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搭建大数据平台系列(1)-Hadoop环境搭建[hdfs,yar

搭建大数据平台系列(1)-Hadoop环境搭建[hdfs,yar

作者: 抹布先生M | 来源:发表于2018-08-09 23:24 被阅读2次

    此文章接着本系列上一篇:搭建大数据平台系列(0)-机器准备

    1.ssh免密码登录设置

    [hadoop@master ~]$ ssh -version
    OpenSSH_5.3p1, OpenSSL 1.0.1e-fips 11 Feb 2013
    Bad escape character 'rsion'.
    

    查看ssh的版本后,如果ssh未安装则需要执行如下安装命令:

    [hadoop@master ~]$ sudo  yum  install openssh-server
    

    在每台机器上都执行一次下面的命令:

    $  ssh-keygen   –t   rsa     #一路回车,提示要填的都默认不填,按回车
    上面执行完成后,每台机器上都会生成一个~/.ssh文件夹
    $  ll  ~/.ssh     #查看.ssh文件下的文件列表
    -rw-------. 1 hadoop hadoop 1580 Apr 18 16:53 authorized_keys
    -rw-------. 1 hadoop hadoop 1675 Apr 15 16:01 id_rsa
    -rw-r--r--. 1 hadoop hadoop  395 Apr 15 16:01 id_rsa.pub
    

    把slave1,slave2,slave3上生成的公钥id_rsa.pub发给master机器:
    在slave1机器上:

    [hadoop@slave1 ~]$ scp  ~/.ssh/id_rsa.pub  hadoop@master:~/.ssh/id_rsa.pub.slave1
    

    在slave2机器上:

    [hadoop@slave2 ~]$ scp  ~/.ssh/id_rsa.pub  hadoop@master:~/.ssh/id_rsa.pub.slave2
    

    在slave3机器上:

    [hadoop@slave3 ~]$ scp  ~/.ssh/id_rsa.pub  hadoop@master:~/.ssh/id_rsa.pub.slave3
    

    在master机器上,将所有公钥加到新增的用于认证的公钥文件authorized_keys中:

    [hadoop@master  ~]$  cat  ~/.ssh/id_rsa.pub*  >>  ~/.ssh/authorized_keys
    

    需要修改文件authorized_keys的权限(权限的设置非常重要,因为不安全的设置安全设置,会让你不能使用RSA功能 )

    [hadoop@master  ~]$  chmod  600  ~/.ssh/authorized_keys  #如果免密码不成功有可能缺少这步
    

    将公钥文件authorized_keys分发给每台slave:

    [hadoop@master  ~]$  scp  ~/.ssh/authorized_keys   hadoop@slave1:~/.ssh/
    [hadoop@master  ~]$  scp  ~/.ssh/authorized_keys   hadoop@slave1:~/.ssh/
    [hadoop@master  ~]$  scp  ~/.ssh/authorized_keys   hadoop@slave1:~/.ssh/
    

    2.Java环境的安装

    下载jdk-8u60-linux-x64.tar.gz安装包后(放在~/bigdataspace路径下):
    
      [hadoop@master ~]$ cd  ~/bigdataspace
    [hadoop@master bigdataspace]$  tar  -zxvf  jdk-8u60-linux-x64.tar.gz
    

    修改环境变量配置文件:

    [hadoop@master bigdataspace]$ sudo vi /etc/profile
    
    (在配置文件末尾加上如下配置)
    export JAVA_HOME=/home/hadoop/bigdataspace/jdk1.8.0_60
    export PATH=$JAVA_HOME/bin:$PATH
    export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
    

    让环境变量设置生效:

    [hadoop@master bigdataspace]$ source /etc/profile
    

    验证Java是否安装成功:

    [hadoop@master bigdataspace]$  java  -version
    java version "1.8.0_60"
    Java(TM) SE Runtime Environment (build 1.8.0_60-b27)
    Java HotSpot(TM) 64-Bit Server VM (build 25.60-b23, mixed mode)
    

    (每台机器上都需要按照上面的操作安装Java)
    每台机器上执行:

    [hadoop@master ~]$ sudo chmod 777 /data/  #让所有用户可操作/data目录下的数据
    

    3.集群上的机器实现同步时间

    检查时间服务是否安装:

    [hadoop@master ~]$ rpm -q ntp
    ntp-4.2.6p5-1.el6.centos.x86_64    #这表示已安装了,如果没有安装,这是空白
    

    如果没有安装,需要执行下面的安装命令:

    [hadoop@master ~]$ sudo yum install ntp
    

    需要配置NTP服务为自启动:

