• 大数据存储计算平台构建(离线存储)


    版本选择:2.7.5或者2.7.5以上版本均可

    软件安装准备工作

    机器规划

    image

    1.所有服务器关闭防火墙和selinux

    #systemctl stop firewalld   ---临时停掉firewalld
    #systemctl disable firewalld ---永久开机关闭firewalld
    #setenforce 0  ----临时停掉selinux
    #vim /etc/selinux/config ---永久开机关闭selinux
    SELINUX=disabled
    #getenfore ---查看selinux状态
    

    2.linux创建hadoop用户组

    #useradd hadoop
    
    创建用户密码
    #password hadoop
    

    3.创建文件路径(每台服务器都要创建)

    创建hadoop临时文件存放路径
    #mkdir -p /home/hadoop/app/hadoop/data/tmp
    #mkdir -p /home/hadoop/app/hadoop/data/journal
    #mkdir -p /home/hadoop/app/hadoop/tmp
    

    4.ssh免密配置(hadoop用户)

    每台机器执行
    #ssh-keygen
    #cat /home/hadoop/.ssh/id_rsa.pub >> /home/hadoop/.ssh/authorized_keys
    
    几台机器之间互传
    #cat /home/hadoop/.ssh/id_rsa.pub >> /home/hadoop/.ssh/authorized_keys
    #scp /home/hadoop/.ssh/authorized_keys root@ip:/home/hadoop/.ssh/authorized_keys
    #chmod 600 authorized_keys ----hadoop用户
    
    修改/etc/hosts
    #vim /etc/hosts
    dba-01 xxxxxx
    dba-02 xxxxxx
    dba-03 xxxxxx
    dba-04 xxxxxx
    dba-05 xxxxxx
    

    5.jdk1.8安装(所有服务器均使用root用户安装)

    #tar -zxvf jdk-8u202-linux-x64.tar.gz -C /opt
    #vim /etc/profile
    export JAVA_HOME=/opt/jdk1.8.0_202/
    export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
    export PATH=$PATH:$JAVA_HOME/bin
    #source /etc/profile
    #which java
    

    hadoop集群安装

    1.下载安装包并解压

    #wget https://archive.apache.org/dist/hadoop/common/hadoop-2.7.5/hadoop-2.7.5.tar.gz
    #tar -zxvf hadoop-2.7.5.tar.gz -C /home/hadoop/app
    #ln -s /home/hadoop/app/hadoop-2.7.5 /home/hadoop/app/hadoop
    

    2.配置环境变量(每台服务器都要添加)

    #vim /etc/profile
    export HADOOP_HOME=/home/hadoop/app/hadoop
    #path路径添加
    export PATH=$PATH:$JAVA_HOME/bin:$ZOOKEEPER_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
    #source /etc/profile
    

    3.配置/home/hadoop/app/hadoop/etc/hadoop/hadoop-env.sh

    export JAVA_HOME=/opt/jdk1.8.0_202/
    

    4.配置/home/hadoop/app/hadoop/etc/hadoop/core-site.xml

    添加内容:
        <property>
              <name>fs.defaultFS</name>
              <value>hdfs://ns1</value>
        </property>
    
        <property>
            <name>hadoop.tmp.dir</name>
            <value>/home/hadoop/app/hadoop-2.7.5/data/tmp</value>
        </property>
    
        <property>
            <name>hadoop.http.staticuser.user</name>
            <value>root</value>
        </property>
    
            <property>
                    <name>io.file.buffer.size</name>
                    <value>131072</value>
            </property>
        <property>
            <name>ipc.server.read.threadpool.size</name>
            <value>3</value>
        </property>
        <property>
            <name>ha.zookeeper.quorum</name>
            <value>dba-01:2181,dba-02:2181,bigdata03:2181</value>
        </property>
        <property>
            <name>hadoop.proxyuser.root.hosts</name>
            <value>*</value>
        </property>
        <property>
            <name>hadoop.proxyuser.root.groups</name>
            <value>*</value>
        </property>
      <property>
         <name>hadoop.proxyuser.root.users</name>
         <value>*</value>
      </property>
    

