【HA High Availability Construction】

Internet 2023-07-18 18:44:50 views: null

After the whole ha is built, the cluster will look like the following

hadoop102 hadoop103 hadoop104
NameNode NameNode NameNode
JournalNode JournalNode JournalNode
DataNode DataNode DataNode
Zookeeper Zookeeper Zookeeper
ZKFC ZKFC ZKFC
ResourceManager ResourceManager ResourceManager
NodeManager NodeManager NodeManager

Configure core-site.xml

<configuration>
  <!-- 把多个NameNode的地址组装成一个集群mycluster -->
  <property>
    <name>fs.defaultFS</name>
    <value>hdfs://mycluster</value>
  </property>

  <!-- 指定hadoop运行时产生文件的存储目录 -->
  <property>
    <name>hadoop.tmp.dir</name>
    <value>/opt/module/ha/hadoop-3.1.3/data</value>
  </property>
<!-- 配置HDFS网页登录使用的静态用户为atguigu -->
    <property>
        <name>hadoop.http.staticuser.user</name>
        <value>atguigu</value>
</property>

<!-- 配置该atguigu(superUser)允许通过代理访问的主机节点 -->
    <property>
        <name>hadoop.proxyuser.atguigu.hosts</name>
        <value>*</value>
</property>
<!-- 配置该atguigu(superUser)允许通过代理用户所属组 -->
    <property>
        <name>hadoop.proxyuser.atguigu.groups</name>
        <value>*</value>
</property>
<!-- 配置该atguigu(superUser)允许通过代理的用户-->
    <property>
        <name>hadoop.proxyuser.atguigu.users</name>
        <value>*</value>
</property>
<!-- 指定zkfc要连接的zkServer地址 -->
<property>
	<name>ha.zookeeper.quorum</name>
	<value>hadoop102:2181,hadoop103:2181,hadoop104:2181</value>
</property>
</configuration>

Configure hdfs-site.xml

<configuration>
   <!-- NameNode数据存储目录 -->
  <property>
    <name>dfs.namenode.name.dir</name>
    <value>file://${hadoop.tmp.dir}/name</value>
  </property>

  <!-- DataNode数据存储目录 -->
  <property>
    <name>dfs.datanode.data.dir</name>
    <value>file://${hadoop.tmp.dir}/data</value>
  </property>

  <!-- JournalNode数据存储目录 -->
  <property>
    <name>dfs.journalnode.edits.dir</name>
    <value>${hadoop.tmp.dir}/jn</value>
  </property>

  <!-- 完全分布式集群名称 -->
  <property>
    <name>dfs.nameservices</name>
    <value>mycluster</value>
  </property>

  <!-- 集群中NameNode节点都有哪些 -->
  <property>
    <name>dfs.ha.namenodes.mycluster</name>
    <value>nn1,nn2,nn3</value>
  </property>

  <!-- NameNode的RPC通信地址 -->
  <property>
    <name>dfs.namenode.rpc-address.mycluster.nn1</name>
    <value>hadoop102:8020</value>
  </property>
  <property>
    <name>dfs.namenode.rpc-address.mycluster.nn2</name>
    <value>hadoop103:8020</value>
  </property>
  <property>
    <name>dfs.namenode.rpc-address.mycluster.nn3</name>
    <value>hadoop104:8020</value>
  </property>

  <!-- NameNode的http通信地址 -->
  <property>
    <name>dfs.namenode.http-address.mycluster.nn1</name>
    <value>hadoop102:9870</value>
  </property>
  <property>
    <name>dfs.namenode.http-address.mycluster.nn2</name>
    <value>hadoop103:9870</value>
  </property>
  <property>
    <name>dfs.namenode.http-address.mycluster.nn3</name>
    <value>hadoop104:9870</value>
  </property>

  <!-- 指定NameNode元数据在JournalNode上的存放位置 -->
  <property>
    <name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://hadoop102:8485;hadoop103:8485;hadoop104:8485/mycluster</value>
  </property>

  <!-- 访问代理类：client用于确定哪个NameNode为Active -->
  <property>
    <name>dfs.client.failover.proxy.provider.mycluster</name>
    <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
  </property>

  <!-- 配置隔离机制，即同一时刻只能有一台服务器对外响应 -->
  <property>
    <name>dfs.ha.fencing.methods</name>
    <value>sshfence</value>
  </property>

