基于jdk1.7和hadoop2.6.4的Hadoop集群搭建

.Ruo

已于 2022-05-05 15:00:52 修改

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于 2022-05-04 11:20:59 首次发布

本文链接：https://blog.youkuaiyun.com/qq_45534066/article/details/124567689

版权

通过xmanager的Xftp上传hadoop-2.6.4.tar.gz文件到/opt目录

hadoop2.6.4下载地址

解压缩hadoop-2.6.4.tar.gz 文件

tar -zxf hadoop-2.6.4.tar.gz -C /usr/local

解压后即可，看到/usr/local/hadoop-2.6.4文件夹

配置Hadoop

进入目录：
cd /usr/local/hadoop-2.6.4/etc/hadoop/
依次修改下面的文件：
4.1 core-site.xml

 <configuration>
    <property>
    <name>fs.defaultFS</name>  
      <value>hdfs://master:8020</value>  
      </property>  
    <property>
      <name>hadoop.tmp.dir</name>
      <value>/var/log/hadoop/tmp</value>
    </property>
</configuration>

4.2 hadoop-env.sh
export JAVA_HOME=/usr/java/jdk1.7.0_80

4.3 hdfs-site.xml

 <configuration>
<property>
    <name>dfs.namenode.name.dir</name>
    <value>file:///data/hadoop/hdfs/name</value>
</property>
<property>
    <name>dfs.datanode.data.dir</name>
    <value>file:///data/hadoop/hdfs/data</value>
</property>
<property>
     <name>dfs.namenode.secondary.http-address</name>
     <value>master:50090</value>
</property>
<property>
     <name>dfs.replication</name>
     <value>3</value>
</property>
</configuration>

4.4 mapred-site.xml

<configuration>
<property>
    <name>mapreduce.framework.name</name>
    <value>yarn</value>
</property>
<!-- jobhistory properties -->
<property>
    <name>mapreduce.jobhistory.address</name>
    <value>master:10020</value>
</property>
<property>
     <name>mapreduce.jobhistory.webapp.address</name>
     <value>master:19888</value>
</property>
</configuration>

4.5 yarn-site.xml

 <property>
    <name>yarn.resourcemanager.hostname</name>
    <value>master</value>
  </property>    
  <property>
    <name>yarn.resourcemanager.address</name>
    <value>${yarn.resourcemanager.hostname}:8032</value>
  </property>
  <property>
    <name>yarn.resourcemanager.scheduler.address</name>
    <value>${yarn.resourcemanager.hostname}:8030</value>
  </property>
  <property>
    <name>yarn.resourcemanager.webapp.address</name>
    <value>${yarn.resourcemanager.hostname}:8088</value>
  </property>
  <property>
    <name>yarn.resourcemanager.webapp.https.address</name>
    <value>${yarn.resourcemanager.hostname}:8090</value>
  </property>
  <property>
    <name>yarn.resourcemanager.resource-tracker.address</name>
    <value>${yarn.resourcemanager.hostname}:8031</value>
  </property>
  <property>
    <name>yarn.resourcemanager.admin.address</name>
    <value>${yarn.resourcemanager.hostname}:8033</value>
  </property>
  <property>
    <name>yarn.nodemanager.local-dirs</name>
    <value>/data/hadoop/yarn/local</value>
  </property>
  <property>
    <name>yarn.log-aggregation-enable</name>
    <value>true</value>
  </property>
  <property>
    <name>yarn.nodemanager.remote-app-log-dir</name>
    <value>/data/tmp/logs</value>
  </property>
<property> 
 <name>yarn.log.server.url</name> 
 <value>http://master:19888/jobhistory/logs/</value>
 <description>URL for job history server</description>
</property>
<property>
   <name>yarn.nodemanager.vmem-check-enabled</name>
    <value>false</value>
  </property>
 <property>
    <name>yarn.nodemanager.aux-services</name>
    <value>mapreduce_shuffle</value>
  </property>
  <property>
    <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
      <value>org.apache.hadoop.mapred.ShuffleHandler</value>
      </property>
<property>  
        <name>yarn.nodemanager.resource.memory-mb</name>  
        <value>2048</value>  
 </property>  
 <property>  
        <name>yarn.scheduler.minimum-allocation-mb</name>  
        <value>512</value>  
 </property>   
 <property>  
        <name>yarn.scheduler.maximum-allocation-mb</name>  
        <value>4096</value>  
 </property> 
 <property> 
    <name>mapreduce.map.memory.mb</name> 
    <value>2048</value> 
 </property> 
 <property> 
    <name>mapreduce.reduce.memory.mb</name> 
    <value>2048</value> 
 </property> 
 <property> 
    <name>yarn.nodemanager.resource.cpu-vcores</name> 
    <value>1</value> 
 </property>

