Hadoop 分布式集群搭建初入门

174次阅读

共计 9078 个字符，预计需要花费 23 分钟才能阅读完成。

Hadoop 分布式集群搭建初入门

一、配置环境
1. 设置主机名和对应的地址映射
[root@master ~]# cat /etc/hosts
127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4
::1 localhost localhost.localdomain localhost6 localhost6.localdomain6
192.168.230.130 master
192.168.230.131 slave1
192.168.230.100 slave2
# 分别对三台设备配置 hostname 和 hosts

2. 在三个节点上分别新建 hadoop 用户
[root@master ~]# tail -1 /etc/passwd
hadoop:x:1001:1001::/home/hadoop:/bin/bash

二、为 hadoop 配置所有节点之间的 ssh 免密登陆

1. 生成密钥
[hadoop@master ~]$ ssh-keygen -t rsa
Generating public/private rsa key pair.
Enter file in which to save the key (/home/hadoop/.ssh/id_rsa):
/home/hadoop/.ssh/id_rsa already exists.
Overwrite (y/n)? y
Enter passphrase (empty for no passphrase):
Enter same passphrase again:
Your identification has been saved in /home/hadoop/.ssh/id_rsa.
Your public key has been saved in /home/hadoop/.ssh/id_rsa.pub.
The key fingerprint is:
1c:16:61:04:4f:76:93:cd:da:9a:08:04:15:58:7d:96 hadoop@master
The key’s randomart image is:
+–[RSA 2048]—-+
| .===B.o= |
| . .=.oE.o |
| . +o o |
| .o .. . |
| .S. o |
| . o |
| |
| |
| |
+—————–+
[hadoop@master ~]$

2. 发送公钥

[hadoop@master ~]$ ssh-copy-id -i ~/.ssh/id_rsa.pub hadoop@slave1
The authenticity of host ‘slave1 (192.168.230.131)’ can’t be established.
ECDSA key fingerprint is 32:1a:8a:37:f8:11:bc:cc:ec:35:e6:37:c2:b8:e1:45.
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
hadoop@slave1’s password:

Number of key(s) added: 1

Now try logging into the machine, with: “ssh ‘hadoop@slave1′”
and check to make sure that only the key(s) you wanted were added.

[hadoop@master ~]$

[hadoop@master ~]$ ssh-copy-id -i ~/.ssh/id_rsa.pub hadoop@slave2
[hadoop@master ~]$ ssh-copy-id -i ~/.ssh/id_rsa.pub hadoop@master
#slave1 和 slave2 对其他节点略

3. 验证登陆

[hadoop@master ~]$ ssh hadoop@slave1
Last login: Wed Jul 26 01:11:22 2017 from master
[hadoop@slave1 ~]$ exit
logout
Connection to slave1 closed.
[hadoop@master ~]$ ssh hadoop@slave2
Last login: Wed Jul 26 13:12:00 2017 from master
[hadoop@slave2 ~]$ exit
logout
Connection to slave2 closed.
[hadoop@master ~]$

三、配置 Java
1. 使用 xftp 将 hadoop-2.7.3.tar.gz 和 jdk-8u131-linux-x64.tar.gz 上传至 master
[hadoop@master ~]$ ls
hadoop-2.7.3.tar.gz jdk-8u131-linux-x64.tar.gz

2. 使用 root 用户解压并移动到 /usr/local 下
[hadoop@master ~]$ exit
exit
[root@master ~]# cd /home/hadoop/
[root@master hadoop]# ls
hadoop-2.7.3.tar.gz jdk-8u131-linux-x64.tar.gz
[root@master hadoop]# tar -zxf jdk-8u131-linux-x64.tar.gz
[root@master hadoop]# ls
hadoop-2.7.3.tar.gz jdk1.8.0_131 jdk-8u131-linux-x64.tar.gz
[root@master hadoop]# mv jdk1.8.0_131 /usr/local/
[root@master hadoop]# cd /usr/local/
[root@master local]# ls
bin etc games include jdk1.8.0_131 lib lib64 libexec sbin share src
[root@master local]#

3. 配置 java 环境变量（这里使用的是全局变量）
[root@master ~]# vim /etc/profile #在文件末尾添加如下 java 环境变量
[root@master ~]# tail -5 /etc/profile

export JAVA_HOME=/usr/local/jdk1.8.0_131 #注意 jdk 版本
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib
export PATH=$JAVA_HOME/bin:$PATH
[root@master ~]#
[root@master ~]# source /etc/profile #使配置生效

4. 测试 master 上的 java 是否配置完成

[root@master ~]# java -version
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)
[root@master ~]#

5. 使用 scp 将 jdk 拷贝到 slave1 和 slave2
12 [root@master ~]# scp -r /usr/local/jdk1.8.0_131/ root@slave1:/usr/local/
[root@master ~]# scp -r /usr/local/jdk1.8.0_131/ root@slave2:/usr/local/

6. 配置 slave1 和 slave2 上的环境变量（同步骤 3），配置完后使用 java -version 验证一下

四、配置 hadoop 环境

1. 解压 hadoop 并移动到 /usr/local 下
[root@master ~]# cd /home/hadoop/
[root@master hadoop]# ls
hadoop-2.7.3.tar.gz jdk-8u131-linux-x64.tar.gz
[root@master hadoop]# tar -zxf hadoop-2.7.3.tar.gz
[root@master hadoop]# mv hadoop-2.7.3 /usr/local/hadoop
[root@master hadoop]# ls /usr/local/
bin etc games hadoop include jdk1.8.0_131 lib lib64 libexec sbin share src

