Hadoop高可用搭建（二）

今天药忘吃喽~ 2024-03-27 17:33 45阅读 0赞

**目录**

解压Hadoop

改名

更改配置文件

workers

hdfs-site.xml

core-site.xml

hadoop-env.sh

mapred-site.xml

yarn-site.xml

设置环境变量

启动集群

启动zk集群

启动journalnode服务

格式化hfds namenode

启动namenode

同步namenode信息

查看namenode节点状态

查看启动情况

关闭所有dfs有关的服务

格式化zk

启动dfs

启动yarn

查看resourcemanager节点状态

测试集群wordcount

创建一个TXT文件

上传到hdfs上面

查看输出结果

--------------------

### 解压Hadoop ###

> \[root@ant51 install\]\# tar -zxvf ./hadoop-3.1.3.tar.gz -C ../soft/

### 改名 ###

> \[root@ant151 install\]\# cd /opt/soft  
> \[root@ant151 soft\]\# mv hadoop-3.1.3/ hadoop313

### 更改配置文件 ###

#### workers ####

> \[root@ant151 ~\] \# cd /opt/soft/hadoop313/etc/hadoop
> 
> \[root@ant151 hadoop\] \# vim workers
> 
> 把所有的虚拟机加上去
> 
> ![6a43d857d5e6442face3be70edb02725.png][]

#### hdfs-site.xml ####

> \[root@ant151 hadoop\] \# vim hdfs-site.xml

<configuration>
      <property>
        <name>dfs.replication</name>
        <value>2</value>
        <description>hadoop中每一个block文件的备份数量</description>
      </property>
      <property>
        <name>dfs.namenode.name.dir</name>
        <value>/opt/soft/hadoop313/data/dfs/name</value>
        <description>namenode上存储hdfs名字空间元数据的目录</description>
      </property>
      <property>
        <name>dfs.datanode.data.dir</name>
        <value>/opt/soft/hadoop313/data/dfs/data</value>
        <description>datanode上数据块的物理存储位置目录</description>
      </property>
     <property>
        <name>dfs.namenode.secondary.http-address</name>
        <value>ant151:9869</value>
       <description></description>
      </property>
     <property>
        <name>dfs.nameservices</name>
        <value>gky</value>
       <description>指定hdfs的nameservice，需要和core-site.xml中的保持一致</description>
      </property>
     <property>
        <name>dfs.ha.namenodes.gky</name>
        <value>nn1,nn2</value>
       <description>gky为集群的逻辑名称，映射两个namenode逻辑名</description>
      </property>
     <property>
        <name>dfs.namenode.rpc-address.gky.nn1</name>
        <value>ant151:9000</value>
       <description>namenode1的rpc通信地址</description>
      </property>
    <property>
        <name>dfs.namenode.http-address.gky.nn1</name>
        <value>ant151:9870</value>
       <description>namenode1的http通信地址</description>
      </property>
     <property>
        <name>dfs.namenode.rpc-address.gky.nn2</name>
        <value>ant152:9000</value>
       <description>namenode2的rpc通信地址</description>
      </property>
    <property>
        <name>dfs.namenode.http-address.gky.nn2</name>
        <value>ant152:9870</value>
       <description>namenode2的http通信地址</description>
      </property>
    <property>
        <name>dfs.namenode.shared.edits.dir</name>
        <value>qjournal://ant151:8485;ant152:8485;ant153:8485/gky</value>
       <description>指定namenode的edits元数据的共享存储位置（JournalNode列表）</description>
      </property>
    <property>
        <name>dfs.journalnode.edits.dir</name>
        <value>/opt/soft/hadoop313/data/journaldata</value>
       <description>指定JournalNode在本地磁盘存放数据的位置</description>
      </property>
    
    <property>
        <name>dfs.ha.automatic-failover.enabled</name>
        <value>true</value>
       <description>开启NameNode故障自动切换</description>
      </property>
    <property>
        <name>dfs.client.failover.proxy.provider.gky</name>
        <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
       <description>如果失败后自动切换的实现的方式</description>
      </property>
    <property>
        <name>dfs.ha.fencing.methods</name>
        <value>sshfence</value>
       <description>防止脑裂的处理</description>
      </property>
    <property>
        <name>dfs.ha.fencing.ssh.private-key-files</name>
        <value>/root/.ssh/id_rsa</value>
       <description>使用sshfence隔离机制时，需要用ssh免密登陆</description>
      </property>
    
