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Hadoop-2.3.0-cdh5.0.1完全分布式环境搭建（NameNode,ResourceManager HA）

Hadoop2.3.0cdh5.0.1NameNode HAResourceMangaer HA 
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编写不易，转载请注明（http://shihlei.iteye.com/blog/2084711）！

说明

       本文搭建Hadoop CDH5.0.1 分布式系统，包括NameNode ，ResourceManger HA，忽略了Web Application Proxy 和Job HistoryServer。 

        word版：见附件吧！

一概述

（一）HDFS

1）基础架构

（1）NameNode（Master）

  • 命名空间管理：命名空间支持对HDFS中的目录、文件和块做类似文件系统的创建、修改、删除、列表文件和目录等基本操作。
  • 块存储管理

（2）DataNode（Slaver）

namenode和client的指令进行存储或者检索block，并且周期性的向namenode节点报告它存了哪些文件的block

2）HA架构

 

 

使用Active NameNode，Standby NameNode 两个结点解决单点问题，两个结点通过JounalNode共享状态，通过ZKFC 选举Active ，监控状态，自动备援。

（1）Active NameNode：

接受client的RPC请求并处理，同时写自己的Editlog和共享存储上的Editlog，接收DataNode的Block report, block location updates和heartbeat；

（2）Standby NameNode：

      同样会接到来自DataNode的Block report, block location updates和heartbeat，同时会从共享存储的Editlog上读取并执行这些log操作，使得自己的NameNode中的元数据（Namespcae information + Block locations map）都是和Active NameNode中的元数据是同步的。所以说Standby模式的NameNode是一个热备（Hot Standby NameNode），一旦切换成Active模式，马上就可以提供NameNode服务

（3）JounalNode：

用于Active NameNode ， Standby NameNode 同步数据，本身由一组JounnalNode结点组成，该组结点基数个，支持Paxos协议，保证高可用，是CDH5唯一支持的共享方式（相对于CDH4 促在NFS共享方式）

（4）ZKFC：

监控NameNode进程，自动备援。

（二）YARN

1）基础架构

（1）ResourceManager(RM)

接收客户端任务请求，接收和监控NodeManager(NM)的资源情况汇报，负责资源的分配与调度，启动和监控ApplicationMaster(AM)。

（2）NodeManager

节点上的资源管理，启动Container运行task计算，上报资源、container情况给RM和任务处理情况给AM。

（3）ApplicationMaster

单个Application(Job)的task管理和调度，向RM进行资源的申请，向NM发出launch Container指令，接收NM的task处理状态信息。NodeManager

（4）Web Application Proxy

用于防止Yarn遭受Web攻击，本身是ResourceManager的一部分，可通过配置独立进程。ResourceManager Web的访问基于守信用户，当Application Master运行于一个非受信用户，其提供给ResourceManager的可能是非受信连接，Web Application Proxy可以阻止这种连接提供给RM。

（5）Job History Server

NodeManager在启动的时候会初始化LogAggregationService服务, 该服务会在把本机执行的container log (在container结束的时候)收集并存放到hdfs指定的目录下. ApplicationMaster会把jobhistory信息写到hdfs的jobhistory临时目录下, 并在结束的时候把jobhisoty移动到最终目录, 这样就同时支持了job的recovery.History会启动web和RPC服务, 用户可以通过网页或RPC方式获取作业的信息

2）HA架构

 

 

      ResourceManager HA 由一对Active，Standby结点构成，通过RMStateStore存储内部数据和主要应用的数据及标记。目前支持的可替代的RMStateStore实现有：基于内存的MemoryRMStateStore，基于文件系统的FileSystemRMStateStore，及基于zookeeper的ZKRMStateStore。

ResourceManager HA的架构模式同NameNode HA的架构模式基本一致，数据共享由RMStateStore，而ZKFC成为 ResourceManager进程的一个服务，非独立存在。

 二 规划

（一）版本

组件名

版本

说明

JRE

java version "1.7.0_60"

Java(TM) SE Runtime Environment (build 1.7.0_60-b19)

Java HotSpot(TM) Client VM (build 24.60-b09, mixed mode)

