hadoop+zookeeper高可用，yarn高可用，Hbase高可用集群部署_hadoop 的yarn的高可用-程序员宅基地
本篇博客基于上篇博客hadoop的配置：https://blog.csdn.net/aaaaaab_/article/details/82080751
实验环境：
搭建zookeeper集群：
[root@server1 ~]# /etc/init.d/nfs start 开启服务
[root@server1 ~]# showmount -e
Export list for server1:
/home/hadoop *
[root@server1 ~]# su - hadoop
[hadoop@server1 ~]$
[hadoop@server1 ~]$ ls
hadoop hadoop-2.7.3.tar.gz jdk1.7.0_79
hadoop-2.7.3 java jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ rm -fr /tmp/*
[hadoop@server1 ~]$ ls
hadoop java zookeeper-3.4.9.tar.gz
hadoop-2.7.3 jdk1.7.0_79
hadoop-2.7.3.tar.gz jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ tar zxf zookeeper-3.4.9.tar.gz 解压zookeeper包
配置server5作为高可用节点：
[root@server5 ~]# yum install nfs-utils -y 安装服务
[root@server5 ~]# /etc/init.d/rpcbind start 开启服务 [ OK ]
[root@server5 ~]# /etc/init.d/nfs start 开启nfs服务
[root@server5 ~]# useradd -u 800 hadoop
[root@server5 ~]# mount 172.25.38.1:/home/hadoop/ /home/hadoop/ 挂载
[root@server5 ~]# df 查看挂载
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/mapper/VolGroup-lv_root 19134332 929548 17232804 6% /
tmpfs 380140 0 380140 0% /dev/shm
/dev/vda1 495844 33478 436766 8% /boot
172.25.38.1:/home/hadoop/ 19134336 3289728 14872704 19% /home/hadoop
[root@server5 ~]# su - hadoop
[hadoop@server5 ~]$ ls
hadoop hadoop-2.7.3.tar.gz jdk1.7.0_79 主机均已经同步
hadoop-2.7.3 java jdk-7u79-linux-x64.tar.gz
[hadoop@server5 ~]$ rm -fr /tmp/*
配置从节点：
[root@server2 ~]# mount 172.25.38.1:/home/hadoop/ /home/hadoop/ 挂载
[root@server2 ~]# df 查看挂载
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/mapper/VolGroup-lv_root 19134332 1860136 16302216 11% /
tmpfs 251120 0 251120 0% /dev/shm
/dev/vda1 495844 33478 436766 8% /boot
172.25.38.1:/home/hadoop/ 19134336 3289728 14872704 19% /home/hadoop
[root@server2 ~]# rm -fr /tmp/*
[root@server2 ~]# su - hadoop
[hadoop@server2 ~]$ ls
hadoop java zookeeper-3.4.9
hadoop-2.7.3 jdk1.7.0_79 zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk-7u79-linux-x64.tar.gz
[hadoop@server2 ~]$ cd zookeeper-3.4.9
[hadoop@server2 zookeeper-3.4.9]$ ls
bin dist-maven LICENSE.txt src
build.xml docs NOTICE.txt zookeeper-3.4.9.jar
CHANGES.txt ivysettings.xml README_packaging.txt zookeeper-3.4.9.jar.asc
conf ivy.xml README.txt zookeeper-3.4.9.jar.md5
contrib lib recipes zookeeper-3.4.9.jar.sha1
[hadoop@server2 zookeeper-3.4.9]$ cd conf/
[hadoop@server2 conf]$ ls
configuration.xsl log4j.properties zoo_sample.cfg
添加从节点信息：
[hadoop@server2 conf]$ cp zoo_sample.cfg zoo.cfg
[hadoop@server2 conf]$ vim zoo.cfg
[hadoop@server2 conf]$ cat zoo.cfg | tail -n 3
server.1=172.25.38.2:2888:3888
server.2=172.25.38.3:2888:3888
server.3=172.25.38.4:2888:3888
[hadoop@server2 conf]$ mkdir /tmp/zookeeper
[hadoop@server2 conf]$ cd /tmp/zookeeper/
[hadoop@server2 zookeeper]$ ls
[hadoop@server2 zookeeper]$ echo 1 > myid
[hadoop@server2 zookeeper]$ ls
myid
[hadoop@server2 zookeeper]$ cd
[hadoop@server2 ~]$ cd zookeeper-3.4.9/conf/
[hadoop@server2 conf]$ ls
configuration.xsl log4j.properties zoo.cfg zoo_sample.cfg
[hadoop@server2 conf]$ cd ..
