准备工作:
搭建集群,所有机器的必须改成静态static!!!
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1. 安装3台centos7服务器
1.1.配置名字hadoop01\hadoop02\hadoop03
hostnamectl set-hostname hadoop01
hostnamectl set-hostname hadoop02
hostnamectl set-hostname hadoop03
1.2.修改hosts文件
vi /etc/hosts
文件末尾添加以下内容:
hadoop01的ip地址 hadoop01
hadoop02的ip地址 hadoop02
hadoop03的ip地址 hadoop03
1.3.关闭防火墙
systemctl stop firewalld
systemctl disable firewalld
2.xshell点击工具,选择发送键输入到所有会话
2.1.所有窗口状态改成NO
3.hadoop01输入以下命令
3.1.做ssh 公私钥 无秘;中途直接回车
ssh-keygen -t rsa -P ''
3.2.copy公钥到hadoop02,hadoop03;输入yes,再输入密码
ssh-copy-id hadoop01
ssh-copy-id hadoop02
ssh-copy-id hadoop03
4.测试以上操作是否成功
4.1.hadoop02,hadoop03分别输入以下命令
cd .ssh/
ls
4.2.hadoop01输入以下命令
ssh hadoop02
ssh hadoop03
exit
5.第2步的基础,hadoop02和hadoop03窗口状态改成OFF
5.1.输入以下命令,和第3步一样
ssh-keygen -t rsa -P ''
ssh-copy-id hadoop01
ssh-copy-id hadoop02
ssh-copy-id hadoop03
5.2.以上操作都完成后hadoop01,hadoop02和hadoop03的窗口状态都改成OFF,任意一个窗口按下ctrl+l
6.安装chrony
yum -y install chrony
7.安装wget
yum install -y gcc vim wget
8.配置chrony
vim /etc/chrony.conf
8.1.文件添加如下内容,注释掉server 0.centos.pool.ntp.org iburst
server ntp1.aliyun.com
server ntp2.aliyun.com
server ntp3.aliyun.com
9.启动chrony
systemctl start chronyd
10.安装psmisc
yum install -y psmisc
11.备份原始源
mv /etc/yum.repos.d/CentOS-Base.repo /etc/yum.repos.d/CentOS-Base.repo.backup
12.下载源
wget -O /etc/yum.repos.d/CentOS-Base.repo https://mirrors.aliyun.com/repo/Centos-7.repo
13.清除缓存
yum clean all
yum makecache
14.打开xftp,将jdk安装包分别拖到三台机器的opt文件夹下,然后执行以下命令,安装jdk
cd /opt
tar -zxf jdk-8u111-linux-x64.tar.gz
mkdir soft
mv jdk1.8.0_111/ soft/jdk180
14.1.配置环境变量
vim /etc/profile
#java env
export JAVA_HOME=/opt/soft/jdk180
export PATH=$JAVA_HOME/bin:$PATH
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
source /etc/profile
java -version
15.打开xftp,将zookeeper安装包分别拖到三台机器的opt文件夹下,然后执行以下命令,安装zookeeper
tar -zxf zookeeper-3.4.5-cdh5.14.2.tar.gz
mv zookeeper-3.4.5-cdh5.14.2 soft/zk345
15.1.修改zoo.cfg文件
cd soft/zk345/conf/
cp zoo_sample.cfg zoo.cfg
vim zoo.cfg
修改dataDir=/opt/soft/zk345/datas:
dataDir=/opt/soft/zk345/datas
文件末尾加上以下内容:
server.1=192.168.239.137:2888:3888
server.2=192.168.239.141:2888:3888
server.3=192.168.239.142:2888:3888
16.创建datas文件夹
cd /opt/soft/zk345/
mkdir datas
17.hadoop01,hadoop02和hadoop03的窗口状态都改成ON
17.1.hadoop01页面输入以下命令
cd datas
echo "1"> myid
cat myid
17.2.hadoop02页面输入以下命令
cd datas
echo "2"> myid
cat myid
17.3.hadoop03页面输入以下命令
cd datas
echo "3"> myid
cat myid
18.hadoop01,hadoop02和hadoop03的窗口状态都改成OFF
18.1.配置zookeeper运行环境
vim /etc/profile
#Zookeeper env
export ZOOKEEPER_HOME=/opt/soft/zk345
export PATH=$PATH:$ZOOKEEPER_HOME/bin
source /etc/profile
19.启动zookeeper集群
zkServer.sh start
20.jps命令查看,必须要有进程QuorumPeerMain
jps
21.打开xftp,将Hadoop安装包分别拖到三台机器的opt文件夹下,然后执行以下命令,安装Hadoop集群
cd /opt
tar -zxf hadoop-2.6.0-cdh5.14.2.tar.gz
mv hadoop-2.6.0-cdh5.14.2 soft/hadoop260
cd soft/hadoop260/etc/hadoop
21.1.添加对应各个文件夹
mkdir -p /opt/soft/hadoop260/tmp
mkdir -p /opt/soft/hadoop260/dfs/journalnode_data
mkdir -p /opt/soft/hadoop260/dfs/edits
mkdir -p /opt/soft/hadoop260/dfs/datanode_data
mkdir -p /opt/soft/hadoop260/dfs/namenode_data
21.2.配置hadoop-env.sh
vim hadoop-env.sh
修改JAVA_HOME和HADOOP_CONF_DIR的值如下:
export JAVA_HOME=/opt/soft/jdk180
export HADOOP_CONF_DIR=/opt/soft/hadoop260/etc/hadoop
21.3.配置core-site.xml,快捷键shift+G到文件末尾添加如下内容(注意改机器名!!!)
