安装hadoop+zookeeper ha
前期工作配置好网络和主机名和关闭防火墙
chkconfig iptables off //关闭防火墙1.安装好java并配置好相关变量 (/etc/profile)
#java
export JAVA_HOME=/usr/java/jdk1.8.0_65
export JRE_HOME=$JAVA_HOME/jre
export PATH=$PATH:$JAVA_HOME/bin
export CLASSPATH=.:$JAVA_HOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar (最前面要有.)
保存退出
source /etc/profile2.设置好主机名和网络映射关系 (/etc/hosts)
// hadoop.master为namenode
// hadoop.slaver1/hadoop.slaver2/hadoop.slaver3 为datanode192.168.22.241 hadoop.master192.168.22.242 hadoop.slaver1192.168.22.243 hadoop.slaver2192.168.22.244 hadoop.slaver33.创建用户并创建密码(以root身份登陆) 1. useradd hadoop(或者其他用户名) 2. passwd hadoop (回车输入密码 两次) 3. su hadoop (使用hadoop用户登陆)
4.免密码登陆 1.安装ssh 具体百度 一般都自带有 2.创建在家目录底下创建.ssh目录(使用hadoop用户) mkdir ~/.ssh 3.创建公钥(namenode端运行)
ssh-keygen -t rsa
一路回车
最后会在~/.ssh目录下生成id_rsa、id_rsa.pub 其中前者是密钥 后者是公钥 4.将id_rsa.pub文件拷贝到slaver节点的相同用户.ssh目录下
scp -r id_rsa.pub 用户名@主机名:目标文件(含路径) 5.在各个子节点执行cat id_rsa.pub >> ~/.ssh/authorized_keys 6.设置权限
chmod 600 authorized_keys
cd ..
chmod 700 -R .ssh 7.注意此时还不能免密码 需在master 节点运行ssh slaver 输入密码后才能免密码5.安装zookeeper(三台 master slaver1 slaver2) 1.下载安装包 2.解压安装包
tar zxvf zookeeper-3.4.7.tar.gz 3.配置环境变量
#zookeeper
export ZOOKEEPER_HOME=/opt/zookeeper-3.4.7
export PATH=$PATH::$ZOOKEEPER_HOME/bin:$ZOOKEEPER_HOME/conf
保存退出
source /etc/profile 4.修改配置文件
cp zoo_sample.cfg zoo.cfg
vim zoo.cfg
####zoo.cfg####
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/opt/zookeeper-3.4.7/tmp/zookeeper (注意创建相关目录)
clientPort=2181
server.1=hadoop.master:2888:3888
server.2=hadoop.slaver1:2888:3888
server.3=hadoop.slaver2:2888:3888
参数说明:
tickTime: zookeeper中使用的基本时间单位, 毫秒值.
dataDir: 数据目录. 可以是任意目录.
dataLogDir: log目录, 同样可以是任意目录. 如果没有设置该参数, 将使用和dataDir相同的设置.
clientPort: 监听client连接的端口号.
initLimit: zookeeper集群中的包含多台server, 其中一台为leader, 集群中其余的server为follower.
syncLimit: 该参数配置leader和follower之间发送消息, 请求和应答的最大时间长度.
server.X=A:B:C 其中X是一个数字, 表示这是第几号server. A是该server所在的IP地址. B配置该server和集群中的leader交换消息所使用的端口. C配置选举leader时所使用的端口.