[hadoop@server2 zookeeper-3.4.9]$ cd bin/
各节点配置文件相同,并且需要在/tmp/zookeeper 目录中创建 myid 文件,写入一个唯一的数字,取值范围在 1-255。
[hadoop@server2 zookeeper-3.4.9]$ cd bin/
[hadoop@server2 bin]$ ls
README.txt zkCli.cmd zkEnv.cmd zkServer.cmd
zkCleanup.sh zkCli.sh zkEnv.sh zkServer.sh
[hadoop@server2 bin]$ ./zkServer.sh start 开启服务
依次按照同样的方法配置其他节点：
[root@server3 ~]# mount 172.25.38.1:/home/hadoop/ /home/hadoop/
[root@server3 ~]# df
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/mapper/VolGroup-lv_root 19134332 1537052 16625300 9% /
tmpfs 251124 0 251124 0% /dev/shm
/dev/vda1 495844 33478 436766 8% /boot
172.25.38.1:/home/hadoop/ 19134336 3289728 14872704 19% /home/hadoop
[root@server3 ~]# rm -fr /tmp/*
[root@server3 ~]# su - hadoop
[hadoop@server3 ~]$ ls
hadoop java zookeeper-3.4.9
hadoop-2.7.3 jdk1.7.0_79 zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk-7u79-linux-x64.tar.gz
[hadoop@server3 ~]$ mkdir /tmp/zookeeper
[hadoop@server3 ~]$ cd /tmp/zookeeper/
[hadoop@server3 zookeeper]$ ls
[hadoop@server3 zookeeper]$ echo 2 > myid
[hadoop@server3 zookeeper]$ cd
[hadoop@server3 ~]$ cd zookeeper-3.4.9/bin/
[hadoop@server3 bin]$ ls
README.txt zkCli.cmd zkEnv.cmd zkServer.cmd zookeeper.out
zkCleanup.sh zkCli.sh zkEnv.sh zkServer.sh
[hadoop@server3 bin]$ ./zkServer.sh start
[root@server4 ~]# mount 172.25.38.1:/home/hadoop/ /home/hadoop/
[root@server4 ~]# df
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/mapper/VolGroup-lv_root 19134332 1350656 16811696 8% /
tmpfs 251124 0 251124 0% /dev/shm
/dev/vda1 495844 33478 436766 8% /boot
172.25.38.1:/home/hadoop/ 19134336 3289728 14872704 19% /home/hadoop
[root@server4 ~]# rm -fr /tmp/*
[root@server4 ~]# su - hadoop
[hadoop@server4 ~]$ mkdir /tmp/zookeeper
[hadoop@server4 ~]$ cd /tmp/zookeeper/
[hadoop@server4 zookeeper]$ ls
[hadoop@server4 zookeeper]$ echo 3 >myid
[hadoop@server4 zookeeper]$ ls
myid
[hadoop@server4 zookeeper]$ cd
[hadoop@server4 ~]$ cd zookeeper-3.4.9/bin/
[hadoop@server4 bin]$ ./zkServer.sh start
ZooKeeper JMX enabled by default
在server2进入命令行：
[hadoop@server2 bin]$ ls
README.txt zkCli.cmd zkEnv.cmd zkServer.cmd zookeeper.out
zkCleanup.sh zkCli.sh zkEnv.sh zkServer.sh
[hadoop@server2 bin]$ pwd
/home/hadoop/zookeeper-3.4.9/bin
[hadoop@server2 bin]$ ./zkCli.sh 连接zookeeper
[zk: localhost:2181(CONNECTED) 0] ls /
[zookeeper]
[zk: localhost:2181(CONNECTED) 1] ls /zookeeper
[quota]
[zk: localhost:2181(CONNECTED) 2] ls /zookeeper/quota
[]
[zk: localhost:2181(CONNECTED) 3] get /zookeeper/quota
cZxid = 0x0
ctime = Thu Jan 01 08:00:00 CST 1970
mZxid = 0x0
mtime = Thu Jan 01 08:00:00 CST 1970
pZxid = 0x0
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 0
numChildren = 0
进行hadoop的配置详解：
[hadoop@server1 ~]$ ls
hadoop java zookeeper-3.4.9
hadoop-2.7.3 jdk1.7.0_79 zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ cd hadoop/etc/hadoop/