vim core-site.xml
<configuration>
<!--指定hadoop集群在zookeeper上注册的节点名-->
<property>
<name>fs.defaultFS</name>
<value>hdfs://hacluster</value>
</property>
<!--指定hadoop运行时产生的临时文件-->
<property>
<name>hadoop.tmp.dir</name>
<value>file:///opt/soft/hadoop260/tmp</value>
</property>
<!--设置缓存大小 默认4KB--> <property>
<name>io.file.buffer.size</name>
<value>4096</value>
</property>
<!--指定zookeeper的存放地址-->
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop01:2181,hadoop02:2181,hadoop03:2181</value>
</property>
<!--配置允许root代理访问主机节点-->
<property>
<name>hadoop.proxyuser.root.hosts</name>
<value>*</value>
</property>
<!--配置该节点允许root用户所属的组-->
<property>
<name>hadoop.proxyuser.root.groups</name>
<value>*</value>
</property>
</configuration>
21.4.配置hdfs-site.xml,文件末尾添加如下内容(注意改机器名!!!)
vim hdfs-site.xml
<configuration>
<property>
<!--数据块默认大小128M-->
<name>dfs.block.size</name>
<value>134217728</value>
</property>
<property>
<!--副本数量 不配置默认为3-->
<name>dfs.replication</name>
<value>3</value>
</property>
<property>
<!--namenode节点数据(元数据)的存放位置-->
<name>dfs.name.dir</name>
<value>file:///opt/soft/hadoop260/dfs/namenode_data</value>
</property>
<property>
<!--datanode节点数据(元数据)的存放位置-->
<name>dfs.data.dir</name>
<value>file:///opt/soft/hadoop260/dfs/datanode_data</value>
</property>
<property>
<!--开启hdfs的webui界面-->
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<!--datanode上负责进行文件操作的线程数-->
<name>dfs.datanode.max.transfer.threads</name>
<value>4096</value> </property>
<property>
<!--指定hadoop集群在zookeeper上的注册名-->
<name>dfs.nameservices</name>
<value>hacluster</value>
</property>
<property>
<!--hacluster集群下有两个namenode分别是nn1,nn2-->
<name>dfs.ha.namenodes.hacluster</name>
<value>nn1,nn2</value>
</property>
<!--nn1的rpc、servicepc和http通讯地址 -->
<property>
<name>dfs.namenode.rpc-address.hacluster.nn1</name>
<value>hadoop01:9000</value>
</property>
<property>
<name>dfs.namenode.servicepc-address.hacluster.nn1</name>
<value>hadoop01:53310</value>
</property>
<property>
<name>dfs.namenode.http-address.hacluster.nn1</name>
<value>hadoop01:50070</value>
</property>
<!--nn2的rpc、servicepc和http通讯地址 -->
<property>
<name>dfs.namenode.rpc-address.hacluster.nn2</name>
<value>hadoop02:9000</value>
</property>
<property>
<name>dfs.namenode.servicepc-address.hacluster.nn2</name>
<value>hadoop02:53310</value>
</property>
<property>
<name>dfs.namenode.http-address.hacluster.nn2</name>
<value>hadoop02:50070</value>
</property>
<property>
<!--指定Namenode的元数据在JournalNode上存放的位置-->
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://hadoop01:8485;hadoop02:8485;hadoop03:8485/hacluster</value>
</property>
<property>
<!--指定JournalNode在本地磁盘的存储位置-->
<name>dfs.journalnode.edits.dir</name>
<value>/opt/soft/hadoop260/dfs/journalnode_data</value>
</property>
<property>
<!--指定namenode操作日志存储位置-->
<name>dfs.namenode.edits.dir</name>
<value>/opt/soft/hadoop260/dfs/edits</value>
</property>
<property>
<!--开启namenode故障转移自动切换-->
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<!--配置失败自动切换实现方式-->
<name>dfs.client.failover.proxy.provider.hacluster</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<!--配置隔离机制-->
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<property>
<!--配置隔离机制需要SSH免密登录-->
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/root/.ssh/id_rsa</value>
</property>
<property>
<!--hdfs文件操作权限 false为不验证-->
<name>dfs.premissions</name>
<value>false</value>
</property>
</configuration>
21.5.配置mapred-site.xml,文件末尾添加如下内容(注意改机器名!!!)