    [hadoop@master ~]$ sudo chkconfig ntpd on
    [hadoop@master ~]$ chkconfig --list ntpd
    ntpd      0:off   1:off   2:on    3:on    4:on    5:on    6:off
    
    (需要打开master机器上udp协议的123端口是为了其他节点使用ntpdate通过该端口同步master机器的时间)
    [hadoop@master ~]$ sudo vi /etc/sysconfig/iptables
    (新增的端口配置)
    -A INPUT -m state --state NEW -m udp -p udp --dport 123 -j ACCEPT
    [hadoop@master ~]$ sudo service iptables restart
    

    在配置前,先使用ntpdate手动同步下时间,免得本机与外部时间服务器时间差距太大,让ntpd不能正常同步。

    [hadoop@master ~]$ sudo ntpdate  pool.ntp.org
    26 Apr 17:12:15 ntpdate[7376]: step time server 202.112.29.82 offset 13.827386 sec
    

    更改master机器上的相关配置文件:

    [hadoop@master ~]$ sudo  vim  /etc/ntp.conf
    
    (下面只显示修改的必要项)
    # Hosts on local network are less restricted.
    restrict 192.168.1.0 mask 255.255.255.0 nomodify notrap
    #让同一局域网ip段可以进行时间同步:
    restrict 10.3.19.0 mask 255.255.255.0 nomodify notrap
    # Use public servers from the pool.ntp.org project.
    # Please consider joining the pool (http://www.pool.ntp.org/join.html).
    #server 0.centos.pool.ntp.org iburst
    #server 1.centos.pool.ntp.org iburst
    #server 2.centos.pool.ntp.org iburst
    #server 3.centos.pool.ntp.org iburst
    #外部时间服务器
    server pool.ntp.org iburst
    server 0.asia.pool.ntp.org iburst
    server 1.asia.pool.ntp.org iburst
    server 1.asia.pool.ntp.org iburst
    server 2.asia.pool.ntp.org iburst
    #broadcast 192.168.1.255 autokey        # broadcast server
    #broadcastclient                        # broadcast client
    #broadcast 224.0.1.1 autokey            # multicast server
    #multicastclient 224.0.1.1              # multicast client
    #manycastserver 239.255.254.254         # manycast server
    #manycastclient 239.255.254.254 autokey # manycast client
    
    # allow update time by the upper server
    
    # Undisciplined Local Clock. This is a fake driver intended for backup
    # and when no outside source of synchronized time is available.
    # 外部时间服务器不可用时,以本地时间作为时间服务
    server  127.127.1.0
    fudge   127.127.1.0 stratum 10
    
    #############################################################
    其他节点/etc/ntp.conf(slave1,slave2,slave3)的配置:
    ……..
    #server 3.centos.pool.ntp.org iburst
    #外部时间服务器,以master时间为准进行同步
    server master  iburst
    ……..
    
    [hadoop@master ~]$ sudo  service  ntpd  start
    (每台机器上都需要,设置ntpd开机启动,并第一次手动打开ntpd),命令如下:
    $  sudo chkconfig ntpd on  #开机启动ntpd
    $  sudo service ntpd start  #启动 ntpd
    

    时间同步设置参考:http://cn.soulmachine.me/blog/20140124/

    时间同步设置总结:
    每个节点上安装ntpd,并设置为开机启动,当然第一次要先手动启动,通过配置/etc/ntp.conf文件,让master作为时间同步服务器,这台机器的时间是根据联网同步网络时间的,其他节点以master的ip作为同步的地址

    配置完成后,发现后面的节点时间可能还未同步,可能需要等30分钟左右,一段时间后时间都会以master为准,进行同步

    4.Hadoop的安装、配置

    下载hadoop-2.6.0-cdh5.5.0.tar.gz安装包后(放在master机器上的~/bigdataspace路径下):

    [hadoop@master ~]$ cd  ~/bigdataspace
    [hadoop@master bigdataspace]$  tar  -zxvf  hadoop-2.6.0-cdh5.5.0.tar.gz
    

    进入hadoop配置文件路径:

    [hadoop@master ~]$ cd  ~/bigdataspace/hadoop-2.6.0-cdh5.5.0/etc/hadoop
    

    1> 在hadoop-env.sh中配置JAVA_HOME:

    [hadoop@master hadoop]$ vi  hadoop-env.sh
    
    # set JAVA_HOME in this file, so that it is correctly defined on
    # The java implementation to use.
    export JAVA_HOME=/home/hadoop/bigdataspace/jdk1.8.0_60
    