    5.修改hdfs-site.xml

    #vim /home/hadoop/app/hadoop-2.7.5/etc/hadoop/hdfs-site.xml
    
    添加内容:
    
        <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>dba-04:8020</value>
        </property>
    
        <property>
            <name>dfs.namenode.http-address.ns1.nn1</name>
            <value>dba-04:50070</value>
        </property>
    
        <property>
            <name>dfs.namenode.rpc-address.ns1.nn2</name>
            <value>dba-05:8020</value>
        </property>
    
        <property>
            <name>dfs.namenode.http-address.ns1.nn2</name>
            <value>dba-05:50070</value>
        </property>
    
        <property>
            <name>dfs.namenode.shared.edits.dir</name>
            <value>qjournal://dba-01:8485;dba-02:8485;dba-03:8485/ns1</value>
        </property>
    
        <property>
            <name>dfs.journalnode.edits.dir</name>
            <value>/home/hadoop/app/hadoop-2.7.5/data/journal</value>
        </property>
    
        <property>
            <name>dfs.ha.automatic-failover.enabled</name>
            <value>true</value>
        </property>
    
        <property>
            <name>dfs.client.failover.proxy.provider.ns1</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.connect-timeout</name>
            <value>30000</value>
        </property>
        <property>
              <name>dfs.webhdfs.enabled</name>
              <value>true</value>
        </property>
    

    6.修改yarn-site.xml

    # vim /home/hadoop/app/hadoop-2.7.5/etc/hadoop/yarn-site.sh
    
    添加内容:
    
            <property>
              <name>yarn.resourcemanager.ha.enabled</name>
              <value>true</value>
            </property>
    
            <property>
              <name>yarn.resourcemanager.cluster-id</name>
              <value>cluster_id</value>
            </property>
    
            <property>
              <name>yarn.resourcemanager.ha.rm-ids</name>
              <value>rm1,rm2</value>
            </property>
    
            <property>
              <name>yarn.resourcemanager.hostname.rm1</name>
              <value>dba-04</value>
            </property>
    
            <property>
              <name>yarn.resourcemanager.hostname.rm2</name>
              <value>dba-05</value>
            </property>
    
            <property>
                    <name>yarn.resourcemanager.webapp.address.rm1</name>
                    <value>dba-04:8088</value>
            </property>
    
            <property>
                    <name>yarn.resourcemanager.webapp.address.rm2</name>
                    <value>dba-05:8088</value>
            </property>
    
            <property>
              <name>yarn.resourcemanager.zk-address</name>
              <value>dba-01:2181,dba-02:2181,dba-03:2181</value>
            </property>
    
            <property>
              <name>yarn.nodemanager.aux-services</name>
              <value>mapreduce_shuffle</value>
            </property>
    
      <property>
            <name>yarn.log-aggregation-enable</name>
            <value>true</value>
         </property>
    
         <property>
            <name>yarn.log-aggregation.retain-seconds</name>
            <value>604800</value>
         </property>
    
     <property>
            <name>yarn.log-aggregation.retain-check-interval-seconds</name>
            <value>3600</value>
     </property>
    
    <property>
            <name>yarn.log.server.url</name>
            <value>http://dba-01:19888/jobhistory/logs/</value>
    </property>
    
    <property>
            <name>yarn.nodemanager.vmem-check-enabled</name>
            <value>false</value>
    </property>
    
