HA分布式集群搭建

一:HA分布式配置的优势:

  1,防止由于一台namenode挂掉,集群失败的情形

  2,适合工业生产的需求

二:HA安装步骤: 1,安装虚拟机

 1,型号:VMware_workstation_full_12.5.0.11529.exe  linux镜像:CentOS-7-x86_64-DVD-1611.iso

  注意点:

  1,网络选择了桥接模式(可以防止route总变),(台式机或服务器最好设置自己的本机的ip地址为静态的ip)

  2,安装过程中选择了基础建设模式(infras...),(减少内存的消耗,但又保证基本的环境的模式)

  3,用户名root  密码 root
  4,网络配置使用了手动网络固定网络ip4地址(固定ip)

 2,linux基本环境配置:(操作都在root权限下进行的)

  1,验证网络服务:ping <主机ip>  主机 ping <虚拟机ip>  ping   验证ok

    备份ip地址:cp /etc/sysconfig/network-scripts/ifcfg-ens33 /etc/sysconfig/network-scripts/ifcfg-ens33.bak 

  2,防火墙设置:关闭并禁用防火墙

   关闭防火墙 systemctl stop firewalld.service(cetos7与前面系列的iptables不同)

      禁用防火墙:systemctl disable firewalld.service

      查看防火墙状态:firewall-cmd --state

  3,设置hosts,hostname,network

vim /etc/hostname
ha1

vim /etc/hosts
192.168.1.116    ha1
192.168.1.117    ha2
192.168.1.118    ha3
192.168.1.119    ha4

vim /etc/sysconfig/network
NETWORKING=yes
HOSTNAME=ha1

4,安装一些必要的包:(不一定全)

yum install -y chkconfig
yum install -y Python
yum install -y bind-utils
yum install -y psmisc
yum install -y libxslt
yum install -y zlib
yum install -y sqlite
yum install -y cyrus-sasl-plain
yum install -y cyrus-sasl-gssapi
yum install -y fuse
yum install -y portmap
yum install -y fuse-libs
yum install -y RedHat-lsb

5,安装Java和Scala

java版本:jdk-7u80-linux-x64.rpm
scala版本:scala-2.11.6.tgz

验证是否有java:
rpm -qa|grep java 无

tar -zxf jdk-8u111-linux-x64.tar.gz
tar -zxf scala-2.11.6.tgz
mv jdk1.8.0_111 /usr/java
mv scala-2.11.6 /usr/scala

配置环境变量:
vim /etc/profile
export JAVA_HOME=/usr/java
export SCALA_HOME=/usr/scala
export PATH=$JAVA_HOME/bin:$SCALA_HOME/bin:$PATH
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

 6,重启,验证上述是否设置  ok :重启  使用vm快照,命名为:初始化ok java,scala,主机名,防火墙,ip

 3,Hadoop+zookeeper集群配置

  1,集群机准备

    连接克隆:对ha1克隆出ha2,ha3,ha4

    对ha2,ha3,ha4修改网络地址,network,防火墙
    vim /etc/sysconfig/network-scripts/ifcfg-ens33
    116 117/118/119
    service network restart
    vim /etc/hostname
    vim /etc/sysconfig/network
    systemctl disable firewalld.service

    对ha2,ha3,ha4重启验证ip,网络,防火墙,分别对三台机快照,命名为:初始化ok java,scala,主机名,防火墙,ip

  2,集群框架图

机子

 

Namenode

 

DataNode

 

Zookeeper

 

ZkFC

 

JournalNode

 

RM

 

DM

 

Ha1

 

1

   

1

 

1

 

1

 

1

   

Ha2

 

1

 

1

 

1

 

1

 

1

   

1

 

Ha3

   

1

 

1

   

1

   

1

 

Ha4

   

1

         

1

 

  3,ssh通信: ok后  快照 ssh ok

四台机:
ssh-keygen -t rsa
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
chmod 600 ~/.ssh/authorized_keys

ha1下:
scp ~/.ssh/* root@ha2:~/.ssh/
scp ~/.ssh/* root@ha3:~/.ssh/
scp ~/.ssh/* root@ha4:~/.ssh/

