Hadoop单机、伪分布式、分布式集群搭建

|▌冷眼眸甩不掉的悲伤 提交于 2019-11-26 20:11:24

JDK安装

设置hostname
[root@bigdata111 ~]# vi /etc/hostname
设置机器hosts
[root@bigdata111 ~]# vi /etc/hosts
192.168.1.111 bigdata111
192.168.1.112 bigdata112
192.168.1.113 bigdata113
创建jdk目录
[root@bigdata111 /]# cd /opt
[root@bigdata111 opt]# ll
总用量 0
drwxr-xr-x. 2 root root 6 3月  26 2015 rh
[root@bigdata111 opt]# mkdir module
[root@bigdata111 opt]# mkdir soft
[root@bigdata111 opt]# ls
module  rh  soft
上传jdk包

打开winSCP工具,通过winscp工具上传java jdk到linux 的/opt/soft文件夹下

[root@bigdata111 opt]# cd soft
[root@bigdata111 soft]# ls
jdk-8u144-linux-x64.tar.gz 
解压jdk

将jdk文件解压到module文件夹下,命令如下:

[root@bigdata111 opt]# cd soft
[root@bigdata111 opt]# tar -zxvf jdk-8u144-linux-x64.tar.gz -C /opt/module/
[root@bigdata111 soft]# cd /opt/module
[root@bigdata111 module]# ls
jdk1.8.0_144
设置jdk的环境变量
[root@bigdata111 module]# vi /etc/profile

在文件末尾添加jdk的环境变量,保存退出:

export JAVA_HOME=/opt/module/jdk1.8.0_144
export PATH=$PATH:$JAVA_HOME/bin
刷新环境变量
[root@bigdata111 module]# source /etc/profile
查看jdk安装是否成功
[root@bigdata111 module]# java -version
java version "1.8.0_144"
Java(TM) SE Runtime Environment (build 1.8.0_144-b01)
Java HotSpot(TM) 64-Bit Server VM (build 25.144-b01, mixed mode)

搭建Hadoop本地模式

本地模式就是单机装hadoop。

安装hadoop

上传hadoop包

通过winSCP上传hadoop包到/opt/soft/文件夹下

[root@bigdata111 soft]# ls
hadoop-2.8.4.tar.gz  jdk-8u144-linux-x64.tar.gz
解压hadoop

解压hadoop到/opt/module/下

[root@bigdata111 module]# tar -zvxf hadoop-2.8.4.tar.gz -C /opt/module/
[root@bigdata111 soft]# cd /opt/module/
[root@bigdata111 module]# ls
hadoop-2.8.4  jdk1.8.0_144
设置hadoop环境变量
[root@bigdata111 module]# vi /etc/profile

末尾添加如下配置,保存退出:

export HADOOP_HOME=/opt/module/hadoop-2.8.4
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
刷新配置文件
[root@bigdata111 module]# source /etc/profile
查看hadoop是否安装成功
[root@bigdata111 module]# hadoop
Usage: hadoop [--config confdir] [COMMAND | CLASSNAME]
  CLASSNAME            run the class named CLASSNAME
 or
  where COMMAND is one of:
  fs                   run a generic filesystem user client
  version              print the version
  jar <jar>            run a jar file
                       note: please use "yarn jar" to launch
                             YARN applications, not this command.
  checknative [-a|-h]  check native hadoop and compression libraries availability
  distcp <srcurl> <desturl> copy file or directories recursively
  archive -archiveName NAME -p <parent path> <src>* <dest> create a hadoop archive
  classpath            prints the class path needed to get the
                       Hadoop jar and the required libraries
  credential           interact with credential providers
  daemonlog            get/set the log level for each daemon
  trace                view and modify Hadoop tracing settings

Most commands print help when invoked w/o parameters.

测试hadoop实例

创建测试文件

在module目录下新建testdoc文件,输入文本:

[root@bigdata111 module]# cd /opt/module
[root@bigdata111 module]# touch testdoc
[root@bigdata111 module]# vi testdoc
[root@bigdata111 module]# cat testdoc
this is a test page!
chinese is the best country
this is a ceshi page!
i love china
listen to the music
and son on
切换jar包目录

切换到hadoop的jar包执行目录:

[root@bigdata111 module]# cd /opt/module/hadoop-2.8.4/share/hadoop/mapreduce/
[root@bigdata111 mapreduce]# ls
hadoop-mapreduce-client-app-2.8.4.jar     hadoop-mapreduce-client-core-2.8.4.jar  hadoop-mapreduce-client-hs-plugins-2.8.4.jar  hadoop-mapreduce-client-jobclient-2.8.4-tests.jar  hadoop-mapreduce-examples-2.8.4.jar  lib           sources
hadoop-mapreduce-client-common-2.8.4.jar  hadoop-mapreduce-client-hs-2.8.4.jar    hadoop-mapreduce-client-jobclient-2.8.4.jar   hadoop-mapreduce-client-shuffle-2.8.4.jar          jdiff                                lib-examples
执行wordcount程序
[root@bigdata111 mapreduce]# hadoop jar hadoop-mapreduce-examples-2.8.4.jar wordcount /opt/module/testdoc /opt/module/out
[root@bigdata111 mapreduce]# ls /opt/module/out
part-r-00000  _SUCCESS
[root@bigdata111 mapreduce]# cat /opt/module/out/part-r-00000
a   2
and 1
best    1
ceshi   1
china   1
chinese 1
country 1
i   1
is  3
listen  1
love    1
music   1
on  1
page!   2
son 1
test    1
the 2
this    2
to  1

搭建Hadoop伪分布式

伪分布式就是在单台机器上配置分布式操作。

查看hadoop可执行文件
[root@bigdata111 mapreduce]# cd /opt/module/hadoop-2.8.4/
[root@bigdata111 hadoop-2.8.4]# ls
bin  etc  include  lib  libexec  LICENSE.txt  NOTICE.txt  README.txt  sbin  share
[root@bigdata111 hadoop-2.8.4]# cd bin
[root@bigdata111 bin]# ls
container-executor  hadoop  hadoop.cmd  hdfs  hdfs.cmd  mapred  mapred.cmd  rcc  test-container-executor  yarn  yarn.cmd
[root@bigdata111 bin]# cd ..
[root@bigdata111 hadoop-2.8.4]# cd sbin
[root@bigdata111 sbin]# ls
distribute-exclude.sh  hadoop-daemons.sh  hdfs-config.sh  kms.sh                   refresh-namenodes.sh  start-all.cmd  start-balancer.sh  start-dfs.sh         start-yarn.cmd  stop-all.cmd  stop-balancer.sh  stop-dfs.sh         stop-yarn.cmd  yarn-daemon.sh
hadoop-daemon.sh       hdfs-config.cmd    httpfs.sh       mr-jobhistory-daemon.sh  slaves.sh             start-all.sh   start-dfs.cmd      start-secure-dns.sh  start-yarn.sh   stop-all.sh   stop-dfs.cmd      stop-secure-dns.sh  stop-yarn.sh   yarn-daemons.sh
切换配置文件目录

进入到hadoop设置/opt/module/hadoop-2.8.4/etc/hadoop/目录:

[root@bigdata111 hadoop]# cd /opt/module/hadoop-2.8.4/etc/hadoop/
[root@bigdata111 hadoop]# ls
capacity-scheduler.xml  core-site.xml   hadoop-metrics2.properties  hdfs-site.xml            httpfs-signature.secret  kms-env.sh            log4j.properties  mapred-queues.xml.template  ssl-client.xml.example  yarn-env.sh
configuration.xsl       hadoop-env.cmd  hadoop-metrics.properties   httpfs-env.sh            httpfs-site.xml          kms-log4j.properties  mapred-env.cmd    mapred-site.xml.template    ssl-server.xml.example  yarn-site.xml
container-executor.cfg  hadoop-env.sh   hadoop-policy.xml           httpfs-log4j.properties  kms-acls.xml             kms-site.xml          mapred-env.sh     slaves                      yarn-env.cmd
配置core-site.xml
[root@bigdata111 hadoop]# vi core-site.xml
<configuration>

<!-- 指定HDFS中NameNode的地址 -->
<property>
<name>fs.defaultFS</name>
<value>hdfs://bigdata111:9000</value>
</property>

<!-- 指定hadoop运行时产生文件的存储目录 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/opt/module/hadoop-2.8.4/data/tmp</value>
</property>

</configuration>
配置hdfs-site.xml
[root@bigdata111 hadoop]# vi hdfs-site.xml
<configuration>

<!--数据冗余数-->
<property>
<name>dfs.replication</name>
<value>1</value>
</property>

</configuration>
配置yarn-site.xml
[root@bigdata111 hadoop]# vi yarn-site.xml 
<configuration>

<!-- Site specific YARN configuration properties -->

<!-- reducer获取数据的方式 -->
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>

<!-- 指定YARN的ResourceManager的地址 -->
<property>
<name>yarn.resourcemanager.hostname</name>
<value>bigdata111</value>
</property>