 

Hadoop

hadoop-2.3.0-cdh5.0.1.tar.gz

主程序包

 

Zookeeper

zookeeper-3.4.5-cdh5.0.1.tar.gz

热切,Yarn 存储数据使用的协调服务

（二）主机规划

IP

Host

部署模块

进程

8.8.8.11

Hadoop-NN-01

NameNode

ResourceManager

NameNode

DFSZKFailoverController

ResourceManager

8.8.8.12

Hadoop-NN-02

NameNode

ResourceManager

NameNode

DFSZKFailoverController

ResourceManager

8.8.8.13

Hadoop-DN-01

Zookeeper-01

DataNode

NodeManager

Zookeeper

DataNode

NodeManager

JournalNode

QuorumPeerMain

8.8.8.14

Hadoop-DN-02

Zookeeper-02

DataNode

NodeManager

Zookeeper

DataNode

NodeManager

JournalNode

QuorumPeerMain

8.8.8.15

Hadoop-DN-03

Zookeeper-03

DataNode

NodeManager

Zookeeper

DataNode

NodeManager

JournalNode

QuorumPeerMain

各个进程解释：

  • NameNode
  • ResourceManager
  • DFSZKFC：DFS Zookeeper Failover Controller 激活Standby NameNode
  • DataNode
  • NodeManager
  • JournalNode：NameNode共享editlog结点服务（如果使用NFS共享，则该进程和所有启动相关配置接可省略）。
  • QuorumPeerMain：Zookeeper主进程

（三）目录规划

名称

路径

$HADOOP_HOME

/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1

Data

$ HADOOP_HOME/data

Log

$ HADOOP_HOME/logs

 三 环境准备

1）关闭防火墙

root 用户：

[root@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]# service iptables stop

iptables: Flushing firewall rules: [  OK  ]

iptables: Setting chains to policy ACCEPT: filter [  OK  ]

iptables: Unloading modules: [  OK  ]

验证：

[root@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]# service  iptables status

iptables: Firewall is not running.

2）安装JRE：略

3）安装Zookeeper ：参见《Zookeeper-3.4.5-cdh5.0.1 单机模式、副本 ...》

4）配置SSH互信：

（1）Hadoop-NN-01创建密钥：

[zero@CentOS-Cluster-01 ~]$ ssh-keygen

Generating public/private rsa key pair.

Enter file in which to save the key (/home/zero/.ssh/id_rsa):

Created directory '/home/zero/.ssh'.

Enter passphrase (empty for no passphrase):

Enter same passphrase again:

Your identification has been saved in /home/zero/.ssh/id_rsa.

Your public key has been saved in /home/zero/.ssh/id_rsa.pub.

The key fingerprint is:

28:0a:29:1d:98:56:55:db:ec:83:93:56:8a:0f:6c:ea zero@CentOS-Cluster-01

The key's randomart image is:

+--[ RSA 2048]----+

|   .....         |

| o.     +        |

|o..    . +       |

|.o .. ..*        |

|+ . .=.*So       |

|.. .o.+ . .      |

|  ..   .         |

|  .              |

|   E             |

+-----------------+

（2）分发密钥：

[zero@CentOS-Cluster-01 ~]$ ssh-copy-id -i ~/.ssh/id_rsa.pub zero@Hadoop-NN-01

The authenticity of host 'hadoop-nn-01 (8.8.8.11)' can't be established.

RSA key fingerprint is a6:11:09:49:8c:fe:b2:fb:49:d5:01:fa:13:1b:32:24.

Are you sure you want to continue connecting (yes/no)? yes

Warning: Permanently added 'hadoop-nn-01,8.8.8.11' (RSA) to the list of known hosts.

puppet@hadoop-nn-01's password:

Permission denied, please try again.

puppet@hadoop-nn-01's password:

[zero@CentOS-Cluster-01 ~]$  ssh-copy-id -i ~/.ssh/id_rsa.pub zero@Hadoop-NN-01

zero@hadoop-nn-01's password:

Now try logging into the machine, with "ssh 'zero@Hadoop-NN-01'", and check in:

 

  .ssh/authorized_keys

 

to make sure we haven't added extra keys that you weren't expecting.

