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  • 安装高可用Hadoop生态 (三) 安装Hadoop

    3.    安装Hadoop

    3.1. 解压程序

    ※ 3台服务器分别执行

    tar -xf ~/install/hadoop-2.7.3.tar.gz -C/opt/cloud/packages
    
    ln -s /opt/cloud/packages/hadoop-2.7.3 /opt/cloud/bin/hadoop
    ln -s /opt/cloud/packages/hadoop-2.7.3/etc/hadoop /opt/cloud/etc/hadoop
    
    mkdir -p /opt/cloud/hdfs/name
    mkdir -p /opt/cloud/hdfs/data
    mkdir -p /opt/cloud/hdfs/journal
    mkdir -p /opt/cloud/hdfs/tmp/java
    mkdir -p /opt/cloud/logs/hadoop/yarn

    3.2. 设置环境变量

    设置JAVA环境变量和Hadoop环境变量

    vi ~/.bashrc

    增加

    export HADOOP_HOME=/opt/cloud/bin/hadoop
    export HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    export HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    export HADOOP_PID_DIR=/opt/cloud/hdfs/tmp
    
    export YARN_PID_DIR=/opt/cloud/hdfs/tmp
    export HADOOP_OPTS="-Djava.io.tmpdir=/opt/cloud/hdfs/tmp/java"
    
    export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH

    即刻生效

    source ~/.bashrc

    复制到另外两台服务器

    scp ~/.bashrc hadoop2:/home/hadoop
    scp ~/.bashrc hadoop3:/home/hadoop

    3.3. 修改Hadoop参数

    cd ${HADOOP_HOME}/etc/hadoop

    修改log4j.properties 、hadoop-env.sh、yarn-env.sh、slaves、core-site.xml、hdfs-site.xml、mapred-site.xml和yarn-site.xml,分发到hadoop2和hadoop2相同的目录下

    3.3.1.    修改log配置文件log4j.properties

    hadoop.root.logger =INFO,DRFA

    hadoop.log.dir=/opt/cloud/logs/hadoop

    3.3.2.    修改hadoop-env.sh

    hadoop-env.sh设置了Hadoop的一些环境变量,但是直到2.7.3都有bug,不能从系统的环境变量中提取正确的值,需要手工修改,在文件头部

    export JAVA_HOME=${JAVA_HOME}

    将其注释,手工修改为

    export JAVA_HOME="/usr/lib/jvm/java"

    在文件中查找#export HADOOP_LOG_DIR,在其下增加

    export HADOOP_LOG_DIR=/opt/cloud/logs/hadoop

    在文件中查找export HADOOP_PID_DIR=${HADOOP_PID_DIR}

    export HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/

    设置java的临时目录,查找

    export HADOOP_OPTS="$HADOOP_OPTS -Djava.net.preferIPv4Stack=true "

    修改为

    export HADOOP_OPTS="$HADOOP_OPTS -Djava.net.preferIPv4Stack=true -Djava.io.tmpdir=/opt/cloud/hdfs/tmp/java"

    3.3.3.    修改yarn-env.sh

    查找default log directory,在其后增加一行

    export YARN_LOG_DIR=/opt/cloud/logs/hadoop/yarn

    3.3.4.    修改slaves

    # vi slaves

    配置内容:

    删除:localhost

    添加:

    hadoop2
    hadoop3

    3.3.5.    修改core-site.xml

    # vi  core-site.xml

    配置内容:

    <configuration>
    
    <property> <name>fs.defaultFS</name> <value>hdfs://mycluster</value> </property> <property> <name>ha.zookeeper.quorum</name> <value>hadoop1:2181,hadoop2:2181,hadoop3:2181</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/opt/cloud/hdfs/tmp</value> </property> <property> <name>io.file.buffer.size</name> <value>131072</value> </property> <property> <name>hadoop.proxyuser.hadoop.groups</name> <value>hadoop</value> </property> <property> <name>hadoop.proxyuser.hadoop.hosts</name> <value>hadoop1, hadoop2, hadoop3,127.0.0.1,localhost</value> </property> <property> <name>ipc.client.rpc-timeout.ms</name>[1] <value>4000</value> </property> <property> <name>ipc.client.connect.timeout</name> <value>4000</value> </property> <property> <name>ipc.client.connect.max.retries</name> <value>100</value> </property> <property> <name>ipc.client.connect.retry.interval</name> <value>10000</value> </property> </configuration>

    3.3.6.    修改hdfs-site.xml

    # vi  hdfs-site.xml

    配置内容:

