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The whole process of building a fully distributed cluster

2020-11-09 08:20:41 osc_ychelles

Full distributed, full step

Three machines , Respectively hdp01,hdp02,hdp03
The idea is to configure first hdp01, Clone again hdp02,hdp03

One . build hdp01

1. Turn off firewall ( There will be delays in general , Even if you turn off the firewall, you can still view the status , Restart can be seen in the state is OK )

systemctl disable firewalld

 Check status 
systemctl status firewalld

reboot -h now---- Restart the computer 

2. Change ip

vi /etc/sysconfig/network-scripts/ifcfg-ens33
 Six places need to be changed 
1.BOOTPROTO=static
2.ONBOOT=yes
3.IPADDR=192.168.73.102
4.NETMASK=255.255.255.0
5.GATEWAY=192.168.73.2
6.DNS1=8.8.8.8
  DNS2=114.114.114.114


It's over ip Be sure to restart the network , Otherwise it will not take effect

systemctl restart network

 Restart the network and check again ip
ip addr

3. Change host name ( The first one doesn't have to be changed )

hostnamectl set-hostname hdp02

 You can check , use hostname command 

4. Change the mapping file

vi /etc/hosts

5. If you connect to a remote finalshell Software etc. , Change local host file

C:\Windows\System32\drivers\etc\host

6. Write the secret key

ssh-keygen -t rsa

cd .ssh You can see that the public key and private key are generated 

 If you are datenode, Also must do to oneself do not secret ( As long as slaves All of them are datenode)
ssh-copy-id localhost

7. install jdk and hadoop

 Extract to the directory you want to extract 
tar -zxvf hadoop-2.7.6.tar.gz -C /usr/local/

 You can change your name , The name is too long 
mv hadoop-2.7.6/ hadoop

7.1 install ntp ntpdate Source , When you set up a cluster , Time synchronization with

# yum -y install ntp ntpdate

8. Configure environment variables

 vi /etc/profile

export JAVA_HOME=/usr/local/jdk
export HADOOP_HOME=/usr/local/hadoop
export PATH=$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH

 source /etc/profile( You have to refresh , Otherwise, the environment variable doesn't work )
 
  Check if it is installed as 
 java -version
 hadoop vesion 

9. Change profile

vi core-site.xml

<configuration>
<property> 
<!-- hdfs Address name of :schame,ip,port   Because of my mapping file IP Mapped to the host name -->
<name>fs.defaultFS</name>
 <value>hdfs://hdp01:8020</value> 
 </property>
<property>
<!-- hdfs The basic path , A base path that is dependent on other properties   Here is metadata and other information  -->
 <name>hadoop.tmp.dir</name>
 <value>/usr/local/tmp</value>
 </property>
</configuration>
vi hdfs-site.xml

<configuration>
 <property>
 # The one that holds metadata fsimage
 <name>dfs.namenode.name.dir</name>
 <value>file://${hadoop.tmp.dir}/dfs/name</value>
 </property>
 <property> 
 # Storage location of blocks 
 <name>dfs.datanode.data.dir</name>
 <value>file://${hadoop.tmp.dir}/dfs/data</value>
 </property>
 <property>
 # Number of copies 
 <name>dfs.replication</name> 
 <value>3</value> 
 </property> 
 <property> 
 # The size of the block 
 <name>dfs.blocksize</name>
 <value>134217728</value> 
 </property>
 <property>
 <name>dfs.namenode.secondary.http-address</name> 
 <value>hdp02:50090</value>
 </property> 
 <property> 
 <name>fs.checkpoint.dir</name>
 <value>file:///${hadoop.tmp.dir}/checkpoint/dfs/cname</value>
 </property>
 <property> 
 <name>fs.checkpoint.edits.dir</name>
 <value>file:///${hadoop.tmp.dir}/checkpoint/dfs/cname</value>
 </property> 
 <property> 
 <name>dfs.http.address</name>
 <value>hdp01:50070</value> 
 </property>
</configuration>
cp mapred-site.xml.template mapred-site.xml   This file does not have 

<configuration>
<property> 
<name>mapreduce.framework.name</name>
 <value>yarn</value> 
 </property> 
 <property> 
 <name>mapreduce.jobhistory.address</name> 
 <value>hdp01:10020</value>
 </property>
 <property> 
 <name>mapreduce.jobhistory.webapp.address</name>
 <value>hdp01:19888</value> 
 </property>
</configuration>
yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
<property> 
<!--  Appoint yarn Of shuffle technology -->
<name>yarn.nodemanager.aux-services</name>
 <value>mapreduce_shuffle</value> 
 </property> 
<!--  Appoint resourcemanager The host name -->
 <property>
 <name>yarn.resourcemanager.hostname</name>
 <value>qianfeng01</value> </property> 
<!-- The following options --> <!-- Appoint shuffle The corresponding class  -->
 <property> 
 <name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name> 
 <value>org.apache.hadoop.mapred.ShuffleHandler</value>
 </property> 
<!-- To configure resourcemanager Internal address of -->
 <property>
<name>yarn.resourcemanager.address</name>
 <value>qianfeng01:8032</value> 
 </property>
 <!-- To configure resourcemanager Of scheduler Internal address of -->
 <property> 
 <name>yarn.resourcemanager.scheduler.address</name>
 <value>qianfeng01:8030</value>
 </property>
<!-- To configure resoucemanager Internal address of resource scheduling for -->
 <property>
 <name>yarn.resourcemanager.resource-tracker.address</name> 
 <value>qianfeng01:8031</value>
 </property> 
<!-- To configure resourcemanager The internal address of the administrator -->
 <property> 
 <name>yarn.resourcemanager.admin.address</name> 
 <value>qianfeng01:8033</value> 
 </property> 
<!-- To configure resourcemanager Of web ui  Monitoring page of -->
 <property> 
 <name>yarn.resourcemanager.webapp.address</name> 
 <value>qianfeng01:8088</value> 
 </property>
</configuration>
hadoop-env.sh

export JAVA_HOME=/usr/local/jdk
vi slaves( Here is datanode)

hdp01
hdp02
hdp03

Two . clone

Try to remember the snapshot

close hdp01, clone hdp02,hdp03

Change ip

Change host name

3. Set up the cluster

1. Time synchronization

Time synchronization detailed configuration

2. format namenode

hdfs namenode -format

3. Start cluster

 The startup script  -- start-dfs.sh  Used to start hdfs The script for the cluster  
start-yarn.sh : Used to start yarn Daemon  
start-all.sh : Used to start hdfs and yarn

4. test

1) Build on distributed systems input Folder 
      hdfs dfs -mkdir /input2) Upload the file at will 
      hdfs dfs -put a.txt /input3) test , They sealed us up mapreduce Small feature , Check the number of words 
      /usr/local/hadoop/share/hadoop/mapreduce( The small function rack bag is all here )
       Be sure to look good at the path when you execute , and output  We can't build it ourselves , You have to generate , Otherwise, it will report a mistake 
      hadoop jar hadoop-mapreduce-examples-2.7.6.jar wordcount /input /output

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