[hadoop@server1 hadoop]$ vim core-site.xml
<configuration>
指定 hdfs 的 namenode 为 masters (名称可自定义)
<property>
<name>fs.defaultFS</name>
<value>hdfs://masters</value>
</property>
<property>
指定 zookeeper 集群主机地址
<name>ha.zookeeper.quorum</name>
<value>172.25.38.2:2181,172.25.38.3:2181,172.25.38.4:2181</value>
</property>
</configuration>
[hadoop@server1 hadoop]$ vim hdfs-site.xml
[hadoop@server1 hadoop]$ cat hdfs-site.xml | tail -n 74
<configuration>
<property>
<name>dfs.replication</name>
<value>3</value>
</property>
<property>
指定 hdfs 的 nameservices 为 masters,和 core-site.xml 文件中的设置保持一致
<name>dfs.nameservices</name>
<value>masters</value>
</property>
masters 下面有两个 namenode 节点,分别是 h1 和 h2
<property>
<name>dfs.ha.namenodes.masters</name>
<value>h1,h2</value>
</property>
指定 h1 节点的 rpc 通信地址
<property>
<name>dfs.namenode.rpc-address.masters.h1</name>
<value>172.25.38.1:9000</value>
</property>
指定 h1 节点的 http 通信地址
<property>
<name>dfs.namenode.http-address.masters.h1</name>
<value>172.25.38.1:50070</value>
</property>
指定 h2 节点的 rpc 通信地址
<property>
<name>dfs.namenode.rpc-address.masters.h2</name>
<value>172.25.38.5:9000</value>
</property>
指定 h2 节点的 http 通信地址
<property>
<name>dfs.namenode.http-address.masters.h2</name>
<value>172.25.38.5:50070</value>
</property>
指定 NameNode 元数据在 JournalNode 上的存放位置
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://172.25.38.2:8485;172.25.38.3:8485;172.25.38.4:8485/masters</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>/tmp/journaldata</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.masters</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
配置隔离机制方法,每个机制占用一行
<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 免密码
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/home/hadoop/.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>[hadoop@server1 hadoop]$ pwd
/home/hadoop/hadoop/etc/hadoop
[hadoop@server1 hadoop]$ vim slaves
[hadoop@server1 hadoop]$ cat slaves
172.25.38.2
172.25.38.3
172.25.38.4
启动 hdfs 集群(按顺序启动)在三个 DN 上依次启动 zookeeper 集群
在三个 DN 上依次启动 journalnode(第一次启动 hdfs 必须先启动 journalnode)
[hadoop@server2 hadoop]$ pwd
/home/hadoop/hadoop
[hadoop@server2 hadoop]$ ls
bigfile etc input libexec logs output sbin
bin include lib LICENSE.txt NOTICE.txt README.txt share
[hadoop@server2 hadoop]$ sbin/hadoop-daemon.sh start journalnode
starting journalnode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-hadoop-journalnode-server2.out
[hadoop@server2 hadoop]$ jps
1459 JournalNode
1508 Jps
1274 QuorumPeerMain
测试与server5的免密连接，传递配置文件搭建高可用：
[hadoop@server1 hadoop]$ pwd
/home/hadoop/hadoop
[hadoop@server1 hadoop]$ ls
bigfile etc input libexec logs output sbin
bin include lib LICENSE.txt NOTICE.txt README.txt share
[hadoop@server1 hadoop]$ bin/hdfs namenode -format
[hadoop@server1 hadoop]$ ssh server5
[hadoop@server5 ~]$ exit
logout
Connection to server5 closed.