[zero@CentOS-Cluster-01 ~]$  ssh-copy-id -i ~/.ssh/id_rsa.pub zero@Hadoop-NN-02

（…略…）

[zero@CentOS-Cluster-01 ~]$  ssh-copy-id -i ~/.ssh/id_rsa.pub zero@Hadoop-DN-01

（…略…）

[zero@CentOS-Cluster-01 ~]$  ssh-copy-id -i ~/.ssh/id_rsa.pub zero@Hadoop-DN-02

（…略…）

[zero@CentOS-Cluster-01 ~]$  ssh-copy-id -i ~/.ssh/id_rsa.pub zero@Hadoop-DN-03

（…略…）

（3）验证：

[zero@CentOS-Cluster-01 ~]$ ssh Hadoop-NN-01

Last login: Sun Jun 22 19:56:23 2014 from 8.8.8.1

[zero@CentOS-Cluster-01 ~]$ exit

logout

Connection to Hadoop-NN-01 closed.

[zero@CentOS-Cluster-01 ~]$ ssh Hadoop-NN-02

Last login: Sun Jun 22 20:03:31 2014 from 8.8.8.1

[zero@CentOS-Cluster-03 ~]$ exit

logout

Connection to Hadoop-NN-02 closed.

[zero@CentOS-Cluster-01 ~]$ ssh Hadoop-DN-01

Last login: Mon Jun 23 02:00:07 2014 from centos_cluster_01

[zero@CentOS-Cluster-03 ~]$ exit

logout

Connection to Hadoop-DN-01 closed.

[zero@CentOS-Cluster-01 ~]$ ssh Hadoop-DN-02

Last login: Sun Jun 22 20:07:03 2014 from 8.8.8.1

[zero@CentOS-Cluster-04 ~]$ exit

logout

Connection to Hadoop-DN-02 closed.

[zero@CentOS-Cluster-01 ~]$ ssh Hadoop-DN-03

Last login: Sun Jun 22 20:07:05 2014 from 8.8.8.1

[zero@CentOS-Cluster-05 ~]$ exit

logout

Connection to Hadoop-DN-03 closed.

5）配置/etc/hosts并分发：

[root@CentOS-Cluster-01 zero]# vi /etc/hosts

127.0.0.1   localhost localhost.localdomain localhost4 localhost4.localdomain4

::1         localhost localhost.localdomain localhost6 localhost6.localdomain6

8.8.8.10 CentOS-StandAlone

8.8.8.11 CentOS-Cluster-01 Hadoop-NN-01

8.8.8.12 CentOS-Cluster-02 Hadoop-NN-02

8.8.8.13 CentOS-Cluster-03 Hadoop-DN-01 Zookeeper-01

8.8.8.14 CentOS-Cluster-04 Hadoop-DN-02 Zookeeper-02

8.8.8.15 CentOS-Cluster-05 Hadoop-DN-03 Zookeeper-03

6）配置环境变量：vi ~/.bashrc 然后 source ~/.bashrc

[zero@CentOS-Cluster-01 ~]$ vi ~/.bashrc

……

 

# hadoop cdh5

export HADOOP_HOME=/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1

export PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/bin

[zero@CentOS-Cluster-01 ~]$ source ~/.bashrc

四 安装

1）解压

[puppet@BigData-01 cdh4.4]$ tar -xvf hadoop-2.0.0-cdh4.4.0.tar.gz

2）修改配置文件

说明：

配置名称

类型

说明

hadoop-env.sh

Bash脚本

Hadoop运行环境变量设置

core-site.xml

xml

配置Hadoop core，如IO

hdfs-site.xml

xml

配置HDFS守护进程：NN、JN、DN

yarn-env.sh

Bash脚本

Yarn运行环境变量设置

yarn-site.xml

xml

Yarn框架配置环境

mapred-site.xml

xml

MR属性设置

capacity-scheduler.xml

xml

Yarn调度属性设置

container-executor.cfg

Cfg

Yarn Container配置

mapred-queues.xml

xml

MR队列设置

hadoop-metrics.properties

Java属性

Hadoop Metrics配置

hadoop-metrics2.properties

Java属性

Hadoop Metrics配置

slaves

Plain Text

DN节点配置

exclude

Plain Text

移除DN节点配置文件

log4j.properties

 

