快速部署Hadoop集群

1. 修改Linux主机名

hostnamectl set-hostname dhf1
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或修改配置文件

vim /etc/sysconfig/network 

NETWORKING=yes
HOSTNAME=dhf1
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2. 修改IP

vim /etc/sysconfig/network-scripts/ifcfg-eth0

systemctl restart network
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3. 修改主机名和IP的映射关系

vim /etc/hosts

192.xxx.xxx.227 dhf1
192.xxx.xxx.228 dhf2
192.xxx.xxx.229 dhf3
192.xxx.xxx.230 dhf4
192.xxx.xxx.231 dhf5
192.xxx.xxx.232 dhf6
192.xxx.xxx.233 dhf7
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4.关闭防火墙

systemctl status firewalld

systemctl stop firewalld

systemctl disable firewalld
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5.ssh免登陆

ssh-keygen -t rsa (四个回车)
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执行完这个命令后,会生成两个文件id_rsa(私钥)、id_rsa.pub(公钥)将公钥拷贝到要免登陆的机器上(包括本机器):

ssh-copy-id dhf1
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需要生成公钥的机器 需要拷贝到的机器
dhf1 dhf1、dhf2、dhf3、dhf4、dhf5、dhf6、dhf7
dhf2 dhf1、dhf2
dhf3 dhf3、dhf4、dhf5、dhf6、dhf7

6. 安装JDK,配置环境变量等

export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.272.b10-1.el7_9.x86_64
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:$JRE_HOME/lib

source /etc/profile
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7. 重启机器

Reboot
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8.集群规划

主机名 IP 安装的软件 运行的进程
dhf1 192.xxx.xxx.227 jdk、hadoop NameNode、DFSZKFailoverController(zkfc)
dhf2 192.xxx.xxx.228 jdk、hadoop NameNode、DFSZKFailoverController(zkfc)
dhf3 192.xxx.xxx.229 jdk、hadoop ResourceManager
dhf4 192.xxx.xxx.230 jdk、hadoop ResourceManager
dhf5 192.xxx.xxx.231 jdk、hadoop、zookeeper DataNode、NodeManager、JournalNode、QuorumPeerMain
dhf6 192.xxx.xxx.232 jdk、hadoop、zookeeper DataNode、NodeManager、JournalNode、QuorumPeerMain
dhf7 192.xxx.xxx.233 jdk、hadoop、zookeeper DataNode、NodeManager、JournalNode、QuorumPeerMain

说明:在hadoop2.0中通常由两个NameNode组成,一个处于active状态,另一个处于standby状态。Active NameNode对外提供服务,而Standby NameNode则不对外提供服务,仅同步active namenode的状态,以便能够在它失败时快速进行切换。hadoop官方提供了两种HDFS HA的解决方案,一种是NFS,另一种是QJM。这里我们使用简单的QJM。在该方案中,主备NameNode之间通过一组JournalNode同步元数据信息,一条数据只要成功写入多数JournalNode即认为写入成功。通常配置奇数个JournalNode。这里还配置了一个zookeeper集群,用于ZKFC(DFSZKFailoverController)故障转移,当Active NameNode挂掉了,会自动切换Standby NameNode为standby状态。两个ResourceManager,一个是Active,一个是Standby,状态由zookeeper进行协调。把namenode和resourcemanager分开是因为性能问题,因为他们都要占用大量资源,所以把他们分开了,他们分开了就要分别在不同的机器上启动。

9.安装zookeeper

9.1.安装配置zooekeeper集群

(在dhf5上操作)

cd /cdc/apache-zookeeper-3.5.8-bin/conf/

cp zoo_sample.cfg zoo.cfg
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修改zoo.cfg

vim zoo.cfg

dataDir=/cdc/apache-zookeeper-3.5.8-bin/tmp

server.1=dhf5:2888:3888
server.2=dhf6:2888:3888
server.3=dhf7:2888:3888
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保存退出

