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notes/installation/Hadoop集群环境搭建.md
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notes/installation/Hadoop集群环境搭建.md
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# Hadoop集群环境搭建
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## 一、集群规划
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这里搭建一个3节点的Hadoop集群，其中三台主机均部署`DataNode`和`NodeManager`服务，但只有hadoop001上部署`NameNode`和`ResourceManager`服务。
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## 二、前置条件
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Hadoop的运行依赖JDK，需要预先安装。其安装步骤单独整理至：
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+ [Linux下JDK的安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/JDK%E5%AE%89%E8%A3%85.md)
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## 三、配置免密登录
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### 3.1 生成密匙
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在每台主机上使用ssh-keygen产生公钥私钥对：
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```shell
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ssh-keygen
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```
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### 3.2 免密登录
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将`hadoop001`的公钥写到本机和远程机器的` ~/ .ssh/authorized_key`文件中：
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```shell
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ssh-copy-id -i ~/.ssh/id_rsa.pub hadoop001
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ssh-copy-id -i ~/.ssh/id_rsa.pub hadoop002
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ssh-copy-id -i ~/.ssh/id_rsa.pub hadoop003
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```
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### 3.3 验证免密登录
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```she
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ssh hadoop002
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ssh hadoop003
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```
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## 四、集群搭建
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### 3.1 下载并解压
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下载Hadoop。这里我下载的是CDH版本Hadoop，下载地址为：http://archive.cloudera.com/cdh5/cdh/5/
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```shell
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# tar -zvxf hadoop-2.6.0-cdh5.15.2.tar.gz
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```
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### 3.2 配置环境变量
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编辑`profile`文件：
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```shell
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# vim /etc/profile
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```
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增加如下配置：
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```
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export HADOOP_HOME=/usr/app/hadoop-2.6.0-cdh5.15.2
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export PATH=${HADOOP_HOME}/bin:$PATH
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```
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执行`source`命令，使得配置立即生效：
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```shell
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# source /etc/profile
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```
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### 3.3 修改配置
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进入`${HADOOP_HOME}/etc/hadoop`目录下，修改配置文件。各个配置文件内容如下：
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#### 1. hadoop-env.sh
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```shell
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# 指定JDK的安装位置
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export JAVA_HOME=/usr/java/jdk1.8.0_201/
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```
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#### 2. core-site.xml
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```xml
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<configuration>
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<property>
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<!--指定namenode的hdfs协议文件系统的通信地址-->
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<name>fs.defaultFS</name>
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<value>hdfs://hadoop001:8020</value>
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</property>
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<property>
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<!--指定hadoop集群存储临时文件的目录-->
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<name>hadoop.tmp.dir</name>
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<value>/home/hadoop/tmp</value>
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</property>
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</configuration>
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```
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#### 3. hdfs-site.xml
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```xml
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<property>
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<!--namenode节点数据（即元数据）的存放位置，可以指定多个目录实现容错，多个目录用逗号分隔-->
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<name>dfs.namenode.name.dir</name>
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<value>/home/hadoop/namenode/data</value>
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</property>
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<property>
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<!--datanode节点数据（即数据块）的存放位置-->
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<name>dfs.datanode.data.dir</name>
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<value>/home/hadoop/datanode/data</value>
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</property>
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```
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#### 4. yarn-site.xml
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```xml
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<property>
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<!--配置NodeManager上运行的附属服务。需要配置成mapreduce_shuffle后才可以在Yarn上运行MapReduce程序。-->
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<name>yarn.nodemanager.aux-services</name>
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<value>mapreduce_shuffle</value>
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</property>
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<property>
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<!--resourcemanager的主机名-->
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<name>yarn.resourcemanager.hostname</name>
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<value>hadoop001</value>
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</property>
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</configuration>
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```
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#### 5. mapred-site.xml
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```xml
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<configuration>
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<property>
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<!--指定mapreduce作业运行在yarn上-->
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<name>mapreduce.framework.name</name>
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<value>yarn</value>
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</property>
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</configuration>
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```
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#### 5. slaves
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配置所有从属节点的主机名或IP地址，每行一个。
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```properties
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hadoop001
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hadoop002
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hadoop003
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```
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### 3.4 分发程序
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将Hadoop安装包分发到其他两台服务器，分发后建议在这两台服务器上也配置一下Hadoop的环境变量。
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```shell
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# 将安装包分发到hadoop002
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scp -r /usr/app/hadoop-2.6.0-cdh5.15.2/ hadoop002:/usr/app/
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# 将安装包分发到hadoop003
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scp -r /usr/app/hadoop-2.6.0-cdh5.15.2/ hadoop003:/usr/app/
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```
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### 3.5 初始化
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在`Hadoop001`上执行namenode初始化命令：
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```
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hadoop namenode -format
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```
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### 3.6 启动集群
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进入到`Hadoop001`的`${HADOOP_HOME}/sbin`目录下，启动Hadoop。此时`hadoop002`和`hadoop003`上的相关服务也会被启动。
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```shell
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# 启动dfs服务
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start-dfs.sh
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# 启动yarn服务
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start-yarn.sh
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```
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### 3.7 查看集群
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在每台服务器上使用`jps`命令查看服务进程，或直接进入Web-UI界面进行查看，端口为`50070`。可以看到此时有三个可用的`Datanode`：
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点击`Live Nodes`进入，可以看到每个`DataNode`的详细情况：
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接着可以查看Yarn集群的情况，端口号为`8088` ：
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## 五、提交服务到集群
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提交作业到集群的方式和单机环境完全一致，这里以提交Hadoop内置的计算Pi的示例程序为例，在任何一个节点上执行都可以，命令如下：
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```shell
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hadoop jar /usr/app/hadoop-2.6.0-cdh5.15.2/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.15.2.jar pi 3 3
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```
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