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Hadoop集群搭建详细步骤(只有JDK和Hadoop)

目录

一、模板虚拟机环境准备

1.新建一台虚拟机hadoop100，并且配置好网络

虚拟机参数参考：

新建虚拟机参考博文《CentOS7中新建虚拟机详细步骤》

注意：1.选择桌面版安装

** 2.设置普通用户**

虚拟机网络配置参考博文《Linux网关设置》

3.安装 epel-release

[root@hadoop100 ~]# yum install -y epel-release

4.其他工具

如果你是最小化安装要执行以下命令，桌面版不需要

[root@hadoop100 ~]# yum install -y net-tools

[root@hadoop100 ~]# yum install -y vim

5. 配置普通用户具有root权限，方便后期加sudo执行root权限的命令

[root@hadoop100 ~]# vim /etc/sudoers

在%wheel下面添加命令如下图：

6.删除/opt/目录下的所有文件

[root@hadoop100 ~]# rm -rf /opt/*

7.在/opt/目录下创建文件夹，并修改所属主和所属组

[root@hadoop100 ~]# mkdir /opt/module
[root@hadoop100 ~]# mkdir /opt/software
[root@hadoop100 ~]# chown atguigu:atguigu /opt/module 
[root@hadoop100 ~]# chown atguigu:atguigu /opt/software

8. 卸载虚拟机自带的JDK

[root@hadoop100 ~]# rpm -qa | grep -i java | xargs -n1 rpm -e --nodeps

# 检查是否删除干净
[root@hadoop100 ~]# rpm -qa | grep -i java

rpm -qa：查询所安装的所有 rpm 软件包

grep -i：忽略大小写

xargs -n1：表示每次只传递一个参数

rpm -e –nodeps：强制卸载软件

9.重启虚拟机

[root@hadoop100 ~]# reboot

二、克隆虚拟机

1.关闭模板虚拟机

2.克隆三台虚拟机

模板虚拟机右键→管理→克隆

再克隆两台虚拟机hadoop103和hadoop104

3.修改三台克隆机的ip和主机名后重启

(1)开启这四台虚拟机

(2)修改ip地址

[root@hadoop100 ~]# vim /etc/sysconfig/network-scripts/ifcfg-ens33

(3)修改主机名

[root@hadoop100 ~]# vim /etc/hostname

(4)重启hadoop102

(5)关闭hadoop102的防火墙

[root@hadoop102 ~]# systemctl stop firewalld
[root@hadoop102 ~]# systemctl disable firewalld.service
[root@hadoop102 ~]# systemctl status firewalld
● firewalld.service - firewalld - dynamic firewall daemon
   Loaded: loaded (/usr/lib/systemd/system/firewalld.service; disabled; vendor preset: enabled)
   Active: inactive (dead)
     Docs: man:firewalld(1)

(6)开启network，测试网络连接

[root@hadoop102 network-scripts]# systemctl stop NetworkManager
[root@hadoop102 network-scripts]# systemctl disable NetworkManager
Removed symlink /etc/systemd/system/multi-user.target.wants/NetworkManager.service.
Removed symlink /etc/systemd/system/dbus-org.freedesktop.NetworkManager.service.
Removed symlink /etc/systemd/system/dbus-org.freedesktop.nm-dispatcher.service.
[root@hadoop102 network-scripts]# systemctl restart network
[root@hadoop102 network-scripts]# ping www.baidu.com
[root@hadoop102 network-scripts]# hostname
hadoop102
[root@hadoop102 network-scripts]# ifconfig