<!-- 日志聚集功能使能 -->
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>

<!-- 日志保留时间设置7天(秒) -->
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>604800</value>
</property>


</configuration>
配置mapred-site.xml

重命名mapred-site.xml.template为mapred-site.xml,配置内容

[root@bigdata111 hadoop]# mv mapred-site.xml.template mapred-site.xml
[root@bigdata111 hadoop]# ls
capacity-scheduler.xml  core-site.xml   hadoop-metrics2.properties  hdfs-site.xml            httpfs-signature.secret  kms-env.sh            log4j.properties  mapred-queues.xml.template  ssl-client.xml.example  yarn-env.sh
configuration.xsl       hadoop-env.cmd  hadoop-metrics.properties   httpfs-env.sh            httpfs-site.xml          kms-log4j.properties  mapred-env.cmd    mapred-site.xml             ssl-server.xml.example  yarn-site.xml
container-executor.cfg  hadoop-env.sh   hadoop-policy.xml           httpfs-log4j.properties  kms-acls.xml             kms-site.xml          mapred-env.sh     slaves                      yarn-env.cmd
[root@bigdata111 hadoop]# vi mapred-site.xml
<configuration>

<!-- 指定mr运行在yarn上-->
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>

<!--历史服务器的地址-->
<property>
<name>mapreduce.jobhistory.address</name>
<value>bigdata111:10020</value>
</property>

<!--历史服务器页面的地址-->
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>bigdata111:19888</value>
</property>


</configuration>
配置hadoop-env.sh

修改java_home为绝对路径,保存退出:

[root@bigdata111 hadoop]# vi hadoop-env.sh
export JAVA_HOME=/opt/module/jdk1.8.0_144
格式化namenode

配置完毕,格式化namenode(仅第一次格式化文件)

[root@bigdata111 hadoop]# hadoop namenode -format

为什么要格式化?

NameNode主要被用来管理整个分布式文件系统的命名空间(实际上就是目录和文件)的元数据信息,同时为了保证数据的可靠性,还加入了操作日志,所以,NameNode会持久化这些数据(保存到本地的文件系统中)。对于第一次使用HDFS,在启动NameNode时,需要先执行-format命令,然后才能正常启动NameNode节点的服务。

格式化做了哪些事情?

在NameNode节点上,有两个最重要的路径,分别被用来存储元数据信息和操作日志,而这两个路径来自于配置文件,它们对应的属性分别是dfs.name.dir和dfs.name.edits.dir,同时,它们默认的路径均是/tmp/hadoop/dfs/name。格式化时,NameNode会清空两个目录下的所有文件,之后,会在目录dfs.name.dir下创建文件

hadoop.tmp.dir 这个配置,会让dfs.name.dir和dfs.name.edits.dir会让两个目录的文件生成在一个目录里

开启hdfs和yarn服务

当namenode和resourcemanager在一台机器时,使用如下命令:

[root@bigdata111 hadoop]# start-all.sh

当二者不为一台机器时,使用如下命令:

[root@bigdata111 hadoop]# start-dfs.sh
[root@bigdata111 hadoop]# start-yarn.sh
访问hdfs 的web页面

默认端口:50070

http://192.168.1.111:50070
访问yarn的web页面

默认端口:8088

http://192.168.1.111:8088

搭建Hadoop集群

采用VMvare克隆模式,以111机器为模板,克隆另外两台机器。

修改主机名和IP

修改克隆的两台机器的hostname和IP地址,方便xshell连接:

[root@bigdata112 ~]# vi /etc/hostname
[root@bigdata112 ~]# vi /etc/sysconfig/network-scripts/ifcfg-eno16777736
[root@bigdata112 ~]# service network restart
[root@bigdata112 ~]# ip addr
TYPE=Ethernet
BOOTPROTO=static
DEFROUTE=yes
PEERDNS=yes
PEERROUTES=yes
IPV4_FAILURE_FATAL=no
IPV6INIT=yes
IPV6_AUTOCONF=yes
IPV6_DEFROUTE=yes
IPV6_PEERDNS=yes
IPV6_PEERROUTES=yes
IPV6_FAILURE_FATAL=no
NAME=eno16777736
UUID=24bbe130-f59a-4b25-9df6-cf5857c89699
DEVICE=eno16777736
ONBOOT=yes
IPADDR=192.168.1.112
GATEWAY=192.168.1.2
DNS1=8.8.8.8
删除data目录

