Hadoop高可用集群（HA）

一、集群的规划
Zookeeper集群：
192.168.157.12 （bigdata12）
192.168.157.13 （bigdata13）
192.168.157.14 （bigdata14）

Hadoop集群：
192.168.157.12 （bigdata12）   NameNode1      ResourceManager1     Journalnode
192.168.157.13 （bigdata13）   NameNode2      ResourceManager2     Journalnode
192.168.157.14 （bigdata14）   DataNode1      NodeManager1
192.168.157.15 （bigdata15）   DataNode2      NodeManager2

二、准备工作
1、安装JDK
2、配置环境变量
3、配置免密码登录
4、配置主机名

三、配置Zookeeper（在192.168.157.12安装）
在主节点（hadoop112）上配置ZooKeeper
（*）配置/root/training/zookeeper-3.4.6/conf/zoo.cfg文件
dataDir=/root/training/zookeeper-3.4.6/tmp

server.1=bigdata12:2888:3888
server.2=bigdata13:2888:3888
server.3=bigdata14:2888:3888

（*）在/root/training/zookeeper-3.4.6/tmp目录下创建一个myid的空文件
echo 1 > /root/training/zookeeper-3.4.6/tmp/myid

（*）将配置好的zookeeper拷贝到其他节点，同时修改各自的myid文件
scp -r /root/training/zookeeper-3.4.6/ bigdata13:/root/training
scp -r /root/training/zookeeper-3.4.6/ bigdata14:/root/training

四、安装Hadoop集群（在bigdata12上安装）
1、修改hadoo-env.sh
export JAVA_HOME=/root/training/jdk1.8.0_144

2、修改core-site.xml
<configuration>
<!-- 指定hdfs的nameservice为ns1 -->
<property>
<name>fs.defaultFS</name>
<value>hdfs://ns1</value>
</property>

<!-- 指定hadoop临时目录 -->
<property>
<name>hadoop.tmp.dir</name>
<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（配置这个nameservice中有几个namenode）
<configuration>
    <!--指定hdfs的nameservice为ns1，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nn1，nn2 -->
<property>
<name>dfs.ha.namenodes.ns1</name>
<value>nn1,nn2</value>
</property>

<!-- nn1的RPC通信地址 -->
<property>
<name>dfs.namenode.rpc-address.ns1.nn1</name>
<value>bigdata12:9000</value>
</property>
<!-- nn1的http通信地址 -->
<property>
<name>dfs.namenode.http-address.ns1.nn1</name>
<value>bigdata12:50070</value>
</property>

<!-- nn2的RPC通信地址 -->
<property>
<name>dfs.namenode.rpc-address.ns1.nn2</name>
<value>bigdata13:9000</value>
</property>
<!-- nn2的http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>
<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-->
<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 -->
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>30000</value>
</property>
</configuration>

4、修改mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>

5、修改yarn-site.xml
<configuration>
    <!-- 开启RM高可靠 -->
<property>
   <name>yarn.resourcemanager.ha.enabled</name>
   <value>true</value>
</property>

        <!-- 指定RM的cluster 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
bigdata14
bigdata15

7、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/

五、启动Zookeeper集群

六、在bigdata12和bigdata13上启动journalnode
hadoop-daemon.sh start journalnode

七、格式化HDFS（在bigdata12上执行）
1. hdfs namenode -format
2. 将/root/training/hadoop-2.7.3/tmp拷贝到bigdata13的/root/training/hadoop-2.7.3/tmp下
3. 格式化zookeeper
   hdfs zkfc -formatZK
   日志：17/07/13 00:34:33 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/ns1 in ZK.
 
  
八、在bigdata12上启动Hadoop集群
    start-all.sh

日志：
Starting namenodes on [bigdata12 bigdata13]
bigdata12: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop113.out
bigdata13: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop112.out
bigdata14: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop115.out
bigdata15: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop114.out

bigdata13: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata13.out
bigdata12: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata12.out


bigdata13上的ResourceManager需要单独启动
命令：yarn-daemon.sh start resourcemanager