      <property>
        <name>dfs.permissions.enabled</name>
        <value>false</value>
        <description>关闭hdfs操作的权限验证</description>
      </property>
    
      <property>
        <name>dfs.image.transfer.bandwidthPerSec</name>
        <value>1048576</value>
        <description></description>
      </property>
     <property>
        <name>dfs.block.scanner.volume.bytes.per.second</name>
        <value>1048576</value>
        <description></description>
      </property>
    
    </configuration>

#### core-site.xml ####

> \[root@ant151 hadoop\] \# vim core-site.xml

<configuration>
      <property>
        <name>fs.defaultFS</name>
        <value>hdfs://gky</value>
        <description>逻辑名称，必须与hdfs-site.xml中的dfs.nameservice值保持一致</description>
      </property>
      <property>
        <name>hadoop.tmp.dir</name>
        <value>/opt/soft/hadoop313/tmpdata</value>
        <description>namenode上本地的hadoop临时文件夹</description>
      </property>
      <property>
        <name>hadoop.http.staticuser.user</name>
        <value>root</value>
       <description>默认用户</description>
      </property>
      <property>
        <name>io.file.buffer.size</name>
        <value>131072</value>
        <description>读写队列缓存：128k；读写文件的buffer大小</description>
      </property>
      <property>
        <name>hadoop.proxyuser.root.hosts</name>
        <value>*</value>
       <description>代理用户</description>
      </property>
      <property>
        <name>hadoop.proxyuser.root.groups</name>
        <value>*</value>
       <description>代理用户组</description>
      </property>
     <property>
        <name>ha.zookeeper.quorum</name>
        <value>ant151:2181,ant152:2181,ant153:2181</value>
       <description>高可用用户连接</description>
      </property>
     <property>
        <name>ha.zookeeper.session-timeout.ms</name>
        <value>10000</value>
       <description>hadoop连接zookeeper会话的超时时长为10s</description>
      </property>
    </configuration>

#### hadoop-env.sh ####

> \[root@ant151 hadoop\] \# vim hadoop-env.sh
> 
> 大概54行左右JAVA\_HOME

export JAVA_HOME=/opt/soft/jdk180
    export HDFS_NAMENODE_USER=root
    export HDFS_DATANODE_USER=root
    export HDFS_SECONDARYNAMENODE_USER=root
    export HDFS_JOURNALNODE_USER=root
    export HDFS_ZKFC_USER=root
    export YARN_RESOURCEMANAGER_USER=root
    export YARN_NODEMANAGER_USER=root

#### mapred-site.xml ####

> \[root@ant151 hadoop\] \# vim mapred-site.xml

<configuration>
      <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
        <description>job执行框架：local,classic or yarn</description>
        <final>true</final>
      </property>
      <property>
       <name>mapreduce.application.classpath</name>
        <value>/opt/soft/hadoop313/etc/hadoop:/opt/soft/hadoop313/share/hadoop/common/lib/*:/opt/soft/hadoop313/share/hadoop/common/*:/opt/soft/hadoop313/share/hadoop/hdfs/*:/opt/soft/hadoop313/share/hadoop/hdfs/lib/*:/opt/soft/hadoop313/share/hadoop/mapreduce/*:/opt/soft/hadoop313/share/hadoop/mapreduce/lib/*:/opt/soft/hadoop313/share/hadoop/yarn/*:/opt/soft/hadoop313/share/hadoop/yarn/lib/*</value>
      </property>
      <property>
        <name>mapreduce.jobhistory.address</name>
        <value>ant151:10020</value>
      </property>
      <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>ant151:19888</value>
      </property>
    
      <property>
        <name>mapreduce.map.memory.mb</name>
        <value>1024</value>
     <description>map阶段task工作内存</description>
      </property>
      <property>
        <name>mapreduce.reduce.memory.mb</name>
        <value>1024</value>
     <description>reduce阶段task工作内存</description>
      </property>
    