删除/opt/module/hadoop-2.8.4的data目录,目的配置分布式集群。

[root@bigdata111 hadoop-2.8.4]# cd /opt/module/hadoop-2.8.4/
[root@bigdata111 hadoop-2.8.4]# rm -rf data/
配置hosts

配置hosts的IP和主机名对应关系

[root@bigdata111 hadoop-2.8.4]# vi /etc/hosts
192.168.1.111 bigdata111
192.168.1.112 bigdata112
192.168.1.113 bigdata113
SCP发送其他机器

将第一台配置好的hosts文件发送到其他两台机器:

[root@bigdata111 hadoop-2.8.4]# scp /etc/hosts root@bigdata112:/etc/
[root@bigdata111 hadoop-2.8.4]# scp /etc/hosts root@bigdata113:/etc/
配置SSH免密登录
  1. 利用Xshell的发送键输入到所有会话功能,在三台机器生成秘钥
[root@bigdata111 hadoop-2.8.4]# ssh-keygen
Generating public/private rsa key pair.
Enter file in which to save the key (/root/.ssh/id_rsa): 
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:
cc:47:37:5a:93:0f:77:38:53:af:a3:57:47:55:27:59 root@bigdata111
The key's randomart image is:
+--[ RSA 2048]----+
|              .oE|
|             ..++|
|          . B = +|
|       o . + * * |
|        S o   + o|
|         .   . o.|
|            . .  |
|             .   |
|                 |
+-----------------+
  1. 利用Xshell的发送键输入到所有会话功能,将秘钥添加到集群中各个机器的秘钥库中
[root@bigdata111 hadoop-2.8.4]# ssh-copy-id bigdata111
[root@bigdata111 hadoop-2.8.4]# ssh-copy-id bigdata112
[root@bigdata111 hadoop-2.8.4]# ssh-copy-id bigdata113
  1. 查看秘钥库是否存在
[root@bigdata111 .ssh]# cd /root/.ssh
[root@bigdata111 .ssh]# ls
authorized_keys  id_rsa  id_rsa.pub  known_hosts
[root@bigdata111 .ssh]# cat authorized_keys 
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQC7cSXZDdNJ0Cg+1wyVoCn4pWEAxy/13/ekg//YVkGwEsR6HO4XaYxxstVBij5JoTEEjSDNmz2HifTZDB098py3x882ZLVHJllJWzXYX4gVof/tmdmk5AJbhIlX3SoauTrrrzFiMtuXKdu6slvzhs9IbDp68xCUNiVI06OnWFSuhQc8Td+tekwlFPfm+v3W/PqUUgQAd+OAqOUC2vEjjnACQNw/wgGvF/lqrXDv5ZIFmYCBlB7YxwP9RykOvAzEe7w2W7TOt0K8V8oKKTui4aZuahWDbsGwlD7TAQRkilXkG59XG48AWOQoU/XFxph+XECqJzjmdxYedzY8inYW/Lfx root@bigdata111
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDYyMVfLaL9w9sGz5hQG96ksUN5ih2RHdwsiXBpL/ZRG7LasKS+OQcszmc61TJfV0Vjad7kuL9wlg2YqlVIQJvaIUQCw4+5BrO0vCy4JBrz/FiDjzxKx0Ba+ILziuMxl35RxDCVGph17i2jpYfy6jGLejYK9kpJH4ueIj8mm+4LTKabRZTcjdNNI0kYM+Tr08wEIuQ45adqVU9MpZc/j6i1FIr4R/RabyuO1FhEh0+Oc5Xbm3jSAYH0MgEvK1cuG9wmX7SaB/opO00Ts+nW/P4umeZQUy51IQSRdUF6BlMrshnCSlKHnuLv2eSCx9yv3QuQMWHnL/SOXUgTnIuzbrv9 root@bigdata112
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDoBOAT/n1QCnaVJtRS1Q9GeoP665gIayWxpSWbjEFus4DL4as5S9jAIhBQWrTnvZzm+Skb4dxGPgdPYLaMFX9tdDYPPsnnRR92sLpRw9gwvG5ROL5XPpV2X+Yxl6yACmlMT0JP1uk+Ekm623n6wtBSBP1BDtJ/fhXkRX6bo2kuXs4BvmP76cikdGBDygKNIEMPTcs6p2lfOnuVdQLSCGm+Q9NswKSBVElNyywNl5J9L/5kIzGXnoGtwhQtdrOjZ+c1tyiwhCz42I3c4z0Sb/zH3OFtHCvRG7cF72uDFxe1QwVJ4h1hJ1dmtwVCckNMbmmgK72PsN8Zg4Y8XtBXgX8n root@bigdata113