[hadoop@server1 hadoop]$ ssh 172.25.38.5
Last login: Tue Aug 28 10:40:53 2018 from server1
[hadoop@server5 ~]$ exit
logout
Connection to 172.25.38.5 closed.
[hadoop@server1 hadoop]$ scp -r /tmp/hadoop-hadoop/ 172.25.38.5:/tmp/
fsimage_0000000000000000000 100% 353 0.3KB/s 00:00
VERSION 100% 202 0.2KB/s 00:00
seen_txid 100% 2 0.0KB/s 00:00
fsimage_0000000000000000000.md5 100% 62 0.1KB/s 00:00 
格式化 zookeeper (只需在 h1 上执行即可)
[hadoop@server1 hadoop]$ ls
bigfile etc input libexec logs output sbin
bin include lib LICENSE.txt NOTICE.txt README.txt share
[hadoop@server1 hadoop]$ bin/hdfs zkfc -formatZK启动 hdfs 集群(只需在 h1 上执行即可)
[hadoop@server1 hadoop]$ sbin/start-dfs.sh 免密没有做好的话需要卡住的时候输入yes
在server2进入命令行：
[hadoop@server2 ~]$ ls
hadoop hadoop-2.7.3.tar.gz jdk1.7.0_79 zookeeper-3.4.9
hadoop-2.7.3 java jdk-7u79-linux-x64.tar.gz zookeeper-3.4.9.tar.gz
[hadoop@server2 ~]$ cd zookeeper-3.4.9
[hadoop@server2 zookeeper-3.4.9]$ ls
bin dist-maven LICENSE.txt src
build.xml docs NOTICE.txt zookeeper-3.4.9.jar
CHANGES.txt ivysettings.xml README_packaging.txt zookeeper-3.4.9.jar.asc
conf ivy.xml README.txt zookeeper-3.4.9.jar.md5
contrib lib recipes zookeeper-3.4.9.jar.sha1
[hadoop@server2 zookeeper-3.4.9]$ bin/zkCli.sh
[zk: localhost:2181(CONNECTED) 0] ls /
[zookeeper, hadoop-ha]
[zk: localhost:2181(CONNECTED) 1] ls /hadoop-ha
[masters]
[zk: localhost:2181(CONNECTED) 2] ls
[zk: localhost:2181(CONNECTED) 3] ls /hadoop-ha/masters
[ActiveBreadCrumb, ActiveStandbyElectorLock]
[zk: localhost:2181(CONNECTED) 4] ls /hadoop-ha/masters/Active
ActiveBreadCrumb ActiveStandbyElectorLock
[zk: localhost:2181(CONNECTED) 4] ls /hadoop-ha/masters/ActiveBreadCrumb
[]
[zk: localhost:2181(CONNECTED) 5] get /hadoop-ha/masters/ActiveBreadCrumb
mastersh2server5 �F(�> 当前master为server5
cZxid = 0x10000000a
ctime = Tue Aug 28 10:46:47 CST 2018
mZxid = 0x10000000a
mtime = Tue Aug 28 10:46:47 CST 2018
pZxid = 0x10000000a
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 28
numChildren = 0
查看主从节点进程：
在网页查看server1和server5的状态，一个为active，一个为standby
测试故障自动切换：
[hadoop@server5 ~]$ ls
hadoop hadoop-2.7.3.tar.gz jdk1.7.0_79 zookeeper-3.4.9
hadoop-2.7.3 java jdk-7u79-linux-x64.tar.gz zookeeper-3.4.9.tar.gz
[hadoop@server5 ~]$ cd hadoop
[hadoop@server5 hadoop]$ ls
bigfile etc input libexec logs output sbin
bin include lib LICENSE.txt NOTICE.txt README.txt share
[hadoop@server5 hadoop]$ bin/hdfs dfs -mkdir /user
[hadoop@server5 hadoop]$ bin/hdfs dfs -mkdir /user/hadoop
[hadoop@server5 hadoop]$ bin/hdfs dfs -ls
[hadoop@server5 hadoop]$ bin/hdfs dfs -put etc/hadoop/ input
[hadoop@server5 hadoop]$ bin/hdfs dfs -ls
