安装hadoop+zookeeper-低调大师

安装hadoop+zookeeper

2017-11-21 496

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

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原文链接：https://yq.aliyun.com/articles/524921

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