5.分发到各个节点中
scp -r /opt/zookeeper-3.4.7 hadoop@主机名:/opt 6.根据dataDir配置的目录下新建myid文件, 写入一个数字, 该数字表示这是第几号server
cd /opt/zookeeper-3.4.7/tmp/zookeeper
touch myid(如果是安装上述配置，则master为1 slaver1为2 slaver3) 7.常用命令
####启动/关闭/查看 zk#####
zkServer.sh start //集群中每台主机执行一次 zkServer.sh stop
zkServer.sh status
####查看/删除节点信息####
zkCli.sh
ls /
rmr /节点名称6.安装hadoop(四台机子 master slaver1 slaver2 slaver3 其中namenode有master和slaver1) 1.下载安装包 2.解压安装包 3.配置环境变量
#hadoop
export HADOOP_HOME=/opt/hadoop-2.5.2
export HADOOP_PREFIX=/opt/hadoop-2.5.2
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"
export JAVA_LIBRARY_PATH=$HADOOP_HOME/lib/native
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HADOOP_HOME/lib
export CLASSPATH=.:$CLASSPATH:$HADOOP_HOME/bin
保存退出
source /etc/profile 4.修改配置文件 1.创建相关目录
cd /opt/hadoop-2.5.2
mkdir logs
mkdir tmp 2.修改相关配置文件相关参数(core-site.xml/hadoop-env.sh/hdfs-site.xml/log4j.properties /mapred-env.sh/mapred-site.xml/masters/slaves/yarn-env.sh/yarn-site.xml)
####core-site.xml#### <configuration>
<!-- 指定hdfs的nameservice为namenode-->
<property>
<name>fs.defaultFS</name>
<value>hdfs://ns1:8020</value>
</property>
<!-- 指定hadoop块大小 -->
<property>
<name>io.file.buffer.size</name>
<value>131072</value>
</property>
<!-- 指定hadoop临时目录 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/opt/hadoop-2.5.2/tmp</value>
<description>A base for other temporary directories.</description>
</property>
<!-- 指定zookeeper地址 -->
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop.master:2181,hadoop.slaver1:2181,hadoop.slaver2:2181</value>
</property>
</configuration>
####hadoop-env.sh####
export JAVA_HOME=/usr/java/jdk1.8.0_65
export HADOOP_CLASSPATH=.:$HADOOP_CLASSPATH:$HADOOP_HOME/bin
export CLASSPATH=.:$CLASSPATH:$HADOOP_HOME/bin
####hdfs-site.xml#### <configuration>
<property>
<name>dfs.namenode.http-address</name>
<value>hadoop.master:50070</value>
<description>The address and the base port where the dfs namenode web ui will listen on.</description>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>hadoop.slaver1:50070</value>
</property>
<property>
<name>dfs.namenode.checkpoint.dir</name>
<value>file://${hadoop.tmp.dir}/dfs/namesecondary</value>
<final>true</final>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file://${hadoop.tmp.dir}/dfs/name</value>
<final>true</final>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file://${hadoop.tmp.dir}/dfs/data</value>
<final>true</final>
</property>
<property>
<name>dfs.replication</name>
<value>3</value>
</property>
<property>
<name>dfs.permissions</name>
<value>false</value>
</property>
<property>
<name>dfs.permissions.enabled</name>
<value>false</value>
</property>
<property>
<name>dfs.namenode.hosts.exclude</name>
<value>/opt/hadoop-2.5.2/other/excludes</value>
<description>Names a file that contains a list of hosts that are not permitted to connect to the namenode. The full pathname of the file must be specified. If the value is empty, no hosts are excluded.</description>
</property>
<property>
<name>dfs.namenode.hosts</name>
<value>/opt/hadoop-2.5.2/etc/hadoop/slaves</value>
</property>
<property>
<name>dfs.blocksize</name>
<value>134217728</value>
</property>
<!-- HBase configuration-->
<property>
<name>dfs.datanode.max.xcievers</name>
<value>4096</value>
</property>
<!--Zookeeper configuration-->
<property>
<name>dfs.nameservices</name>
<value>ns1</value>
</property>
<property>
<name>dfs.ha.namenodes.ns1</name>
<value>nn1,nn2</value>
</property>
<property>
