MapReduce——分布式文件计算系统

1修改配置文件

mapred-site.xml:

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

说明mapreduce是有yarn控制

yarn-site.xml:

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

 <property>
   <name>yarn.resourcemanager.ha.enabled</name>是否开启高可用
   <value>true</value>
 </property>
 <property>
   <name>yarn.resourcemanager.cluster-id</name>
   <value>cluster1</value>
 </property>
 <property>
   <name>yarn.resourcemanager.ha.rm-ids</name>逻辑名称
   <value>rm1,rm2</value>
 </property>
 <property>
   <name>yarn.resourcemanager.hostname.rm1</name>
   <value>slave2</value>
 </property>
 <property>
   <name>yarn.resourcemanager.hostname.rm2</name>
   <value>slave3</value>
 </property>
 <property>
   <name>yarn.resourcemanager.zk-address</name>
   <value>slave1:2181,slave2:2181,slave3:2181</value>
 </property>

</configuration>

分发配置文件到slave1、2、3
scp mapred-site.xml yarn-site.xml slave1:/usr/local/src/hadoop-2.6.5/etc/hadoop

slave2 slave3免密钥登陆 
cat id_rsa.pub >> authorized_keys 
scp id_rsa.pub slave3:/root/.ssh/slave2.pub

2、开始启动集群
启动zookeeper： zkServer.sh start
启动hdfs： start-dfs.sh
启动yarn：start-yarn.sh

slave2 slave3启动Resourcemanager: yarn-daemon.sh start resourcemanager

8088端口可查看mapreduce相关情况：

利用框架jar包封装的单词统计样例测试：
hadoop jar hadoop-mapreduce-examples-2.6.5.jar wordcount /user/root/test.txt  /usr（输出目录）