    <configuration>
        <property>
          <name>dfs.nameservices</name>
          <value>mycluster</value>
        </property>
        <property>
          <name>dfs.ha.namenodes.mycluster</name>
          <value>nn1,nn2</value>
        </property>
        <property>
          <name>dfs.namenode.rpc-address.mycluster.nn1</name>
          <value>hadoop1:9000</value>
        </property>
        <property>
          <name>dfs.namenode.http-address.mycluster.nn1</name>
          <value>hadoop1:50070</value>
        </property>
        <property>
          <name>dfs.namenode.rpc-address.mycluster.nn2</name>
          <value>hadoop2:9000</value>
        </property>
        <property>
          <name>dfs.namenode.http-address.mycluster.nn2</name>
          <value>hadoop2:50070</value>
        </property>
        <property>
          <name>dfs.namenode.shared.edits.dir</name>
          <value>qjournal://hadoop1:8485;hadoop2:8485;hadoop3:8485/mycluster</value>
        </property>
        <property>
          <name>dfs.journalnode.edits.dir</name>
          <value>/opt/cloud/hdfs/journal</value>
        </property>
        <property>
          <name>dfs.ha.automatic-failover.enabled</name>
          <value>true</value>
        </property>
        <property>
          <name>dfs.client.failover.proxy.provider.mycluster</name>
          <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
        </property>
        <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>
        <property>
           <name>dfs.ha.fencing.ssh.connect-timeout</name>
           <value>30000</value>
        </property>
    
       <property>
            <name>dfs.replication</name>
            <value>2</value>
        </property>
        <property>
            <name>dfs.name.dir</name>
            <value>/opt/cloud/hdfs/name</value>
        </property>
        <property>
            <name>dfs.data.dir</name>
            <value>/opt/cloud/hdfs/data</value>
        </property>
        <property>
            <name>dfs.permissions</name>
            <value>false</value>
        </property>
        <property>
            <name>dfs.support.append</name>
            <value>true</value>
        </property>
        <property>
            <name>dfs.webhdfs.enabled</name>
            <value>true</value>
        </property>
        <property>
            <name>dfs.client.block.write.replace-datanode-on-failure.enable</name>
            <value>true</value>
        </property>
        <property>
            <name>dfs.client.block.write.replace-datanode-on-failure.policy</name>
            <value>NEVER</value>
        </property>
        <property>
            <name>dfs.datanode.max.xcievers</name>
            <value>8192</value>
        </property>
    </configuration>

    3.3.7.    修改mapred-site.xml

    mv mapred-site.xml.template mapred-site.xml
    vi mapred-site.xml

    配置内容:

    <configuration>
      <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
      </property>
      <property>
         <name>mapreduce.jobhistory.address</name>
         <value>0.0.0.0:10020</value>
      </property>
      <property>
         <name>mapreduce.jobhistory.webapp.address</name>
         <value>0.0.0.0:19888</value>
      </property>
      <property> 
        <name>yarn.app.mapreduce.am.resource.mb</name>
        <value>1024</value>
      </property>
      <property>
        <name>yarn.app.mapreduce.am.command-opts</name>
        <value>-Xmx800m</value>
      </property>
      <property>
         <name>mapreduce.map.memory.mb</name>
         <value>512</value>
      </property>
      <property>
        <name>mapreduce.map.java.opts</name>
        <value>-Xmx400m</value>
      </property>
      <property>
         <name>mapreduce.reduce.memory.mb</name>
         <value>1024</value>
      </property>
      <property>
        <name>mapreduce.reduce.java.opts</name>
        <value>-Xmx800m</value>
      </property>
    </configuration>

    3.3.8.    修改yarn-site.xml(非HA版)

    vi yarn-site.xml

    配置内容:

    <configuration>
        <property>
            <name>yarn.resourcemanager.hostname</name>
            <value>hadoop1</value>
        </property>
        <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>
    </configuration>

    3.3.9.    修改yarn-site.xml(HA版)

    vi yarn-site.xml

    配置内容:

    <configuration>  
        <property>  
           <name>yarn.resourcemanager.ha.enabled</name>  
           <value>true</value>  
        </property>  
        <property>  
           <name>yarn.resourcemanager.cluster-id</name>  
           <value>clusteryarn</value>  
        </property>  
        <property>  
           <name>yarn.resourcemanager.ha.rm-ids</name>  
           <value>rm1,rm2</value>  
        </property>  
        <property>  
           <name>yarn.resourcemanager.hostname.rm1</name>  
           <value>hadoop1</value>  
        </property>  
        <property>  
           <name>yarn.resourcemanager.hostname.rm2</name>  
           <value>hadoop2</value>  
        </property>
        <property>
           <name>yarn.log-aggregation-enable</name>
           <value>true</value>
        </property>
        <property>  
           <name>yarn.resourcemanager.zk-address</name>  
           <value>hadoop1:2181,hadoop2:2181,hadoop3:2181</value>  
        </property>
        <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.connect.retry-interval.ms</name>
          <value>5000</value>
        </property>
        <property> 
           <name>yarn.nodemanager.resource.memory-mb</name>
           <value>3072</value>
        </property> 
        <property> 
          <name>yarn.nodemanager.vmem-pmem-ratio</name>
          <value>4</value>
        </property>
        <property>
           <name>yarn.nodemanager.resource.cpu-vcores</name>
           <value>2</value>
        </property>
        <property>
            <name>yarn.scheduler.minimum-allocation-mb</name>
            <value>512</value>
        </property>
        <property>
            <name>yarn.scheduler.maximum-allocation-mb</name>
            <value>2048</value>
        </property>
        <property>
            <name>yarn.scheduler.minimum-allocation-vcores</name>
            <value>1</value>
        </property>
        <property>
            <name>yarn.scheduler.maximum-allocation-vcores</name>
            <value>2</value>
        </property>
    </configuration>  

    3.3.10.   复制到另外2台服务器

    配置文件打包为 

    scp /opt/cloud/bin/hadoop/etc/hadoop/* hadoop2:/opt/cloud/bin/hadoop/etc/hadoop/
    scp /opt/cloud/bin/hadoop/etc/hadoop/* hadoop3:/opt/cloud/bin/hadoop/etc/hadoop/

    3.4. 首次启动HDFS

    • 启动JournalNode集群:
    cexec 'hadoop-daemon.sh start journalnode'

    注意只有第一次需要这么启动,之后启动hdfs会包含journalnode。

    • 格式化第1个NameNode:
    ssh hadoop1 'hdfs namenode -format -clusterId mycluster'

    输出信息的最后部分出现下面两行表示格式化成功

    INFO common.Storage: Storage directory /opt/cloud/hdfs/name has been successfully formatted.

    ...

    INFO util.ExitUtil: Exiting with status 0

    • 启动第1个NameNode:
    ssh hadoop1 'hadoop-daemon.sh start namenode'
    • 格式化第2个NameNode:
    ssh hadoop2 'hdfs namenode -bootstrapStandby'

    输出信息的最后部分出现下面两行表示格式化成功

    INFO common.Storage: Storage directory /opt/cloud/hdfs/name has been successfully formatted.

    ...

    INFO util.ExitUtil: Exiting with status 0

    • 启动第2个NameNode:
    ssh hadoop2 'hadoop-daemon.sh start namenode'
    • 格式化Zk
    ssh hadoop1 'hdfs zkfc -formatZK'

    信息

    INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/mycluster in ZK.

    即为格式化成功

    • 启动2个Zkfc
    ssh hadoop1 'hadoop-daemon.sh start zkfc'
    ssh hadoop2 'hadoop-daemon.sh start zkfc'
    • 启动所有的DataNodes:
    ssh hadoop1 'hadoop-daemons.sh start datanode'

    用浏览器访问http://hadoop1:50070和http://hadoop2:50070 查看状态

    namenode一个是active一个是standby,其中active的网页中QJM三台服务器的Written txid相同。

    3.5. 正式启动hdfs和Yarn

    在hadoop1上执行

    start-dfs.sh
    start-yarn.sh

    在hadoop2上执行

    ssh hadoop2 'yarn-daemon.sh start resourcemanager'

    通过jps查看进程

    [hadoop@hadoop1 ~]$ cexec jps
    ************************* cloud *************************
    --------- hadoop1---------
    1223 QuorumPeerMain
    3757 DFSZKFailoverController
    4787 Jps
    3872 ResourceManager
    3365 NameNode
    3578 JournalNode
    --------- hadoop2---------
    1220 QuorumPeerMain
    24240 NodeManager
    24545 Jps
    24022 JournalNode
    24139 DFSZKFailoverController
    23847 NameNode
    23923 DataNode
    24419 ResourceManager
    --------- hadoop3---------
    23764 Jps
    23578 NodeManager
    23471 JournalNode
    23372 DataNode
    1224 QuorumPeerMain