系统日志设置

configuration.xsl

 

 

（1）修改$HADOOP_HOME/etc/hadoop/hadoop-env.sh：

#--------------------Java Env------------------------------
export JAVA_HOME="/usr/runtime/java/jdk1.7.0_60"

#--------------------Hadoop Env------------------------------
#export HADOOP_PID_DIR=
export HADOOP_PREFIX="/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1"

#--------------------Hadoop Daemon Options-----------------
#export HADOOP_NAMENODE_OPTS="-XX:+UseParallelGC ${HADOOP_NAMENODE_OPTS}"
#export HADOOP_DATANODE_OPTS=

#--------------------Hadoop Logs---------------------------
#export HADOOP_LOG_DIR=

（2）修改$HADOOP_HOME/etc/hadoop/hadoop-site.xml

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
	<!--Yarn 需要使用 fs.defaultFS 指定NameNode URI -->
	<property>
		<name>fs.defaultFS</name>
		<value>hdfs://mycluster</value>
	</property>
	<!--HDFS超级用户 -->
	<property>
		<name>dfs.permissions.superusergroup</name>
		<value>zero</value>
	</property>
	<!--==============================Trash机制======================================= -->
	<property>
		<!--多长时间创建CheckPoint NameNode截点上运行的CheckPointer 从Current文件夹创建CheckPoint;默认：0 由fs.trash.interval项指定 -->
		<name>fs.trash.checkpoint.interval</name>
		<value>0</value>
	</property>
	<property>
		<!--多少分钟.Trash下的CheckPoint目录会被删除,该配置服务器设置优先级大于客户端，默认：0 不删除 -->
		<name>fs.trash.interval</name>
		<value>1440</value>
	</property>
</configuration>

 （3）修改$HADOOP_HOME/etc/hadoop/hdfs-site.xml

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
	<!--开启web hdfs -->
	<property>
		<name>dfs.webhdfs.enabled</name>
		<value>true</value>
	</property>
	<property>
		<name>dfs.namenode.name.dir</name>
		<value>/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/data/dfs/name</value>
		<description> namenode 存放name table(fsimage)本地目录（需要修改）</description>
	</property>
	<property>
		<name>dfs.namenode.edits.dir</name>
		<value>${dfs.namenode.name.dir}</value>
		<description>namenode粗放 transaction file(edits)本地目录（需要修改）</description>
	</property>
	<property>
		<name>dfs.datanode.data.dir</name>
		<value>/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/data/dfs/data</value>
		<description>datanode存放block本地目录（需要修改）</description>
	</property>
	<property>
		<name>dfs.replication</name>
		<value>1</value>
	</property>
	<!-- 块大小 （默认） -->
	<property>
		<name>dfs.blocksize</name>
		<value>268435456</value>
	</property>
	<!--======================================================================= -->
	<!--HDFS高可用配置 -->
	<!--nameservices逻辑名 -->
	<property>
		<name>dfs.nameservices</name>
		<value>mycluster</value>
	</property>
	<property>
		<!--设置NameNode IDs 此版本最大只支持两个NameNode -->
		<name>dfs.ha.namenodes.mycluster</name>
		<value>nn1,nn2</value>
	</property>
	<!-- Hdfs HA: dfs.namenode.rpc-address.[nameservice ID] rpc 通信地址 -->
	<property>
		<name>dfs.namenode.rpc-address.mycluster.nn1</name>
		<value>Hadoop-NN-01:8020</value>
	</property>
	<property>
		<name>dfs.namenode.rpc-address.mycluster.nn2</name>
		<value>Hadoop-NN-02:8020</value>
	</property>
	<!-- Hdfs HA: dfs.namenode.http-address.[nameservice ID] http 通信地址 -->
	<property>
		<name>dfs.namenode.http-address.mycluster.nn1</name>
		<value>Hadoop-NN-01:50070</value>
	</property>
	<property>
		<name>dfs.namenode.http-address.mycluster.nn2</name>
		<value>Hadoop-NN-02:50070</value>
	</property>

