集群的规划

Zookeeper集群:

192.168.142.12 bigdata12

192.168.142.13 bigdata13

192.168.142.14 bigdata14

Hadoop集群:

192.168.142.12 bigdata12)   NameNode1      ResourceManager1     Journalnode

192.168.142.13 bigdata13)   NameNode2      ResourceManager2     Journalnode

192.168.142.14 bigdata14)   DataNode1      NodeManager1

192.168.142.15 bigdata15)   DataNode2      NodeManager2

1、准备工作:

(1)、关闭防火墙:

查看防火墙的状态: systemctl status firewalld.service

关闭防火墙:       systemctl stop firewalld.service

禁用防火墙(永久):systemctl disable firewalld.service

(2)、安装JDK及配置环境变量

tar -zxvf jdk-8u144-linux-x64.tar.gz -C ~/training/

设置环境变量:vi ~/.bash_profile

JAVA_HOME=/root/training/jdk1.8.0_144

export JAVA_HOME

PATH=$JAVA_HOME/bin:$PATH

export PATH

生效环境变量: source  ~/.bash_profile

(3)、安装Hadoop及设置环境变量:

解压:tar -zxvf hadoop-2.7.3.tar.gz -C ~/training/

设置环境变量:

vi ~/.bash_profile

HADOOP_HOME=/root/training/hadoop-2.7.3

export HADOOP_HOME  

PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH

export PATH

生效环境变量:

source ~/.bash_profile

(4)、设置免密码登录:

a、生成密钥:

ssh-keygen -t rsa

(存储在~/.ssh目录)

b、分发公钥:

ssh-copy-id -i /root/.ssh/id_rsa.pub root@bigdata12

c、验证:
 ssh bigdata12

(5)、配置主机名:/etc/hosts文件

vi /etc/hosts

192.168.157.11 bigdata11

2、安装配置ZooKeeper集群:参考“ZooKeeper安装说明”

3、配置Hadoop集群:(在bigdata12上安装)

1)修改hadoop-env.sh文件:(在bigdata12上执行)

export JAVA_HOME=/root/training/jdk1.8.0_144

2)修改core-site.xml文件:(在bigdata12上执行)

<configuration>

<!-- 指定hdfsnameservicens1 -->

<property>

<name>fs.defaultFS</name>

<value>hdfs://ns1</value>

</property>

<!-- 指定hadoop临时目录 -->

<property>

<name>hadoop.tmp.dir</name>

<!-- /tmp目录事先存在 -->

<value>/root/training/hadoop-2.7.3/tmp</value>

</property>

<!-- 指定zookeeper地址 -->

<property>

<name>ha.zookeeper.quorum</name>

<value>bigdata12:2181,bigdata13:2181,bigdata14:2181</value>

</property>

</configuration>

3)修改hdfs-site.xml(在bigdata12上执行)

<configuration>

<!--指定hdfsnameservicens1,需要和core-site.xml中的保持一致 -->

<property>

<name>dfs.nameservices</name>

<value>ns1</value>

</property>

<!-- ns1下面有两个NameNode,分别是nn1nn2 -->

<property>

<name>dfs.ha.namenodes.ns1</name>

<value>nn1,nn2</value>

</property>

<!-- nn1RPC通信地址 -->

<property>

<name>dfs.namenode.rpc-address.ns1.nn1</name>

<value>bigdata12:9000</value>

</property>

<!-- nn1http通信地址 -->

<property>

<name>dfs.namenode.http-address.ns1.nn1</name>

<value>bigdata12:50070</value>

</property>


<!-- nn2RPC通信地址 -->

<property>

<name>dfs.namenode.rpc-address.ns1.nn2</name>

<value>bigdata13:9000</value>

</property>

<!-- nn2http通信地址 -->

<property>

<name>dfs.namenode.http-address.ns1.nn2</name>

<value>bigdata13:50070</value>

</property>

<!-- 指定NameNode的日志在JournalNode上的存放位置 -->

<property>

<name>dfs.namenode.shared.edits.dir</name>

<value>qjournal://bigdata12:8485;bigdata13:8485;/ns1</value>

</property>

<!-- 指定JournalNode在本地磁盘存放数据的位置 -->

<property>

<name>dfs.journalnode.edits.dir</name>

<!-- /journal目录事先存在 -->

<value>/root/training/hadoop-2.7.3/journal</value>

</property>

<!-- 开启NameNode失败自动切换 -->

<property>

<name>dfs.ha.automatic-failover.enabled</name>

<value>true</value>

</property>

<!-- 配置失败自动切换实现方式 -->

<property>

<name>dfs.client.failover.proxy.provider.ns1</name>

<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>

</property>

<!-- 配置隔离机制方法,多个机制用换行分割,即每个机制暂用一行-->

<!--为什么HA的实现,需要配置隔离机制??