    2> 在yarn-env.sh中配置JAVA_HOME:

    [hadoop@master hadoop]$ vi  yarn-env.sh
    
    # some Java parameters
    export JAVA_HOME=/home/hadoop/bigdataspace/jdk1.8.0_60
    

    3> 在slaves中配置slave节点的ip或者host

    [hadoop@master hadoop]$ vi  slaves
    
    slave1
    slave2
    slave3
    

    4> 修改core-site.xml

    [hadoop@master hadoop]$ vi  core-site.xml
    
    <!-- Put site-specific property overrides in this file. -->
    <configuration>
        <property>
            <name>fs.defaultFS</name>
            <value>hdfs://master:8020</value>
        </property>
        <property>
            <name>hadoop.tmp.dir</name>
            <value>/data/hadoop-2.6.0-cdh5.5.0/tmp</value>
        </property>
    </configuration>
    

    5> 修改hdfs-site.xml

    [hadoop@master hadoop]$ vi  hdfs-site.xml
    
    <!-- Put site-specific property overrides in this file. -->
    <configuration>
        <property>
            <name>dfs.namenode.secondary.http-address</name>
            <value>master:50090</value>
        </property>
        <property>
            <name>dfs.namenode.name.dir</name>
            <value>file:/data/hadoop-2.6.0-cdh5.5.0/dfs/name</value>
        </property>
        <property>
            <name>dfs.namenode.data.dir</name>
    <name>dfs.datanode.data.dir</name>
            <value>file:/data/hadoop-2.6.0-cdh5.5.0/dfs/data</value>
        </property>
        <property>
            <name>dfs.replication</name>
            <value>3</value>
        </property>
    </configuration>
    

    6> 修改mapred-site.xml

    [hadoop@master hadoop]$ vi  mapred-site.xml
    
    <!-- Put site-specific property overrides in this file. -->
    <configuration>
        <property>
            <name>mapreduce.framework.name</name>
            <value>yarn</value>
        </property>
        <property>
            <name>mapreduce.jobhistory.address</name>
            <value>master:10020</value>
        </property>
        <property>
            <name>mapreduce.jobhistory.webapp.address</name>
            <value>master:19888</value>
        </property>
    </configuration>
    

    7> 修改yarn-site.xml

    [hadoop@master hadoop]$ vi  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.address</name>
            <value>master:8032</value>
        </property>
        <property>
            <name>yarn.resourcemanager.scheduler.address</name>
            <value>master:8030</value>
        </property>
        <property>
            <name>yarn.resourcemanager.resource-tracker.address</name>
            <value>master:8031</value>
        </property>
        <property>
            <name>yarn.resourcemanager.admin.address</name>
            <value>master:8033</value>
        </property>
        <property>
            <name>yarn.resourcemanager.webapp.address</name>
            <value>master:8088</value>
        </property>
    </configuration>
    

    因为CDH版本缺少hadoop的native库,因此需要引入,否则会报错,解决方法:
    http://www.cnblogs.com/huaxiaoyao/p/5046374.html
    本次安装具体采取的解决方法:

    [hadoop@master ~]$ cd ~/bigdataspace
    [hadoop@master bigdataspace]$ wget  http://archive.cloudera.com/cdh5/redhat/6/x86_64/cdh/5.5.0/RPMS/x86_64/hadoop-2.6.0+cdh5.5.0+921-1.cdh5.5.0.p0.15.el6.x86_64.rpm
    [hadoop@master bigdataspace]$  rpm2cpio *.rpm | cpio -div
    

    在bigdataspace文件夹下

    $ cp -r ./usr/lib/hadoop/lib/native/  ~/bigdataspace/hadoop-2.6.0-cdh5.5.0/lib/native/
    

    删除解压后得到的文件:

    [hadoop@master bigdataspace]$ rm -r ~/bigdataspace/etc/
    [hadoop@master bigdataspace]$ rm -r ~/bigdataspace/usr/
    [hadoop@master bigdataspace]$ rm -r ~/bigdataspace/var//
    $  rm  ~/ bigdataspace/hadoop-2.6.0+cdh5.5.0+921-1.cdh5.5.0.p0.15.el6.x86_64.rpm
    

    5.使用scp命令分发配置好的hadoop到各个子节点

    $  scp  –r  ~/bigdataspace/hadoop-2.6.0-cdh5.5.0/  hadoop@slave1:~/bigdataspace/
    $  scp  –r  ~/bigdataspace/hadoop-2.6.0-cdh5.5.0/  hadoop@slave2:~/bigdataspace/
    $  scp  –r  ~/bigdataspace/hadoop-2.6.0-cdh5.5.0/  hadoop@slave3:~/bigdataspace/
    