	<!--==================Namenode editlog同步 ============================================ -->
	<!--保证数据恢复 -->
	<property>
		<name>dfs.journalnode.http-address</name>
		<value>0.0.0.0:8480</value>
	</property>
	<property>
		<name>dfs.journalnode.rpc-address</name>
		<value>0.0.0.0:8485</value>
	</property>
	<property>
		<!--设置JournalNode服务器地址，QuorumJournalManager 用于存储editlog -->
		<!--格式：qjournal://<host1:port1>;<host2:port2>;<host3:port3>/<journalId> 端口同journalnode.rpc-address -->
		<name>dfs.namenode.shared.edits.dir</name>
		<value>qjournal://Hadoop-DN-01:8485;Hadoop-DN-02:8485;Hadoop-DN-03:8485/mycluster</value>
	</property>
	<property>
		<!--JournalNode存放数据地址 -->
		<name>dfs.journalnode.edits.dir</name>
		<value>/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/data/dfs/jn</value>
	</property>
	<!--==================DataNode editlog同步 ============================================ -->
	<property>
		<!--DataNode,Client连接Namenode识别选择Active NameNode策略 -->
		<name>dfs.client.failover.proxy.provider.mycluster</name>
		<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
	</property>
	<!--==================Namenode fencing：=============================================== -->
	<!--Failover后防止停掉的Namenode启动，造成两个服务 -->
	<property>
		<name>dfs.ha.fencing.methods</name>
		<value>sshfence</value>
	</property>
	<property>
		<name>dfs.ha.fencing.ssh.private-key-files</name>
		<value>/home/zero/.ssh/id_rsa</value>
	</property>
	<property>
		<!--多少milliseconds 认为fencing失败 -->
		<name>dfs.ha.fencing.ssh.connect-timeout</name>
		<value>30000</value>
	</property>

	<!--==================NameNode auto failover base ZKFC and Zookeeper====================== -->
	<!--开启基于Zookeeper及ZKFC进程的自动备援设置,监视进程是否死掉 -->
	<property>
		<name>dfs.ha.automatic-failover.enabled</name>
		<value>true</value>
	</property>
	<property>
		<name>ha.zookeeper.quorum</name>
		<value>Zookeeper-01:2181,Zookeeper-02:2181,Zookeeper-03:2181</value>
	</property>
	<property>
		<!--指定ZooKeeper超时间隔，单位毫秒 -->
		<name>ha.zookeeper.session-timeout.ms</name>
		<value>2000</value>
	</property>
</configuration>

 （4）修改$HADOOP_HOME/etc/hadoop/yarn-env.sh

#Yarn Daemon Options
#export YARN_RESOURCEMANAGER_OPTS
#export YARN_NODEMANAGER_OPTS
#export YARN_PROXYSERVER_OPTS
#export HADOOP_JOB_HISTORYSERVER_OPTS

#Yarn Logs
export YARN_LOG_DIR=” /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/logs”

 （5）$HADOOP_HOEM/etc/hadoop/mapred-site.xml

<configuration>
	<!-- 配置 MapReduce Applications -->
	<property>
		<name>mapreduce.framework.name</name>
		<value>yarn</value>
	</property>
	<!-- JobHistory Server ============================================================== -->
	<!-- 配置 MapReduce JobHistory Server 地址 ，默认端口10020 -->
	<property>
		<name>mapreduce.jobhistory.address</name>
		<value>0.0.0.0:10020</value>
	</property>
	<!-- 配置 MapReduce JobHistory Server web ui 地址， 默认端口19888 -->
	<property>
		<name>mapreduce.jobhistory.webapp.address</name>
		<value>0.0.0.0:19888</value>
	</property>
</configuration>

 （6）修改$HADOOP_HOME/etc/hadoop/yarn-site.xml

<configuration>
	<!-- nodemanager 配置 ================================================= -->
	<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>
		<description>Address where the localizer IPC is.</description>
		<name>yarn.nodemanager.localizer.address</name>
		<value>0.0.0.0:23344</value>
	</property>
	<property>
		<description>NM Webapp address.</description>
		<name>yarn.nodemanager.webapp.address</name>
		<value>0.0.0.0:23999</value>
	</property>