[root@hadoop102 network-scripts]# systemctl stop NetworkManager
[root@hadoop102 network-scripts]# systemctl disable NetworkManager
Removed symlink /etc/systemd/system/multi-user.target.wants/NetworkManager.service.
Removed symlink /etc/systemd/system/dbus-org.freedesktop.NetworkManager.service.
Removed symlink /etc/systemd/system/dbus-org.freedesktop.nm-dispatcher.service.
[root@hadoop102 network-scripts]# systemctl restart network
[root@hadoop102 network-scripts]# ping www.baidu.com
PING www.a.shifen.com (180.101.50.242) 56(84) bytes of data.
64 bytes from 180.101.50.242 (180.101.50.242): icmp_seq=1 ttl=128 time=2.99 ms
64 bytes from 180.101.50.242 (180.101.50.242): icmp_seq=2 ttl=128 time=3.26 ms
^C
--- www.a.shifen.com ping statistics ---
2 packets transmitted, 2 received, 0% packet loss, time 1001ms
rtt min/avg/max/mdev = 2.999/3.134/3.269/0.135 ms
[root@hadoop102 network-scripts]# hostname
hadoop102
[root@hadoop102 network-scripts]# ifconfig
ens33: flags=4163<UP,BROADCAST,RUNNING,MULTICAST>  mtu 1500
        inet 192.168.180.152  netmask 255.255.255.0  broadcast 192.168.180.255
        inet6 fe80::20c:29ff:fec5:2a4e  prefixlen 64  scopeid 0x20<link>
        ether 00:0c:29:c5:2a:4e  txqueuelen 1000  (Ethernet)
        RX packets 5  bytes 524 (524.0 B)
        RX errors 0  dropped 0  overruns 0  frame 0
        TX packets 30  bytes 4235 (4.1 KiB)
        TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0

lo: flags=73<UP,LOOPBACK,RUNNING>  mtu 65536
        inet 127.0.0.1  netmask 255.0.0.0
        inet6 ::1  prefixlen 128  scopeid 0x10<host>
        loop  txqueuelen 1  (Local Loopback)
        RX packets 0  bytes 0 (0.0 B)
        RX errors 0  dropped 0  overruns 0  frame 0
        TX packets 0  bytes 0 (0.0 B)
        TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0

virbr0: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
        inet 192.168.122.1  netmask 255.255.255.0  broadcast 192.168.122.255
        ether 52:54:00:55:4e:cf  txqueuelen 1000  (Ethernet)
        RX packets 0  bytes 0 (0.0 B)
        RX errors 0  dropped 0  overruns 0  frame 0
        TX packets 0  bytes 0 (0.0 B)
        TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0

(7)另外两台虚拟机hadoop103和hadoop104重复(1)~(6)操作

(8)《关于Job for network.service failed because the control process exited with error code.》

4.Windows主机host文件下配置集群的ip地址映射

进入 C:\Windows\System32\drivers\etc 路径，添加下面的ip映射

三、hadoop102安装JDK

1.检查hadoop102是否有JDK

注意：安装 JDK 前，一定确保提前删除了虚拟机自带的 JDK。参考一、8

[lxm@hadoop102 ~]$ rpm -qa | grep -i java | xargs -n1 rpm -e --nodeps
rpm：未给出要擦除的软件包

2.xftp上传JDK8压缩包至/opt/software目录下

3.解压JDK至/opt/software目录下

[lxm@hadoop102 module]$ tar -zxvf /opt/software/jdk-8u321-linux-x64.tar.gz -C /opt/module/
[lxm@hadoop102 module]$ ll
总用量 0
drwxr-xr-x. 8 lxm lxm 273 12月 16 2021 jdk1.8.0_321

4.配置JDK环境变量

[lxm@hadoop102 module]$ sudo vim /etc/profile.d/my_env.sh

# JAVA_HOME
export JAVA_HOME=/opt/module/jdk1.8.0_321
export PATH=$PATH:$JAVA_HOME/bin

5.重启环境变量并测试JDK是否安装成功

[lxm@hadoop102 module]$ source /etc/profile
[lxm@hadoop102 module]$ javac
[lxm@hadoop102 module]$ java -version
java version "1.8.0_321"
Java(TM) SE Runtime Environment (build 1.8.0_321-b07)
Java HotSpot(TM) 64-Bit Server VM (build 25.321-b07, mixed mode)

四、hadoop102安装Hadoop

1.xftp上传Hadoop压缩包至/opt/software目录下

2.解压Hadoop压缩包至/opt/module

[lxm@hadoop102 module]$ sudo vim /etc/profile.d/my_env.sh

# HADOOP_HOME
export HADOOP_HOME=/opt/module/hadoop-3.1.3
export PATH=$PATH:$HADOOP_HOME/bin
export PATH=$PATH:$HADOOP_HOME/sbin

