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)
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