Hadoop2 namenode联邦实验分析

本篇内容主要讲解"Hadoop2 namenode联邦实验分析"，感兴趣的朋友不妨来看看。本文介绍的方法操作简单快捷，实用性强。下面就让小编来带大家学习"Hadoop2 namenode联邦实验分析"吧!

实验的Hadoop版本为2.5.2，硬件环境是5台虚拟机，使用的均是CentOS6.6操作系统，虚拟机IP和hostname分别为：
192.168.63.171 node1.zhch
192.168.63.172 node2.zhch
192.168.63.173 node3.zhch
192.168.63.174 node4.zhch
192.168.63.175 node5.zhch

ssh免密码、防火墙、JDK这里就不在赘述了。虚拟机的角色分配是 node1、2是namendoe节点，node3、4、5为datanode节点。

步骤和 搭建普通hadoop集群 基本相同 ，主要的不同在于 hdfs-site.xml这个配置文件，其余配置和hadoop的安装配置基本一致。

一、配置Hadoop

## 解压[yyl@node1 program]$ tar -zxf hadoop-2.5.2.tar.gz ## 创建文件夹[yyl@node1 program]$ mkdir hadoop-2.5.2/name[yyl@node1 program]$ mkdir hadoop-2.5.2/data[yyl@node1 program]$ mkdir hadoop-2.5.2/tmp## 配置hadoop-env.sh[yyl@node1 program]$ cd hadoop-2.5.2/etc/hadoop/[yyl@node1 hadoop]$ vim hadoop-env.shexport JAVA_HOME=/usr/lib/java/jdk1.7.0_80## 配置yarn-env.sh[yyl@node1 hadoop]$ vim yarn-env.shexport JAVA_HOME=/usr/lib/java/jdk1.7.0_80## 配置slaves[yyl@node1 hadoop]$ vim slaves node3.zhchnode4.zhchnode5.zhch## 配置core-site.xml[yyl@node1 program]$ cd hadoop-2.5.2/etc/hadoop/[yyl@node1 hadoop]$ vim core-site.xml  fs.defaultFS  hdfs://node1.zhch:9000  io.file.buffer.size  131072  hadoop.tmp.dir  file:/home/yyl/program/hadoop-2.5.2/tmp  hadoop.proxyuser.hduser.hosts  *  hadoop.proxyuser.hduser.groups  *## 配置hdfs-site.xml[yyl@node1 hadoop]$ vim hdfs-site.xml  dfs.namenode.name.dir  file:/home/yyl/program/hadoop-2.5.2/name  dfs.datanode.data.dir  file:/home/yyl/program/hadoop-2.5.2/data  dfs.replication  1  dfs.webhdfs.enabled  true  dfs.permissions  false  dfs.nameservices  ns1,ns2  dfs.namenode.rpc-address.ns1  node1.zhch:9000  dfs.namenode.http-address.ns1  node1.zhch:50070  dfs.namenode.rpc-address.ns2  node2.zhch:9000  dfs.namenode.http-address.ns2  node2.zhch:50070##配置 mapred-site.xml[yyl@node1 hadoop]$ cp mapred-site.xml.template mapred-site.xml[yyl@node1 hadoop]$ vim mapred-site.xml  mapreduce.framework.name  yarn  mapreduce.jobhistory.address  node1.zhch:10020  mapreduce.jobhistory.webapp.address  node1.zhch:19888##配置 yarn-site.xml[yyl@node1 hadoop]$ vim yarn-site.xml  yarn.nodemanager.aux-services  mapreduce_shuffle  yarn.nodemanager.aux-services.mapreduce.shuffle.class  org.apache.hadoop.mapred.ShuffleHandler  yarn.resourcemanager.address  node1.zhch:8032  yarn.resourcemanager.scheduler.address  node1.zhch:8030  yarn.resourcemanager.resource-tracker.address  node1.zhch:8031  yarn.resourcemanager.admin.address  node1.zhch:8033  yarn.resourcemanager.webapp.address  node1.zhch:8088## 分发到各个节点[yyl@node1 hadoop]$ cd /home/yyl/program/[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node2.zhch:/home/yyl/program/[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node3.zhch:/home/yyl/program/[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node4.zhch:/home/yyl/program/[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node5.zhch:/home/yyl/program/## 在各个节点上设置hadoop环境变量[yyl@node1 ~]$ vim .bash_profile export HADOOP_PREFIX=/home/yyl/program/hadoop-2.5.2export HADOOP_COMMON_HOME=$HADOOP_PREFIXexport HADOOP_HDFS_HOME=$HADOOP_PREFIXexport HADOOP_MAPRED_HOME=$HADOOP_PREFIXexport HADOOP_YARN_HOME=$HADOOP_PREFIXexport HADOOP_CONF_DIR=$HADOOP_PREFIX/etc/hadoopexport PATH=$PATH:$HADOOP_PREFIX/bin:$HADOOP_PREFIX/sbin

二、NameNode

## 在namenode1上执行格式化[yyl@node1 ~]$ hdfs namenode -format -clusterId c1## 在namenode2上执行格式化[yyl@node2 ~]$ hdfs namenode -format -clusterId c1## 在namenode1启动namenode[yyl@node1 ~]$ hadoop-daemon.sh start namenodestarting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node1.zhch.out[yyl@node1 ~]$ jps1177 NameNode1240 Jps## 在namenode2启动namenode[yyl@node2 ~]$ hadoop-daemon.sh start namenodestarting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node2.zhch.out[yyl@node2 ~]$ jps1508 Jps1445 NameNode

三、HDFS联邦检查

http://node1.zhch:50070/

http://node2.zhch:50070/



四、启动DataNode和yarn

[yyl@node1 ~]$ hadoop-daemons.sh start datanodenode4.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node4.zhch.outnode5.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node5.zhch.outnode3.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node3.zhch.out[yyl@node1 ~]$ start-yarn.shstarting yarn daemonsstarting resourcemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-resourcemanager-node1.zhch.outnode5.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node5.zhch.outnode3.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node3.zhch.outnode4.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node4.zhch.out[yyl@node1 ~]$ jps1402 Jps1177 NameNode1333 ResourceManager[yyl@node2 ~]$ jps1445 NameNode1539 Jps[yyl@node3 ~]$ jps1214 NodeManager1166 DataNode1256 Jps

下次启动不需要重复上面的步骤，可以直接使用下面的命令启动集群：
sh $HADOOP_HOME/sbin/start-dfs.sh
sh $HADOOP_HOME/sbin/start-yarn.sh

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