    <property>
            <name>yarn.resourcemanager.scheduler.class</name>
            <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
    </property>
            <property>
                    <name>yarn.scheduler.fair.allocation.file</name>
                    <value>/home/hadoop/app/hadoop-2.7.5/etc/hadoop/fair-scheduler.xml</value>
            </property>
            <property>
                    <name>yarn.scheduler.fair.user-as-default-queue</name>
                    <value>false</value>
            </property>
            <property>
                    <name>yarn.scheduler.fair.preemption</name>
                    <value>false</value>
            </property>
            <property>
                    <name>yarn.scheduler.fair.sizebasedweight</name>
                    <value>false</value>
            </property>
            <property>
                    <name>yarn.scheduler.fair.assignmultiple</name>
                    <value>true</value>
            </property>
            <property>
                    <name>yarn.scheduler.fair.max.assign</name>
                    <value>3</value>
            </property>
            <property>
                    <name>yarn.scheduler.fair.allow-undeclared-pools</name>
                    <value>false</value>
            </property>
    
            <property>
                    <name>yarn.resourcemanager.recovery.enabled</name>
                    <value>true</value>
            </property>
            <property>
                    <name>yarn.resourcemanager.store.class</name>
                    <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
            </property>
            <property>
                <name>yarn.resourcemanager.zk-state-store.parent-path</name>
                <value>/rmstore</value>
            </property>
    
            <property>
                    <name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
                    <value>true</value>
            </property>
            <property>
                    <name>yarn.client.failover-proxy-provider</name>
                    <value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value>
            </property>
    
            <property>
                    <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
                    <value>org.apache.hadoop.mapred.ShuffleHandler</value>
            </property>
    
        <property>
            <name>yarn.nodemanager.aux-services.spark_shuffle.class</name>
            <value>org.apache.spark.network.yarn.YarnShuffleService</value>
        </property>
    

    7.创建yarn公平调度模式配置文件fair-scheduler.xml

    <?xml version="1.0"?>
    
    <allocations>
     <queue name="root">
       <aclSubmitApps> </aclSubmitApps>
    
       <queue name="default">
           <minResources>1mb,1vcores</minResources>
           <maxResources>1mb,1vcores</maxResources>
       </queue>
       <!-- min 1/3 max 1/2 -->
       <queue name="offline">
           <minResources>1048576mb,330vcores</minResources>
           <maxResources>1572864mb,500vcores</maxResources>
           <queue name="algo">
              <weight>2.0</weight>
              <minResources>524288mb,166vcores</minResources>
              <maxResources>786432mb,250vcores</maxResources>
              <aclSubmitApps>algo</aclSubmitApps>
              <aclAdministerApps>algo</aclAdministerApps>
              <schedulingPolicy>fair</schedulingPolicy>
           </queue>
    
           <queue name="dp">
              <weight>2.0</weight>
              <minResources>786432mb,250vcores</minResources>
              <maxResources>1572864mb,500vcores</maxResources>
              <!--<maxResources>1048576mb,332vcores</maxResources>-->
              <aclSubmitApps>work</aclSubmitApps>
              <aclAdministerApps>work</aclAdministerApps>
              <schedulingPolicy>fair</schedulingPolicy>
           </queue>
    
       </queue>
    
       <queueMaxAMShareDefault>0.5</queueMaxAMShareDefault>
    
       <!-- Queue 'secondary_group_queue' is a parent queue and may have
                         user queues under it    type="parent"   -->
       <!-- min 1/4 max 1/3 -->
       <queue name="online">
           <minResources>393216mb,124vcores</minResources>
           <maxResources>1048576mb,330vcores</maxResources>
    
           <queue name="algo">
              <weight>2.0</weight>
              <minResources>524288mb,165vcores</minResources>
              <maxResources>699050mb,220vcores</maxResources>
              <aclSubmitApps>algo</aclSubmitApps>
              <aclAdministerApps>algo</aclAdministerApps>
              <schedulingPolicy>fair</schedulingPolicy>
           </queue>
    
           <queue name="dp">
              <weight>2.0</weight>
              <minResources>349525mb,110vcores</minResources>
              <maxResources>524288mb,165vcores</maxResources>
              <aclSubmitApps>work</aclSubmitApps>
              <aclAdministerApps>work</aclAdministerApps>
              <schedulingPolicy>fair</schedulingPolicy>
           </queue>
    