    在浏览器中下列网址,会看到图形界面的监控程序

    http://hadoop1:50070/  dfs的图形界面的监控程序

    http://hadoop2:50070/  dfs的图形界面的监控程序,hadoop1和hadoop2其中一个是active,另外一个是standby

    http://hadoop1:8088

    http://hadoop2:8088 自动跳转到http://hadoop1:8088

    3.6. 开机自动运行hdfs

           Centos7 采用Systemd作为自启动管理器,有方便设置依赖关系等多个优点,不过,每个服务的环境变量都是初始化的,即“systemd不继承任何上下文环境”,所以服务脚本需要设置必要的所有环境变量,每个变量需要用Environment = name = value的方式设置,好消息Environment可以多行,坏消息是Environment中不支持已经使用已经声明的变量,就是说value中不能有$name,${name}。

    3.6.1.    journalnode service

    vi hadoop-journalnode.service

    [Unit]
    Description=hadoop journalnode service
    After= network.target
    [Service]
    Type=forking
    User=hadoop
    Group=hadoop
    Environment = JAVA_HOME=/usr/lib/jvm/java
    Environment = JRE_HOME=/usr/lib/jvm/java/jre
    Environment = CLASSPATH='.:/usr/lib/jvm/java/jre/lib/rt.jar:/usr/lib/jvm/java/lib/dt.jar:$JAVA_HOME/lib/tools.jar'
    Environment = HADOOP_HOME=/opt/cloud/bin/hadoop
    Environment = HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    Environment = HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    Environment = HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/
    
    ExecStart=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh start journalnode'
    ExecStop =/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh stop journalnode'
    [Install]
    WantedBy=multi-user.target

    3.6.2.    namenode service

    vi hadoop-namenode.service

    [Unit]
    Description=hadoop namenode service
    After= network.target
    [Service]
    Type=forking
    User=hadoop
    Group=hadoop
    Environment = JAVA_HOME=/usr/lib/jvm/java
    Environment = JRE_HOME=/usr/lib/jvm/java/jre
    Environment = CLASSPATH='.:/usr/lib/jvm/java/jre/lib/rt.jar:/usr/lib/jvm/java/lib/dt.jar:$JAVA_HOME/lib/tools.jar'
    Environment = HADOOP_HOME=/opt/cloud/bin/hadoop
    Environment = HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    Environment = HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    Environment = HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/
    
    ExecStart=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh start namenode'
    ExecStop=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh stop namenode'
    [Install]
    WantedBy=multi-user.target

    3.6.3.    datanode service

    vi hadoop-datanode.service

    [Unit]
    Description=hadoop datanode service
    After= network.target
    [Service]
    Type=forking
    User=hadoop
    Group=hadoop
    Environment = JAVA_HOME=/usr/lib/jvm/java
    Environment = JRE_HOME=/usr/lib/jvm/java/jre
    Environment = CLASSPATH='.:/usr/lib/jvm/java/jre/lib/rt.jar:/usr/lib/jvm/java/lib/dt.jar:$JAVA_HOME/lib/tools.jar'
    Environment = HADOOP_HOME=/opt/cloud/bin/hadoop
    Environment = HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    Environment = HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    Environment = HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/
    
    ExecStart=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh start datanode'
    ExecStop =/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh stop datanode'
    [Install]
    WantedBy=multi-user.target

    3.6.4.    zkfc service

    vi hadoop-zkfc.service

    [Unit]
    Description=hadoop zkfc service
    After= network.target
    [Service]
    Type=forking
    User=hadoop
    Group=hadoop
    Environment = JAVA_HOME=/usr/lib/jvm/java
    Environment = JRE_HOME=/usr/lib/jvm/java/jre
    Environment = CLASSPATH='.:/usr/lib/jvm/java/jre/lib/rt.jar:/usr/lib/jvm/java/lib/dt.jar:$JAVA_HOME/lib/tools.jar'
    Environment = HADOOP_HOME=/opt/cloud/bin/hadoop
    Environment = HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    Environment = HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    Environment = HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/
    
    ExecStart=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh start zkfc'
    ExecStop=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/hadoop-daemon.sh stop zkfc'
    [Install]
    WantedBy=multi-user.target

    3.6.5.    yarn resource manager service

    vi yarn-rm.service

    [Unit]
    Description=yarn resource manager service
    After= network.target
    [Service]
    Type=forking
    User=hadoop
    Group=hadoop
    Environment = JAVA_HOME=/usr/lib/jvm/java
    Environment = JRE_HOME=/usr/lib/jvm/java/jre
    Environment = CLASSPATH='.:/usr/lib/jvm/java/jre/lib/rt.jar:/usr/lib/jvm/java/lib/dt.jar:$JAVA_HOME/lib/tools.jar'
    Environment = HADOOP_HOME=/opt/cloud/bin/hadoop
    Environment = HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    Environment = HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    Environment = HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/
    