cp mapred-site.xml.template mapred-site.xml
vim mapred-site.xml
<configuration>
<property>
<!--指定mapreduce在yarn上运行-->
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<!--配置历史服务器地址-->
<name>mapreduce.jobhistory.address</name>
<value>hadoop01:10020</value>
</property>
<property>
<!--配置历史服务器webUI地址-->
<name>mapreduce.jobhistory.webapp.address</name>
<value>hadoop01:19888</value>
</property>
<property>
<!--开启uber模式-->
<name>mapreduce.job.ubertask.enable</name>
<value>true</value>
</property>
</configuration>
21.6.配置yarn-site.xml,文件末尾添加如下内容(注意改机器名!!!)
vim yarn-site.xml
<configuration>
<property>
<!--开启yarn高可用-->
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<property>
<!-- 指定Yarn集群在zookeeper上注册的节点名-->
<name>yarn.resourcemanager.cluster-id</name>
<value>hayarn</value>
</property>
<property>
<!--指定两个resourcemanager的名称-->
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<property>
<!--指定rm1的主机-->
<name>yarn.resourcemanager.hostname.rm1</name>
<value>hadoop02</value>
</property>
<property>
<!--指定rm2的主机-->
<name>yarn.resourcemanager.hostname.rm2</name>
<value>hadoop03</value>
</property>
<property>
<!--配置zookeeper的地址-->
<name>yarn.resourcemanager.zk-address</name>
<value>hadoop01:2181,hadoop02:2181,hadoop03:2181</value>
</property> <property>
<!--开启yarn恢复机制-->
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
<property>
<!--配置执行resourcemanager恢复机制实现类-->
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<property>
<!--指定主resourcemanager的地址-->
<name>yarn.resourcemanager.hostname</name>
<value>hadoop03</value>
</property>
<property>
<!--nodemanager获取数据的方式-->
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<!--开启日志聚集功能-->
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<!--配置日志保留7天-->
<name>yarn.log-aggregation.retain-seconds</name>
<value>604800</value>
</property>
</configuration>
22.配置slaves
vim slaves
22.1.快捷键dd删除localhost,添加如下内容
hadoop01
hadoop02
hadoop03
23.配置hadoop环境变量
vim /etc/profile
#hadoop env
export HADOOP_HOME=/opt/soft/hadoop260
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export YARN_HOME=$HADOOP_HOME
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/bin
export HADOOP_INSTALL=$HADOOP_HOME
source /etc/profile
24.启动Hadoop集群
24.1.输入以下命令
hadoop-daemon.sh start journalnode
24.2.输入jps命令,会发现多了一个进程JournalNode
jps
24.3.格式化namenode(只在hadoop01主机上)(hadoop02和hadoop03的窗口状态改成ON)
hdfs namenode -format
24.4.将hadoop01上的Namenode的元数据复制到hadoop02相同位置
scp -r /opt/soft/hadoop260/dfs/namenode_data/current/ root@hadoop02:/opt/soft/hadoop260/dfs/namenode_data
24.5.在hadoop01上格式化故障转移控制器zkfc
hdfs zkfc -formatZK
24.6.在hadoop01上启动dfs服务,再输入jps查看进程
start-dfs.sh
jps
24.7.在hadoop03上启动yarn服务,再输入jps查看进程
start-yarn.sh
jps
24.8.在hadoop02上输入jps查看进程,如下图
24.9.在hadoop01上启动history服务器,jps则会多了一个JobHistoryServer的进程
mr-jobhistory-daemon.sh start historyserver
jps
24.10.在hadoop02上启动resourcemanager服务,jps则会多了一个Resourcemanager的进程
yarn-daemon.sh start resourcemanager
jps
25.检查集群情况
25.1.在hadoop01上查看服务状态,hdfs haadmin -getServiceState nn1则会对应显示active,nn2则显示standby
hdfs haadmin -getServiceState nn1
hdfs haadmin -getServiceState nn2
25.2.在hadoop03上查看resourcemanager状态,yarn rmadmin -getServiceState rm1则会对应显示standby,rm2则显示active
yarn rmadmin -getServiceState rm1
yarn rmadmin -getServiceState rm2
26.浏览器输入IP地址:50070,对比以下图片
26.1.hadoop01的IP地址,注意查看是否为“active”
26.2.hadoop02的IP地址,注意查看是否为“standby”
26.3.最后选择上方的Datanodes,查看是否是三个节点,如何是,则高可用hadoop集群搭建成功!!!
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