	<!-- HA 配置 =============================================================== -->
	<!-- Resource Manager Configs -->
	<property>
		<name>yarn.resourcemanager.connect.retry-interval.ms</name>
		<value>2000</value>
	</property>
	<property>
		<name>yarn.resourcemanager.ha.enabled</name>
		<value>true</value>
	</property>
	<property>
		<name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
		<value>true</value>
	</property>
	<!-- 使嵌入式自动故障转移。HA环境启动，与 ZKRMStateStore 配合 处理fencing -->
	<property>
		<name>yarn.resourcemanager.ha.automatic-failover.embedded</name>
		<value>true</value>
	</property>
	<!-- 集群名称，确保HA选举时对应的集群 -->
	<property>
		<name>yarn.resourcemanager.cluster-id</name>
		<value>yarn-cluster</value>
	</property>
	<property>
		<name>yarn.resourcemanager.ha.rm-ids</name>
		<value>rm1,rm2</value>
	</property>
    <!—这里RM主备结点需要单独指定,（可选）
	<property>
        <name>yarn.resourcemanager.ha.id</name>
        <value>rm2</value>
</property>
-->
	<property>
		<name>yarn.resourcemanager.scheduler.class</name>
		<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
	</property>
	<property>
		<name>yarn.resourcemanager.recovery.enabled</name>
		<value>true</value>
	</property>
	<property>
		<name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name>
		<value>5000</value>
	</property>
	<!-- ZKRMStateStore 配置 -->
	<property>
		<name>yarn.resourcemanager.store.class</name>
		<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
	</property>
	<property>
		<name>yarn.resourcemanager.zk-address</name>
		<value>Zookeeper-01:2181,Zookeeper-02:2181,Zookeeper-03:2181</value>
	</property>
	<property>
		<name>yarn.resourcemanager.zk.state-store.address</name>
		<value>Zookeeper-01:2181,Zookeeper-02:2181,Zookeeper-03:2181</value>
	</property>
	<!-- Client访问RM的RPC地址 (applications manager interface) -->
	<property>
		<name>yarn.resourcemanager.address.rm1</name>
		<value>Hadoop-NN-01:23140</value>
	</property>
	<property>
		<name>yarn.resourcemanager.address.rm2</name>
		<value>Hadoop-NN-02:23140</value>
	</property>
	<!-- AM访问RM的RPC地址(scheduler interface) -->
	<property>
		<name>yarn.resourcemanager.scheduler.address.rm1</name>
		<value>Hadoop-NN-01:23130</value>
	</property>
	<property>
		<name>yarn.resourcemanager.scheduler.address.rm2</name>
		<value>Hadoop-NN-02:23130</value>
	</property>
	<!-- RM admin interface -->
	<property>
		<name>yarn.resourcemanager.admin.address.rm1</name>
		<value>Hadoop-NN-01:23141</value>
	</property>
	<property>
		<name>yarn.resourcemanager.admin.address.rm2</name>
		<value>Hadoop-NN-02:23141</value>
	</property>
	<!--NM访问RM的RPC端口 -->
	<property>
		<name>yarn.resourcemanager.resource-tracker.address.rm1</name>
		<value>Hadoop-NN-01:23125</value>
	</property>
	<property>
		<name>yarn.resourcemanager.resource-tracker.address.rm2</name>
		<value>Hadoop-NN-02:23125</value>
	</property>
	<!-- RM web application 地址 -->
	<property>
		<name>yarn.resourcemanager.webapp.address.rm1</name>
		<value>Hadoop-NN-01:23188</value>
	</property>
	<property>
		<name>yarn.resourcemanager.webapp.address.rm2</name>
		<value>Hadoop-NN-02:23188</value>
	</property>
	<property>
		<name>yarn.resourcemanager.webapp.https.address.rm1</name>
		<value>Hadoop-NN-01:23189</value>
	</property>
	<property>
		<name>yarn.resourcemanager.webapp.https.address.rm2</name>
		<value>Hadoop-NN-02:23189</value>
	</property>
</configuration>

（7）修改slaves

[zero@CentOS-Cluster-01  hadoop]$ vi slaves

Hadoop-DN-01

Hadoop-DN-02

Hadoop-DN-03

3）分发程序

[zero@CentOS-Cluster-01 ~]$ scp -r /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1 zero@Hadoop-NN-02: /home/zero/hadoop/

…….