Found 1 items
drwxr-xr-x - hadoop supergroup 0 2018-08-28 10:59 input
[hadoop@server5 hadoop]$ jps
1479 DFSZKFailoverController
1382 NameNode
1945 Jps
[hadoop@server5 hadoop]$ kill -9 1382 直接结束进程
在server2的命令行查看：
[zk: localhost:2181(CONNECTED) 6] get /hadoop-ha/masters/ActiveBreadCrumb
mastersh1server1 �F(�> master已经变成了server1
cZxid = 0x10000000a
ctime = Tue Aug 28 10:46:47 CST 2018
mZxid = 0x10000000f
mtime = Tue Aug 28 11:00:22 CST 2018
pZxid = 0x10000000a
cversion = 0
dataVersion = 1
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 28
numChildren = 0
[hadoop@server5 hadoop]$ pwd
/home/hadoop/hadoop
[hadoop@server5 hadoop]$ jps
1479 DFSZKFailoverController
1991 Jps
[hadoop@server5 hadoop]$ sbin/hadoop-daemon.sh start namenode 恢复节点
starting namenode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-hadoop-namenode-server5.out
[hadoop@server5 hadoop]$ jps 查看进程已经恢复
1479 DFSZKFailoverController
2020 NameNode
2100 Jps
yarn 的高可用
[hadoop@server1 hadoop]$ ls
bigfile etc input libexec logs output sbin
bin include lib LICENSE.txt NOTICE.txt README.txt share
[hadoop@server1 hadoop]$ pwd
/home/hadoop/hadoop
[hadoop@server1 hadoop]$ cd etc/hadoop/
[hadoop@server1 hadoop]$ cp mapred-site.xml.template mapred-site.xml
[hadoop@server1 hadoop]$ vim mapred-site.xml
[hadoop@server1 hadoop]$ cat mapred-site.xml | tail -n 8
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>
[hadoop@server1 hadoop]$ vim mapred-site.xml
[hadoop@server1 hadoop]$ cat mapred-site.xml | tail -n 8
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>
[hadoop@server1 hadoop]$ vim yarn-site.xml
[hadoop@server1 hadoop]$ cat yarn-site.xml | tail -n 48
<configuration>
配置可以在 nodemanager 上运行 mapreduce 程序
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
激活 RM 高可用
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
指定 RM 的集群 id
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>RM_CLUSTER</value>
</property>
定义 RM 的节点
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
指定 RM1 的地址
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>172.25.38.1</value>
</property>
指定 RM2 的地址
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>172.25.38.5</value>
</property>
激活 RM 自动恢复
<property>
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
配置 RM 状态信息存储方式,有 MemStore 和 ZKStore
<property>
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
配置为 zookeeper 存储时,指定 zookeeper 集群的地址
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>172.25.38.2:2181,172.25.38.3:2181,172.25.38.4:2181</value>
</property>
</configuration>启动 yarn 服务
[hadoop@server1 hadoop]$ cd ..
[hadoop@server1 etc]$ cd ..
