【大数据入门核心技术-Hadoop】（六）Hadoop3.2.1高可用集群搭建

秒速五厘米 2024-03-31 14:29 29阅读 0赞

**目录**

一、Hadoop部署的三种方式

1、Standalone mode（独立模式）

2、Pseudo-Distributed mode（伪分布式模式）

3、Cluster mode（集群模式）

二、准备工作

1、先完成zk高可用搭建

2、/etc/hosts增加内容

3、各台服务器分别创建目录

4、关闭防火墙和禁用swap交换分区

5、三台机器间免密

6、安装jdk

7、下载好hadoop安装包

三、高可用配置

1、配置core-site.xml

2、配置hdfs-site.xml

3、配置yarn-site.xml文件

4、配置mapred-site.xml

5、配置workers

6、修改配置hadoop-env.sh

四、分发文件

五、启动服务

六、查看服务

七、常见问题解决

1、高可用下提示Operation category READ is not supported in state standby

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

## 一、Hadoop部署的三种方式 ##

### 1、Standalone mode（独立模式） ###

独立模式又称为单机模式，仅1个机器运行1个java进程，主要用于调试。

### 2、Pseudo-Distributed mode（伪分布式模式） ###

伪分布模式也是在1个机器上运行HDFS的NameNode和DataNode、YARN的 ResourceManger和NodeManager，但分别启动单独的java进程，主要用于调试。

### 3、Cluster mode（集群模式） ###

单Namenode节点模式-高可用HA模式

集群模式主要用于生产环境部署。会使用N台主机组成一个Hadoop集群。这种部署模式下，主节点和从节点会分开部署在不同的机器上。

**本教程主要安装 多Namenode 节点 高可用集群模式**

## 二、准备工作 ##

### 1、先完成zk高可用搭建 ###

[【大数据入门核心技术-Zookeeper】（五）ZooKeeper集群搭建][-Zookeeper_ZooKeeper]

### 2、/etc/hosts增加内容 ###

> 172.30.1.56 hadoop001
> 
> 172.30.1.57 hadoop001
> 
> 172.30.1.58 hadoop001

### 3、各台服务器分别创建目录 ###

> mkdir -p /data/bigdata/hadoop/tmp
> 
> mkdir -p /data/bigdata/hadoop/var
> 
> mkdir -p /data/bigdata/hadoop/dfs/name
> 
> mkdir -p /data/bigdata/hadoop/dfs/data
> 
> mkdir -p /data/bigdata/hadoop/jn

### 4、关闭防火墙和禁用swap交换分区 ###

1)关闭防火墙和SeLinux

> systemctl stop firewalld && systemctl disable firewalld  
> setenforce 0  
> sed -i 's/SELINUX=.\*/SELINUX=disabled/g' /etc/sysconfig/selinux

2)禁用swap交换分区

> swapoff -a && sed -i 's/SELINUX=.\*/SELINUX=disabled/g' /etc/sysconfig/selinux

##  ##

### 5、三台机器间免密 ###

生成密钥

> ssh-keygen -t rsa

将密钥复制到其他机器

> ssh-copy-id slave1  
> ssh-copy-id slave2

##  ##

### 6、安装jdk ###

将jdk目录复制到/usr/local

vim /etc/profile

> export JAVA\_HOME=/usr/local/jdk1.8.0\_131  
> export JRE\_HOME=$\{JAVA\_HOME\}/jre  
> export CLASSPATH=.:$\{JAVA\_HOME\}/lib:$\{JRE\_HOME\}/lib  
> export PATH=$\{JAVA\_HOME\}/bin:$PATH

source /etc/profile

java -version

查看结果

java version "1.8.0\_131"  
Java(TM) SE Runtime Environment (build 1.8.0\_131-b11)  
Java HotSpot(TM) 64-Bit Server VM (build 25.131-b11, mixed mode)

### 7、下载好hadoop安装包 ###

下载地址

[Apache Hadoop][]

本次以hadoop3.2.1下载为例

> 解压  
> tar zxvf hadoop-3.2.1.tar.gz -C /usr/local
> 
> vim /etc/profile
> 
> export HADOOP\_HOME=/usr/local/hadoop-3.2.1  
> export PATH=$PATH:$HADOOP\_HOME/sbin:$HADOOP\_HOME/bin
> 
> source /etc/profile

## 三、高可用配置 ##

### 1、**配置core-site.xml** ###

<configuration>
        
        <property>
            <name>fs.defaultFS</name>
            <value>hdfs://mycluster</value>
        </property>
        
        <property>
            <name>hadoop.tmp.dir</name>
            <value>/data/bigdata/hadoop/tmp</value>
        </property>
        
        <property>
            <name>ha.zookeeper.quorum</name>
            <value>hadoop101:2181,hadoop102:2181,hadoop103:2181</value>
        </property>
        
        <property>
            <name>ipc.client.connect.max.retries</name>
            <value>20</value>
        </property>
        
