环境:centos7
准备工作:
- 三台机器(内存大于2G) 分别写hosts、设定hostname
192.168.8.139 master
192.168.8.131 slave1
192.168.8.132 slave2
-
关闭防火墙
关闭selinux
关闭firewalld -
设定密钥登录
- master可以通过密钥登陆本机和两台slave
- master上生成密钥对:
ssh-keygen 一直回车 - 复制~/.ssh/id_rsa.pub 内容到本机和两台slave的 ~/.ssh/authorized_keys
- 设置本机和两台slave机器上的~/.ssh/authorized_keys文件权限为600
- chmod 600 ~/.ssh/authorized_keys
- 在master上
ssh master
ssh slave1
ssh slave2 - 可以直接登陆
安装Hadoop
部署Hadoop环境最少需要三台机器(运行内存大于2G),本次实验只是在master上安装Hadoop。
部署JDK环境
参考:https://my.oschina.net/u/3497124/blog/1525269
1[root@study src]# mv jdk-8u144-linux-x64.tar.gz\?AuthParam\=1507689673_6c0c57db8c3433e1c37ba89d61ea4cf4 jdk-8u144-linux-x64.tar.gz 2 3[root@study src]# tar zxf jdk-8u144-linux-x64.tar.gz 4 5[root@study src]# mv jdk1.8.0_144 /usr/local/jdk1.8 6 7环境配置: 8[root@study src]# vim /etc/profile 9#jdk 10JAVA_HOME=/usr/local/jdk1.8/ 11JAVA_BIN=/usr/local/jdk1.8/bin 12JRE_HOME=/usr/local/jdk1.8/jre 13PATH=$PATH:/usr/local/jdk1.8/bin:/usr/local/jdk1.8/jre/bin 14CLASSPATH=/usr/local/jdk1.8/jre/lib:/usr/local/jdk1.8/lib:/usr/local/jdk1.8/jre/lib/charset.jar 15 16[root@study src]# source /etc/profile 17 18检测配置是否成功: 19[root@study src]# java -version
安装Hadoop
1下载二进制包: 2[root@study src]# wget http://mirror.bit.edu.cn/apache/hadoop/common/hadoop-2.8.1/hadoop-2.8.1.tar.gz 3[root@study src]# tar zxvf hadoop-2.8.1.tar.gz 4 5[root@study src]# mv hadoop-2.8.1 /usr/local/hadoop 6 7[root@study src]# cd /usr/local/hadoop/ 8 9[root@study hadoop]# mkdir tmp dfs dfs/data dfs/name
配置Hadoop
1[root@study hadoop]# vim /usr/local/hadoop/etc/hadoop/core-site.xml 2<configuration> 3 <property> 4 <name>fs.defaultFS</name> 5 <value>hdfs://192.168.8.139:9000</value> 6#注意更改此处IP为自己主机的IP 7 </property> 8 <property> 9 <name>hadoop.tmp.dir</name> 10 <value>file:/usr/local/hadoop/tmp</value> 11 </property> 12 <property> 13 <name>io.file.buffer.size</name> 14 <value>131702</value> 15 </property> 16</configuration> 17 18 19[root@study hadoop]# vim /usr/local/hadoop/etc/hadoop/hdfs-site.xml 20<configuration> 21 <property> 22 <name>dfs.namenode.name.dir</name> 23 <value>file:/usr/local/hadoop/dfs/name</value> 24 </property> 25 <property> 26 <name>dfs.datanode.data.dir</name> 27 <value>file:/usr/local/hadoop/dfs/data</value> 28 </property> 29 <property> 30 <name>dfs.replication</name> 31 <value>2</value> 32 </property> 33 <property> 34 <name>dfs.namenode.secondary.http-address</name> 35 <value>192.168.8.139:9001</value> 36#更改为master主机IP 37 </property> 38 <property> 39 <name>dfs.webhdfs.enabled</name> 40 <value>true</value> 41 </property> 42</configuration> 43 44 45[root@study hadoop]# vim /usr/local/hadoop/etc/hadoop/mapred--site.xml 46<configuration> 47 <property> 48 <name>mapreduce.framework.name</name> 49 <value>yarn</value> 50 </property> 51 <property> 52 <name>mapreduce.jobhistory.address</name> 53 <value>192.168.8.139:10020</value> 54 </property> 55 <property> 56 <name>mapreduce.jobhistory.webapp.address</name> 57 <value>192.168.8.139:19888</value> 58 </property> 59</configuration> 60 61 62[root@study hadoop]# vim /usr/local/hadoop/etc/hadoop/yarn-site.xml 63<configuration> 64<!