[hadoop@server1 hadoop]$ pwd
/home/hadoop/hadoop
[hadoop@server1 hadoop]$ sbin/start-yarn.sh
[hadoop@server1 hadoop]$ jps
1606 NameNode
2409 Jps
1900 DFSZKFailoverController
2335 ResourceManager
[hadoop@server4 hadoop]$ jps
1407 DataNode
1645 NodeManager
1205 QuorumPeerMain
1316 JournalNode
1759 Jps
server5需要手动启动：
[hadoop@server5 ~]$ ls
hadoop hadoop-2.7.3.tar.gz jdk1.7.0_79 zookeeper-3.4.9
hadoop-2.7.3 java jdk-7u79-linux-x64.tar.gz zookeeper-3.4.9.tar.gz
[hadoop@server5 ~]$ cd hadoop
[hadoop@server5 hadoop]$ sbin/yarn-daemon.sh start
[hadoop@server5 hadoop]$ jps
1479 DFSZKFailoverController
2762 Jps
2020 NameNode
2711 ResourceManager
重点内容在网页查看server1状态：
在server2的命令行查看当前master：
[hadoop@server2 zookeeper-3.4.9]$ bin/zkCli.sh
[zk: localhost:2181(CONNECTED) 0]
[zk: localhost:2181(CONNECTED) 0]
[zk: localhost:2181(CONNECTED) 0] ls /
[zookeeper, yarn-leader-election, hadoop-ha, rmstore]
[zk: localhost:2181(CONNECTED) 1] ls /yarn-leader-election
[RM_CLUSTER]
[zk: localhost:2181(CONNECTED) 2] ls /yarn-leader-election/RM_CLUSTER
[ActiveBreadCrumb, ActiveStandbyElectorLock]
[zk: localhost:2181(CONNECTED) 3] ls /yarn-leader-election/RM_CLUSTER/Active
ActiveBreadCrumb ActiveStandbyElectorLock
[zk: localhost:2181(CONNECTED) 3] ls /yarn-leader-election/RM_CLUSTER/ActiveBreadCrumb
[]
[zk: localhost:2181(CONNECTED) 4] get /yarn-leader-election/RM_CLUSTER/ActiveBreadCrumb
RM_CLUSTERrm1
cZxid = 0x100000016
ctime = Tue Aug 28 11:58:18 CST 2018
mZxid = 0x100000016
mtime = Tue Aug 28 11:58:18 CST 2018
pZxid = 0x100000016
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 17
numChildren = 0
在网页分别访问server1为当前master：
进行故障切换检测：
[hadoop@server1 hadoop]$ jps
1606 NameNode
1900 DFSZKFailoverController
2829 Jps
2335 ResourceManager
[hadoop@server1 hadoop]$ kill -9 2335 结束当前master进程
[hadoop@server1 hadoop]$ jps
1606 NameNode
2839 Jps
1900 DFSZKFailoverController
在网页查看server5变成了master：
恢复server1的服务：
[hadoop@server1 hadoop]$ ls
bigfile etc input libexec logs output sbin
bin include lib LICENSE.txt NOTICE.txt README.txt share
[hadoop@server1 hadoop]$ pwd
/home/hadoop/hadoop
[hadoop@server1 hadoop]$ sbin/yarn-daemon.sh start resourcemanager
starting resourcemanager, logging to /home/hadoop/hadoop-2.7.3/logs/yarn-hadoop-resourcemanager-server1.out
[hadoop@server1 hadoop]$ jps
2897 ResourceManager
1606 NameNode
1900 DFSZKFailoverController
2926 Jps
网页查看server1的状态为standby，作为备用节点：
hbase高可用
[hadoop@server1 ~]$ ls
hadoop hbase-1.2.4-bin.tar.gz jdk-7u79-linux-x64.tar.gz
hadoop-2.7.3 java zookeeper-3.4.9
hadoop-2.7.3.tar.gz jdk1.7.0_79 zookeeper-3.4.9.tar.gz
[hadoop@server1 ~]$ tar zxf hbase-1.2.4-bin.tar.gz 解压包
[hadoop@server1 ~]$ ls
hadoop hbase-1.2.4-bin.tar.gz zookeeper-3.4.9
hadoop-2.7.3 java zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk1.7.0_79
hbase-1.2.4 jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ cd hbase-1.2.4
[hadoop@server1 hbase-1.2.4]$ ls
bin conf hbase-webapps lib NOTICE.txt