        <property>
            <name>ipc.client.connect.retry.interval</name>
            <value>5000</value>
        </property>
    </configuration>

### 2、**配置hdfs-site.xml** ###

<configuration>
        <property>
            <name>dfs.namenode.name.dir</name>
            <value>/data/bigdata/hadoop/dfs/name</value>
            <description>datanode 上存储 hdfs 名字空间元数据</description>
        </property>
        <property>
            <name>dfs.datanode.data.dir</name>
            <value>/data/bigdata/hadoop/dfs/data</value>
            <description>datanode 上数据块的物理存储位置</description>
        </property>
        <property>
            <name>dfs.replication</name>
            <value>2</value>
            <description>副本个数，默认配置是 3，应小于 datanode 机器数量</description>
        </property>
        <property>
            <name>dfs.webhdfs.enabled</name>
            <value>true</value>
        </property>
        <property>
            <name>dfs.permissions.enabled</name>
            <value>false</value>
        </property>
    	
    	
        
        <property>
            <name>dfs.journalnode.edits.dir</name>
            <value>/data/bigdata/hadoop/jn</value>
        </property>
        
        <property>
            <name>dfs.nameservices</name>
            <value>mycluster</value>
        </property>
        
        <property>
            <name>dfs.ha.namenodes.mycluster</name>
            <value>nn1,nn2,nn3</value>
        </property>
        
        <property>
            <name>dfs.namenode.rpc-address.mycluster.nn1</name>
            <value>hadoop101:8020</value>
        </property>
        <property>
            <name>dfs.namenode.rpc-address.mycluster.nn2</name>
            <value>hadoop102:8020</value>
        </property>
    	<property>
            <name>dfs.namenode.rpc-address.mycluster.nn3</name>
            <value>hadoop103:8020</value>
        </property>
    	
        
        <property>
            <name>dfs.namenode.http-address.mycluster.nn1</name>
            <value>hadoop101:9870</value>
        </property>
        <property>
            <name>dfs.namenode.http-address.mycluster.nn2</name>
            <value>hadoop102:9870</value>
        </property>
    	<property>
            <name>dfs.namenode.http-address.mycluster.nn3</name>
            <value>hadoop103:9870</value>
        </property>
    	
        
        <property>
            <name>dfs.namenode.shared.edits.dir</name>
            <value>qjournal://hadoop101:8485;hadoop102:8485;hadoop103:8485/mycluster</value>
        </property>
        
        <property>
            <name>dfs.client.failover.proxy.provider.mycluster</name>
            <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
        </property>
        
        <property>
            <name>dfs.ha.fencing.methods</name>
            <value>sshfence</value>
        </property>
        
        <property>
            <name>dfs.ha.fencing.ssh.private-key-files</name>
            <value>/root/.ssh/id_rsa</value>
        </property>
        
        <property>
            <name>dfs.ha.automatic-failover.enabled</name>
            <value>true</value>
        </property>
    </configuration>

### 3、配置yarn-site.xml文件 ###

<configuration>
        <property>
            <name>yarn.nodemanager.aux-services</name>
            <value>mapreduce_shuffle</value>
        </property>
    	
        
        <property>
            <name>yarn.resourcemanager.ha.enabled</name>
            <value>true</value>
        </property>
    	
        
        <property>
            <name>yarn.resourcemanager.cluster-id</name>
            <value>cluster-yarn1</value>
        </property>
    	
        
        <property>
            <name>yarn.resourcemanager.ha.rm-ids</name>
            <value>rm1,rm2,rm3</value>
        </property>
    	
        
        
        <property>
            <name>yarn.resourcemanager.hostname.rm1</name>
            <value>hadoop101</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.webapp.address.rm1</name>
            <value>hadoop101:8088</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.address.rm1</name>
            <value>hadoop101:8032</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.scheduler.address.rm1</name>
            <value>hadoop101:8030</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.resource-tracker.address.rm1</name>
            <value>hadoop101:8031</value>
        </property>
    	
        
        
        <property>
            <name>yarn.resourcemanager.hostname.rm2</name>
            <value>hadoop102</value>
        </property>
        <property>
            <name>yarn.resourcemanager.webapp.address.rm2</name>
            <value>hadoop102:8088</value>
        </property>
        <property>
            <name>yarn.resourcemanager.address.rm2</name>
            <value>hadoop102:8032</value>
        </property>
        <property>
            <name>yarn.resourcemanager.scheduler.address.rm2</name>
            <value>hadoop102:8030</value>
        </property>
        <property>
            <name>yarn.resourcemanager.resource-tracker.address.rm2</name>
            <value>hadoop102:8031</value>
        </property>
    	
        
        
        <property>
            <name>yarn.resourcemanager.hostname.rm3</name>
            <value>hadoop103</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.webapp.address.rm3</name>
            <value>hadoop103:8088</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.address.rm3</name>
            <value>hadoop103:8032</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.scheduler.address.rm3</name>
            <value>hadoop103:8030</value>
        </property>
        