验证:
ssh ha2/ha3/ha4

  4,zookeeper集群配置:

   1,配置环境变量

zook安装:
tar -zxf zookeeper-3.4.8.tar.gz
mv zookeeper-3.4.8 /usr/zookeeper-3.4.8
修改配置文件:
export ZK_HOME=/usr/zookeeper-3.4.8
scp /etc/profile root@ha2:/etc/
scp /etc/profile root@ha3:/etc/
source /etc/profile

   2,zoo.cfg配置(加粗修改出)

cd /usr/zookeeper-3.4.8/conf
cp zoo_sample.cfg zoo.cfg
内容:
# The number of milliseconds of each tick
tickTime=2000
# The number of ticks that the initial
# synchronization phase can take
initLimit=10
# The number of ticks that can pass between
# sending a request and getting an acknowledgement
syncLimit=5
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just
# example sakes.
dataDir=/opt/zookeeper/datas
dataLogDir=/opt/zookeeper/logs
# the port at which the clients will connect
clientPort=2181
# the maximum number of client connections.
# increase this if you need to handle more clients
#maxClientCnxns=60
#
# Be sure to read the maintenance section of the
# administrator guide before turning on autopurge.
#
# #sc_maintenance
#
# The number of snapshots to retain in dataDir
#autopurge.snapRetainCount=3
# Purge task interval in hours
# Set to "0" to disable auto purge feature
#autopurge.purgeInterval=1
server.1=ha1:2888:3888
server.2=ha2:2888:3888
server.3=ha3:2888:3888

   3,启动zookeeper集群:

#三台机(ha1,ha2,ha3)
新建文件夹:
mkdir -p /opt/zookeeper/datas
mkdir -p /opt/zookeeper/logs
cd /opt/zookeeper/datas
vim myid    写1/2/3

#分发给ha2,ha3(注意ha4不需要)
cd /usr
scp -r zookeeper-3.4.8 root@ha2:/usr
scp -r zookeeper-3.4.8 root@ha3:/usr
#启动(三台机)
cd $ZK_HOME/bin
zkServer.sh start
zkServer.sh status 一个leader和连个follower

  5,hadoop集群配置

   1,配置环境变量:

版本:hadoop-2.7.3.tar.gz

tar -zxf hadoop-2.7.3.tar.gz
mv hadoop2.7.3 /usr/hadoop2.7.3

export JAVA_HOME=/usr/java
export SCALA_HOME=/usr/scala
export HADOOP_HOME=/usr/hadoop-2.7.3
export PATH=$JAVA_HOME/bin:$SCALA_HOME/bin:$HADOOP_HOME/bin:$PATH
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
source /etc/profile

   2,hadoop.env.sh配置:

export JAVA_HOME=/usr/java source hadoop.env.sh hadoop version 验证ok

   3,hdfs-site.xml配置:后续修改后发送(scp hdfs-site.xml root@ha4:/usr/hadoop-2.7.3/etc/hadoop/)

vim hdfs-site.xml
<configuration>
    <property>
            <name>dfs.nameservices</name>
            <value>mycluster</value>
    </property>
    <property>
            <name>dfs.ha.namenodes.mycluster</name>
            <value>nn1,nn2</value>
    </property>
    <property>
            <name>dfs.namenode.rpc-address.mycluster.nn1</name>
            <value>ha1:9000</value>
    </property>
    <property>
            <name>dfs.namenode.rpc-address.mycluster.nn2</name>
            <value>ha2:9000</value>
    </property>
    <property>
            <name>dfs.namenode.http-address.mycluster.nn1</name>
            <value>ha1:50070</value>
    </property>
    <property>
            <name>dfs.namenode.http-address.mycluster.nn2</name>
            <value>ha2:50070</value>
    </property>
    <property>
            <name>dfs.namenode.shared.edits.dir</name>
            <value>qjournal://ha2:8485;ha3:8485;ha4:8485/mycluster</value>
    </property>
    <property>
            <name>dfs.client.failover.proxy.provider.mycluster</name>
            <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
    </property>
    <property>
            <name>dfs.ha.fencing.methods</name>
            <value>sshfence</value>
    </property>
    <property>
            <name>dfs.ha.fencing.ssh.private-key-files</name>
            <value>/root/.ssh/id_rsa</value>
    </property>
    <property>
            <name>dfs.journalnode.edits.dir</name>
            <value>/opt/jn/data</value>
    </property>
    <property>
            <name>dfs.ha.automatic-failover.enabled</name>
            <value>true</value>
    </property>
</configuration>