<name>dfs.namenode.rpc-address.ns1.nn1</name>
<value>hadoop.master:8020</value>
</property>
<property>
<name>dfs.namenode.rpc-address.ns1.nn2</name>
<value>hadoop.slaver1:8020</value>
</property>
<property>
<name>dfs.namenode.http-address.ns1.nn1</name>
<value>hadoop.master:50070</value>
</property>
<property>
<name>dfs.namenode.http-address.ns1.nn2</name>
<value>hadoop.slaver1:50070</value>
</property>
<property>
<name>dfs.namenode.servicerpc-address.ns1.nn1</name>
<value>hadoop.master:53310</value>
</property>
<property>
<name>dfs.namenode.servicerpc-address.ns1.nn2</name>
<value>hadoop.slaver1:53310</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>/opt/zookeeper-3.4.7/journal</value>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://hadoop.master:8485;hadoop.slaver1:8485;hadoop.slaver2:8485/ns1</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.ns1</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<!-- 指定zookeeper地址 -->
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop.master:2181,hadoop.slaver1:2181,hadoop.slaver2:2181</value>
</property>
<!-- 配置隔离机制方法，多个机制用换行分割，即每个机制暂用-->
<property>
<name>dfs.ha.fencing.methods</name>
<value>
sshfence
shell(/bin/true) </value>
</property>
<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>
####log4j.properties####
hadoop.root.logger=INFO,console
hadoop.log.dir=/opt/hadoop-2.5.2/logs
hadoop.log.file=hadoop.log
####mapred-env.sh####
export HADOOP_JOB_HISTORYSERVER_HEAPSIZE=1000
export HADOOP_MAPRED_ROOT_LOGGER=INFO,RFA
####mapred-site.xml#### <configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.application.classpath</name>
<value>
/opt/hadoop-2.5.2/etc/hadoop, /opt/hadoop-2.5.2/share/hadoop/common/*,
/opt/hadoop-2.5.2/share/hadoop/common/lib/*,
/opt/hadoop-2.5.2/share/hadoop/hdfs/*,
/opt/hadoop-2.5.2/share/hadoop/hdfs/lib/*,
/opt/hadoop-2.5.2/share/hadoop/mapreduce/*,
/opt/hadoop-2.5.2/share/hadoop/mapreduce/lib/*,
/opt/hadoop-2.5.2/share/hadoop/yarn/*,
/opt/hadoop-2.5.2/share/hadoop/yarn/lib/*
</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>hadoop.master:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>hadoop.master:19888</value>
</property>
<property>
<name>mapreduce.jobhistory.done-dir</name>
<value>/history/done</value>
</property>
<property>
<name>mapreduce.jobhistory.intermediate-done-dir</name>
<value>/history/done_intermediate</value>
</property>
</configuration>
####masters####
hadoop.slaver1 //存储secondary namenode节点主机名
####slaves####
hadoop.slaver1
hadoop.slaver2
hadoop.slaver3
####yarn-env.sh####
export JAVA_HOME=/usr/java/jdk1.8.0_65
####yarn-site.xml####
<configuration>
<!-- Site specific YARN configuration properties -->
<property>
<name>yarn.resourcemanager.address</name>
<value>hadoop.master:18040</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>hadoop.master:18030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>hadoop.master:18025</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>hadoop.master:18041</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>hadoop.master:8088</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>/opt/hadoop-2.5.2/other/mynode</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/opt/hadoop-2.5.2/other/logs</value>
</property>
<property>
<name>yarn.nodemanager.log.retain-seconds</name>
<value>10800</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/opt/hadoop-2.5.2/other/logs</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir-suffix</name>
<value>logs</value>
</property>