3.重启环境变量并检查Hadoop是否配置成功

[lxm@hadoop102 module]$ source /etc/profile
[lxm@hadoop102 module]$ hadoop version
Hadoop 3.1.3
Source code repository https://gitbox.apache.org/repos/asf/hadoop.git -r ba631c436b806728f8ec2f54ab1e289526c90579
Compiled by ztang on 2019-09-12T02:47Z
Compiled with protoc 2.5.0
From source with checksum ec785077c385118ac91aadde5ec9799
This command was run using /opt/module/hadoop-3.1.3/share/hadoop/common/hadoop-common-3.1.3.jar

五、测试Hadoop官方WordCount

1.在/opt/module/hadoop-3.1.3目录下新建wcinput文件夹

[lxm@hadoop102 hadoop-3.1.3]$ mkdir wcinput

2.wcinput文件夹下新建word.txt文件并输入内容

[lxm@hadoop102 hadoop-3.1.3]$ cd ./wcinput/
[lxm@hadoop102 wcinput]$ vim word.txt

hello world
hello java
hello hadoop

3.执行wordcount命令

[lxm@hadoop102 wcinput]$ hadoop jar /opt/module/hadoop-3.1.3/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.1.3.jar wordcount /opt/module/hadoop-3.1.3/wcinput/ /opt/module/hadoop-3.1.3/wcoutput/

4.检查结果

[lxm@hadoop102 hadoop-3.1.3]$ cat ./wcoutput/part-r-00000 
hadoop    1
hello    3
java    1
world    1

注意：如果第二次提交wordcount命令就要删除/opt/module/hadoop-3.1.3目录下的wcoutput文件。

六、SSH免密登录

免密登录就是从一台虚拟机登录另一台虚拟机不需要输入密码

1.在hadoop102上登录hadoop103

[lxm@hadoop102 ~]$ ssh hadoop103

2.输入yes

Are you sure you want to continue connecting (yes/no)? yes

3.输入hadoop103密码

lxm@hadoop103's password:

4.退出登录

[lxm@hadoop103 ~]# exit
登出
Connection to hadoop103 closed.
[lxm@hadoop102 ~]

5.查看/home目录下生成的ssh文件

[lxm@hadoop102 ~]$ ll -al
[lxm@hadoop102 ~]$ cd .ssh

6.生成私钥和公钥

[lxm@hadoop102 .ssh]$ ssh-keygen -t rsa -P ''

回车

[lxm@hadoop102 .ssh]$ ll
-rw-------. 1 lxm lxm 1675 2月  12 11:10 id_rsa
-rw-r--r--. 1 lxm lxm  395 2月  12 11:10 id_rsa.pub
-rw-r--r--. 1 lxm lxm  561 2月  12 11:11 known_hosts

7.将公钥拷贝到要免密登录的目标机器上

[lxm@hadoop102 .ssh]$ ssh-copy-id hadoop102
/usr/bin/ssh-copy-id: INFO: Source of key(s) to be installed: "/home/lxm/.ssh/id_rsa.pub"
The authenticity of host 'hadoop102 (192.168.180.152)' can't be established.
ECDSA key fingerprint is SHA256:GFkoioPRq02rdq9bMm4L+OWi08ZceOxyBAaKGj4pObQ.
ECDSA key fingerprint is MD5:8f:f8:55:6a:f6:ba:13:a4:81:3e:04:d2:3c:07:1c:a5.
Are you sure you want to continue connecting (yes/no)? yes
/usr/bin/ssh-copy-id: INFO: attempting to log in with the new key(s), to filter out any that are already installed
/usr/bin/ssh-copy-id: INFO: 1 key(s) remain to be installed -- if you are prompted now it is to install the new keys
lxm@hadoop102's password: 

Number of key(s) added: 1

Now try logging into the machine, with:   "ssh 'hadoop102'"
and check to make sure that only the key(s) you wanted were added.

[lxm@hadoop102 .ssh]$ ssh-copy-id hadoop103
[lxm@hadoop102 .ssh]$ ssh-copy-id hadoop104

8.hadoop102尝试免密登录102、103、104三台机器

[lxm@hadoop102 .ssh]$ ssh hadoop102
Last login: Sun Feb 12 10:11:45 2023 from 192.168.180.1
[lxm@hadoop102 ~]$ exit
登出
Connection to hadoop102 closed.
[lxm@hadoop102 .ssh]$ ssh hadoop103
Last login: Sun Feb 12 11:10:15 2023 from 192.168.180.152
[lxm@hadoop103 ~]$ exit
登出
Connection to hadoop103 closed.
[lxm@hadoop102 .ssh]$ ssh hadoop104
Last login: Sun Feb 12 09:57:31 2023 from 192.168.180.1
[lxm@hadoop104 ~]$ exit
登出
Connection to hadoop104 closed.