[zero@CentOS-Cluster-01 ~]$ scp -r /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1 zero@Hadoop-DN-01: /home/zero/hadoop/

…….

[zero@CentOS-Cluster-01 ~]$ scp -r /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1 zero@Hadoop-DN-02: /home/zero/hadoop/

…….

[zero@CentOS-Cluster-01 ~]$ scp -r /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1 zero@Hadoop-DN-03: /home/zero/hadoop/

…….

4）启动HDFS

（1）启动JournalNode

格式化前需要在JournalNode结点上启动JournalNode：

[zero@CentOS-Cluster-03 hadoop-2.3.0-cdh5.0.1]$ hadoop-daemon.sh start journalnode

starting journalnode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-journalnode-BigData-03.out
验证JournalNode：

[zero@CentOS-Cluster-03 hadoop-2.3.0-cdh5.0.1]$ jps

25918 QuorumPeerMain

16728 JournalNode

16772 Jps

（2）NameNode 格式化：

结点Hadoop-NN-01：hdfs namenode -format

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ hdfs namenode -format

14/06/23 21:02:49 INFO namenode.NameNode: STARTUP_MSG:

/************************************************************

STARTUP_MSG: Starting NameNode

STARTUP_MSG:   host = CentOS-Cluster-01/8.8.8.11

STARTUP_MSG:   args = [-format]

STARTUP_MSG:   version = 2.3.0-cdh5.0.1

STARTUP_MSG:   classpath =…

STARTUP_MSG:   build =…

STARTUP_MSG:   java = 1.7.0_60

************************************************************/

 (…略…)

14/06/23 21:02:57 INFO common.Storage: Storage directory /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/data/dfs/name has been successfully formatted. (…略…)

14/06/23 21:02:59 INFO namenode.NameNode: SHUTDOWN_MSG:

/************************************************************

SHUTDOWN_MSG: Shutting down NameNode at CentOS-Cluster-01/8.8.8.11

************************************************************/

（3）同步NameNode元数据：

同步Hadoop-NN-01元数据到Hadoop-NN-02

主要是：dfs.namenode.name.dir，dfs.namenode.edits.dir还应该确保共享存储目录下(dfs.namenode.shared.edits.dir ) 包含NameNode 所有的元数据。

[puppet@BigData-01 hadoop-2.0.0-cdh4.4.0]$ scp -r data/ zero@Hadoop-NN-02:/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1

seen_txid                           100%    2     0.0KB/s   00:00   

VERSION                            100%  201     0.2KB/s   00:00   

seen_txid                           100%    2     0.0KB/s   00:00   

fsimage_0000000000000000000.md5    100%   62     0.1KB/s   00:00   

fsimage_0000000000000000000         100%  121     0.1KB/s   00:00   

VERSION                            100%  201     0.2KB/s   00:00 

（4）初始化ZFCK：

创建ZNode，记录状态信息。

结点Hadoop-NN-01：hdfs zkfc -formatZK

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ hdfs zkfc -formatZK

14/06/23 23:22:28 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

14/06/23 23:22:28 INFO tools.DFSZKFailoverController: Failover controller configured for NameNode NameNode at Hadoop-NN-01/8.8.8.11:8020

14/06/23 23:22:28 INFO zookeeper.ZooKeeper: Client environment:zookeeper.version=3.4.5-cdh5.0.1--1, built on 05/06/2014 18:50 GMT

14/06/23 23:22:28 INFO zookeeper.ZooKeeper: Client environment:host.name=CentOS-Cluster-01

14/06/23 23:22:28 INFO zookeeper.ZooKeeper: Client environment:java.version=1.7.0_60

14/06/23 23:22:28 INFO zookeeper.ZooKeeper: Client environment:java.vendor=Oracle Corporation

14/06/23 23:22:28 INFO zookeeper.ZooKeeper: Client environment:java.home=/usr/runtime/java/jdk1.7.0_60/jre

14/06/23 23:22:28 INFO zookeeper.ZooKeeper: Client environment:java.class.path=...