  <!-- 使用隔离机制时需要ssh秘钥登录-->
  <property>
    <name>dfs.ha.fencing.ssh.private-key-files</name>
    <value>/home/atguigu/.ssh/id_rsa</value>
  </property> 
    <!-- 测试环境指定HDFS副本的数量1 -->
    <property>
        <name>dfs.replication</name>
        <value>3</value>
    </property>
<!-- 启用nn故障自动转移 -->
<property>
	<name>dfs.ha.automatic-failover.enabled</name>
	<value>true</value>
</property>

</configuration>

On [nn1], format it, and start

[atguigu@hadoop102 ~]$ hdfs namenode -format
[atguigu@hadoop102 ~]$ hdfs --daemon start namenode

On [nn2] and [nn3], synchronize the metadata information of nn1

[atguigu@hadoop103 ~]$ hdfs namenode -bootstrapStandby
[atguigu@hadoop104 ~]$ hdfs namenode -bootstrapStandby

Start [nn2] and [nn3]

[atguigu@hadoop103 ~]$ hdfs --daemon start namenode
[atguigu@hadoop104 ~]$ hdfs --daemon start namenode

On all nodes, start datanode

[atguigu@hadoop102 ~]$ hdfs --daemon start datanode
[atguigu@hadoop103 ~]$ hdfs --daemon start datanode
[atguigu@hadoop104 ~]$ hdfs --daemon start datanode

Switch [nn1] to Active

[atguigu@hadoop102 ~]$ hdfs haadmin -transitionToActive nn1

Check if Active

[atguigu@hadoop102 ~]$ hdfs haadmin -getServiceState nn1

HDFS-HA automatic mode
Start the zk cluster first,
start Zookeeper, and then initialize the state of HA in Zookeeper

hdfs zkfc -formatZK

Start the HDFS service:
group up:

start-dfs.sh

Single point start:

#单点启动NameNode
hdfs --daemon start namenode
#单点启动DataNode
hdfs --daemon start datanode

You can go to the zkCli.sh client to view the content of the Namenode election lock node

get -s /hadoop-ha/mycluster/ActiveStandbyElectorLock

Configure yarn-site.xml

<configuration>
	<!-- 指定MR走shuffle -->
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>

    <!-- 启用resourcemanager ha -->
    <property>
        <name>yarn.resourcemanager.ha.enabled</name>
        <value>true</value>
    </property>
 
    <!-- 声明两台resourcemanager的地址 -->
    <property>
        <name>yarn.resourcemanager.cluster-id</name>
        <value>cluster-yarn1</value>
    </property>

    <!--指定resourcemanager的逻辑列表-->
    <property>
        <name>yarn.resourcemanager.ha.rm-ids</name>
        <value>rm1,rm2,rm3</value>
    </property>
<!-- ========== rm1的配置 ========== -->
    <!-- 指定rm1的主机名 -->
    <property>
        <name>yarn.resourcemanager.hostname.rm1</name>
        <value>hadoop102</value>
    </property>

    <!-- 指定rm1的web端地址 -->
    <property>
        <name>yarn.resourcemanager.webapp.address.rm1</name>
        <value>hadoop102:8088</value>
    </property>

    <!-- 指定rm1的内部通信地址 -->
    <property>
        <name>yarn.resourcemanager.address.rm1</name>
        <value>hadoop102:8032</value>
    </property>

    <!-- 指定AM向rm1申请资源的地址 -->
    <property>
        <name>yarn.resourcemanager.scheduler.address.rm1</name>  
        <value>hadoop102:8030</value>
    </property>

    <!-- 指定供NM连接的地址 -->  
    <property>
    <name>yarn.resourcemanager.resource-tracker.address.rm1</name>
        <value>hadoop102:8031</value>
    </property>

<!-- ========== rm2的配置 ========== -->
    <!-- 指定rm2的主机名 -->
    <property>
        <name>yarn.resourcemanager.hostname.rm2</name>
        <value>hadoop103</value>
    </property>
    <property>
        <name>yarn.resourcemanager.webapp.address.rm2</name>
        <value>hadoop103:8088</value>
    </property>
    <property>
        <name>yarn.resourcemanager.address.rm2</name>
        <value>hadoop103:8032</value>
    </property>
    <property>
        <name>yarn.resourcemanager.scheduler.address.rm2</name>
        <value>hadoop103:8030</value>
    </property>

    <property>
<name>yarn.resourcemanager.resource-tracker.address.rm2</name>
        <value>hadoop103:8031</value>
    </property>