       </queue>
                               
       <!-- min 1/3 max 2/3 -->                         
       <queue name="spark">
           <minResources>786432mb,248vcores</minResources>
           <maxResources>2184532mb,682vcores</maxResources>
           <!--<maxResources>1048576mb,330vcores</maxResources>-->
           
           <queue name="algo">
              <weight>2.0</weight>
              <minResources>524288mb,165vcores</minResources>
              <maxResources>2184532mb,682vcores</maxResources>
              <!--<maxResources>699050mb,220vcores</maxResources>-->
              <aclSubmitApps>algo</aclSubmitApps>
              <aclAdministerApps>algo</aclAdministerApps>
              <schedulingPolicy>fair</schedulingPolicy>
           </queue>
    
           <queue name="dp">
              <weight>2.0</weight>
              <minResources>349525mb,110vcores</minResources>
              <maxResources>524288mb,165vcores</maxResources>
              <aclSubmitApps>work</aclSubmitApps>
              <aclAdministerApps>work</aclAdministerApps>
              <schedulingPolicy>fair</schedulingPolicy>
           </queue>
    
       </queue>
    
    <!--   
             <user name="sample_user">
                   <maxRunningApps>30</maxRunningApps>
                     </user>
    -->
       <userMaxAppsDefault>5</userMaxAppsDefault>
    <!--
       <queuePlacementPolicy>
          <rule name="specified" />
          <rule name="primaryGroup" create="false" />
          <rule name="nestedUserQueue">
          <rule name="secondaryGroupExistingQueue" create="false" />
          </rule>
          <rule name="default" queue="sample_queue"/>
       </queuePlacementPolicy>
    -->
     </queue>
    </allocations>
    

    8.修改mapred-env.sh

    #vim /home/hadoop/app/hadoop-2.7.5/etc/hadoop/mapred-env.sh
    

    9.修改pid目录配置

    export HADOOP_MAPRED_PID_DIR=/home/hadoop/app/hadoop-2.7.5/data/tmp
    

    10.修改mapred-site.xml

    #vim /home/hadoop/app/hadoop-2.7.5/etc/hadoop/mapred-site.xml
    增加配置:
    
    <property>
            <name>mapreduce.framework.name</name>
            <value>yarn</value>
            <final>true</final>
        </property>
    
            <property>
                    <name>mapreduce.jobhistory.address</name>
                    <value>dba-01:10020</value>
            </property>
    
            <property>
                    <name>mapreduce.jobhistory.webapp.address</name>
                    <value>dba-01:19888</value>
            </property>
    
    
            <property>
                    <name>mapreduce.jobhistory.joblist.cache.size</name>
                    <value>10000</value>
            </property>
    
            <property>
                    <name>yarn.app.mapreduce.am.resource.mb</name>
                    <value>2048</value>
            </property>
            <property>
                    <name>yarn.app.mapreduce.am.resource.cpu-vcores</name>
                    <value>2</value>
            </property>
            <property>
                    <name>mapreduce.am.max-attempts</name>
                    <value>2</value>
            </property>
            <property>
                    <name>yarn.app.mapreduce.am.command-opts</name>
                    <value>-Xmx1638m -Xms1638m -Xmn256m -XX:MaxDirectMebaiwanrySize=128m -XX:SurvivorRatio=6 -XX:MaxPermSize=128m</value>
            </property>
    
