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Hadoop2.6集群搭建(CentOS7)

一、环境准备

    1.三台虚拟机(CentOS7 + jdk1.8)

          1)192.168.122.11    master    配置:2G内存+32G储存

          2)192.168.122.12    slave1    配置:1G内存+32G储存

          3)192.168.122.13    slave2    配置:1G内存+32G储存

    2.Hadoop2.6的安装包

          下载地址:https://pan.baidu.com/s/1bO6IB37b75Nb7hD2KO6ixA

    3.CentOS安装、配置及jdk的安装教程如下:

           1)虚拟机的:https://blog.csdn.net/qq_34256296/article/details/81322243

           2)jdk1.8的:https://blog.csdn.net/qq_34256296/article/details/81321110

    4.下面配置的Hadoop文件可以下载直接拷贝到hadoop安装目录下的/etc/hadoop/文件夹下用

           hadoop配置文件:https://github.com/Kara-Feite/hadoop-config

二、Hadoop安装前的环境设置

    1.关闭防火墙

systemctl stop firewalld.service
systemctl disable firewalld.service
           

    2.修改主机名和配置hosts(依次对每个虚拟机进行修改)

1)vim /etc/hosts(在后面添加)
    192.168.122.11 master
    192.168.122.12 slave1
    192.168.122.13 slave2
2)vim /etc/sysconfig/network
    # Created by anaconda
    NETWORKING=yes
    HOSTNAME=master    #对应主机名,master、slave1、slave2
3)vim /etc/hostname
    master #对应主机名,master、slave1、slave2
           

    3.配置无密ssh连接(每台机器依次执行完前一步骤,然后才能再执行下一步骤)

1)ssh-keygen -t rsa

2)cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys

3)分别ssh另外两台虚拟机
   ssh slave1 cat /root/.ssh/authorized_keys  >> /root/.ssh/authorized_keys
   ssh slave2 cat /root/.ssh/authorized_keys  >> /root/.ssh/authorized_keys
           

 三、安装Hadoop(这里统一将大数据相关软件放/usr/local/src目录下)

    1.解压文件夹

cd /usr/local/src
tar -xzvf hadoop-2.6.0-x64.tar.gz
           

    2.配置hadoop环境变量

vim /etc/profile    #最后一行加入如下代码
# set hadoop environment
export HADOOP_HOME=/usr/local/src/hadoop-2.6.0
export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
           

    3.创建目录,后续搭建过程中需要使用

mkdir /usr/local/src/hadoop-2.6.0/tmp
mkdir /usr/local/src/hadoop-2.6.0/var
mkdir /usr/local/src/hadoop-2.6.0/dfs
mkdir /usr/local/src/hadoop-2.6.0/dfs/name
mkdir /usr/local/src/hadoop-2.6.0/dfs/data
           

    4.修改hadoop-env.sh文件(cd /usr/local/src/hadoop-2.6.0/etc/hadoop/)

vim hadoop-env.sh 
    将:export JAVA_HOME=${JAVA_HOME} 
    修改为:export JAVA_HOME=/usr/local/src/jdk1.8.0_171 #修改为jdk目录
           

    5. 修改slaves文件

vim slaves    #添加如下
slave1
slave2
           

    6. 修改core-site.xml文件

vim core-site.xml    #内容如下

<configuration>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/usr/local/src/hadoop-2.6.0/tmp</value>
    </property>
    <property>
        <name>fs.default.name</name>
        <value>hdfs://master:9000</value>
    </property>
</configuration>
           

    7. 修改hdfs-site.xml文件

vim hdfs-site.xml    #内容如下

<configuration>
    <property>
        <name>dfs.name.dir</name>
        <value>/usr/local/src/hadoop-2.6.0/dfs/name</value>
    </property>
    <property>
        <name>dfs.data.dir</name>
        <value>/usr/local/src/hadoop-2.6.0/dfs/data</value>
    </property>
    <property>
        <name>dfs.replication</name>
        <value>3</value>
    </property>
    <property>
         <name>dfs.permissions</name>
         <value>false</value>
        <description>need not permissions</description>
    </property>
</configuration>
           

    8. 修改mapred-site.xml文件

cp mapred-site.xml.template mapred-site.xml
vim mapred-site.xml    #内容如下

<configuration>
    <property>
        <name>mapred.job.tracker</name>
        <value>master:49001</value>
    </property>
    <property>
        <name>mapred.local.dir</name>
        <value>/usr/local/src/hadoop-2.6.0/var</value>
    </property>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
</configuration>
           

    9. 修改yarn-site.xml文件

vim yarn-site.xml    #内容如下

<configuration>
    <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>master</value>
    </property>
    <property>
        <description>The address of the applications manager interface in the RM.</description>
        <name>yarn.resourcemanager.address</name>
        <value>${yarn.resourcemanager.hostname}:8032</value>
    </property>
    <property>
        <description>The address of the scheduler interface.</description>
        <name>yarn.resourcemanager.scheduler.address</name>
        <value>${yarn.resourcemanager.hostname}:8030</value>
    </property>
    <property>
        <description>The http address of the RM web application.</description>
        <name>yarn.resourcemanager.webapp.address</name>
        <value>${yarn.resourcemanager.hostname}:8088</value>
    </property>
    <property>
        <description>The https adddress of the RM web application.</description>
        <name>yarn.resourcemanager.webapp.https.address</name>
        <value>${yarn.resourcemanager.hostname}:8090</value>
    </property>
    <property>
        <name>yarn.resourcemanager.resource-tracker.address</name>
        <value>${yarn.resourcemanager.hostname}:8031</value>
    </property>
    <property>
        <description>The address of the RM admin interface.</description>
        <name>yarn.resourcemanager.admin.address</name>
        <value>${yarn.resourcemanager.hostname}:8033</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.scheduler.maximum-allocation-mb</name>
        <value>12288</value>
        <discription>每个节点可用内存,单位MB,默认8182MB</discription>
    </property>
</configuration>
           

    10.将配置好的hadoop复制到其他节点

scp -rp /usr/local/src/hadoop-2.6.0/ [email protected]:/usr/local/src
scp -rp /usr/local/src/hadoop-2.6.0/ [email protected]:/usr/local/src
           

    11.初始化hadoop集群

cd /usr/local/src/hadoop-2.6.0/bin 
./hadoop namenode -format
           

    12.启动hadoop集群

cd /usr/local/src/hadoop-2.6.0/sbin 
./start-all.sh
           

    13.测试Hadoop是否安装成功

vim hadoop_test.txt    #随便写点东西
#上传成功说明集群搭建成功了
hadoop fs -put hadoop_test.txt /
#删除文件
rm hadoop_test.txt
           

    14.Hadoop各个Web页面

1、HDFS页面:50070

    2、YARN的管理界面:8088

    3、HistoryServer的管理界面:19888

    4、Zookeeper的服务端口号:2181

    5、Mysql的服务端口号:3306

    6、Hive.server1=10000

    7、Kafka的服务端口号:9092

    8、azkaban界面:8443

    9、Hbase界面:16010,60010

    10、Spark的界面:8080

    11、Spark的URL:7077
           

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