五节点HadoopHA安装教程

2022-01-14 04:26:01

五节点HadoopHA安装教程：
Master1 namenode,resourcemanager,nodemanager,datanode,journalnode, DFSZKFailoverController
Master2 namenode,resourcemanager,nodemanager,datanode,journalnode, DFSZKFailoverController
Slave1 nodemanager,datenode,journalnode, QuorumPeerMain
Slave2 nodemanager,datenode,journalnode, QuorumPeerMain
Slave3 nodemanager,datenode,journalnode, QuorumPeerMain

  1. 安装jdk
    配置环境变量
JAVA

export JAVA_HOME=/home/zhouwang/jdk1.8.0_151
export PATH=$JAVA_HOME/bin:$PATH
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib:$CLASSPATH

2.配置个节点的/etc/hosts文件
192.168.71.128 master1
192.168.71.132 master2
192.168.71.129 slave1
192.168.71.130 slave2
192.168.71.131 slave3

3.配置SSH免密登录
Ssh-keygen -t rsa
Cat id_rsa.pub >> authorized_keys
Chmod 644 authorized_keys
Scp ~/.ssh/id_rsa.pub authorized_keys zhouwang@master:~/.ssh
Authorized_keys的权限必须是640
4.安装zookeeper
重命名conf文件夹下的zoo.example.cfg为zoo.cfg。新修改内容
clientPort=2181
dataDir=/home/zhouwang/zookeeper/data
dataLogDir=/home/zhouwang/zookeeper/log
server.0=master1:2888:3888
server.1=master2:2888:3888
server.2=slave1:2888:3888
server.3=slave2:2888:3888
server.4=slave3:2888:3888
在zookeeper文件夹下面创建相应的data和log文件夹，还有myid文件
Mkdir data
Mkdir log
Vim myid 输入1，每个节点的myid文件的值与server.x对应上

配置环境变量如下：

ZOOKEEPER

export ZOOKEEPER_HOME=/home/zhouwang/zookeeper
export PATH=$PATH:$ZOOKEEPER_HOME/bin

  1. 安装Hadoop
    修改etc/hadoop下的四个配置文件

（1） core-site.xml

<property> 
    <name>fs.defaultFS</name> 
    <value>hdfs://master/</value> 
</property> 

<property> 
    <name>hadoop.tmp.dir</name> 
    <value>/home/zhouwang/hadoop/tmp</value> 
</property> 

<property> 
    <name>ha.zookeeper.quorum</name> 
    <value>master1:2181,master2:2181,slave1:2181,slave2:2181,slave3:2181</value> 
</property>

（2） hdfs_site.xml

<property> 
    <name>dfs.namenode.name.dir</name> 
    <value>/home/zhouwang/hadoop/dfs/name</value> 
</property> 
<property> 
    <name>dfs.datanode.data.dir</name> 
    <value>/home/zhouwang/hadoop/dfs/data</value> 
</property> 
<property> 
    <name>dfs.replication</name> 
    <value>3</value> 
</property> 

<!--HDFS高可用配置 --> 
<!--指定hdfs的nameservice，需要和core-site.xml中的保持一致--> 
<property> 
    <name>dfs.nameservices</name> 
    <value>master</value> 
</property> 
<!--指定master的两个namenode的名称 --> 
<property> 
    <name>dfs.ha.namenodes.master</name> 
    <value>nn1,nn2</value> 
</property> 

<!-- nn1,nn2 rpc 通信地址 --> 
<property> 
    <name>dfs.namenode.rpc-address.master.nn1</name> 
    <value>master1:9000</value> 
</property> 
<property> 
    <name>dfs.namenode.rpc-address.master.nn2</name> 
    <value>master2:9000</value> 
</property> 

<!-- nn1.nn2 http 通信地址 --> 
<property> 
    <name>dfs.namenode.http-address.master.nn1</name> 
    <value>master1:50070</value> 
</property> 
<property> 
    <name>dfs.namenode.http-address.master.nn2</name> 
    <value>master2:50070</value> 
</property> 

<!--=========Namenode同步==========--> 
<!--保证数据恢复 --> 
<property> 
    <name>dfs.journalnode.http-address</name> 
    <value>0.0.0.0:8480</value> 
</property> 
<property> 
    <name>dfs.journalnode.rpc-address</name> 
    <value>0.0.0.0:8485</value> 
</property> 
<property> 
    <!--指定NameNode的元数据在JournalNode上的存放位置 --> 
    <name>dfs.namenode.shared.edits.dir</name> 
    <value>qjournal://master1:8485;master2:8485;slave1:8485;slave2:8485;slave3:8485/master</value> 
</property> 

<property> 
    <!--JournalNode存放数据地址 --> 
    <name>dfs.journalnode.edits.dir</name> 
    <value>/home/zhouwang/hadoop/dfs/journal</value> 
</property> 
<property> 
    <!--NameNode失败自动切换实现方式 --> 
    <name>dfs.client.failover.proxy.provider.master</name> 
    <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> 
</property> 

<!--=========Namenode fencing：======== --> 
<!-- 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>/home/zhouwang/.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> 

<!--开启基于Zookeeper及ZKFC进程的自动备援设置,监视进程是否死掉 --> 
<property> 
    <name>dfs.ha.automatic-failover.enabled</name> 
    <value>true</value> 
</property>

(3) mapred-site.xml

<!-- 指定mr框架为yarn方式 -->  

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



    <name>mapreduce.jobhistory.address</name> 
    <value>master1:10020</value> 



    <name>mapreduce.jobhistory.webapp.address</name> 
    <value>master1:19888</value>


