本文章采用Hadoop版本为hadoop-2.6.0-cdh5.7.0，jdk版本为1.7

• Hadoop环境搭建

1. 下载Hadoop
   下载地址：http://archive.cloudera.com/cdh5/cdh/5/2.6.0-cdh5.7.0
   wget http://archive.cloudera.com/cdh5/cdh/5/hadoop-2.6.0-cdh5.7.0.tar.gz

2. 安装jdk
   下载jdk-7u51-linux-x64.tar.gz
   解压到app目录：tar -zxvf jdk-7u51-linux-x64.tar.gz -C ~/app/
   验证安装是否成功：~/app/jdk1.7.0_51/bin ./java -version
   建议把bin目录配置到系统环境变量(~/.bash_profile)中

   export JAVA_HOME=/home/hadoop/app/jdk1.7.0_51
   export PATH=$JAVA_HOME/bin:$PATH
   

3. 机器参数设置
   设置机器hostname为hadoop001

   • 修改机器名: /etc/sysconfig/network
     NETWORKING=yes
     HOSTNAME=hadoop001

   • 设置ip和hostname的映射关系: /etc/hosts
     192.168.199.200 hadoop001
     127.0.0.1 localhost

   • ssh免密码登陆(本步骤可以省略，但是后面你重启hadoop进程时是需要手工输入密码才行)
     ssh-keygen -t rsa
     cp ~/.ssh/id_rsa.pub ~/.ssh/authorized_keys

4. Hadoop配置文件修改: ~/app/hadoop-2.6.0-cdh5.7.0/etc/hadoop

   • hadoop-env.sh
     export JAVA_HOME=/home/hadoop/app/jdk1.7.0_51

   • core-site.xml

     <property>
         <name>fs.defaultFS</name>
         <value>hdfs://hadoop001:8020</value>
     </property> 
     <property>
         <name>hadoop.tmp.dir</name>
         <value>/home/hadoop/app/tmp</value>
     </property> 
     

   • hdfs-site.xml

     <property>
         <name>dfs.replication</name>
         <value>1</value>
     </property>
     

5. 格式化HDFS
   注意：这一步操作，只是在第一次时执行，每次如果都格式化的话，那么HDFS上的数据就会被清空
   bin/hdfs namenode -format

6. 启动HDFS
   sbin/start-dfs.sh

   验证是否启动成功:
   jps
   DataNode
   SecondaryNameNode
   NameNode

   浏览器访问 http://hadoop001:50070/

7. 停止HDFS
   sbin/stop-dfs.sh

• YARN环境搭建

1. 配置文件修改

   • mapred-site.xml

     <property>
       <name>mapreduce.framework.name</name>
       <value>yarn</value>
     </property>
     

   • yarn-site.xml

     <property>
       <name>yarn.nodemanager.aux-services</name>
       <value>mapreduce_shuffle</value>
     </property>
     

2. 启动yarn
   sbin/start-yarn.sh

3. 验证是否启动成功
   jps
   ResourceManager
   NodeManager

   浏览器访问: http://hadoop001:8088

4. 停止yarn
   sbin/stop-yarn.sh

5. 提交mr作业到yarn上运行： wc
   hadoop jar /home/hadoop/app/hadoop-2.6.0-cdh5.7.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.7.0.jar wordcount /input/wc/hello.txt /output/wc/