如果没有隔离机制,会造成脑裂的问题:由于某种原因(FailOverControllerNameNode通信出现问题,FailOverController的到的是错误信息),造成存在多个activeNameNode,这时DataNode就会发生脑裂问题,不知道谁是真正的NameNode

-->

<property>

<name>dfs.ha.fencing.methods</name>

<value>

sshfence

shell(/bin/true)

</value>

</property>

<!-- 使用sshfence隔离机制时需要ssh免登陆 -->

<property>

<name>dfs.ha.fencing.ssh.private-key-files</name>

<value>/root/.ssh/id_rsa</value>

</property>

<!-- 配置sshfence隔离机制超时时间:毫秒,超过30秒切换失败 -->

<property>

<name>dfs.ha.fencing.ssh.connect-timeout</name>

<value>30000</value>

</property>

</configuration>

4)、修改mapred-site.xml文件(在bigdata12上执行)

<configuration>

<property>

<name>mapreduce.framework.name</name>

<value>yarn</value>

</property>

</configuration>

5)、修改yarn-site.xml文件(在bigdata12上执行)

<configuration>

    <!-- 开启RM高可靠 -->

<property>

   <name>yarn.resourcemanager.ha.enabled</name>

   <value>true</value>

</property>

        <!-- 指定RMcluster id -->

<property>

   <name>yarn.resourcemanager.cluster-id</name>

   <value>yrc</value>

</property>

<!-- 指定RM的名字 -->

<property>

   <name>yarn.resourcemanager.ha.rm-ids</name>

   <value>rm1,rm2</value>

</property>

<!-- 分别指定RM的地址 -->

<property>

   <name>yarn.resourcemanager.hostname.rm1</name>

   <value>bigdata12</value>

</property>

<property>

   <name>yarn.resourcemanager.hostname.rm2</name>

   <value>bigdata13</value>

</property>

<!-- 指定zk集群地址 -->

<property>

   <name>yarn.resourcemanager.zk-address</name>

   <value>bigdata12:2181,bigdata13:2181,bigdata14:2181</value>

</property>

<property>

   <name>yarn.nodemanager.aux-services</name>

   <value>mapreduce_shuffle</value>

</property>

</configuration>

6)、修改slaves文件(/root/training/hadoop-2.7.3/etc/hadoop),设置从节点

bigdata14

bigdata15

7)、创建目录(在bigdata12上执行)

/root/training/hadoop-2.7.3/tmp

/root/training/hadoop-2.7.3/journal

8)、将配置好的hadoop拷贝到其他节点

scp -r /root/training/hadoop-2.7.3/ root@bigdata13:/root/training/

scp -r /root/training/hadoop-2.7.3/ root@bigdata14:/root/training/

scp -r /root/training/hadoop-2.7.3/ root@bigdata15:/root/training/

(8)、启动ZooKeeper集群

zkServer.sh start

(9)、单独启动启动journalnodebigdata12bigdata13

hadoop-daemon.sh start journalnode

(10)NameNode节点格式化HDFS(在bigdata12上执行)

hdfs namenode -format

(11)拷贝bigdata12dfs目录到bigdata13

/root/training/hadoop-2.7.3/tmp/dfs拷贝到bigdata13/root/training/hadoop-2.7.3/tmp

scp -r  dfs/ root@bigdata13:/root/training/hadoop-2.7.3/tmp

(12)、格式化ZooKeeper(在bigdata12上执行)

hdfs zkfc -formatZK

日志:INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/ns1 in ZK.

(13)、启动Hadoop集群(在bigdata12bigdata13上执行)

    start-all.sh

(14)、单独启动ResourceManagerbigdata12bigdata13上执行,取决于待启动)

yarn-daemon.sh start resourcemanager