然后创建一个tmp文件夹

mkdir /cdc/apache-zookeeper-3.5.8-bin/tmp
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再创建一个空文件

touch /cdc/apache-zookeeper-3.5.8-bin/tmp/myid
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最后向该文件写入ID

echo 1 > /cdc/apache-zookeeper-3.5.8-bin/tmp/myid
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9.2将配置好的zookeeper拷贝到其他节点

scp -r /cdc/apache-zookeeper-3.5.8-bin/ dhf6:/cdc/

scp -r /cdc/apache-zookeeper-3.5.8-bin/ dhf7:/cdc/
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注意:修改dhf6、dhf7对应/cdc/apache-zookeeper-3.5.8-bin/tmp/myid内容

dhf6:echo 2 > /cdc/apache-zookeeper-3.5.8-bin/tmp/myid

dhf7:echo 3 > /cdc/apache-zookeeper-3.5.8-bin/tmp/myid
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10.安装hadoop

10.1安装配置hadoop集群

(在dhf1上操作)

10.1.1将hadoop添加到环境变量中

vim /etc/profile

export HADOOP_HOME=/cdc/hadoop-3.3.0
export PATH=$PATH:$JAVA_HOME/bin:$JRE_HOME/bin:$HADOOP_HOME/bin
export HDFS_NAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=root
export HDFS_JOURNALNODE_USER=root
export HDFS_ZKFC_USER=root
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10.1.2配置HDFS

(hadoop所有的配置文件都在$HADOOP_HOME/etc/hadoop目录下)

首先通过hadoop classpath命令获取HADOOP_CLASSPATH,如下:

/cdc/hadoop-3.3.0/etc/hadoop:/cdc/hadoop-3.3.0/share/hadoop/common/lib/*:/cdc/hadoop-3.3.0/share/hadoop/common/*:/cdc/hadoop-3.3.0/share/hadoop/hdfs:/cdc/hadoop-3.3.0/share/hadoop/hdfs/lib/*:/cdc/hadoop-3.3.0/share/hadoop/hdfs/*:/cdc/hadoop-3.3.0/share/hadoop/mapreduce/*:/cdc/hadoop-3.3.0/share/hadoop/yarn:/cdc/hadoop-3.3.0/share/hadoop/yarn/lib/*:/cdc/hadoop-3.3.0/share/hadoop/yarn/*
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10.1.2.1修改hadoop-env.sh
export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.272.b10-1.el7_9.x86_64