  1. 验证SSH免密码登录是否配置成功
[root@bigdata111 .ssh]# ssh bigdata112
Last login: Mon Aug  5 09:23:11 2019 from bigdata112
[root@bigdata112 ~]# ssh bigdata111
Last login: Mon Aug  5 09:09:23 2019 from 192.168.1.1
部署jdk和hadoop
  1. 去除勾选“发送键输入到所有会话”,从bigdata111发送module文件夹到另外两台机器/opt/文件夹下:
[root@bigdata111 module]# scp -r /opt/module/ root@bigdata112:/opt/
[root@bigdata111 module]# scp -r /opt/module/ root@bigdata113:/opt/
  1. 将环境变量/etc/profile发送到另外两台机器:
[root@bigdata111 module]# scp -r /etc/profile root@bigdata112:/etc/
[root@bigdata111 module]# scp -r /etc/profile root@bigdata113:/etc/
  1. 切换到另外两台机器,刷新环境变量:
[root@bigdata112 module]# source /etc/profile
[root@bigdata112 module]# jps
2775 Jps
[root@bigdata113 module]# source /etc/profile
[root@bigdata113 module]# jps
2820 Jps
配置集群xml

勾选“发送键输入到所有会话”,配置hdfs-site,yarn-site,mapred-site的xml文件:

  1. hdfs-site.xml配置如下(SecondaryNameNode配置在113上):
<configuration>

<!--数据冗余数-->
<property>
<name>dfs.replication</name>
<value>3</value>
</property>
<!--secondary的地址-->
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>bigdata113:50090</value>
</property>
<!--关闭权限-->
<property>
<name>dfs.permissions</name>
<value>false</value>
</property>

</configuration>
  1. yarn-site.xml配置如下(yarn配置在112上):
<configuration>

<!-- Site specific YARN configuration properties -->
<!-- reducer获取数据的方式 -->
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>

<!-- 指定YARN的ResourceManager的地址 -->
<property>
<name>yarn.resourcemanager.hostname</name>
<value>bigdata112</value>
</property>

<!-- 日志聚集功能使能 -->
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>

<!-- 日志保留时间设置7天(秒) -->
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>604800</value>
</property>

</configuration>
  1. mapred-site.xml配置如下:
<configuration>

<!-- 指定mr运行在yarn上-->
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>

<!--历史服务器的地址-->
<property>
<name>mapreduce.jobhistory.address</name>
<value>bigdata112:10020</value>
</property>

<!--历史服务器页面的地址-->
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>bigdata112:19888</value>
</property>

</configuration>
配置slaves的datanode
[root@bigdata111 ~]# cd /opt/module/hadoop-2.8.4/etc/hadoop/
[root@bigdata111 hadoop]# ls
capacity-scheduler.xml  core-site.xml   hadoop-metrics2.properties  hdfs-site.xml            httpfs-signature.secret  kms-env.sh            log4j.properties  mapred-queues.xml.template  ssl-client.xml.example  yarn-env.sh
configuration.xsl       hadoop-env.cmd  hadoop-metrics.properties   httpfs-env.sh            httpfs-site.xml          kms-log4j.properties  mapred-env.cmd    mapred-site.xml             ssl-server.xml.example  yarn-site.xml
container-executor.cfg  hadoop-env.sh   hadoop-policy.xml           httpfs-log4j.properties  kms-acls.xml             kms-site.xml          mapred-env.sh     slaves                      yarn-env.cmd
[root@bigdata111 hadoop]# vi slaves
bigdata111
bigdata112
bigdata113
格式化namenode

利用xshell的“发送键输入到所有会话”功能,格式化namenode

[root@bigdata111 hadoop]# hadoop namenode -format
[root@bigdata112 hadoop]# hadoop namenode -format
[root@bigdata113 hadoop]# hadoop namenode -format
启动111的hdfs
[root@bigdata111 hadoop]# start-dfs.sh
启动112的yarn
[root@bigdata112 hadoop]# start-yarn.sh
输出三台机器的jps进程
[root@bigdata111 hadoop]# jps
2512 DataNode
2758 NodeManager
2377 NameNode
2894 Jps
[root@bigdata112 ~]# jps
2528 NodeManager
2850 Jps
2294 DataNode
2413 ResourceManager
[root@bigdata113 ~]# jps
2465 NodeManager
2598 Jps
2296 DataNode
2398 SecondaryNameNode
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