这篇文章主要介绍Hadoop2 namenode HA的示例分析，文中介绍的非常详细，具有一定的参考价值，感兴趣的小伙伴们一定要看完！
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为 主namenode 节点，node2为 备namendoe节点，node3、4、5为 datanode节点；node1、2、3上还将部署 zookeeper 和 journalnode。
一、搭建Zookeeper集群
Storm0.9.4安装 中搭建Zookeeper集群的部分
[yyl@node1 ~]$ zkServer.sh start JMX enabled by default Using config: /home/yyl/program/zookeeper-3.4.6/bin/../conf/zoo.cfg Starting zookeeper ... STARTED [yyl@node1 ~]$ zkServer.sh status JMX enabled by default Using config: /home/yyl/program/zookeeper-3.4.6/bin/../conf/zoo.cfg Mode: follower [yyl@node2 ~]$ zkServer.sh start JMX enabled by default Using config: /home/yyl/program/zookeeper-3.4.6/bin/../conf/zoo.cfg Starting zookeeper ... STARTED [yyl@node2 ~]$ zkServer.sh status JMX enabled by default Using config: /home/yyl/program/zookeeper-3.4.6/bin/../conf/zoo.cfg Mode: leader [yyl@node3 ~]$ zkServer.sh start JMX enabled by default Using config: /home/yyl/program/zookeeper-3.4.6/bin/../conf/zoo.cfg Starting zookeeper ... STARTED [yyl@node3 ~]$ zkServer.sh status JMX enabled by default Using config: /home/yyl/program/zookeeper-3.4.6/bin/../conf/zoo.cfg Mode: follower
二、配置Hadoop环境
## 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/journal [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.sh export JAVA_HOME=/usr/lib/java/jdk1.7.0_80 ## 配置yarn-env.sh [yyl@node1 hadoop]$ vim yarn-env.sh export JAVA_HOME=/usr/lib/java/jdk1.7.0_80 ## 配置slaves [yyl@node1 hadoop]$ vim slaves node3.zhch node4.zhch node5.zhch ## 配置core-site.xml [yyl@node1 hadoop]$ vim core-site.xml <configuration> <property> <name>fs.defaultFS</name> <value>hdfs://mycluster</value> </property> <property> <name>io.file.buffer.size</name> <value>131072</value> </property> <property> <name>hadoop.tmp.dir</name> <value>file:/home/yyl/program/hadoop-2.5.2/tmp</value> </property> <property> <name>hadoop.proxyuser.hadoop.hosts</name> <value>*</value> </property> <property> <name>hadoop.proxyuser.hadoop.groups</name> <value>*</value> </property> <property> <name>ha.zookeeper.quorum</name> <value>node1.zhch:2181,node2.zhch:2181,node3.zhch:2181</value> </property> <property> <name>ha.zookeeper.session-timeout.ms</name> <value>1000</value> </property> </configuration> ## 配置hdfs-site.xml [yyl@node1 hadoop]$ vim hdfs-site.xml <configuration> <property> <name>dfs.namenode.name.dir</name> <value>file:/home/yyl/program/hadoop-2.5.2/name</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>file:/home/yyl/program/hadoop-2.5.2/data</value> </property> <property> <name>dfs.replication</name> <value>1</value> </property> <property> <name>dfs.webhdfs.enabled</name> <value>true</value> </property> <property> <name>dfs.permissions</name> <value>false</value> </property> <property> <name>dfs.permissions.enabled</name> <value>false</value> </property> <property> <name>dfs.nameservices</name> <value>mycluster</value> </property> <property> <name>dfs.ha.namenodes.mycluster</name> <value>nn1,nn2</value> </property> <property> <name>dfs.namenode.rpc-address.mycluster.nn1</name> <value>node1.zhch:9000</value> </property> <property> <name>dfs.namenode.rpc-address.mycluster.nn2</name> <value>node2.zhch:9000</value> </property> <property> <name>dfs.namenode.servicerpc-address.mycluster.nn1</name> <value>node1.zhch:53310</value> </property> <property> <name>dfs.namenode.servicerpc-address.mycluster.nn2</name> <value>node