9.在hadoop103和hadoop104重复步骤6~8

七、配置集群

1.集群部署规划

注意：

  • NameNode和SecondaryNameNode不要安装在同一台服务器；
  • ResourceManager也很消耗内存，不要和NameNode、SecondaryNameNode配置在同一台机器上。

2.进入/opt/module/hadoop-3.1.3/etc/hadoop/目录下

[lxm@hadoop102 hadoop]$ pwd
/opt/module/hadoop-3.1.3/etc/hadoop

在下面四个xml文件的<configuration></configuration>标签内插入以下内容，注意根据你的主机名更改对应的localhost

3.配置core-site.xml

<!-- 指定 NameNode 的地址 -->
 <property>
 <name>fs.defaultFS</name>
 <value>hdfs://hadoop102:8020</value>
 </property>
 <!-- 指定 hadoop 数据的存储目录 -->
 <property>
 <name>hadoop.tmp.dir</name>
 <value>/opt/module/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>

4.配置hdfs-site.xml

<!-- nn web 端访问地址-->
<property>
 <name>dfs.namenode.http-address</name>
 <value>hadoop102:9870</value>
 </property>
<!-- 2nn web 端访问地址-->
 <property>
 <name>dfs.namenode.secondary.http-address</name>
 <value>hadoop104:9868</value>
 </property>

5.配置mapred-site.xml

<!-- 指定 MapReduce 程序运行在 Yarn 上 -->
 <property>
 <name>mapreduce.framework.name</name>
 <value>yarn</value>
 </property>

6.配置yarn-site.xml

<!-- 指定 MR 走 shuffle -->
 <property>
 <name>yarn.nodemanager.aux-services</name>
 <value>mapreduce_shuffle</value>
 </property>
 <!-- 指定 ResourceManager 的地址-->
 <property>
 <name>yarn.resourcemanager.hostname</name>
 <value>hadoop103</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>

八、xsync分发脚本

1.编写一个xsync脚本，期望脚本全局调用

脚本放在声明了全局环境变量的路径

2. 在根目录下创建bin文件夹

[lxm@hadoop102 ~]$ cd /home/lxm
[lxm@hadoop102 ~]$ mkdir bin
[lxm@hadoop102 ~]$ cd bin
[lxm@hadoop102 ~]$ vim xsync

3.xsync脚本内容，注意主机名

#!/bin/bash
#1. 判断参数个数
if [ $# -lt 1 ]
then
 echo Not Enough Arguement!
 exit;
fi
#2. 遍历集群所有机器
for host in hadoop102 hadoop103 hadoop104
do
 echo ==================== $host ====================
 #3. 遍历所有目录，挨个发送
 for file in $@
 do
 #4. 判断文件是否存在
 if [ -e $file ]
 then
 #5. 获取父目录
 pdir=$(cd -P $(dirname $file); pwd)
 #6. 获取当前文件的名称
 fname=$(basename $file)
 ssh $host "mkdir -p $pdir"
 rsync -av $pdir/$fname $host:$pdir
 else
 echo $file does not exists!
 fi
 done
done

4.赋予xsync脚本执行权限

[lxm@hadoop102 bin]$ chmod 777 xsync

5.测试脚本

[lxm@hadoop102 ~]$ xsync /home/lxm/bin

执行成功

6.将脚本复制到/bin 中，以便全局调用

​[lxm@hadoop102 ~]$ sudo cp xsync /bin/

7.分发/opt/module

[lxm@hadoop102 ~]$ xsync /opt/module/

8.同步环境变量配置

# 同步环境变量配置
# 注意：如果用了sudo，那么xsync一定要给它的路径补全。
[lxm@hadoop102 ~]$ sudo ./bin/xsync /etc/profile.d/my_env.sh

# 刷新环境
[lxm@hadoop103 ~]$ source /etc/profile
[lxm@hadoop104 ~]$ source /etc/profile

九、时间同步

参考博文《Linux中CentOS7时间与网络时间orWindows同步的方法》

十、配置workers

1.输入主机名

[lxm@hadoop102 ~]$ vim /opt/module/hadoop-3.1.3/etc/hadoop/workers 
hadoop102
hadoop103
hadoop104