            <property>
                    <name>mapreduce.map.mebaiwanry.mb</name>
                    <value>2548</value>
            </property>
            <property>
                    <name>mapreduce.reduce.mebaiwanry.mb</name>
                    <value>4596</value>
            </property>
            <property>
                    <name>mapreduce.map.java.opts</name>
                    <value>-Xmx2048m -Xms2048m -Xmn256m -XX:MaxDirectMebaiwanrySize=128m -XX:SurvivorRatio=6 -XX:MaxPermSize=128m -XX:ParallelGCThreads=10</value>
                    <final>true</final>
            </property>
            <property>
                    <name>mapreduce.reduce.java.opts</name>
                    <value>-Xmx4096m -Xms4096m -Xmn256m -XX:MaxDirectMebaiwanrySize=128m -XX:SurvivorRatio=6 -XX:MaxPermSize=128m -XX:ParallelGCThreads=10</value>
                    <final>true</final>
            </property>
            <property>
                    <name>mapreduce.task.io.sort.factor</name>
                    <value>100</value>
            </property>
            <property>
                    <name>mapreduce.task.io.sort.mb</name>
                    <value>512</value>
            </property>
            <property>
                    <name>mapreduce.reduce.shuffle.parallelcopies</name>
                    <value>10</value>
            </property>
            <property>
                    <name>mapreduce.reduce.shuffle.merge.percent</name>
                    <value>0.8</value>
            </property>
            <property>
                    <name>mapreduce.reduce.input.buffer.percent</name>
                    <value>0.25</value>
            </property>
    
            <property>
                    <name>mapreduce.job.reduce.slowstart.completedmaps</name>
                    <value>0.5</value>
            </property>
            <property>
                    <name>mapreduce.map.speculative</name>
                    <value>true</value>
            </property>
    
            <property>
                    <name>mapreduce.shuffle.max.threads</name>
                    <value>100</value>
            </property>
            <property>
                    <name>mapreduce.reduce.input.buffer.percent</name>
                    <value>0.25</value>
            </property>
            <property>
                    <name>mapreduce.reduce.shuffle.parallelcopies</name>
                    <value>40</value>
            </property>
            <property>
                    <name>mapreduce.reduce.shuffle.merge.percent</name>
                    <value>0.8</value>
            </property>
    

    11.修改slaves文件(哪些节点运行datanode)

    #vim /home/hadoop/app/hadoop-2.7.5/etc/hadoop/slaves
    
    添加datanode节点:
    dba-01
    dba-02
    dba-03
    

    12.hadoop包分发到其他节点上

    scp -r /home/hadoop/app/hadoop-2.7.5 dba-02:/home/hadoop/app
    scp -r /home/hadoop/app/hadoop-2.7.5 dba-03:/home/hadoop/app
    scp -r /home/hadoop/app/hadoop-2.7.5 dba-04:/home/hadoop/app
    scp -r /home/hadoop/app/hadoop-2.7.5 dba-05:/home/hadoop/app
    

    13.首先启动所有的journalnode

    #cd /home/hadoop/app/hadoop-2.7.5/sbin
    #./hadoop-daemon.sh start journalnode
    

    14.namenode中一个节点上初始化

    #cd /home/hadoop/app/hadoop-2.7.5/sbin
    #hadoop namenode -format
    #hdfs zkfc -formatZK 
    #hadoop-daemon.sh start namenode
    #hadoop-daemon.sh start zkfc
    #yarn-daemon.sh start resourcemanager
    

    15.namenode另外一个节点上初始化

    #hdfs namenode -bootstrapStandby
    #hadoop-daemon.sh start namenode
    #hadoop-daemon.sh start zkfc
    #yarn-daemon.sh start resourcemanager
    

    16.namenode第一个节点上启动集群

    #cd /home/hadoop/app/hadoop-2.7.5/sbin
    #hadoop-daemon.sh start datanode
    #./mr-jobhistory-daemon.sh start historyserver
    

    17.jobserver机器启动jobhistory

    ./mr-jobhistory-daemon.sh start historyserver
    

    18.hadoop性能压测(自己选型工具进行压测)

    常见问题

    1.启动journalnode时报错:/home/hadoop/app/hadoop-2.7.5/bin/hdfs: line 304: /opt/jdk1.8.0_202//bin/java: No such file or directory