(4) yarn-site.xml

<!--NodeManager上运行的附属服务。需配置成mapreduce_shuffle，才可运行MapReduce程序--> 
<property> 
    <name>yarn.nodemanager.aux-services</name> 
    <value>mapreduce_shuffle</value> 
</property> 
<property> 
    <name>yarn.resourcemanager.connect.retry-interval.ms</name> 
    <value>2000</value> 
</property> 
<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>cluster</value> 
</property> 
<!--指定两台RM主机名标识符--> 
<property> 
    <name>yarn.resourcemanager.ha.rm-ids</name> 
    <value>rm1,rm2</value> 
</property> 
<!--RM主机1--> 
<property> 
    <name>yarn.resourcemanager.hostname.rm1</name> 
    <value>master1</value> 
</property> 
<!--RM主机2--> 
<property> 
    <name>yarn.resourcemanager.hostname.rm2</name> 
    <value>master2</value> 
</property> 
<!--RM故障自动切换--> 
<property> 
    <name>yarn.resourcemanager.ha.automatic-failover.enabled</name> 
    <value>true</value> 
</property> 
<!--RM故障自动恢复 --> 
<property> 
<name>yarn.resourcemanager.recovery.enabled</name>  
    <value>true</value>  
</property> 
<!--RM状态信息存储方式，一种基于内存(MemStore)，另一种基于ZK(ZKStore)--> 
<property> 
    <name>yarn.resourcemanager.store.class</name> 
    <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value> 
</property> 
<!-- 指定zk集群地址 --> 
<property> 
    <name>yarn.resourcemanager.zk-address</name> 
    <value>master1:2181,master2:2181,slave1:2181,slave2:2181,slave3:2181</value> 
</property> 
<!--向RM调度资源地址--> 
<property> 
    <name>yarn.resourcemanager.scheduler.address.rm1</name> 
    <value>master1:8030</value> 
</property> 
<property> 
    <name>yarn.resourcemanager.scheduler.address.rm2</name> 
    <value>master2:8030</value> 
</property> 
<!--NodeManager通过该地址交换信息--> 
<property> 
    <name>yarn.resourcemanager.resource-tracker.address.rm1</name> 
    <value>master1:8031</value> 
</property> 
<property> 
    <name>yarn.resourcemanager.resource-tracker.address.rm2</name> 
    <value>master2:8031</value> 
</property> 
<!--客户端通过该地址向RM提交对应用程序操作--> 
<property> 
    <name>yarn.resourcemanager.address.rm1</name> 
    <value>master1:8032</value> 
</property> 
<property> 
    <name>yarn.resourcemanager.address.rm2</name> 
    <value>master2:8032</value> 
</property> 
<!--管理员通过该地址向RM发送管理命令--> 
<property> 
    <name>yarn.resourcemanager.admin.address.rm1</name> 
    <value>master1:8033</value> 
</property> 
<property> 
    <name>yarn.resourcemanager.admin.address.rm2</name> 
    <value>master2:8033</value> 
</property> 
<!--RM HTTP访问地址,查看集群信息--> 
<property> 
    <name>yarn.resourcemanager.webapp.address.rm1</name> 
    <value>master1:8088</value> 
</property> 
<property> 
    <name>yarn.resourcemanager.webapp.address.rm2</name> 
    <value>master2:8088</value> 
</property>

(5) slaves

localhost

192.168.71.129 slave1
192.168.71.130 slave2
192.168.71.131 slave3
192.168.71.128 master1
192.168.71.132 master2

设置配置文件：

HADOOP

export HADOOP_HOME=/home/zhouwang/hadoop
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export YARN_CONF_DIR=$HADOOP_HOME/etc/Hadoop

将hadoop文件夹分发到各个节点上去：
Scp -r Hadoop zhouwang@XXX:~/Hadoop

  1. 第一次启动集群
    配置了zookeeper的节点启动zkServer.sh服务

zkServer.sh start
然后查看zookeeper状态，zkServer.sh status，显式为follower或者leader则说明启动成功

然后，数据节点启动journalnode服务，hadoop-deamen.sh start journalnode

在master1格式化namenode: Hadoop namenode -format
然后启动namenode服务： Hadoop-deamon.sh start namenode

在master2同步master1的元数据： HDFS namenode -bootstrapStandby
然后再master2上启动namenode服务： Hadoop-deamon.sh start namenode

在master上格式化ZKFC
Hdfs zkfc -formatZK

在master1和master2上执行hadoop-deamon.sh start zkfc 启动DFSZKFailoverController 服务#ZKFC用于监控NameNode active和standby节点状态

在master1上启动hadoop-deamons.sh start datanode 启动所有数据节点上的datanode服务。

在master1上执行start-yarn.xml启动yarn服务。

至此安装完成。

7．第一次停止集群
先停止hdfs：stop-dfs.sh
在停止yarn：stop-yarn.sh
再次启动或者停止就可以执行start-all.sh 和stop-all.sh了。

8．Hdfs操作命令
Hadoop dfsadmin -report #查看datanode的节点信息
Hdfs haadmin -getServiceState nn1 查看namenode的状态
hdfs haadmin -transitionToActive/transitionToStandby -forcemanual nn1 强制切换节点的active和是standby状态。

上一篇：Ignite自定义函数注意事项


下一篇：Ignite的jdbc与网格的连接方式的查询性能对比