安装hadoop+zookeeper

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/profile

2.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datanode

192.168.22.241 hadoop.master
192.168.22.242 hadoop.slaver1
192.168.22.243 hadoop.slaver2
192.168.22.244 hadoop.slaver3

3.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####
            
            
            
                fs.defaultFS
                hdfs://ns1:8020
            
            
             
            
                io.file.buffer.size
                131072
            
            
             
            
                hadoop.tmp.dir
                /opt/hadoop-2.5.2/tmp
                A base for other temporary directories.
            
            
            
            
                ha.zookeeper.quorum
                hadoop.master:2181,hadoop.slaver1:2181,hadoop.slaver2:2181
            
            
            
            ####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####
            
            
            dfs.namenode.http-address
            hadoop.master:50070
            The address and the base port where the dfs namenode web ui will listen on.
            

            
            dfs.namenode.secondary.http-address
            hadoop.slaver1:50070
            

            
            dfs.namenode.checkpoint.dir
            file://${hadoop.tmp.dir}/dfs/namesecondary
            <final>truefinal>
            

            
            dfs.namenode.name.dir
            file://${hadoop.tmp.dir}/dfs/name
            <final>truefinal>
            

            
            dfs.datanode.data.dir
            file://${hadoop.tmp.dir}/dfs/data
            <final>truefinal>
            

            
            dfs.replication
            3
            

            
            dfs.permissions
            false
            

            
            dfs.permissions.enabled
            false
            

            
            dfs.namenode.hosts.exclude
            /opt/hadoop-2.5.2/other/excludes
            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.
            

            
            dfs.namenode.hosts
            /opt/hadoop-2.5.2/etc/hadoop/slaves
            

            
            dfs.blocksize
            134217728
            

            
             
            dfs.datanode.max.xcievers 
            4096 
            


            
            
            dfs.nameservices
            ns1
            

            
            dfs.ha.namenodes.ns1
            nn1,nn2
            

            
            dfs.namenode.rpc-address.ns1.nn1
            hadoop.master:8020
            

            
            dfs.namenode.rpc-address.ns1.nn2
            hadoop.slaver1:8020
            

            
            dfs.namenode.http-address.ns1.nn1
            hadoop.master:50070
            

            
            dfs.namenode.http-address.ns1.nn2
            hadoop.slaver1:50070
            
            
            
            dfs.namenode.servicerpc-address.ns1.nn1
            hadoop.master:53310
            
            
            dfs.namenode.servicerpc-address.ns1.nn2
            hadoop.slaver1:53310
            

             
            
            dfs.journalnode.edits.dir
            /opt/zookeeper-3.4.7/journal
            


            
            dfs.namenode.shared.edits.dir
            qjournal://hadoop.master:8485;hadoop.slaver1:8485;hadoop.slaver2:8485/ns1
            

            
            
            dfs.ha.automatic-failover.enabled
            true
            

            
            
            dfs.client.failover.proxy.provider.ns1
            org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider
            

             
            
            ha.zookeeper.quorum
            hadoop.master:2181,hadoop.slaver1:2181,hadoop.slaver2:2181
            

            
            
            dfs.ha.fencing.methods
            
            sshfence
            shell(/bin/true)
            
            

            
            dfs.ha.fencing.ssh.private-key-files
            /home/hadoop/.ssh/id_rsa
            

            
            
            dfs.ha.fencing.ssh.connect-timeout
            30000
             
            
            
            ####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####
            
             
                mapreduce.framework.name
                yarn
                

            
                mapreduce.application.classpath
                
                /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/*
                
            
            
                mapreduce.jobhistory.address
                hadoop.master:10020
            
            
                mapreduce.jobhistory.webapp.address
                hadoop.master:19888
            
            
                    mapreduce.jobhistory.done-dir
                    /history/done
            
            
               mapreduce.jobhistory.intermediate-done-dir
               /history/done_intermediate
            
            

            ####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####
            
            
            
            yarn.resourcemanager.address
            hadoop.master:18040
            

            
            yarn.resourcemanager.scheduler.address
            hadoop.master:18030
            

            
            yarn.resourcemanager.resource-tracker.address
            hadoop.master:18025
            

            
            yarn.resourcemanager.admin.address
            hadoop.master:18041
            

            
            yarn.resourcemanager.webapp.address
            hadoop.master:8088
            

            
            yarn.nodemanager.local-dirs
            /opt/hadoop-2.5.2/other/mynode
            

            
            yarn.nodemanager.log-dirs
            /opt/hadoop-2.5.2/other/logs
            

            
            yarn.nodemanager.log.retain-seconds
            10800
            

            
            yarn.nodemanager.remote-app-log-dir
            /opt/hadoop-2.5.2/other/logs
            

            
            yarn.nodemanager.remote-app-log-dir-suffix
            logs
            

            
            yarn.log-aggregation.retain-seconds
            -1
            

            
            yarn.log-aggregation.retain-check-interval-seconds
            -1
            

            
            yarn.nodemanager.aux-services
            mapreduce_shuffle
            

            
            
            yarn.resourcemanager.ha.enabled
            true
            

            
            yarn.resourcemanager.cluster-id
            yrc
            


            
            yarn.resourcemanager.ha.rm-ids
            rm1,rm2
            


            
            yarn.resourcemanager.hostname.rm1
            hadoop.master
            
            
            yarn.resourcemanager.hostname.rm2
            hadoop.slaver1
            


            
            yarn.resourcemanager.zk-address
            hadoop.master:2181,hadoop.slaver1:2181,hadoop.slaver2:2181
            

            
            yarn.nodemanager.aux-services
            mapreduce_shuffle
            
            
    5.分发到各个节点中
       scp -r /opt/hadoop-2.5.2 [email protected]:/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)

转自http://www.cnblogs.com/ciade/p/5141264.html