          public void map(Object key, Text value, Context context                    ) throws IOException, InterruptedException {      StringTokenizer itr = new StringTokenizer(value.toString());      while (itr.hasMoreTokens()) {        word.set(itr.nextToken());        context.write(word, one);      }    }  }    public static class IntSumReducer        extends Reducer
      
        {    private IntWritable result = new IntWritable();    public void reduce(Text key, Iterable
       
         values,                        Context context                       ) throws IOException, InterruptedException {      int sum = 0;      for (IntWritable val : values) {        sum += val.get();      }      result.set(sum);      context.write(key, result);    }  }  public static void main(String[] args) throws Exception {    Configuration conf = new Configuration();   	conf.set("mapred.job.tracker", "192.168.1.150:9001");	conf.set("yarn.resourcemanager.address", "192.168.1.150:8032");        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();    if (otherArgs.length < 2) {      System.err.println("Usage: wordcount 
        
          [
         
          ...] 
          
           "); System.exit(2); } Job job = Job.getInstance(conf, "word count"); job.setJarByClass(WordCount.class); job.setMapperClass(TokenizerMapper.class); job.setCombinerClass(IntSumReducer.class); job.setReducerClass(IntSumReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(IntWritable.class); for (int i = 0; i < otherArgs.length - 1; ++i) { FileInputFormat.addInputPath(job, new Path(otherArgs[i])); } FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1])); System.exit(job.waitForCompletion(true) ? 0 : 1); }}
          
         
        
       
      
     

　　

Main方法的头三行代码，需要自己来配置

 

5. 将部署好的Hadoop集群中的配置文件拷贝至项目中

log4j.properties必须要配置，不然提交任务至集群时，Console无法显示信息，以下是我的配置

log4j.rootLogger=DEBUG, CAlog4j.appender.CA=org.apache.log4j.ConsoleAppenderlog4j.appender.CA.layout=org.apache.log4j.PatternLayoutlog4j.appender.CA.layout.ConversionPattern=%-4r [%t] %-5p %c %x - %m%n

　　

 

 

6. 右键点击WordCount.java -> Run as -> Run on Hadoop

错误1：

org.apache.hadoop.util.Shell$ExitCodeException: /bin/bash: line 0: fg: no job control 

Hadoop读取Windows和Linux系统变量时的引发的问题，有几种解决方案，嫌麻烦不想重新编译整个Hadoop就在本项目中直接重写来解决

在Hadoop的源代码中找到YARNRunner.java，拷贝至项目中，项目中的Package要和Hadoop源代码中的一样，运行时才会覆盖

 

修改YARNRunner.java

（1）修改读取Windows系统变量的方式

注释掉的代码是原来的代码

（2）新增一个处理Windows系统变量的方法

private void replaceEnvironment(Map
     
       environment) {      String tmpClassPath = environment.get("CLASSPATH");      tmpClassPath=tmpClassPath.replaceAll(";", ":");      tmpClassPath=tmpClassPath.replaceAll("%PWD%", "\\$PWD");      tmpClassPath=tmpClassPath.replaceAll("%HADOOP_MAPRED_HOME%", "\\$HADOOP_MAPRED_HOME");      tmpClassPath= tmpClassPath.replaceAll("\\\\", "/" );      environment.put("CLASSPATH",tmpClassPath);}
     

　在此处使用

 

错误2：

exited with exitCode: 1 due to: Exception from container-launch

Diagnostics: Exception from container-launch.

修改项目中的mapred-site.xml，增加以下内容

       
       
        mapreduce.application.classpath
        
       
         $HADOOP_CONF_DIR, $HADOOP_COMMON_HOME/share/hadoop/common/*, $HADOOP_COMMON_HOME/share/hadoop/common/lib/*, $HADOOP_HDFS_HOME/share/hadoop/hdfs/*, $HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/*, $HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*, $HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*, $HADOOP_YARN_HOME/share/hadoop/yarn/*, $HADOOP_YARN_HOME/share/hadoop/yarn/lib/* 
        
      

 

有时还会遇到Mapper class not found <init>() 这个错误

有2个问题

1. Mapper和Reduce的实现类如果是在其他类里面，例如包含Main方法的类，则必须为Static

2. Hadoop找不到本项目的Jar包，因为是从Windows上提交远程任务

（1）可以Export后传到Hadoop服务器上

（2）本地Export后

conf.set("mapred.jar", "C:/Users/14699_000/Desktop/0725.jar");

后面JAR的文件路径是我Export的路径