2.zhch:53310</value> </property> <property> <name>dfs.namenode.http-address.mycluster.nn1</name> <value>node1.zhch:50070</value> </property> <property> <name>dfs.namenode.http-address.mycluster.nn2</name> <value>node2.zhch:50070</value> </property> <property> <name>dfs.namenode.shared.edits.dir</name> <value>qjournal://node1.zhch:8485;node2.zhch:8485;node3.zhch:8485/mycluster</value> </property> <property> <name>dfs.client.failover.proxy.provider.mycluster</name> <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> </property> <property> <name>dfs.ha.fencing.methods</name> <value>sshfence</value> </property> <property> <name>dfs.ha.fencing.ssh.private-key-files</name> <value>/home/yyl/.ssh/id_rsa</value> </property> <property> <name>dfs.ha.fencing.ssh.connect-timeout</name> <value>30000</value> </property> <property> <name>dfs.journalnode.edits.dir</name> <value>/home/yyl/program/hadoop-2.5.2/journal</value> </property> <property> <name>dfs.ha.automatic-failover.enabled</name> <value>true</value> </property> <property> <name>ha.failover-controller.cli-check.rpc-timeout.ms</name> <value>60000</value> </property> <property> <name>ipc.client.connect.timeout</name> <value>60000</value> </property> <property> <name>dfs.image.transfer.bandwidthPerSec</name> <value>4194304</value> </property> </configuration> ## 配置mapred-site.xml [yyl@node1 hadoop]$ cp mapred-site.xml.template mapred-site.xml [yyl@node1 hadoop]$ vim mapred-site.xml <configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobhistory.address</name> <value>node1.zhch:10020,node2.zhch:10020</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>node1.zhch:19888,node2.zhch:19888</value> </property> </configuration> ## 配置yarn-site.xml [yyl@node1 hadoop]$ vim yarn-site.xml <configuration> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name> <value>org.apache.hadoop.mapred.ShuffleHandler</value> </property> <property> <name>yarn.resourcemanager.address</name> <value>node1.zhch:8032</value> </property> <property> <name>yarn.resourcemanager.scheduler.address</name> <value>node1.zhch:8030</value> </property> <property> <name>yarn.resourcemanager.resource-tracker.address</name> <value>node1.zhch:8031</value> </property> <property> <name>yarn.resourcemanager.admin.address</name> <value>node1.zhch:8033</value> </property> <property> <name>yarn.resourcemanager.webapp.address</name> <value>node1.zhch:8088</value> </property> </configuration> ## 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-2.5.2 export HADOOP_COMMON_HOME=$HADOOP_PREFIX export HADOOP_HDFS_HOME=$HADOOP_PREFIX export HADOOP_MAPRED_HOME=$HADOOP_PREFIX export HADOOP_YARN_HOME=$HADOOP_PREFIX export HADOOP_CONF_DIR=$HADOOP_PREFIX/etc/hadoop export PATH=$PATH:$HADOOP_PREFIX/bin:$HADOOP_PREFIX/sbin
三、创建znode
把各个 zookeeper 启动，在其中一个 namenode 节点执行如下命令，用于在 Zookeeper 中创建一个 znode
[yyl@node1 ~]$ hdfs zkfc -formatZK ## 验证创建是否成功： [yyl@node3 ~]$ zkCli.sh [zk: localhost:2181(CONNECTED) 0] ls / [hadoop-ha, zookeeper] [zk: localhost:2181(CONNECTED) 1] ls /hadoop-ha [mycluster] [zk: localhost:2181(CONNECTED) 2]
四、启动journalnode
在 node1.zhch、node2.zhch、node3.zhch 上运行命令：hadoop-daemon.sh start journalnode