    </configuration>

#### yarn-site.xml ####

> \[root@ant151 hadoop\] \# vim yarn-site.xml

<configuration>
    	<property>
    		<name>yarn.resourcemanager.ha.enabled</name>
    		<value>true</value>
    		<description>开启resourcemanager高可用</description>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.cluster-id</name>
    		<value>yrcabc</value>
    		<description>指定yarn集群中的id</description>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.ha.rm-ids</name>
    		<value>rm1</value>
    		<description>指定resourcemanager的名字</description>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.hostname.rm1</name>
    		<value>ant153</value>
    		<description>设置rm1的名字</description>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.webapp.address.rm1</name>
    		<value>ant153:8088</value>
    		<description></description>
    	</property>	
    	<property>
    		<name>yarn.resourcemanager.zk-address</name>
    		<value>ant151:2181,ant152:2181,ant153:2181</value>
    		<description>指定zk集群地址</description>
    	</property>
    	<property>
    		<name>yarn.nodemanager.aux-services</name>
    		<value>mapreduce_shuffle</value>
    		<description>运行mapreduce程序必须配置的附属服务</description>
    	</property>
    	<property>
    		<name>yarn.nodemanager.local-dirs</name>
    		<value>/opt/soft/hadoop313/tmpdata/yarn/local</value>
    		<description>nodemanager本地存储目录</description>
    	</property>
    	<property>
    		<name>yarn.nodemanager.log-dirs</name>
    		<value>/opt/soft/hadoop313/tmpdata/yarn/log</value>
    		<description>nodemanager本地日志目录</description>
    	</property>
    	
    	<property>
    		<name>yarn.nodemanager.resource.memory-mb</name>
    		<value>1024</value>
    		<description>resource进程的工作内存</description>
    	</property>
    	<property>
    		<name>yarn.nodemanager.resource.cpu-vcores</name>
    		<value>2</value>
    		<description>resource工作中所能使用机器的内核数</description>
    	</property>
    	<property>
    		<name>yarn.scheduler.minimum-allocation-mb</name>
    		<value>256</value>
    		<description></description>
    	</property>
    	<property>
    		<name>yarn.log-aggregation-enable</name>
    		<value>true</value>
    		<description></description>
    	</property>
    	<property>
    		<name>yarn.log-aggregation.retain-seconds</name>
    		<value>86400</value>
    		<description>日志保留多少秒</description>
    	</property>
    	<property>
    		<name>yarn.nodemanager.vmem-check-enabled</name>
    		<value>false</value>
    		<description></description>
    	</property>
    	<property>
    		<name>yarn.application.classpath</name>
    		<value>/opt/soft/hadoop313/etc/hadoop:/opt/soft/hadoop313/share/hadoop/common/lib/*:/opt/soft/hadoop313/share/hadoop/common/*:/opt/soft/hadoop313/share/hadoop/hdfs/*:/opt/soft/hadoop313/share/hadoop/hdfs/lib/*:/opt/soft/hadoop313/share/hadoop/mapreduce/*:/opt/soft/hadoop313/share/hadoop/mapreduce/lib/*:/opt/soft/hadoop313/share/hadoop/yarn/*:/opt/soft/hadoop313/share/hadoop/yarn/lib/*</value>
    		<description></description>
    	</property>
    	<property>
    		<name>yarn.nodemanager.env-whitelist</name>
    		<value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_MAPRED_HOME</value>
    		<description></description>
    	</property>
    </configuration>

#### 设置环境变量 ####

> \[root@ant151 hadoop\] \# vim /etc/profile

#HADOOP_HOME
    export HADOOP_HOME=/opt/soft/hadoop313
    export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HADOOP_HOME/lib

![7362d3a07fc04defba6664287130ca60.png][]

配置完成之后把hadoop313和配置文件拷贝到其余机器上面

> hadoop
> 
> \[root@ant151 shell\]\# scp -r ./hadoop313/ root@ant152:/opt/soft/  
> \[root@ant151 shell\]\# scp -r ./hadoop313/ root@ant153:/opt/soft/
> 
> 环境变量
> 
> \[root@ant151 shell\]\# scp /etc/profile root@ant152:/etc
> 
> \[root@ant151 shell\]\# scp /etc/profile root@ant153:/etc  
> 所有机器刷新资源
> 
> \[root@ant151 shell\]\# source /etc/profile

