Linux: hadoop部署

0. 准备工作

• 3台主机
• java环境
• host配置
• 免密登陆

1. 安装包下载

我们先在Master节点下载Hadoop包，然后修改配置，随后复制到其他Slave节点稍作修改就可以了。

1. 下载安装包，创建Hadoop目录

#下载  
wget http://http://apache.claz.org/hadoop/common/hadoop-3.2.1//hadoop-3.2.1.tar.gz
#解压到 /usr/local 目录
sudo tar -xzvf  hadoop-3.2.1.tar.gz    -C /usr/local 
#修改hadoop的文件权限
sudo chown -R ubuntu:ubuntu hadoop-3.2.1.tar.gz
#重命名文件夹   
sudo mv  hadoop-3.2.1  hadoop
#建议使用软连接
ln -s hadoop-3.2.1 hadoop

2. 配置Master节点的Hadoop环境变量

2.1 全局环境变量

[root@hadoop01 hadoop]# vi /etc/profile

export HADOOP_HOME=/apprun/hadoop
export PATH=$PATH:$HADOOP_HOME/bin 
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop

[root@hadoop01 apprun]# source /etc/profile
[root@hadoop01 ~]# echo $HADOOP_HOME
/apprun/hadoop

2.2 hadoop 环境变量

hadoop-env.sh中的JAVA_HOME参数，请指向自己系统的jdk路径。该参数是hadoop运行时读取环境变量的路径。(整个脚本就这一行，其他都是注释掉的)

[root@hadoop01 hadoop]# vi etc/hadoop/hadoop-env.sh
export JAVA_HOME=/apprun/jdk
export HADOOP_HOME=/apprun/hadoop
export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export HADOOP_LOG_DIR=${HADOOP_HOME}/logs

3. 配置Master节点

Hadoop 的各个组件均用XML文件进行配置, 配置文件都放在 /usr/local/hadoop/etc/hadoop 目录中：

• core-site.xml：配置通用属性，例如HDFS和MapReduce常用的I/O设置等
• hdfs-site.xml：Hadoop守护进程配置，包括namenode、辅助namenode和datanode等
• mapred-site.xml：MapReduce守护进程配置
• yarn-site.xml：资源调度相关配置

3.1 编辑core-site.xml文件，修改内容如下：

<configuration>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>file:/apprun/hadoop/tmp</value>
        <description>Abase for other temporary directories.</description>
    </property>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://hadoop01:9000</value>
    </property>
</configuration>

参数说明：

• fs.defaultFS：默认文件系统，HDFS的客户端访问HDFS需要此参数
• hadoop.tmp.dir：指定Hadoop数据存储的临时目录，其它目录会基于此路径, 建议设置到一个足够空间的地方，而不是默认的/tmp下

如没有配置hadoop.tmp.dir参数，系统使用默认的临时目录：/tmp/hadoo-hadoop。而这个目录在每次重启后都会被删除，必须重新执行format才行，否则会出错。

3.2 编辑hdfs-site.xml，修改内容如下：

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>3</value>
    </property>
    <property>
        <name>dfs.name.dir</name>
        <value>/apprun/hadoop/hdfs/name</value>
    </property>
    <property>
        <name>dfs.data.dir</name>
        <value>/apprun/hadoop/hdfs/data</value>
    </property>
    <!--namenode和second-->
    <property>
    	<name>dfs.http.address</name>
    	<value>hadoop01:50070</value>
  	</property>
    <property>
        <name>dfs.secondary.http.address</name>
        <value>hadoop02:50090</value>
  	</property>
</configuration>

参数说明：

• dfs.replication：数据块副本数
• dfs.name.dir：指定namenode节点的文件存储目录
• dfs.data.dir：指定datanode节点的文件存储目录

3.3 编辑mapred-site.xml，修改内容如下：

<configuration>
  <property>
      <name>mapreduce.framework.name</name>
      <value>yarn</value>
  </property>
  <property>
    <name>mapreduce.application.classpath</name>
    <value>$HADOOP_HOME/share/hadoop/mapreduce/*:$HADOOP_HOME/share/hadoop/mapreduce/lib/*</value>
  </property>
</configuration>

3.4 编辑yarn-site.xml，修改内容如下：

<configuration>
<!-- Site specific YARN configuration properties -->
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
            <name>yarn.resourcemanager.hostname</name>
            <value>hadoop01</value>
    </property>
    <property>
        <name>yarn.nodemanager.env-whitelist</name>
        <value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_HOME</value>
    </property>
</configuration>

3.5 编辑workers, 修改内容如下：

hadoop01
hadoop02
hadoop03

4. 配置worker 的 Slave节点

将Master节点配置好的Hadoop打包，发送到其他两个节点：

# 打包hadoop包
tar -czf hadoop.tar.gz /apprun/hadoop
# 拷贝到其他两个节点
scp hadoop.tar.gz root@hadoop02:~
scp hadoop.tar.gz root@hadoop03:~