-- Site specific YARN configuration properties --> 65<property> 66 <name>yarn.nodemanager.aux-services</name> 67 <value>mapreduce_shuffle</value> 68 </property> 69 <property> 70 <name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name> 71 <value>org.apache.hadoop.mapred.ShuffleHandler</value> 72 </property> 73 <property> 74 <name>yarn.resourcemanager.address</name> 75 <value>192.168.8.139:8032</value> 76 </property> 77 <property> 78 <name>yarn.resourcemanager.scheduler.address</name> 79 <value>192.168.8.139:8030</value> 80 </property> 81 <property> 82 <name>yarn.resourcemanager.resource-tracker.address</name> 83 <value>192.168.8.139:8031</value> 84 </property> 85 <property> 86 <name>yarn.resourcemanager.admin.address</name> 87 <value>192.168.8.139:8033</value> 88 </property> 89 <property> 90 <name>yarn.resourcemanager.webapp.address</name> 91 <value>192.168.8.139:8088</value> 92 </property> 93 <property> 94 <name>yarn.nodemanager.resource.memory-mb</name> 95 <value>768</value> 96 </property> 97</configuration>
注意更改IP。
更改脚本环境变量:
1[root@study hadoop]# pwd 2/usr/local/hadoop/etc/hadoop 3[root@study hadoop]# vim hadoop-env.sh 4export JAVA_HOME=/usr/local/jdk1.8 5 6[root@study hadoop]# vim yarn-env.sh 7export JAVA_HOME=/usr/local/jdk1.8 8 9 10配置从机器: 11[root@study hadoop]# vim slaves 12192.168.8.131 13192.168.8.132 14##在此添加slaves的IP
至此,master配置完成。然后将Hadoop的配置文件同步到slave机器,便完成了Hadoop的配置!
启动
在master上操作即可,两台slave机器上会自动启动。
1初始化; 2[root@study hadoop]# /usr/local/hadoop/bin/hdfs namenode -format 3[root@study hadoop]# echo $? 40 5 6 7启动服务: 8[root@study hadoop]# /usr/local/hadoop/sbin/start-all.sh 9 10查看服务状态: 11[root@study hadoop]# netstat -lntp |grep java 12tcp 0 0 0.0.0.0:50070 0.0.0.0:* LISTEN 4026/java 13tcp 0 0 192.168.8.139:9000 0.0.0.0:* LISTEN 4026/java 14tcp 0 0 192.168.8.139:9001 0.0.0.0:* LISTEN 4216/java 15tcp6 0 0 192.168.8.139:8088 :::* LISTEN 4368/java 16tcp6 0 0 192.168.8.139:8030 :::* LISTEN 4368/java 17tcp6 0 0 192.168.8.139:8031 :::* LISTEN 4368/java 18tcp6 0 0 192.168.8.139:8032 :::* LISTEN 4368/java 19tcp6 0 0 192.168.8.139:8033 :::* LISTEN 4368/java 20 21 22停止服务: 23[root@study hadoop]# /usr/local/hadoop/sbin/stop-all.sh
访问Hadoop的web端主页:
浏览器打开 http://192.168.8.139:8088/

浏览器打开 http://192.168.8.139:50070/

测试
以下操作在master上实现:
1[root@study ~]# cd /usr/local/hadoop/ 2 3建立测试目录 4[root@study hadoop]# bin/hdfs dfs -mkdir /123 5如果在此提示: 6copyFromLocal: Cannot create directory /123/. Name node is in safe mode. 7这是因为开启了安全模式,解决办法: 8[root@study hadoop]# bin/hdfs dfsadmin -safemode leave 9 10查看123目录是否创建成功: 11[root@study hadoop]# bin/hdfs dfs -ls / 12Found 1 items 13drwxr-xr-x - root supergroup 0 2017-10-11 12:57 /123 14 15将当前目录下的LICENSE.txt复制到hadopp中: 16[root@study hadoop]# bin/hdfs dfs -copyFromLocal ./LICENSE.txt /123 17#不开启slave无法执行该操作 18 19创建测试文件: 20[root@study hadoop]# bin/hdfs dfs -touchz /123/123.txt 21 22查看/123/下有哪些文件: 23[root@study hadoop]# bin/hdfs dfs -ls /123/ 24Found 1 items 25-rw-r--r-- 2 root supergroup 0 2017-10-11 13:06 /123/123.txt 26 27 28用wordcount分析LICENSE.txt: 29[root@study hadoop]# bin/hadoop jar ./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.1.jar wordcount /123/LICENSE.txt /output/123 30 31 32 33查看分析后的文件: 34[root@study hadoop]# bin/hdfs dfs -ls /output/123 35 36查看分析结果: 37[root@study hadoop]# bin/hdfs dfs -cat /output/123/part-r-00000
由于本实验机器配置较低,无法完成数据分析工作,操作流程无误!