    (每台机器)修改环境变量配置文件:

    [hadoop@master bigdataspace]$ sudo vi /etc/profile
    

    (在配置文件末尾加上如下配置)

    export HADOOP_HOME=/home/hadoop/bigdataspace/hadoop-2.6.0-cdh5.5.0
    export PATH=$JAVA_HOME/bin:$HADOOP_HOME/bin:$PATH
    

    让环境变量设置生效:

    [hadoop@master bigdataspace]$ source  /etc/profile
    

    6.启动并验证Hadoop

    [hadoop@master ~]$ cd  ~/bigdataspace/hadoop-2.6.0-cdh5.5.0   #进入hadoop目录
      [hadoop@master hadoop-2.6.0-cdh5.5.0]$ ./bin/hdfs namenode –format #格式化namenode
    [hadoop@master hadoop-2.6.0-cdh5.5.0]$ ./sbin/start-dfs.sh     #启动dfs
    [hadoop@master hadoop-2.6.0-cdh5.5.0]$ ./sbin/start-yarn.sh    #启动yarn
    

    可以通过jps命令查看各个节点启动的进程是否正常。在 master 上应该有以下几个进程

    [hadoop@master hadoop-2.6.0-cdh5.5.0]$ jps
    3407 SecondaryNameNode
    3218 NameNode
    3552 ResourceManager
    3910 Jps
    

    在 slave1 上应该有以下几个进程

    [hadoop@slave1 ~]$ jps
    2072 NodeManager
    2213 Jps
    1962 DataNode
    

    或者在浏览器中输入 http://master:8088 ,应该有 hadoop 的管理界面出来了,并通过http://master:8088/cluster/nodes能看到 slave1、slave2、slave3节点

    7.启动Hadoop自带的jobhistoryserver

    [hadoop@master ~]cd ~/bigdataspace/hadoop-2.6.0-cdh5.5.0 #进入hadoop目录 [hadoop@master hadoop-2.6.0-cdh5.5.0] sbin/mr-jobhistory-daemon.sh start historyserver
    (mapred-site.xml配置文件有对jobhistory的相关配置)
    [hadoop@master hadoop-2.6.0-cdh5.5.0]$ jps
    5314 Jps
    19994 JobHistoryServer
    19068 NameNode
    19422 ResourceManager
    19263 SecondaryNameNode

    参考:
    http://blog.csdn.net/liubei_whut/article/details/42397985

    8.停止hadoop集群的问题

    Linux运行一段时间后,/tmp下的文件夹下面会清空一些文件,hadoop的停止脚本stop-all.sh是需要根据/tmp下面的pid文件关闭对应的进程,当/tmp下的文件被自动清理后可能会出出先的错误:

    $   ./sbin/stop-all.sh
    Stopping namenodes on [master]
    master: no namenode to stop
    slave1: no datanode to stop
    slave2: no datanode to stop
    slave3: no datanode to stop
    Stopping secondary namenodes [master]
    master: no secondarynamenode to stop
    ……
    

    方法1:这时需要在/tmp文件夹下手动创建恢复这些pid文件
    master节点(每个文件中保存对应的进程id):
    hadoop-hadoop-namenode.pid
    hadoop-hadoop-secondarynamenode.pid
    yarn-hadoop-resourcemanager.pid
    slave节点(每个文件中保存对应的进程id):
    hadoop-hadoop-datanode.pid
    yarn-hadoop-nodemanager.pid
    方法2:使用kill -9逐个关闭相应的进程id

    从根本上解决的方法:
    (首先使用了方法1或方法2关闭了hadoop集群)
    1.修改配置文件hadoop-env.sh:

    #export HADOOP_PID_DIR=${HADOOP_PID_DIR}
    export HADOOP_PID_DIR=/data/hadoop-2.6.0-cdh5.5.0/pids
    #export HADOOP_SECURE_DN_PID_DIR=${HADOOP_PID_DIR}
    export HADOOP_SECURE_DN_PID_DIR=/data/hadoop-2.6.0-cdh5.5.0/pids
    

    2.修改配置文件yarn-env.sh:

    export YARN_PID_DIR=/data/hadoop-2.6.0-cdh5.5.0/pids
    

    3.创建文件夹pids:

    $  mkdir /data/hadoop-2.6.0-cdh5.5.0/pids(发现会自动创建pids文件,因此不需要创建)
    

    这2个步骤需要在各个节点都执行.

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