        <property>
            <name>yarn.resourcemanager.resource-tracker.address.rm3</name>
            <value>hadoop103:8031</value>
        </property>
    	
        
        <property>
            <name>yarn.resourcemanager.zk-address</name>
            <value>hadoop101:2181,hadoop102:2181,hadoop103:2181</value>
        </property>
    	
        
        <property>
            <name>yarn.resourcemanager.recovery.enabled</name>
            <value>true</value>
        </property>
    	
        
        <property>
            <name>yarn.resourcemanager.store.class</name>
            <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateSt ore</value>
        </property>
    	
        
        <property>
            <name>yarn.nodemanager.env-whitelist</name>
            <value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLAS
    SPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_MAPRED_HOME</value>
        </property>
    
        
        <property>
            <name>yarn.resourcemanager.zk-max-znode-size.bytes</name>
            <value>104857600</value>
        </property>
     
        
        <property>
            <name>yarn.resourcemanager.store.class</name>
       <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
        </property>
    </configuration>

### 4、配置mapred-site.xml ###

<configuration>
        
        <property>
            <name>mapreduce.framework.name</name>
            <value>yarn</value>
        </property>
        
        <property>
            <name>mapreduce.jobhistory.address</name>
            <value>hadoop101:10020</value>
        </property>
        
        <property>
            <name>mapreduce.jobhistory.webapp.address</name>
            <value>hadoop101:19888</value>
        </property>
    </configuration>

### 5、配置workers ###

hadoop101
    hadoop102
    hadoop103

### 6、修改配置**hadoop-env.sh** ###

export JAVA_HOME=/usr/local/jdk1.8.0_131
    export HADOOP_HOME=/usr/local/hadoop-2.3.1
    
    
    
    export HDFS_NAMENODE_USER=root
    export HDFS_DATANODE_USER=root
    export HDFS_JOURNALNODE_USER=root
    export HDFS_ZKFC_USER=root
    export HDFS_SECONDARYNAMENODE_USER=root
    export YARN_RESOURCEMANAGER_USER=root
    export YARN_NODEMANAGER_USER=root

## 四、分发文件 ##

> scp -r /usr/local/hadoop-3.2.1 hadoop102:/usr/local
> 
> scp -r /usr/local/hadoop-3.2.1 hadoop103:/usr/local

## 五、启动服务 ##

在各个 JournalNode 节点上（每台虚拟机），输入以下命令启动 journalnode 服务

**hdfs --daemon start journalnode**

node1上格式化namenode  
**hdfs namenode -format**

node1上启动namenode  
**hdfs --daemon start namenode**

在 \[nn2,nn3\] 上，同步 nn1 的元数据信息  
**hdfs namenode -bootstrapStandby**

在node1节点上格式化ZKFC  
**hdfs zkfc -formatZK**

node1节点上启动HDFS和Yarn  
**start-dfs.sh  
start-yarn.sh**

到此hadoop高可用集群搭建就完成了。

## 六、查看服务 ##

> jps

![b0a485c1c4a74dc282b2581718e766f0.png][]

![3388cb77502e4369862a138830059b00.png][]

![1fd49f420f6d46999bea1d140782aa63.png][]

查看yarn服务状态

> yarn rmadmin -getAllServiceState
> 
> yarn rmadmin -getServiceState rm1

zkCli.sh 客户端查看 ResourceManager 选举锁节点内容：

> get -s /yarn-leader-election/cluster-yarn1/ActiveStandbyElectorLock

## 七、常见问题解决 ##

### 1、高可用下提示Operation category READ is not supported in state standby ###

hadoop fs -ls /

总提示

hadoop fs -ls /

2022-12-06 02:02:22,062 INFO retry.RetryInvocationHandler: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.ipc.StandbyException): Operation category READ is not supported in state standby. Visit [https://s.apache.org/sbnn-error][https_s.apache.org_sbnn-error]

at org.apache.hadoop.hdfs.server.namenode.ha.StandbyState.checkOperation(StandbyState.java:98)

at org.apache.hadoop.hdfs.server.namenode.NameNode$NameNodeHAContext.checkOperation(NameNode.java:2021)

at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.checkOperation(FSNamesystem.java:1449)

at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getFileInfo(FSNamesystem.java:3183)

at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.getFileInfo(NameNodeRpcServer.java:1173)

**解决办法：**

手动将活跃的namenode切换到第一台

hdfs haadmin -failover nn3 nn1

[-Zookeeper_ZooKeeper]: https://blog.csdn.net/forest_long/article/details/128155528
[Apache Hadoop]: https://hadoop.apache.org/releases.html
[b0a485c1c4a74dc282b2581718e766f0.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/31/68b9d16f5e3744f080f9b564d0c368b3.png
[3388cb77502e4369862a138830059b00.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/31/7a486a0dd5b24e4caf9310a49b579a73.png
[1fd49f420f6d46999bea1d140782aa63.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/31/9de51d98892541038930a6c3e732b92e.png
[https_s.apache.org_sbnn-error]: https://s.apache.org/sbnn-error