CHANGES.txt docs LEGAL LICENSE.txt README.txt
[hadoop@server1 hbase-1.2.4]$ cd conf/
[hadoop@server1 conf]$ ls
hadoop-metrics2-hbase.properties hbase-env.sh hbase-site.xml regionservers
hbase-env.cmd hbase-policy.xml log4j.properties
[hadoop@server1 conf]$ vim hbase-env.sh
export JAVA_HOME=/home/hadoop/java 指定 jdk
export HBASE_MANAGES_ZK=false 默认值时 true,hbase 在启动时自
动开启 zookeeper,如需自己维护 zookeeper集群需设置为 false
export HADOOP_HOME=/home/hadoop/hadoop 指定 hadoop 目录,否则 hbase
无法识别 hdfs 集群配置。
[hadoop@server1 conf]$ vim hbase-site.xml
[hadoop@server1 conf]$ cat hbase-site.xml | tail -n 22
指定 region server 的共享目录,用来持久化 HBase。这里指定的 HDFS 地址
是要跟 core-site.xml 里面的 fs.defaultFS 的 HDFS 的 IP 地址或者域名、端口必须一致
<property>
<name>hbase.rootdir</name>
<value>hdfs://masters/hbase</value>
</property>
启用 hbase 分布式模式
<property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
Zookeeper 集群的地址列表,用逗号分割。默认是 localhost,是给伪分布式用
的。要修改才能在完全分布式的情况下使用。
<property>
<name>hbase.zookeeper.quorum</name>
<value>172.25.38.2,172.25.38.3,172.25.38.4</value>
</property>
指定 hbase 的 master
<property>
<name>hbase.master</name>
<value>h1</value>
</property>
</configuration>
[hadoop@server1 conf]$ vim regionservers
[hadoop@server1 conf]$ cat regionservers
172.25.38.2
172.25.38.3
172.25.38.4
启动 hbase主节点运行:
[hadoop@server1 hbase-1.2.4]$ ls
bin conf hbase-webapps lib logs README.txt
CHANGES.txt docs LEGAL LICENSE.txt NOTICE.txt
[hadoop@server1 hbase-1.2.4]$ bin/start-hbase.sh
[hadoop@server1 hbase-1.2.4]$ jps
2897 ResourceManager
1606 NameNode
3451 Jps
1900 DFSZKFailoverController
在server2命令行查看：
[hadoop@server2 bin]$ ./zkCli.sh
[zk: localhost:2181(CONNECTED) 2] ls /
[zookeeper, yarn-leader-election, hadoop-ha, hbase, rmstore]
[zk: localhost:2181(CONNECTED) 3] ls /habase
Node does not exist: /habase
[zk: localhost:2181(CONNECTED) 4] ls /hbase/master
[]
[zk: localhost:2181(CONNECTED) 5] get /hbase/master
�master:16000L��S���PBUF
server1�}����,�} 当前master为server1
cZxid = 0x100000278
ctime = Tue Aug 28 13:30:52 CST 2018
mZxid = 0x100000278
mtime = Tue Aug 28 13:30:52 CST 2018
pZxid = 0x100000278
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x3657e35d7150005
dataLength = 55
numChildren = 0
备节点运行:
[hadoop@server5 ~]$ ls
hadoop hbase-1.2.4-bin.tar.gz zookeeper-3.4.9
hadoop-2.7.3 java zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk1.7.0_79
hbase-1.2.4 jdk-7u79-linux-x64.tar.gz
[hadoop@server5 ~]$ cd hbase-1.2.4
[hadoop@server5 hbase-1.2.4]$ ls
bin conf hbase-webapps lib logs README.txt
CHANGES.txt docs LEGAL LICENSE.txt NOTICE.txt
[hadoop@server5 hbase-1.2.4]$ bin/hbase-daemon.sh start master
starting master, logging to /home/hadoop/hbase-1.2.4/bin/../logs/hbase-hadoop-master-server5.out
[hadoop@server5 hbase-1.2.4]$ jps
1479 DFSZKFailoverController
2020 NameNode
2711 ResourceManager
3978 Jps
在网页查看server1为master，server5为backup master：
HBase Master 默认端口时 16000,还有个 web 界面默认在 Master 的 16010 端口
上,HBase RegionServers 会默认绑定 16020 端口,在端口 16030 上有一个展示
信息的界面
测试故障切换：