   4,core-site.xml配置

<configuration>
      <property>
                <name>fs.defaultFS</name>
                <value>hdfs://mycluster</value>
      </property>
      <property>
                <name>ha.zookeeper.quorum</name>
                <value>ha1:2181,ha2:2181,ha3:2181</value>
        </property>
      <property>
              <name>hadoop.tmp.dir</name>
              <value>/opt/hadoop2</value>
              <description>A base for other temporary  directories.</description>
      </property>
</configuration>

   5,yarn-site.xml配置

vim yarn-site.xml
<configuration>

<!-- Site specific YARN configuration properties -->
        <property>
              <name>yarn.nodemanager.aux-services</name>
              <value>mapreduce_shuffle</value>
        </property>
        <property>                                                             
                <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
                <value>org.apache.hadoop.mapred.ShuffleHandler</value>
        </property>
        <property>
              <name>yarn.resourcemanager.hostname</name>
              <value>ha1</value>
      </property>
</configuration>

   6,mapred-site.xml配置

<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> </configuration>

   7,slaves配置:

vim slaves ha2 ha3 ha4

   8,分发并启动:

#分发
scp -r hadoop-2.7.3 root@ha2:/usr/
scp -r hadoop-2.7.3 root@ha3:/usr/
scp -r hadoop-2.7.3 root@ha4:/usr/
#启动JN(在ha2,ha3,ha4)
cd sbin
./hadoop-daemon.sh start journalnode

[root@ha2 sbin]# jps
JournalNode
Jps
QuorumPeerMain(#zk启动的线程)

#ha1:namenode格式化
cd bin
./hdfs namenode -format
#zk格式化
./hdfs zkfc -formatZK
#可以查看cd /opt/hadoop2文件来查看元数据是否格式化正常

#ha2:namenode格式化
1,ha1要先启动namenode:
./hadoop-daemon.sh start namenode
2,ha2下
./hdfs namenode -bootstrapStandby

   9,验证::50070/验证 ok   快照 ha模式下的hadoop+zookeeper安装ok

#hdfs集群验证
[root@ha1 sbin]# ./stop-dfs.sh
Stopping namenodes on [ha1 ha2]
ha2: no namenode to stop
ha1: stopping namenode
ha2: no datanode to stop
ha3: no datanode to stop
ha4: no datanode to stop
Stopping journal nodes [ha2 ha3 ha4]
ha3: stopping journalnode
ha4: stopping journalnode
ha2: stopping journalnode
Stopping ZK Failover Controllers on NN hosts [ha1 ha2]
ha2: no zkfc to stop
ha1: no zkfc to stop
[root@ha1 sbin]# ./start-dfs.sh
ha1下:
[root@ha1 sbin]# jps
Jps
NameNode
QuorumPeerMain
DFSZKFailoverController
[root@ha2 dfs]# jps
NameNode
DFSZKFailoverController
Jps
DataNode
JournalNode
QuorumPeerMain
[root@ha3 sbin]# jps
QuorumPeerMain
DataNode
JournalNode
Jps
[root@ha4 sbin]# jps
Jps
DataNode
JournalNode

配置yarn和mapred
[root@ha1 sbin]# jps
NameNode
DFSZKFailoverController
Jps
QuorumPeerMain
ResourceManager
[root@ha2 hadoop]# jps
DataNode
NameNode
DFSZKFailoverController
JournalNode
NodeManager
Jps
QuorumPeerMain
[root@ha3 ~]# jps
QuorumPeerMain
DataNode
NodeManager
Jps
JournalNode
[root@ha4 ~]# jps
JournalNode
NodeManager
DataNode
Jps

内容版权声明:除非注明,否则皆为本站原创文章。

转载注明出处:https://www.heiqu.com/c578a5a5bcc8d868461ecb361f2db1fc.html