2.1.6 hadoop体系之离线计算-hdfs分布式文件系统-全分布式安装（2）

本是古典何须时尚 2022-12-11 09:29 141阅读 0赞

**目录**

1.集群的规划

2.上传并解压

3.修改配置文件

3.1 core-site.xml

3.2 hadoop-env.sh

3.3 hdfs-site.xml

3.4 mapred-site.xml

3.5 yarn-site.xml

3.6 worker

3.7 创建数据和临时文件夹

4.分发安装包到其他机器

5.为每个节点配置环境变量

6.格式化HDFS

7.启动集群

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

# 1.集群的规划 #

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L1N1eWViaXViaXU_size_16_color_FFFFFF_t_70][]

我们将分为5个部分介绍（与上篇全分布式安装，配置文件不一样）：1. 上传并解压 2. 修改配置文件 3. 分发安装包 4. 格式化HDFS 5. 启动集群

# 2.上传并解压 #

*  1. 上传压缩包到/export/software目录
 *  2. cd /export/software
 *  3. tar xzvf hadoop-3.1.1.tar.gz -C ../servers

# 3.修改配置文件 #

## 3.1 core-site.xml ##

<configuration>
        <property>
    		<name>fs.defaultFS</name>
    		<value>hdfs://node01:8020</value>
    	</property>
    	
    	<property>
    		<name>hadoop.tmp.dir</name>
    		<value>/export/servers/hadoop-3.1.1/datas/tmp</value>
    	</property>
        
    	<property>
    		<name>io.file.buffer.size</name>
    		<value>8192</value>
    	</property>
        
    	<property>
    		<name>fs.trash.interval</name>
    		<value>10080</value>
    	</property>
    </configuration>

## 3.2 hadoop-env.sh ##

export JAVA_HOME=/export/servers/jdk1.8.0_141
    export HDFS_NAMENODE_USER="root"
    export HDFS_DATANODE_USER="root"
    export HDFS_SECONDARYNAMENODE_USER="root"
    export YARN_RESOURCEMANAGER_USER="root"
    export YARN_NODEMANAGER_USER="root"

## 3.3 hdfs-site.xml ##

<configuration>
    	<property>
    		<name>dfs.namenode.name.dir</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/namenode/namenodedatas</value>
    	</property>
    	<property>
    		<name>dfs.blocksize</name>
    		<value>134217728</value>
    	</property>
    	<property>
    		<name>dfs.namenode.handler.count</name>
    		<value>10</value>
    	</property>
    	<property>
    		<name>dfs.datanode.data.dir</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/datanode/datanodeDatas</value>
    	</property>
    	<property>
    		<name>dfs.namenode.http-address</name>
    		<value>node01:50070</value>
    	</property>
    	<property>
    		<name>dfs.replication</name>
    		<value>3</value>
    	</property>
    	<property>
    		<name>dfs.permissions.enabled</name>
    		<value>false</value>
    	</property>
    	<property>
    		<name>dfs.namenode.checkpoint.edits.dir</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/dfs/nn/snn/edits</value>
    	</property>
    	<property>
    		<name>dfs.namenode.secondary.http-address</name>
    		<value>node01.hadoop.com:50090</value>
    	</property>
    	<property>
    		<name>dfs.namenode.edits.dir</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/dfs/nn/edits</value>
    	</property>
    	<property>
    		<name>dfs.namenode.checkpoint.dir</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/dfs/snn/name</value>
    	</property>
    </configuration>

查看了下官方文档，默认的绑定IP就是在127.0.0.1上，当然，这应该也是出于安全性的考虑吧。于是，修改默认参数：  
在hdfs-site.xml中，更改开放端口的绑定IP：（hadoop3默认端口已经改成了9870）

<property>
      <name>dfs.http.address</name>
      <value>0.0.0.0:9870</value>
    </property>

*  将绑定IP改为0.0.0.0，而不是本地回环IP，这样，就能够实现外网访问本机的9870端口了。
 *  node01.hadoop.com 这个需要添加到 /etc/hosts 中间
 *  ![20201007180818352.png][]

## 3.4 mapred-site.xml ##

<configuration>
    	<property>
    		<name>mapreduce.framework.name</name>
    		<value>yarn</value>
    	</property>
    	<property>
    		<name>mapreduce.map.memory.mb</name>
    		<value>1024</value>
    	</property>
    	<property>
    		<name>mapreduce.map.java.opts</name>
    		<value>-Xmx512M</value>
    	</property>
    	<property>
    		<name>mapreduce.reduce.memory.mb</name>
    		<value>1024</value>
    	</property>
    	<property>
    		<name>mapreduce.reduce.java.opts</name>
    		<value>-Xmx512M</value>
    	</property>
    	<property>
    		<name>mapreduce.task.io.sort.mb</name>
    		<value>256</value>
    	</property>
    	<property>
    		<name>mapreduce.task.io.sort.factor</name>
    		<value>100</value>
    	</property>
    	<property>
    		<name>mapreduce.reduce.shuffle.parallelcopies</name>
    		<value>25</value>
    	</property>
    	<property>
    		<name>mapreduce.jobhistory.address</name>
    		<value>node01.hadoop.com:10020</value>
    	</property>
    	<property>
    		<name>mapreduce.jobhistory.webapp.address</name>
    		<value>node01.hadoop.com:19888</value>
    	</property>
    	<property>
    		<name>mapreduce.jobhistory.intermediate-done-dir</name>
    		<value>/export/servers/hadoop-3.1.1/datas/jobhsitory/intermediateDoneDatas</value>
    	</property>
    	<property>
    		<name>mapreduce.jobhistory.done-dir</name>
    		<value>/export/servers/hadoop-3.1.1/datas/jobhsitory/DoneDatas</value>
    	</property>
    	<property>
    	  <name>yarn.app.mapreduce.am.env</name>
    	  <value>HADOOP_MAPRED_HOME=/export/servers/hadoop-3.1.1</value>
    	</property>
    	<property>
    	  <name>mapreduce.map.env</name>
    	  <value>HADOOP_MAPRED_HOME=/export/servers/hadoop-3.1.1/</value>
    	</property>
    	<property>
    	  <name>mapreduce.reduce.env</name>
    	  <value>HADOOP_MAPRED_HOME=/export/servers/hadoop-3.1.1</value>
    	</property>
    </configuration>