[hadoop@server1 ~]$ ls
hadoop hbase-1.2.4-bin.tar.gz zookeeper-3.4.9
hadoop-2.7.3 java zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk1.7.0_79
hbase-1.2.4 jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ cd hbase-1.2.4
[hadoop@server1 hbase-1.2.4]$ ls
bin conf hbase-webapps lib logs README.txt
CHANGES.txt docs LEGAL LICENSE.txt NOTICE.txt
[hadoop@server1 hbase-1.2.4]$ bin/hbase shell 打开一个shell
hbase(main):004:0> create 'linux', 'cf'
0 row(s) in 18.6610 seconds
=> Hbase::Table - linux
hbase(main):005:0> list 'linux'
TABLE
linux
1 row(s) in 0.0290 seconds
=> ["linux"]
hbase(main):006:0> put 'linux', 'row1', 'cf:a', 'value1'
0 row(s) in 1.6750 seconds
hbase(main):007:0> put 'linux', 'row2', 'cf:b', 'value2'
0 row(s) in 0.1740 seconds
hbase(main):008:0> put 'linux', 'row3', 'cf:c', 'value3'
0 row(s) in 0.0470 seconds
hbase(main):009:0> scan 'linux' 创建字段信息
ROW COLUMN+CELL
row1 column=cf:a, timestamp=1535435781214, value=value1
row2 column=cf:b, timestamp=1535435793162, value=value2
row3 column=cf:c, timestamp=1535435801252, value=value3
3 row(s) in 0.2010 seconds
[hadoop@server1 ~]$ ls
hadoop hbase-1.2.4-bin.tar.gz zookeeper-3.4.9
hadoop-2.7.3 java zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk1.7.0_79
hbase-1.2.4 jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ cd hadoop
[hadoop@server1 hadoop]$ bin/hdfs dfs -ls
Found 1 items
drwxr-xr-x - hadoop supergroup 0 2018-08-28 10:59 input
[hadoop@server1 hadoop]$ bin/hdfs dfs -ls /
Found 2 items
drwxr-xr-x - hadoop supergroup 0 2018-08-28 13:35 /hbase
drwxr-xr-x - hadoop supergroup 0 2018-08-28 10:59 /user
[hadoop@server1 hadoop]$ jps
5152 Jps
2897 ResourceManager
3829 HMaster
1606 NameNode
[hadoop@server1 hadoop]$ kill -9 3829 结束进程
[hadoop@server1 hadoop]$ jps
5200 Jps
2897 ResourceManager
5185 GetJavaProperty
1606 NameNode
在网页查看server5接管成为新的master：
在server2的命令行也可以看到server5成为了master：
[zk: localhost:2181(CONNECTED) 0] ls /
[zookeeper, yarn-leader-election, hadoop-ha, hbase, rmstore]
[zk: localhost:2181(CONNECTED) 1] ls /hbase/master
[]
[zk: localhost:2181(CONNECTED) 2] get /hbase/master
�master:16000�2V��Ex�PBUF
server5�}�����,�}
cZxid = 0x1000003c8
ctime = Tue Aug 28 13:58:59 CST 2018
mZxid = 0x1000003c8
mtime = Tue Aug 28 13:58:59 CST 2018
pZxid = 0x1000003c8
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x2657e356bc6000d
dataLength = 55
numChildren = 0
在server1可以查看字段信息：
[hadoop@server1 ~]$ ls
hadoop hbase-1.2.4-bin.tar.gz zookeeper-3.4.9
hadoop-2.7.3 java zookeeper-3.4.9.tar.gz
hadoop-2.7.3.tar.gz jdk1.7.0_79
hbase-1.2.4 jdk-7u79-linux-x64.tar.gz
[hadoop@server1 ~]$ cd hbase-1.2.4
[hadoop@server1 hbase-1.2.4]$ bin/hbase shell
hbase(main):001:0> scan 'linux'
ROW COLUMN+CELL
row1 column=cf:a, timestamp=1535435781214, value=value1
row2 column=cf:b, timestamp=1535435793162, value=value2
row3 column=cf:c, timestamp=1535435801252, value=value3
3 row(s) in 0.5400 seconds
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