4.6 yarn-env.sh

export JAVA_HOME=/usr/java/jdk1.7.0_80

拷贝hadoop安装文件到集群slave节点

scp -r /usr/local/hadoop-2.6.4 slave1:/usr/local
scp -r /usr/local/hadoop-2.6.4 slave2:/usr/local
scp -r /usr/local/hadoop-2.6.4 slave3:/usr/local

4.7 slaves文件后加上
slave1
slave2
slave3

4.8 设置IP映射
编辑/etc/hosts
前面是自己虚拟机的IP地址，后面是自己的主机名称

192.168.128.130 master master.centos.com
192.168.128.131 slave1 slave1.centos.com
192.168.128.132 slave2 slave2.centos.com
192.168.128.133 slave3 slave3.centos.com

5.配置SSH无密码登录
（1）使用ssh-keygen产生公钥与私钥对。
输入命令

ssh-keygen -t rsa

接着按三次Enter键

[root@master ~]# ssh-keygen -t rsa
Generating public/private rsa key pair.
Enter file in which to save the key (/root/.ssh/id_rsa):
Created directory ‘/root/.ssh’.
Enter passphrase (empty for no passphrase):
Enter same passphrase again:
Your identification has been saved in /root/.ssh/id_rsa.
Your public key has been saved in /root/.ssh/id_rsa.pub.
The key fingerprint is:
a6:13:5a:7b:54:eb:77:58:bd:56:ef:d0:64:90:66:d4 root@master.centos.com
The key’s randomart image is:
±-[ RSA 2048]----+
| … |
| . .E|
| . = |
| . . o o |
| o S . . =|
| o * . o ++|
| . + . . o ooo|
| o . …o |
| .|
±----------------+

生成私有密钥id_rsa和公有密钥id_rsa.pub两个文件。ssh-keygen用来生成RSA类型的密钥以及管理该密钥，参数“-t”用于指定要创建的SSH密钥的类型为RSA。
（2）用ssh-copy-id将公钥复制到远程机器中
ssh-copy-id -i /root/.ssh/id_rsa.pub master//依次输入yes,123456（root用户的密码）

ssh-copy-id -i /root/.ssh/id_rsa.pub slave1
ssh-copy-id -i /root/.ssh/id_rsa.pub slave2
ssh-copy-id -i /root/.ssh/id_rsa.pub slave3

（3）验证时间是否同步
依次输入

ssh slave1
ssh slave2
ssh slave3

6.配置时间同步服务

（1）安装NTP服务。在各节点：

yum -y install ntp

（2）设置假设master节点为NTP服务主节点，那么其配置如下。
使用命令

vim /etc/ntp.conf

打开/etc/ntp.conf文件，注释掉以server开头的行，并添加:

restrict 192.168.0.0 mask 255.255.255.0 nomodify notrap
server 127.127.1.0
fudge 127.127.1.0 stratum 10

（3）分别在slave1、slave2、slave2中配置NTP，同样修改/etc/ntp.conf文件，注释掉server开头的行，并添加:

server master

（4）执行命令

service iptables stop & chkconfig iptables off

永久性关闭防火墙，主节点和从节点都要关闭。
（5）启动NTP服务。
① 在master节点执行命令

service ntpd start & chkconfig ntpd on

所有节点都要关闭nptd服务，查看nptd状态

service nptd status

记住在ntpdate之前一定要关闭，如果主节点的时间跟系统时间对不上，则先在主节点上nptdate ntp1.aliyun.com
② 在slave1、slave2、slave3上执行命令

ntpdate master

即可同步时间
③ 在slave1、slave2、slave3上分别执行

service ntpd start & chkconfig ntpd on

即可启动并永久启动NTP服务。

7.在/etc/profile添加JAVA_HOME和Hadoop路径

export HADOOP_HOME=/usr/local/hadoop-2.6.4
export PATH=$HADOOP_HOME/bin:$PATH:/usr/java/jdk1.7.0_80/bin

source /etc/profile

使修改生效

cd /opt/hadoop-2.6.4/bin

执行格式化

hdfs namenode -format

9.启动集群
进入目录

cd /usr/local/hadoop-2.6.4/sbin

执行启动：

./start-dfs.sh
./start-yarn.sh
./mr-jobhistory-daemon.sh start historyserver

使用jps，查看进程
[root@centos67 sbin]# jps
3672 NodeManager
3301 DataNode
3038 NameNode
4000 JobHistoryServer
4058 Jps
3589 ResourceManager
3408 SecondaryNameNode