## 3.5 yarn-site.xml ##

<configuration>
    	<property>
    		<name>dfs.namenode.handler.count</name>
    		<value>100</value>
    	</property>
    	<property>
    		<name>yarn.log-aggregation-enable</name>
    		<value>true</value>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.address</name>
    		<value>node01:8032</value>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.scheduler.address</name>
    		<value>node01:8030</value>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.resource-tracker.address</name>
    		<value>node01:8031</value>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.admin.address</name>
    		<value>node01:8033</value>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.webapp.address</name>
    		<value>node01:8088</value>
    	</property>
    	<property>
    		<name>yarn.resourcemanager.hostname</name>
    		<value>node01</value>
    	</property>
    	<property>
    		<name>yarn.scheduler.minimum-allocation-mb</name>
    		<value>1024</value>
    	</property>
    	<property>
    		<name>yarn.scheduler.maximum-allocation-mb</name>
    		<value>2048</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.vmem-pmem-ratio</name>
    		<value>2.1</value>
    	</property>
    	
    	<property>
    		<name>yarn.nodemanager.vmem-check-enabled</name>
    		<value>false</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.resource.memory-mb</name>
    		<value>1024</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.resource.detect-hardware-capabilities</name>
    		<value>true</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.local-dirs</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerDatas</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.log-dirs</name>
    		<value>file:///export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerLogs</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.log.retain-seconds</name>
    		<value>10800</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.remote-app-log-dir</name>
    		<value>/export/servers/hadoop-3.1.1/datas/remoteAppLog/remoteAppLogs</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.remote-app-log-dir-suffix</name>
    		<value>logs</value>
    	</property>
    	<property>
    		<name>yarn.nodemanager.aux-services</name>
    		<value>mapreduce_shuffle</value>
    	</property>
    	<property>
    		<name>yarn.log-aggregation.retain-seconds</name>
    		<value>18144000</value>
    	</property>
    	<property>
    		<name>yarn.log-aggregation.retain-check-interval-seconds</name>
    		<value>86400</value>
    	</property>
    	
    	<property>
            <name>yarn.app.mapreduce.am.resource.mb</name>
            <value>1024</value>
    	</property>
    </configuration>

## 3.6 worker ##

node01
    node02
    node03

## 3.7 创建数据和临时文件夹 ##

mkdir -p /export/servers/hadoop-3.1.1/datas/tmp
    mkdir -p /export/servers/hadoop-3.1.1/datas/dfs/nn/snn/edits
    mkdir -p /export/servers/hadoop-3.1.1/datas/namenode/namenodedatas
    mkdir -p /export/servers/hadoop-3.1.1/datas/datanode/datanodeDatas
    mkdir -p /export/servers/hadoop-3.1.1/datas/dfs/nn/edits
    mkdir -p /export/servers/hadoop-3.1.1/datas/dfs/snn/name
    mkdir -p /export/servers/hadoop-3.1.1/datas/jobhsitory/intermediateDoneDatas
    mkdir -p /export/servers/hadoop-3.1.1/datas/jobhsitory/DoneDatas
    mkdir -p /export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerDatas
    mkdir -p /export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerLogs
    mkdir -p /export/servers/hadoop-3.1.1/datas/remoteAppLog/remoteAppLogs

# 4.分发安装包到其他机器 #

cd /export/servers
    scp -r hadoop-3.1.1/ node02:$PWD
    scp -r hadoop-3.1.1/ node03:$PWD

# 5.为每个节点配置环境变量 #

vi /etc/profile
    export HADOOP_HOME=/export/servers/hadoop-3.1.1/
    export PATH=:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH

激活每个节点的环境变量：source /etc/profile

# 6.格式化HDFS #

为什么要格式化HDFS

*  HDFS需要一个格式化的过程来创建存放元数据(image, editlog)的目录，格式化一次就可以了，始终保持，所有集群中配置文件是一样的，可能会导致某一个节点起不来

bin/hdfs namenode -format

# 7.启动集群 #

# 会登录进所有的worker启动相关进行, 也可以手动进行, 但是没必要
    /export/servers/hadoop-3.1.1/sbin/start-dfs.sh
    /export/servers/hadoop-3.1.1/sbin/start-yarn.sh
    mapred --daemon start historyserver

此时便可以通过如下三个URL访问Hadoop了

*  HDFS: `http://192.168.174.100:50070/dfshealth.html#tab-overview`
 *  Yarn: `http://192.168.174.100:8088/cluster`

当访问不到页面的时候：

需要关闭防火墙，selinux设置为disabled。  
注意不同CentOs版本关闭防火墙的指令不同。

systemctl stop firewalld.service

关闭防火墙；

禁止自动启动就用

systemctl  disable  firewalld.service

想要关闭的话：

/export/servers/hadoop-3.1.1/sbin/stop-dfs.sh  
/export/servers/hadoop-3.1.1/sbin/stop-yarn.sh

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[20201007180818352.png]: /images/20221123/4ee40baf11bb44a0bd6dbf9d4a9a0b6f.png