export HADOOP_CLASSPATH=/cdc/hadoop-3.3.0/etc/hadoop:/cdc/hadoop-3.3.0/share/hadoop/common/lib/*:/cdc/hadoop-3.3.0/share/hadoop/common/*:/cdc/hadoop-3.3.0/share/hadoop/hdfs:/cdc/hadoop-3.3.0/share/hadoop/hdfs/lib/*:/cdc/hadoop-3.3.0/share/hadoop/hdfs/*:/cdc/hadoop-3.3.0/share/hadoop/mapreduce/*:/cdc/hadoop-3.3.0/share/hadoop/yarn:/cdc/hadoop-3.3.0/share/hadoop/yarn/lib/*:/cdc/hadoop-3.3.0/share/hadoop/yarn/*
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10.1.2.2修改core-site.xml
<configuration>
	<!-- 指定hdfs的nameservice为ns1 -->
	<property>
        <name>fs.defaultFS</name>
        <value>hdfs://ns1</value>
	</property>
    <!-- 指定hadoop临时目录 -->
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/cdc/hadoop-3.3.0/tmp</value>
    </property>
    <!-- 指定zookeeper地址 -->
    <property>
        <name>ha.zookeeper.quorum</name>
        <value>dhf5:2181,dhf6:2181,dhf7:2181</value>
    </property>
	<property>
        <name>hadoop.proxyuser.root.hosts</name>
        <value>*</value>
	</property>
	<property>
    	<name>hadoop.proxyuser.root.groups</name>
    	<value>*</value>
	</property>
</configuration>
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10.1.2.3修改hdfs-site.xml
<configuration>
	<!--指定hdfs的nameservice为ns1,需要和core-site.xml中的保持一致 -->
	<property>
        <name>dfs.nameservices</name>
        <value>ns1</value>
    </property>
    <!-- ns1下面有两个NameNode,分别是nn1,nn2 -->
	<property>
        <name>dfs.ha.namenodes.ns1</name>
        <value>nn1,nn2</value>
	</property>
	<!-- nn1的RPC通信地址 -->
	<property>
        <name>dfs.namenode.rpc-address.ns1.nn1</name>
        <value>dhf1:9000</value>
    </property>
    <!-- nn1的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.ns1.nn1</name>
        <value>dhf1:50070</value>
    </property>
    <!-- nn2的RPC通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.ns1.nn2</name>
        <value>dhf2:9000</value>
    </property>
    <!-- nn2的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.ns1.nn2</name>
        <value>dhf2:50070</value>
    </property>
    <!-- 指定NameNode的元数据在JournalNode上的存放位置 -->
    <property>
        <name>dfs.namenode.shared.edits.dir</name>
        <value>qjournal://dhf5:8485;dhf6:8485;dhf7:8485/ns1</value>
    </property>
    <!-- 指定JournalNode在本地磁盘存放数据的位置 -->
    <property>
        <name>dfs.journalnode.edits.dir</name>
        <value>/cdc/hadoop-3.3.0/journal</value>
    </property>
    <!-- 开启NameNode失败自动切换 -->
    <property>
        <name>dfs.ha.automatic-failover.enabled</name>
        <value>true</value>
    </property>
    <!-- 配置失败自动切换实现方式 -->
    <property>
        <name>dfs.client.failover.proxy.provider.ns1</name>
        <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
    </property>
    <!-- 配置隔离机制方法,多个机制用换行分割,即每个机制暂用一行-->
    <property>
        <name>dfs.ha.fencing.methods</name>
        <value>
        sshfence
        shell(/bin/true)
        </value>
    </property>
    <!-- 使用sshfence隔离机制时需要ssh免登陆 -->
    <property>
        <name>dfs.ha.fencing.ssh.private-key-files</name>
        <value>/root/.ssh/id_rsa</value>
    </property>
    <!-- 配置sshfence隔离机制超时时间 -->
    <property>
        <name>dfs.ha.fencing.ssh.connect-timeout</name>
        <value>30000</value>
    </property>
</configuration>
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10.1.2.4修改mapred-site.xml
<configuration>
    <!-- 指定mr框架为yarn方式 -->
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>yarn.app.mapreduce.am.env</name>
        <value>HADOOP_MAPRED_HOME=$HADOOP_HOME</value>
    </property>
    <property>
        <name>mapreduce.map.env</name>
        <value>HADOOP_MAPRED_HOME=$HADOOP_HOME</value>
    </property>
    <property>
        <name>OP_MAPRED_HOME=$HADOOP_HOME</value>
    </property>
</configuration>   
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10.1.2.5修改yarn-site.xml
<configuration>
    <!-- 开启RM高可靠 -->
    <property>
        <name>yarn.resourcemanager.ha.enabled</name>
        <value>true</value>
    </property>
    <!-- 指定RM的cluster id -->
    <property>
        <name>yarn.resourcemanager.cluster-id</name>
        <value>yrc</value>
    </property>
    <!-- 指定RM的名字 -->
    <property>
        <name>yarn.resourcemanager.ha.rm-ids</name>
        <value>rm1,rm2</value>
    </property>
    <!-- 分别指定RM的地址 -->
    <property>
        <name>yarn.resourcemanager.hostname.rm1</name>
        <value>dhf3</value>
    </property>
    <property>
        <name>yarn.resourcemanager.hostname.rm2</name>
        <value>dhf4</value>
    </property>
    <property> 
        <name>yarn.resourcemanager.webapp.address.rm1</name> 
        <value>dhf3:8088</value>
    </property> 
    <property> 
        <name>yarn.resourcemanager.webapp.address.rm2</name> 
        <value>dhf4:8088</value>
    </property>
    <!-- 指定zk集群地址 -->
    <property>
        <name>yarn.resourcemanager.zk-address</name>
        <value>dhf5:2181,dhf6:2181,dhf7:2181</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.application.classpath</name>
        <value>/cdc/hadoop-3.3.0/etc/hadoop:/cdc/hadoop-3.3.0/share/hadoop/common/lib/*:/cdc/hadoop-				3.3.0/share/hadoop/common/*:/cdc/hadoop-3.3.0/share/hadoop/hdfs:/cdc/hadoop-								3.3.0/share/hadoop/hdfs/lib/*:/cdc/hadoop-3.3.0/share/hadoop/hdfs/*:/cdc/hadoop-							3.3.0/share/hadoop/mapreduce/*:/cdc/hadoop-3.3.0/share/hadoop/yarn:/cdc/hadoop-								3.3.0/share/hadoop/yarn/lib/*:/cdc/hadoop-3.3.0/share/hadoop/yarn/*
        </value>
    </property>   
</configuration>
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10.1.2.6修改workers (workers)