在其他节点加压Hadoop包到/usr/local目录

sudo tar -xzvf hadoop.tar.gz -C /apprun/

配置Slave1和Slaver2两个节点的Hadoop环境变量：

[root@hadoop01 hadoop]# vi /etc/profile

export HADOOP_HOME=/apprun/hadoop
export PATH=$PATH:$HADOOP_HOME/bin 
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop

[root@hadoop01 apprun]# source /etc/profile
[root@hadoop01 ~]# echo $HADOOP_HOME
/apprun/hadoop

启动集群

4.1 格式化HDFS文件系统

进入Master节点的Hadoop目录，执行一下操作：

bin/hadoop namenode -format

格式化namenode，第一次启动服务前执行的操作，以后不需要执行。

如果在后面的日志信息中能看到这一行，则说明 namenode 格式化成功。

common.Storage: Storage directory /apprun/elk/hadoop_repo/dfs/name has been successfully formatted.

4.2 启动Hadoop集群

服务启动

[root@hadoop01 hadoop]# sbin/start-all.sh
Starting namenodes on [hadoop01]
Starting datanodes
Starting secondary namenodes [hadoop02]
2020-08-21 14:08:09,698 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Starting resourcemanager
Starting nodemanagers
[root@hadoop01 hadoop]#
[root@hadoop01 hadoop]# jps
31188 NodeManager
30439 NameNode
30615 DataNode
31531 Jps

服务状态

[root@hadoop01 hadoop]# hadoop dfsadmin -report
WARNING: Use of this script to execute dfsadmin is deprecated.
WARNING: Attempting to execute replacement "hdfs dfsadmin" instead.

2020-08-21 14:13:48,047 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Configured Capacity: 303759667200 (282.90 GB)
Present Capacity: 261995925504 (244.00 GB)
DFS Remaining: 261995827200 (244.00 GB)
DFS Used: 98304 (96 KB)
DFS Used%: 0.00%
Replicated Blocks:
        Under replicated blocks: 0
        Blocks with corrupt replicas: 0
        Missing blocks: 0
        Missing blocks (with replication factor 1): 0
        Low redundancy blocks with highest priority to recover: 0
        Pending deletion blocks: 0
Erasure Coded Block Groups:
        Low redundancy block groups: 0
        Block groups with corrupt internal blocks: 0
        Missing block groups: 0
        Low redundancy blocks with highest priority to recover: 0
        Pending deletion blocks: 0

-------------------------------------------------
Live datanodes (3):

Name: 10.20.1.188:9866 (hadoop01)
Hostname: hadoop01
Decommission Status : Normal
Configured Capacity: 101253222400 (94.30 GB)
DFS Used: 32768 (32 KB)
Non DFS Used: 6546034688 (6.10 GB)
DFS Remaining: 89563734016 (83.41 GB)
DFS Used%: 0.00%
DFS Remaining%: 88.46%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Fri Aug 21 14:13:47 CST 2020
Last Block Report: Fri Aug 21 14:08:05 CST 2020
Num of Blocks: 0


Name: 10.20.1.189:9866 (hadoop02)
Hostname: hadoop02
Decommission Status : Normal
Configured Capacity: 101253222400 (94.30 GB)
DFS Used: 32768 (32 KB)
Non DFS Used: 10085851136 (9.39 GB)
DFS Remaining: 86023917568 (80.12 GB)
DFS Used%: 0.00%
DFS Remaining%: 84.96%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Fri Aug 21 14:13:47 CST 2020
Last Block Report: Fri Aug 21 14:08:05 CST 2020
Num of Blocks: 0


Name: 10.20.1.190:9866 (hadoop03)
Hostname: hadoop03
Decommission Status : Normal
Configured Capacity: 101253222400 (94.30 GB)
DFS Used: 32768 (32 KB)
Non DFS Used: 9701593088 (9.04 GB)
DFS Remaining: 86408175616 (80.47 GB)
DFS Used%: 0.00%
DFS Remaining%: 85.34%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Fri Aug 21 14:13:47 CST 2020
Last Block Report: Fri Aug 21 14:08:05 CST 2020
Num of Blocks: 0


[root@hadoop01 hadoop]#

服务关闭

[root@hadoop01 hadoop]# sbin/stop-all.sh
Stopping namenodes on [hadoop01]
Stopping datanodes
Stopping secondary namenodes [hadoop02]
2020-08-21 14:06:07,290 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Stopping nodemanagers
hadoop01: WARNING: nodemanager did not stop gracefully after 5 seconds: Trying to kill with kill -9
hadoop02: WARNING: nodemanager did not stop gracefully after 5 seconds: Trying to kill with kill -9
hadoop03: WARNING: nodemanager did not stop gracefully after 5 seconds: Trying to kill with kill -9
Stopping resourcemanager
[root@hadoop01 hadoop]#

参考

Hadoop3.2.1版本的环境搭建