一、集群的规划

Zookeeper集群：

192.168.176.131 （bigdata112）192.168.176.132 （bigdata113）192.168.176.135 （bigdata114）

Hadoop集群：

192.168.176.131 （bigdata112） NameNode1 ResourceManager1 Journalnode192.168.176.132 （bigdata113） NameNode2 ResourceManager2 Journalnode192.168.176.135 （bigdata114） DataNode1 NodeManager1192.168.176.136 （bigdata115） DataNode2 NodeManager2

二、准备工作

1、安装JDK

2、配置环境变量3、配置免密码登录4、配置主机名

三、配置Zookeeper（在192.168.176.131安装）

在主节点（bigdata112）上配置ZooKeeper

（*）配置/training/zookeeper-3.4.6/conf/zoo.cfg文件

dataDir=/training/zookeeper-3.4.6/tmpserver.1=bigdata112:2888:3888server.2=bigdata113:2888:3888server.3=bigdata114:2888:3888

（*）在/training/zookeeper-3.4.6/tmp目录下创建一个myid的空文件

echo 1 > /training/zookeeper-3.4.6/tmp/myid

（*）将配置好的zookeeper拷贝到其他节点，同时修改各自的myid文件

scp -r /training/zookeeper-3.4.6/ bigdata113:/training        scp -r /training/zookeeper-3.4.6/ bigdata114:/training

（*）分别修改113和114上/training/zookeeper-3.4.6/tmp/myid为2和3

四、安装Hadoop集群（在bigdata112上安装）

1、修改hadoo-env.sh

export JAVA_HOME=/training/jdk1.8.0_144

2、修改core-site.xml

                
                 
                         
      
       fs.defaultFS
                          
      
       hdfs://ns1
                  
                 
                 
                         
      
       hadoop.tmp.dir
                          
      
       /training/hadoop-2.7.3/tmp
                  
                 
                 
                         
      
       ha.zookeeper.quorum
                          
      
       bigdata112:2181,bigdata113:2181,bigdata114:2181
                  
     
    

3、修改hdfs-site.xml（配置这个nameservice中有几个namenode）

            
     
      dfs.replication
             
     
      2
     
    
            
     
      dfs.webhdfs.enabled
             
     
      true
     
    
                 
                 
                     
      
       dfs.nameservices
                      
      
       ns1
                  
                 
                 
                     
      
       dfs.ha.namenodes.ns1
                      
      
       nn1,nn2
                  
                 
                 
                     
      
       dfs.namenode.rpc-address.ns1.nn1
                      
      
       bigdata112:9000
                  
                 
                 
                     
      
       dfs.namenode.http-address.ns1.nn1
                      
      
       bigdata112:50070
                  
                 
                 
                     
      
       dfs.namenode.rpc-address.ns1.nn2
                      
      
       bigdata113:9000
                  
                 
                 
                     
      
       dfs.namenode.http-address.ns1.nn2
                      
      
       bigdata113:50070
                  
                 
                 
                     
      
       dfs.namenode.shared.edits.dir
                      
      
       qjournal://bigdata112:8485;bigdata113:8485;/ns1
                  
                 
                 
                     
      
       dfs.journalnode.edits.dir
                      
      
       /training/hadoop-2.7.3/journal
                  
                 
                 
                     
      
       dfs.ha.automatic-failover.enabled
                      
      
       true
                  
                 
                 
                     
      
       dfs.client.failover.proxy.provider.ns1
                      
      
       org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider
                  
                 
                 
                     
      
       dfs.ha.fencing.methods
                      
      
                           sshfence                    shell(/bin/true)                
                  
                 
                 
                     
      
       dfs.ha.fencing.ssh.private-key-files
                      
      
       /root/.ssh/id_rsa
                  
                 
                 
                     
      
       dfs.ha.fencing.ssh.connect-timeout
                      
      
       30000
                  
     
    

4、修改mapred-site.xml

        
                 
      
       mapreduce.framework.name
                  
      
       yarn
          
         
    

5、修改yarn-site.xml

            
             
                
      
       yarn.resourcemanager.ha.enabled
                 
      
       true
              
             
             
                
      
       yarn.resourcemanager.cluster-id
                 
      
       yrc
              
             
             
                
      
       yarn.resourcemanager.ha.rm-ids
                 
      
       rm1,rm2
              
             
             
                
      
       yarn.resourcemanager.hostname.rm1
                 
      
       bigdata112
              
             
                
      
       yarn.resourcemanager.hostname.rm2
                 
      
       bigdata113
              
             
             
                
      
       yarn.resourcemanager.zk-address
                 
      
       bigdata112:2181,bigdata113:2181,bigdata114:2181
              
             
                
      
       yarn.nodemanager.aux-services
                 
      
       mapreduce_shuffle
              
         
    

6、修改slaves

bigdata14    bigdata15

7、将配置好的hadoop拷贝到其他节点

scp -r /training/hadoop-2.7.3/ root@bigdata113:/training/    scp -r /training/hadoop-2.7.3/ root@bigdata114:/training/    scp -r /training/hadoop-2.7.3/ root@bigdata115:/training/

五、启动Zookeeper集群

进到zk的安装目录的bin目录下：

启动    ./zkServer.sh start     查看状态    ./zkServer.sh status

六、在bigdata112和bigdata113上启动journalnode

hadoop-daemon.sh start journalnode

七、格式化HDFS（在bigdata112上执行）

1. 格式化HDFS

   hdfs namenode -format

2.将112上这台的/training/hadoop-2.7.3/tmp/dfs拷贝到bigdata13的/training/hadoop-2.7.3/tmp/dfs下

scp -r /training/hadoop-2.7.3/tmp/dfs/* root@bigdata113:/training/hadoop-2.7.3/tmp/dfs/

3.格式化zookeeper

hdfs zkfc -formatZK

日志：

17/07/13 00:34:33 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/ns1 in ZK.

八、在bigdata12上启动Hadoop集群

start-all.sh日志：    Starting namenodes on [bigdata12 bigdata13]    bigdata12: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop113.out    bigdata13: starting namenode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-namenode-hadoop112.out    bigdata14: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop115.out    bigdata15: starting datanode, logging to /root/training/hadoop-2.4.1/logs/hadoop-root-datanode-hadoop114.out    bigdata13: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata13.out    bigdata12: starting zkfc, logging to /root/training/hadoop-2.7.3/logs/hadoop-root-zkfc-bigdata12.outbigdata113上的ResourceManager需要单独启动

命令：yarn-daemon.sh start resourcemanager

九、问题延伸

1、隔离机制和隔离级别    （*）关系型数据库：如果不考虑事务隔离级别，造成脏读、不可重复读、幻读    （*）HDFS的HA：如果不考虑隔离机制（隔离级别），造成脑裂的问题2、什么是脑裂的问题？    脑裂的问题，针对的是数据节点（DataNode）    由于某种原因，造成了整个HDFS中存在多个active的NameDode，这时候DataNode就不知道谁是真正的NameNode。