### 启动集群 ###

#### 启动zk集群 ####

> \[root@ant151 shell\]\# ./zkop.sh start
> 
> \[root@ant151 shell\]\# ./zkop.sh status
> 
> \[root@ant151 shell\]\# ./showjps.sh
> 
> ![8a4f0f182c50448db4d4ef9b90cb2ba8.png][]

#### 启动journalnode服务 ####

启动ant151,ant152,ant153的journalnode服务

> \[root@ant151 soft\]\# hdfs --daemon start journalnode
> 
> ![6b432a34607a465290074948feda6c33.png][]

#### 格式化hfds namenode ####

在ant151上面操作

> \[root@ant151 soft\]\# hdfs namenode -format

#### 启动namenode ####

在ant151上面操作

> \[root@ant151 soft\]\# hdfs --daemon start namenode

#### 同步namenode信息 ####

在ant152上操作

> \[root@ant152 soft\]\# hdfs namenode -bootstrapStandby
> 
> 启动namenode
> 
> \[root@ant152 soft\]\# hdfs --daemon start namenode

#### 查看namenode节点状态 ####

> \[root@ant151 zk345\]\# hdfs haadmin -getServiceState nn1  
> \[root@ant151 zk345\]\# hdfs haadmin -getServiceState nn2
> 
> ![d2283fb956264bc38aeb86b14971157c.png][]

#### 查看启动情况 ####

\[root@ant152 shell\]\# ./showjps.sh

![6fe0388b683d45c4ba1865a4e607bed0.png][]

#### 关闭所有dfs有关的服务 ####

> \[root@ant151 soft\]\# stop-dfs.sh

#### 格式化zk ####

> \[root@ant151 soft\]\# hdfs zkfc -formatZK

#### 启动dfs ####

> \[root@ant151 soft\]\# start-dfs.sh
> 
> ![1daf9ac427a84ca2841dded3ba6a3891.png][]

#### 启动yarn ####

> \[root@ant151 soft\]\# start-yarn.sh
> 
> ![e2554abcf5844a3487e4802542234514.png][]

#### 查看resourcemanager节点状态 ####

> \[root@ant151 zk345\]\# yarn rmadmin -getServiceState rm1
> 
> ![e0fc8aa042bd4db89b5042e208a2547a.png][]

### 测试集群wordcount ###

#### 创建一个TXT文件 ####

> \[root@ant151 soft\]\# vim ./aa.txt

#### 上传到hdfs上面 ####

> \[root@ant151 soft\]\# hdfs dfs -put ./aa.txt /
> 
> 查看
> 
> \[root@ant151 soft\]\# hdfs dfs -ls /  
> ![07fedbf325754a1fb883e0b25a2702ba.png][]

mapreduce里面的jar包运行wordcount

![0604a3747fc945428c281346a3fcb4ed.png][]

运行

> \[root@ant151 mapreduce\]\# hadoop jar ./hadoop-mapreduce-examples-3.1.3.jar wordcount /aa.txt /out1![a7ed6f6795bb42c6b986097d2c95d8ad.png][]

#### 查看输出结果 ####

> \[root@ant151 mapreduce\]\# hdfs dfs -ls /  
> \[root@ant151 mapreduce\]\# hdfs dfs -ls /out1  
> \[root@ant151 mapreduce\]\# hdfs dfs -cat /out1/part-r-00000  
> ![b67df3d14b9145f1bb9efde648b0dbd4.png][]
> 
> 出现
> 
> aa 1
> 
> bb 2
> 
> cc 3
> 
> 则成功

[6a43d857d5e6442face3be70edb02725.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/e7bc5dc6f4644f12bce6ae360b557ae7.png
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[e2554abcf5844a3487e4802542234514.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/b9671eed2e3142bda950a074abda2f59.png
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[07fedbf325754a1fb883e0b25a2702ba.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/53d22bd565ca42cf9f7805381542eafc.png
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