2.分发workers

[lxm@hadoop102 ~]$ xsync /opt/module/hadoop-3.1.3/etc/hadoop/workers

十一、启动集群

1.初次启动集群要进行初始化

[lxm@hadoop102 ~]$ hdfs namenode -format

2.hadoop102开启dfs

[lxm@hadoop102 ~]$ start-dfs.sh

3.hadoop103开启yarn

[lxm@hadoop103 ~]$ start-yarn.sh

4.jps命令查看

5.浏览器测试

http://hadoop102:9870

十二、配置历史服务器与日志聚集

为了查看程序的历史运行情况，需要配置一下历史服务器。

1.配置mapred-site.xml

<!-- 历史服务器端地址 -->
<property>
 <name>mapreduce.jobhistory.address</name>
 <value>hadoop102:10020</value>
</property>
<!-- 历史服务器 web 端地址 -->
<property>
 <name>mapreduce.jobhistory.webapp.address</name>
 <value>hadoop102:19888</value>
</property>

2.配置yarn-site.xml

<!-- 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>

3.分发

[lxm@hadoop102 ~]$ xsync /opt/module/hadoop-3.1.3/etc/hadoop/

4.重启Hadoop集群

[lxm@hadoop102 ~]$ stop-dfs.sh

[lxm@hadoop103 ~]$ stop-yarn.sh

[lxm@hadoop102 ~]$ start-dfs.sh

[lxm@hadoop103 ~]$ start-yarn.sh

5.hadoop102启动历史服务器

[lxm@hadoop102 hadoop]$ mapred --daemon start historyserver

十三、执行wordcount

参考博文《Hadoop之——WordCount案例与执行本地jar包》

十四、**Hadoop **集群启停脚本

1.myhadoop.sh脚本

[lxm@hadoop102 bin]$ vim myhadoop.sh

#!/bin/bash
if [ $# -lt 1 ]
then
 echo "No Args Input..."
 exit ;
fi
case $1 in
"start")
 echo " =================== 启动 hadoop 集群 ==================="
 echo " --------------- 启动 hdfs ---------------"
 ssh hadoop102 "/opt/module/hadoop-3.1.3/sbin/start-dfs.sh"
 echo " --------------- 启动 yarn ---------------"
ssh hadoop103 "/opt/module/hadoop-3.1.3/sbin/start-yarn.sh"
 echo " --------------- 启动 historyserver ---------------"
 ssh hadoop102 "/opt/module/hadoop-3.1.3/bin/mapred --daemon start historyserver"
;;
"stop")
 echo " =================== 关闭 hadoop 集群 ==================="
 echo " --------------- 关闭 historyserver ---------------"
 ssh hadoop102 "/opt/module/hadoop-3.1.3/bin/mapred --daemon stop historyserver"
 echo " --------------- 关闭 yarn ---------------"
 ssh hadoop103 "/opt/module/hadoop-3.1.3/sbin/stop-yarn.sh"
 echo " --------------- 关闭 hdfs ---------------"
 ssh hadoop102 "/opt/module/hadoop-3.1.3/sbin/stop-dfs.sh"
;;
*)
 echo "Input Args Error..."
;;
esac

2.赋予权限

[lxm@hadoop102 bin]$ chmod +x myhadoop.sh

3.分发脚本

[lxm@hadoop102 ~]$ sudo ./bin/xsync /home/lxm/bin/

十五、jspall脚本

1.jpsall脚本

[lxm@hadoop102 bin]$ vim jpsall

#!/bin/bash
for host in hadoop102 hadoop103 hadoop104
do
 echo =============== $host ===============
 ssh $host jps 
done

2.赋予权限

[lxm@hadoop102 bin]$ chmod +x jpsall

3.分发脚本

[lxm@hadoop102 ~]$ sudo ./bin/xsync /home/lxm/bin/
标签： hadoop 大数据 java
本文转载自: https://blog.csdn.net/Helen_1997_1997/article/details/128963448
版权归原作者 雷神乐乐 所有， 如有侵权，请联系我们删除。
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