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>-1</value>
</property>
<property>
<name>yarn.log-aggregation.retain-check-interval-seconds</name>
<value>-1</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<!--zookeeper-->
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>yrc</value>
</property>
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>hadoop.master</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>hadoop.slaver1</value>
</property>
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>hadoop.master:2181,hadoop.slaver1:2181,hadoop.slaver2:2181</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
</configuration>
5.分发到各个节点中
scp -r /opt/hadoop-2.5.2 hadoop@hadoop.master:/opt
6.首次启动
6.1 启动zk
zkServer.sh start(zk 各个节点执行)
6.2 启动journalnode
hadoop-daemon.sh start journalnode(zk 各个节点执行)
6.3 格式化Namenode
hadoop namenode -format(namenode 节点运行 注意是hadoop 不是hdfs)
6.4 启动Namenode
hadoop-daemon.sh start namenode(namenode 节点运行)
6.5 格式化另一个Namenode
hadoop namenode -bootstrapStandby(在secondary namenode节点运行)
6.6 格式化zk
hdfs zkfc -formatZK (namenode节点执行)
6.7 将所有的服务停止
stop-all.sh
注意此时需在每个zk节点执行 zkServer.sh stop
7.正常启动
1.启动zk
zkServer.sh start(zk 各个节点执行)
2.启动所有服务
start-all.sh //或者先执行start-dfs.sh 再执行start-yarn.sh
3.启动后台历史服务
mr-jobhistory-daemon.sh start historyserver(在namenode节点执行即可)
4.启动备份resourcemanger
yarn-daemon.sh start resourcemanager //在备份节点运行
5.启动备份namenode
hadoop-daemon.sh start namenode //在备份节点运行
8.验证
1.jps验证 查看相关进程
2.web验证
hdfs 主机名:50070
yarn 主机名:8088
history 主机名:19888
//以上主机名均指 namenode节点主机名 (此时namenode节点是active状态)
3.查看active状态
hdfs web查看 有active状态和stangby状态两种
yarn shell命令查看
yarn rmadmin -getServiceState rm1(或者rm2)
//其中rm1/rm2为配置文件中配置的名称
4.kill当前active的namenode 看能不自己切换到standby namenode上
9.常见命令
####启动/关闭yarn jobhistory记录####
web: //namenode:19888 //其中namenode 为集群任意节点主机名
mr-jobhistory-daemon.sh start historyserver //集群中每台主机执行一次
mr-jobhistory-daemon.sh stop historyserver
####启动/关闭/查看 zk#####
zkServer.sh start //集群中每台主机执行一次
zkServer.sh stop
zkServer.sh status
####启动/关闭/查看 yarn####
yarn-daemon.sh start resourcemanager
yarn-daemon.sh stop resourcemanager
yarn-daemon.sh stop nodemanager
yarn rmadmin -getServiceState rm2 //其中rm2是集群配置的别名
web: //namenode:8088 //其中namenode是active状态的主机名
####启动/关闭/查看 hadoop####
hadoop-daemon.sh start namenode
hadoop-daemon.sh stop namenode
hadoop-daemon.sh stop datanode
web: //namenode:50070 //其中namenode是active状态的主机名
####格式化zkNode####
hdfs zkfc -formatZK //namenode节点执行 注意是hdfs 不是hadoop
####启动/关闭zkNode#####
hadoop-daemon.sh start zkfc
hadoop-daemon.sh stop zkfc
####查看/删除job####
hadoop job -list
hadoop job -kill 任务ID //注意不是applicationID
####初始化Journal Storage Directory####
hdfs namenode -initializeSharedEdits //非ha转成ha时执行 如果一开始已经是ha了无需执行
####初始化namenode####
hadoop namenode -format //namenode端执行
hdfs namenode -bootstrapStandby //secend namenode端执行 执行前需保证namenode已经启动
10.常见异常
1.Journal Storage Directory /opt/zookeeper-3.4.7/journal/ns1 not formatted
原因：由于之前hadoop没部署ha,改成ha后形成错误
解决办法：
1.将配置文件hdfs-site.xml中dfs.journalnode.edits.dir对应的目录删除
2.hdfs namenode -initializeSharedEdits(namenode 执行)
2.datanode起来了,namenode起不来
解决办法:
1.查看配置文件相关配置项是否配置正确
2.查看环境变量是否配置正确
3.查看主机网络映射是否配置正确
4.是否二次格式化namenode 如果是,则需要将datanode 的clusterID和namespaceID改成namenode一致
目录一般是tmp目录下
5.重启hdfs
6.如果执行上述还不行,则在hadoop服务运行状态下将tmp目录下所有文件夹删除,再格式化,重启服务
3.两个namenode起来了,但都是standby状态
解决办法:
1.是否均启动zk
2.格式化zfkc
hdfs zkfc -formatZK
3.所有服务重启(含zk)
本文转自 chengxuyonghu 51CTO博客，原文链接：http://blog.51cto.com/6226001001/1895949，如需转载请自行联系原作者
