大数据必备——Hadoop环境搭建

1. 环境准备

一个纯净版的centos7 虚拟机，配置好静态ip，主机名，主机映射

1.1 配置静态ip

vi /etc/sysconfig/network-scripts/ifcfg-eno16777736 
-----------------------------------------------------
TYPE=Ethernet
BOOTPROTO=none
DEFROUTE=yes
IPV4_FAILURE_FATAL=no
IPV6INIT=yes
IPV6_AUTOCONF=yes
IPV6_DEFROUTE=yes
IPV6_FAILURE_FATAL=no
NAME=eno16777736
UUID=f19fae49-46da-4b52-b704-6e1ec4c0470e
ONBOOT=yes
HWADDR=00:0C:29:EC:14:1F
IPADDR0=192.168.191.101
PREFIX0=24
GATEWAY0=192.168.191.2
IPV6_PEERDNS=yes
IPV6_PEERROUTES=yes
DNS1=114.114.114.114
DNS2=8.8.8.8

1.2 配置主机映射

vi /etc/hosts
-----------------------------------------------------
192.168.191.101 hadoop1

1.3 在/opt下创建两个文件夹，software，install

cd  /opt
mkdir software install

1.4 免密登陆

ssh-keygen
#3次回车
#拷贝密钥
ssh-copy-id hadoop1

1.5 安装jdk

#解压
tar zxvf jdk-8u171-linux-x64.tar.gz -C /opt/install/

#配置环境变量
vi /etc/profile
export JAVA_HOME=/opt/install/jdk1.8.0_171
export PATH=$JAVA_HOME/bin:$PATH
#刷新环境变量
source /etc/profile
#验证
java -version
java version "1.8.0_171"
Java(TM) SE Runtime Environment (build 1.8.0_171-b11)
Java HotSpot(TM) 64-Bit Server VM (build 25.171-b11, mixed mode)

2. 安装Hadoop

Hadoop 的安装模式分为3种：单机（本地）模式，伪分布式，完全分布式（集群模式）

2.1 本地模式安装

2.1.1 解压

tar zxvf hadoop-2.6.0-cdh5.14.2.tar.gz -C /opt/install/

2.1.2 环境变量

vi /etc/profile
---------------------------
# hadoop
export HADOOP_HOME=/opt/install/hadoop-2.6.0-cdh5.14.2
export PATH=$HADOOP_HOME/bin:$PATH
---------------------------------
source /etc/profile

2.1.3 测试

bin/hadoop

2.1.4 官方示例演示

mkdir input
cp etc/hadoop/*.xml input
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.14.2.jar grep input output 'dfs[a-z.]+'
cat output/*

2.2 伪分布式搭建

2.2.1 修改HDFS配置文件

(1) etc/hadoop/hadoop-env.sh

export JAVA_HOME=/opt/install/jdk1.8.0_171

(2) etc/hadoop/core-site.xml

<property>
    <name>fs.defaultFSname>
    <value>hdfs://hadoop1:9000value>
property>

(3) etc/hadoop/hdfs-site.xml

<property>
    <name>dfs.replicationname>
    <value>1value>
property>

(4) etc/hadoop/slaves

hadoop1

2.2.2 格式化文件系统

bin/hdfs namenode -format

2.2.3 启动HDFS

sbin/start-dfs.sh

2.2.4 验证是否成功

jps
20896 Jps
20787 SecondaryNameNode
20521 NameNode
20638 DataNode

使用web浏览器访问50070端口，查看是否能打开

2.2.5 官方示例演示

hdfs dfs -mkdir /input
hdfs dfs -put etc/hadoop/*.xml /input
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.14.2.jar grep /input /output 'dfs[a-z.]+'
hdfs dfs -cat /output/part-r-00000

2.2.6 修改Yarn配置

mapred-site.xml

cp etc/hadoop/mapred-site.xml.template etc/hadoop/mapred-site.xml
--------------------------
<property>
    <name>mapreduce.framework.namename>
    <value>yarnvalue>
property>

yarn-site.xml

<configuration>
    <property>
        <name>yarn.nodemanager.aux-servicesname>
        <value>mapreduce_shufflevalue>
    property>
configuration>

2.2.7 启动Yarn

sbin/start-yarn.sh

查看jps进程

jps
22304 ResourceManager
21989 DataNode
22389 NodeManager
21868 NameNode
22143 SecondaryNameNode
22703 Jps

使用web浏览器访问8088端口，查看是否能打开

2.2.8 官方示例演示

hdfs dfs -rm -r -f /output
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.14.2.jar grep /input /output 'dfs[a-z.]+'
hdfs dfs -cat /output/part-r-00000

put
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.14.2.jar grep /input /output 'dfs[a-z.]+'
hdfs dfs -cat /output/part-r-00000