(workers 是指定子节点的位置,因为要在dhf1上启动HDFS、在dhf3启动yarn,所以dhf1上的workers 文件指定的是datanode的位置,dhf3上的workers 文件指定的是nodemanager的位置)

vim workers 

dhf5
dhf6
dhf7
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10.2将配置好的hadoop拷贝到其他节点

scp -r /cdc/hadoop-3.3.0/ root@dhf2:/cdc/
scp -r /cdc/hadoop-3.3.0/ root@dhf3:/cdc/
scp -r /cdc/hadoop-3.3.0/ root@dhf4:/cdc/
scp -r /cdc/hadoop-3.3.0/ root@dhf5:/cdc/
scp -r /cdc/hadoop-3.3.0/ root@dhf6:/cdc/
scp -r /cdc/hadoop-3.3.0/ root@dhf7:/cdc/
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11.启动服务

11.1启动zookeeper集群

(分别在dhf5、dhf6、dhf7上启动zk)(QuorumPeerMain)

cd /cdc/apache-zookeeper-3.5.8-bin/bin/

./zkServer.sh start
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查看状态:一个leader,两个follower

./zkServer.sh status
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11.2启动journalnode

cd /cdc/hadoop-3.3.0/;rm -rf journal/ns1/;rm -rf logs/; rm -rf tmp/;
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(分别在在dhf5、dhf6、tcast07上执行)

cd /cdc/hadoop-3.3.0/sbin/

./hadoop-daemon.sh start journalnode
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运行jps命令检验,dhf5、dhf6、dhf7上多了JournalNode进程

11.3格式化HDFS

(在dhf1上执行命令)

hdfs namenode -format
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格式化后会在根据core-site.xml中的hadoop.tmp.dir配置生成个文件,这里我配置的是/cdc/hadoop-3.3.0/tmp,然后将/cdc/hadoop-3.3.0/tmp拷贝到dhf2的/cdc/hadoop-3.3.0/下。

scp -r /cdc/hadoop-3.3.0/tmp/ root@dhf2:/cdc/hadoop-3.3.0/   
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11.4格式化ZK

(在dhf1上执行)

hdfs zkfc -formatZK
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11.5启动HDFS

(在dhf1上执行)

cd /cdc/hadoop-3.3.0/sbin/

./start-dfs.sh
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11.6启动YARN

(在dhf3上执行)

cd /cdc/hadoop-3.3.0/sbin/

./start-yarn.sh
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12.验证

192.xxx.xxx.228:50070

NameNode ‘dhf2:9000’ (active)

clip_image002.jpg

192.xxx.xxx.227:50070

NameNode ‘dhf1:9000’ (standby)

clip_image004.jpg

查看datanode节点状态全部上线

clip_image006.jpg

首先向hdfs上传一个文件

hadoop fs -mkdir /dhf

hadoop fs -put /test.txt /dhf

hadoop fs -ls /dhf
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clip_image008.jpg

然后再kill掉active的NameNode(dhf2)

kill -9 16950
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通过浏览器访问:192.xxx.xxx.227:50070

NameNode ‘dhf1:9000’ (active)

这个时候dhf1上的NameNode变成了active

hadoop fs -ls /dhf
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刚才上传的文件依然存在

clip_image010.jpg

手动启动那个挂掉的NameNode

./hadoop-daemon.sh start namenode
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通过浏览器访问:192.xxx.xxx.228:50070

NameNode ‘dhf2:9000’ (standby)

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