[yyl@node1 ~]$ hadoop-daemon.sh start journalnode starting journalnode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-journalnode-node1.zhch.out [yyl@node1 ~]$ jps 1126 QuorumPeerMain 1349 JournalNode 1395 Jps [yyl@node2 ~]$ hadoop-daemon.sh start journalnode starting journalnode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-journalnode-node2.zhch.out [yyl@node2 ~]$ jps 1524 JournalNode 1570 Jps 1376 QuorumPeerMain [yyl@node3 ~]$ hadoop-daemon.sh start journalnode starting journalnode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-journalnode-node3.zhch.out [yyl@node3 ~]$ jps 1289 JournalNode 1126 QuorumPeerMain 1335 Jps
五、NameNode
## 在 主namenode 节点上使用命令 hadoop namenode -format 格式化 namenode 和 journalnode 目录 [yyl@node1 ~]$ hadoop namenode -format ## 启动主namenode [yyl@node1 ~]$ hadoop-daemon.sh start namenode starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node1.zhch.out [yyl@node1 ~]$ jps 1478 NameNode 1561 Jps 1126 QuorumPeerMain 1349 JournalNode ## 在 备namenode节点 同步元数据 [yyl@node2 ~]$ hdfs namenode -bootstrapStandby ## 启动 备NameNode [yyl@node2 ~]$ hadoop-daemon.sh start namenode starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node2.zhch.out [yyl@node2 ~]$ jps 1524 JournalNode 1626 NameNode 1709 Jps 1376 QuorumPeerMain ## 在 两个namenode节点 都执行以下命令来配置自动故障转移：安装和运行ZKFC [yyl@node1 ~]$ hadoop-daemon.sh start zkfc starting zkfc, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-zkfc-node1.zhch.out [yyl@node1 ~]$ jps 1624 DFSZKFailoverController 1478 NameNode 1682 Jps 1126 QuorumPeerMain 1349 JournalNode [yyl@node2 ~]$ hadoop-daemon.sh start zkfc starting zkfc, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-zkfc-node2.zhch.out [yyl@node2 ~]$ jps 1524 JournalNode 1746 DFSZKFailoverController 1626 NameNode 1800 Jps 1376 QuorumPeerMain
六、启动 DataNode 和 Yarn
[yyl@node1 ~]$ hadoop-daemons.sh start datanode node4.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node4.zhch.out node3.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node3.zhch.out node5.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node5.zhch.out [yyl@node1 ~]$ start-yarn.sh starting yarn daemons starting resourcemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-resourcemanager-node1.zhch.out node4.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node4.zhch.out node3.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node3.zhch.out node5.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node5.zhch.out [yyl@node1 ~]$ jps 1763 ResourceManager 1624 DFSZKFailoverController 1478 NameNode 1126 QuorumPeerMain 1349 JournalNode 2028 Jps [yyl@node3 ~]$ jps 1289 JournalNode 1462 NodeManager 1367 DataNode 1126 QuorumPeerMain 1559 Jps
下次启动的时候，在 zookeeper 集群已启动的前提下，直接执行以下命令就可以全部启动所有进程和服务了：
sh start-dfs.sh
sh start-yarn.sh
可以通过URL来查看namenode状态
http://node1.zhch:50070 http://node2.zhch:50070
也可以通过命令来查看
[yyl@node1 ~]$ hdfs haadmin -getServiceState nn1
active
[yyl@node1 ~]$ hdfs haadmin -getServiceState nn2
standby
七、测试
在主namenode机器上通过jps命令查找到namenode的进程号，然后通过kill -9的方式杀掉进程，观察另一个namenode节点是否会从状态standby变成active状态：
[yyl@node1 ~]$ jps 1763 ResourceManager 1624 DFSZKFailoverController 1478 NameNode 2128 Jps 1126 QuorumPeerMain 1349 JournalNode [yyl@node1 ~]$ kill -9 1478 [yyl@node1 ~]$ hdfs haadmin -getServiceState nn2 active [yyl@node1 ~]$ hadoop-daemon.sh start namenode starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node1.zhch.out [yyl@node1 ~]$ hdfs haadmin -getServiceState nn1 standby
以上是“Hadoop2 namenode HA的示例分析”这篇文章的所有内容，感谢各位的阅读！希望分享的内容对大家有帮助，更多相关知识，欢迎关注亿速云行业资讯频道！
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