2. 更改 hadoop 的文件所属用户
[root@master ~]# cd /usr/local
[root@master local]# chown -R hadoop:hadoop /usr/local/hadoop
[root@master local]# ll
drwxr-xr-x 9 hadoop hadoop 149 Aug 17 2016 hadoop
[root@master local]#

3. 配置 hadoop 环境变量

[root@master local]# vim /etc/profile
[root@master local]# tail -4 /etc/profile

#hadoop
export HADOOP_HOME=/usr/local/hadoop #注意路径
export PATH=”$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin”
[root@master local]#
[root@master local]# source /etc/profile #使配置生效

4. 测试

[root@master local]# hadoop version
Hadoop 2.7.3
Subversion https://git-wip-us.apache.org/repos/asf/hadoop.git -r baa91f7c6bc9cb92be5982de4719c1c8af91ccff
Compiled by root on 2016-08-18T01:41Z
Compiled with protoc 2.5.0
From source with checksum 2e4ce5f957ea4db193bce3734ff29ff4
This command was run using /usr/local/hadoop/share/hadoop/common/hadoop-common-2.7.3.jar
[root@master local]#

5. 配置 hadoop-env.sh
[root@master local]# cd $HADOOP_HOME/etc/hadoop
[root@master hadoop]# pwd
/usr/local/hadoop/etc/hadoop
[root@master hadoop]#
[root@master hadoop]# vim hadoop-env.sh
[root@master hadoop]# tail -1 hadoop-env.sh
export JAVA_HOME=/usr/local/jdk1.8.0_131 #在末尾添加
[root@master hadoop]#

6. 配置 core-site.xml
<configuration>
<!– 指定 hdfs 的 nameService –>
<property>
<name>fs.defaultFS</name>
<value>hdfs://master:9000</value>
</property>
</configuration>

7. 配置 hdfs-site.xml
<configuration>
<!– 数据节点数 –>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<!– nameNode 数据目录 –>
#目录不存在需要手动创建，并把所属改为 hadoop
<property>
<name>dfs.namenode.name.dir</name>
<value>/usr/local/hadoop/dfs/name</value>
</property>
<!– dataNode 数据目录 –>
#目录不存在需要手动创建，并把所属改为 hadoop
<property>
<name>dfs.datanode.data.dir</name>
<value>/usr/local/hadoop/dfs/data</value>
</property>
</configuration>

8. 配置 yarn-site.xml
<configuration>
<!– 指定 YARN 的 ResourceManager 的地址 –>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>master</value>
</property>
<!– reducer 取数据的方式 –>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
</configuration>

9. 配置 mapred-site.xml
[root@master hadoop]# cp mapred-site.xml.template mapred-site.xml
[root@master hadoop]# vim mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>

10. 配置 slaves
[root@master hadoop]# vim slaves
[root@master hadoop]# cat slaves
slave1
slave2
[root@master hadoop]#

11. 使用 scp 将配置好的 hadoop 传输到 slave1 和 slave2 节点上
[root@master ~]# scp -r /usr/local/hadoop root@slave1:/usr/local/
[root@master ~]# scp -r /usr/local/hadoop root@slave2:/usr/local/

12. 配置 slave1 和 slave2 上的环境变量（同步骤 3），配置完后使用 hadoop version 验证一下

13. 格式化 hdfs namenode–format
[root@master hadoop]# su hadoop
[hadoop@master hadoop]$ cd /usr/local/hadoop/
[hadoop@master hadoop]$ hdfs namenode -format #一定要在 hadoop 用户下进行
17/07/26 20:26:12 INFO namenode.NameNode: STARTUP_MSG:
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG: host = master/192.168.230.130
STARTUP_MSG: args = [-format]
STARTUP_MSG: version = 2.7.3
.
.
.
17/07/26 20:26:15 INFO util.ExitUtil: Exiting with status 0 #status 为 0 才是成功
17/07/26 20:26:15 INFO namenode.NameNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at master/192.168.230.130
************************************************************/
[hadoop@master hadoop]$

五、启动 hadoop 服务

1. 启动所有的服务
[hadoop@master dfs]$ start-all.sh
This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [master]
hadoop@master’s password: #输入 master 上的 hadoop 的密码
master: starting namenode, logging to /usr/local/hadoop/logs/hadoop-hadoop-namenode-master.out
slave1: starting datanode, logging to /usr/local/hadoop/logs/hadoop-hadoop-datanode-slave1.out
slave2: starting datanode, logging to /usr/local/hadoop/logs/hadoop-hadoop-datanode-slave2.out
Starting secondary namenodes [0.0.0.0]
hadoop@0.0.0.0’s password: #输入 master 上的 hadoop 的密码
0.0.0.0: starting secondarynamenode, logging to /usr/local/hadoop/logs/hadoop-hadoop-secondarynamenode-master.out
starting yarn daemons
starting resourcemanager, logging to /usr/local/hadoop/logs/yarn-hadoop-resourcemanager-master.out
slave1: starting nodemanager, logging to /usr/local/hadoop/logs/yarn-hadoop-nodemanager-slave1.out
slave2: starting nodemanager, logging to /usr/local/hadoop/logs/yarn-hadoop-nodemanager-slave2.out
[hadoop@master dfs]$

2. 验证
[hadoop@master dfs]$ jps #master 上的进程
7491 Jps
6820 NameNode
7014 SecondaryNameNode
7164 ResourceManager
[hadoop@master dfs]$

[root@slave1 name]# jps #slave1 上的进程
3160 NodeManager
3050 DataNode
3307 Jps
[root@slave1 name]#

[root@slave2 name]# jps #slave2 上的进程
3233 DataNode
3469 Jps
3343 NodeManager
[root@slave2 name]#

3. 使用浏览器管理

Hadoop 分布式集群搭建初入门