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 www.baidu.ok 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. # # http://zookeeper.apache.org/doc/current/zookeeperAdmin.html#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 2646 JournalNode 2695 Jps 2287 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：http://192.168.1.116:50070/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 3506 Jps 3140 NameNode 2255 QuorumPeerMain 3439 DFSZKFailoverController [root@ha2 dfs]# jps 31264 NameNode 31556 DFSZKFailoverController 31638 Jps 31336 DataNode 31436 JournalNode 2287 QuorumPeerMain [root@ha3 sbin]# jps 2290 QuorumPeerMain 31074 DataNode 31173 JournalNode 31242 Jps [root@ha4 sbin]# jps 31153 Jps 30986 DataNode 31084 JournalNode
配置yarn和mapred [root@ha1 sbin]# jps 4614 NameNode 4920 DFSZKFailoverController 5356 Jps 2255 QuorumPeerMain 5103 ResourceManager [root@ha2 hadoop]# jps 32320 DataNode 32243 NameNode 32548 DFSZKFailoverController 32423 JournalNode 32713 NodeManager 32813 Jps 2287 QuorumPeerMain [root@ha3 ~]# jps 2290 QuorumPeerMain 31495 DataNode 31736 NodeManager 31885 Jps 31598 JournalNode [root@ha4 ~]# jps 31505 JournalNode 31641 NodeManager 31404 DataNode 31790 Jps