<!-- ========== rm3的配置 ========== -->
    <!-- 指定rm1的主机名 -->
    <property>
        <name>yarn.resourcemanager.hostname.rm3</name>
        <value>hadoop104</value>
    </property>
    <!-- 指定rm1的web端地址 -->
    <property>
        <name>yarn.resourcemanager.webapp.address.rm3</name>
        <value>hadoop104:8088</value>
    </property>
    <!-- 指定rm1的内部通信地址 -->
    <property>
        <name>yarn.resourcemanager.address.rm3</name>
        <value>hadoop104:8032</value>
    </property>
    <!-- 指定AM向rm1申请资源的地址 -->
    <property>
        <name>yarn.resourcemanager.scheduler.address.rm3</name>  
        <value>hadoop104:8030</value>
    </property>

    <!-- 指定供NM连接的地址 -->  
    <property>
    <name>yarn.resourcemanager.resource-tracker.address.rm3</name>
        <value>hadoop104:8031</value>
    </property>

    <!-- 指定zookeeper集群的地址 --> 
    <property>
        <name>yarn.resourcemanager.zk-address</name>
        <value>hadoop102:2181,hadoop103:2181,hadoop104:2181</value>
    </property>

    <!-- 启用自动恢复 --> 
    <property>
        <name>yarn.resourcemanager.recovery.enabled</name>
        <value>true</value>
    </property>
 
    <!-- 指定resourcemanager的状态信息存储在zookeeper集群 --> 
    <property>
        <name>yarn.resourcemanager.store.class</name>     <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>

    <!-- 环境变量的继承 -->
    <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>
    </property>
    
    <!--yarn单个容器允许分配的最大最小内存 -->
    <property>
        <name>yarn.scheduler.minimum-allocation-mb</name>
        <value>512</value>
    </property>
    <property>
        <name>yarn.scheduler.maximum-allocation-mb</name>
        <value>4096</value>
    </property>
    
    <!-- yarn容器允许管理的物理内存大小 -->
    <property>
        <name>yarn.nodemanager.resource.memory-mb</name>
        <value>4096</value>
    </property>
    
    <!-- 关闭yarn对物理内存和虚拟内存的限制检查 -->
    <property>
        <name>yarn.nodemanager.pmem-check-enabled</name>
        <value>true</value>
    </property>
    <property>
        <name>yarn.nodemanager.vmem-check-enabled</name>
        <value>false</value>
    </property>
    <!-- 开启日志聚集功能 -->
	<property>
	    <name>yarn.log-aggregation-enable</name>
	    <value>true</value>
	</property>
	
	<!-- 设置日志聚集服务器地址 -->
	<property>  
	    <name>yarn.log.server.url</name>  
	    <value>http://hadoop102:19888/jobhistory/logs</value>
	</property>
	
	<!-- 设置日志保留时间为7天 -->
	<property>
	    <name>yarn.log-aggregation.retain-seconds</name>
	    <value>604800</value>
	</property>
</configuration>

Start YARN:

#群启：
start-yarn.sh
#单点启动：
yarn-daemon.sh start resourcemanager

View service status

yarn rmadmin -getServiceState rm1

You can go to the zkCli.sh client to view the content of the ResourceManager election lock node.

zkCli.sh
[zk: localhost:2181(CONNECTED) 16] get -s /yarn-leader-election/cluster-yarn1/ActiveStandbyElectorLock

cluster-yarn1rm1
cZxid = 0x100000022
ctime = Tue Jul 14 17:06:44 CST 2020
mZxid = 0x100000022
mtime = Tue Jul 14 17:06:44 CST 2020
pZxid = 0x100000022
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x30000da33080005
dataLength = 20
numChildren = 0

[atguigu@hadoop102 hadoop]$ xcall jps
>>>>>>>>>>>>  hadoop102  <<<<<<<<<<<<
 18336 NameNode
 19312 JobHistoryServer
 13121 Kafka
 15331 ZooKeeperMain
 18902 DFSZKFailoverController
 18680 JournalNode
 18984 ResourceManager
 18456 DataNode
 19065 NodeManager
 10987 QuorumPeerMain
 20012 Jps
>>>>>>>>>>>>  hadoop103  <<<<<<<<<<<<
 13493 NodeManager
 14150 Jps
 12679 NameNode
 9064 Kafka
 13002 DFSZKFailoverController
 12763 DataNode
 7500 QuorumPeerMain
 12862 JournalNode
 13375 ResourceManager
>>>>>>>>>>>>  hadoop104  <<<<<<<<<<<<
 10320 ResourceManager
 10401 NodeManager
 6932 Kafka
 9896 NameNode
 10219 DFSZKFailoverController
 9980 DataNode
 10749 Jps
 10079 JournalNode
 5759 QuorumPeerMain

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Origin blog.csdn.net/Tonystark_lz/article/details/127195627
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