    ExecStart=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/yarn-daemon.sh start resourcemanager'
    ExecStop=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/yarn-daemon.sh stop resourcemanager'
    [Install]
    WantedBy=multi-user.target

    3.6.6.    yarn nodemanager service

    vi yarn-nm.service

    [Unit]
    Description=yarn node manager service
    After= network.target
    [Service]
    Type=forking
    User=hadoop
    Group=hadoop
    Environment = JAVA_HOME=/usr/lib/jvm/java
    Environment = JRE_HOME=/usr/lib/jvm/java/jre
    Environment = CLASSPATH='.:/usr/lib/jvm/java/jre/lib/rt.jar:/usr/lib/jvm/java/lib/dt.jar:$JAVA_HOME/lib/tools.jar'
    Environment = HADOOP_HOME=/opt/cloud/bin/hadoop
    Environment = HADOOP_CONF_DIR=/opt/cloud/etc/hadoop
    Environment = HADOOP_LOG_DIR=/opt/cloud/logs/hadoop
    Environment = HADOOP_PID_DIR=/opt/cloud/hdfs/tmp/
    
    ExecStart=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/yarn-daemon.sh start nodemanager'
    ExecStop=/usr/bin/sh -c '/opt/cloud/bin/hadoop/sbin/yarn-daemon.sh stop nodemanager'
    [Install]
    WantedBy=multi-user.target

    3.6.7.    测试和设置为自动启动服务

           编写6种服务的启动脚本,分别复制到对应服务的/etc/systemd/system目录

    hadoop2 (6种服务)

    systemctl start hadoop-journalnode
    systemctl start hadoop-namenode
    systemctl start hadoop-datanode
    systemctl start hadoop-zkfc
    systemctl start yarn-rm
    systemctl start yarn-nm

    测试通过后

    systemctl enable hadoop-journalnode
    systemctl enable hadoop-namenode
    systemctl enable hadoop-datanode
    systemctl enable hadoop-zkfc
    systemctl enable yarn-rm
    systemctl enable yarn-nm

    hadoop1 (4种服务)

    systemctl enable hadoop-journalnode
    systemctl enable hadoop-namenode
    systemctl enable hadoop-zkfc
    systemctl enable yarn-rm

    hadoop3 (3种服务)

    systemctl enable hadoop-journalnode
    systemctl enable hadoop-datanode
    systemctl enable yarn-nm

    重新启动3台服务器,运行 cexec jps 查看系统状态

    3.7. 卸载

    • 停止yarn,停止DFS:
    ssh hadoop1 'stop-yarn.sh'
    ssh hadoop2 'yarn-daemon.sh stop resourcemanager'
    ssh hadoop1 'stop-dfs.sh'

         cexec jps 不再看到hdfs和yarn的进程

    • 停止并删除系统服务

    hadoop2 (6种服务)

    systemctl disable hadoop-journalnode
    systemctl disable hadoop-namenode
    systemctl disable hadoop-datanode
    systemctl disable hadoop-zkfc
    systemctl disable yarn-rm
    systemctl disable yarn-nm

    hadoop1 (4种服务)

    systemctl disable hadoop-journalnode
    systemctl disable hadoop-namenode
    systemctl disable hadoop-zkfc
    systemctl disable yarn-rm

    hadoop3 (3种服务)

    systemctl disable hadoop-journalnode
    systemctl disable hadoop-datanode
    systemctl disable yarn-nm
    • 删除数据目录
    rm /opt/cloud/hdfs -rf
    rm /opt/cloud/logs/hadoop -rf
    • 删除程序目录
    rm /opt/cloud/bin/hadoop -rf
    rm /opt/cloud/etc/hadoop -rf
    rm /opt/cloud/packages/hadoop-2.7.3 -rf
    • 复原环境变量

           vi ~/.bashrc

           删除hadoop相关行



    [1] 重要的参数,设置hadoop服务之间通讯超时,尤其是nodemanager和resoucemanager之间的ha机制

    [2] 适应虚拟机4G内存,各项值都较低

    [3] 与yarn的高可用有关,属于nodemanager连接失败后的策略参数

    [4] 虚拟机仅4G内存2个核,这些资源参数也偏小

    [5] 内存不足,虚拟内存比由2.1改为4

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  • 原文地址:https://www.cnblogs.com/fanzhenyong/p/6188845.html
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