    原因:/home/hadoop/app/hadoop/etc/hadoop/hadoop-env.sh配置文件中java_home配置路径下无java

    2.hdfs集群启动之后,检查各个节点进程,发现有datanode节点未启动,启动日志如下:

    Starting namenodes on [dba-04 dba-05]
    dba-04: starting namenode, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-namenode-dba-04.out
    dba-05: starting namenode, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-namenode-dba-05.out
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: @       WARNING: POSSIBLE DNS SPOOFING DETECTED!          @
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: The ECDSA host key for dba-01 has changed,
    dba-01: and the key for the corresponding IP address 10.3.0.42
    dba-01: is unknown. This could either mean that
    dba-01: DNS SPOOFING is happening or the IP address for the host
    dba-01: and its host key have changed at the same time.
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: @    WARNING: REMOTE HOST IDENTIFICATION HAS CHANGED!     @
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: IT IS POSSIBLE THAT SOMEONE IS DOING SOMETHING NASTY!
    dba-01: Someone could be eavesdropping on you right now (man-in-the-middle attack)!
    dba-01: It is also possible that a host key has just been changed.
    dba-01: The fingerprint for the ECDSA key sent by the remote host is
    dba-01: SHA256:zCbOslLNiDBjkO5qKNSgbzvgUDYMQurHHe47MJmCueA.
    dba-01: Please contact your system administrator.
    dba-01: Add correct host key in /home/hadoop/.ssh/known_hosts to get rid of this message.
    dba-01: Offending ECDSA key in /home/hadoop/.ssh/known_hosts:2
    dba-01: ECDSA host key for dba-01 has changed and you have requested strict checking.
    dba-01: Host key verification failed.
    dba-04: starting datanode, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-datanode-dba-04.out
    dba-05: starting datanode, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-datanode-dba-05.out
    dba-03: starting datanode, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-datanode-dba-03.out
    dba-02: starting datanode, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-datanode-dba-02.out
    Starting journal nodes [dba-01 dba-02 dba-03 dba-04 dba-05]
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: @       WARNING: POSSIBLE DNS SPOOFING DETECTED!          @
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: The ECDSA host key for dba-01 has changed,
    dba-01: and the key for the corresponding IP address 10.3.0.42
    dba-01: is unknown. This could either mean that
    dba-01: DNS SPOOFING is happening or the IP address for the host
    dba-01: and its host key have changed at the same time.
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: @    WARNING: REMOTE HOST IDENTIFICATION HAS CHANGED!     @
    dba-01: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
    dba-01: IT IS POSSIBLE THAT SOMEONE IS DOING SOMETHING NASTY!
    dba-01: Someone could be eavesdropping on you right now (man-in-the-middle attack)!
    dba-01: It is also possible that a host key has just been changed.
    dba-01: The fingerprint for the ECDSA key sent by the remote host is
    dba-01: SHA256:zCbOslLNiDBjkO5qKNSgbzvgUDYMQurHHe47MJmCueA.
    dba-01: Please contact your system administrator.
    dba-01: Add correct host key in /home/hadoop/.ssh/known_hosts to get rid of this message.
    dba-01: Offending ECDSA key in /home/hadoop/.ssh/known_hosts:2  
    dba-01: ECDSA host key for dba-01 has changed and you have requested strict checking.
    dba-01: Host key verification failed.
    dba-05: journalnode running as process 22165. Stop it first.
    dba-04: journalnode running as process 23866. Stop it first.
    dba-03: journalnode running as process 17302. Stop it first.
    dba-02: journalnode running as process 16164. Stop it first.
    Starting ZK Failover Controllers on NN hosts [dba-04 dba-05]
    dba-04: starting zkfc, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-zkfc-dba-04.out
    dba-05: starting zkfc, logging to /home/hadoop/app/hadoop-2.7.5/logs/hadoop-hadoop-zkfc-dba-05.out
    
    
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  • 原文地址:https://www.cnblogs.com/slqdba/p/15702491.html
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