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:java.library.path=/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/lib/native

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:java.io.tmpdir=/tmp

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:java.compiler=<NA>

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:os.name=Linux

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:os.arch=i386

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:os.version=2.6.32-431.el6.i686

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:user.name=zero

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:user.home=/home/zero

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Client environment:user.dir=/home/zero/hadoop/hadoop-2.3.0-cdh5.0.1

14/06/23 23:22:29 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=Zookeeper-01:2181,Zookeeper-02:2181,Zookeeper-03:2181 sessionTimeout=2000 watcher=org.apache.hadoop.ha.ActiveStandbyElector$WatcherWithClientRef@150c2b0

14/06/23 23:22:29 INFO zookeeper.ClientCnxn: Opening socket connection to server CentOS-Cluster-03/8.8.8.13:2181. Will not attempt to authenticate using SASL (unknown error)

14/06/23 23:22:29 INFO zookeeper.ClientCnxn: Socket connection established to CentOS-Cluster-03/8.8.8.13:2181, initiating session

14/06/23 23:22:29 INFO zookeeper.ClientCnxn: Session establishment complete on server CentOS-Cluster-03/8.8.8.13:2181, sessionid = 0x146cc0517b30002, negotiated timeout = 4000

14/06/23 23:22:29 INFO ha.ActiveStandbyElector: Session connected.

14/06/23 23:22:30 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/mycluster in ZK.

14/06/23 23:22:30 INFO zookeeper.ZooKeeper: Session: 0x146cc0517b30002 closed

（5）启动

集群启动法：Hadoop-NN-01:

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ start-dfs.sh

14/04/23 01:54:58 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

Starting namenodes on [Hadoop-NN-01 Hadoop-NN-02]

Hadoop-NN-01: starting namenode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-namenode-BigData-01.out

Hadoop-NN-02: starting namenode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-namenode-BigData-02.out

Hadoop-DN-01: starting datanode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-datanode-BigData-03.out

Hadoop-DN-02: starting datanode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-datanode-BigData-04.out

Hadoop-DN-03: starting datanode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-datanode-BigData-05.out

Starting journal nodes [Hadoop-DN-01 Hadoop-DN-02 Hadoop-DN-03]

Hadoop-DN-01: starting journalnode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-journalnode-BigData-03.out

Hadoop-DN-03: starting journalnode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-journalnode-BigData-05.out

Hadoop-DN-02: starting journalnode, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-journalnode-BigData-04.out

14/04/23 01:55:29 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

Starting ZK Failover Controllers on NN hosts [Hadoop-NN-01 Hadoop-NN-02]

Hadoop-NN-01: starting zkfc, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-zkfc-BigData-01.out

Hadoop-NN-02: starting zkfc, logging to /home/puppet/hadoop/cdh4.4/hadoop-2.0.0-cdh4.4.0/logs/hadoop-puppet-zkfc-BigData-02.out

单进程启动法：

<1>NameNode（Hadoop-NN-01，Hadoop-NN-02）：

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ hadoop-daemon.sh start namenode

<2>DataNode（Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03）：

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ hadoop-daemon.sh start datanode

<3>JournalNode（Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03）：

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ hadoop-daemon.sh start journalnode

<4>ZKFC（Hadoop-NN-01，Hadoop-NN-02）：

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ hadoop-daemon.sh start zkfc
（6）验证
<1>进程
NameNode：

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ jps

4001 NameNode

4290 DFSZKFailoverController

4415 Jps
DataNode：

[zero@CentOS-Cluster-03 hadoop-2.3.0-cdh5.0.1]$ jps

25918 QuorumPeerMain

19217 JournalNode

19143 DataNode

19351 Jps

<2>页面:

Active结点:http://8.8.8.10:50070



 JSP:


 StandBy结点：


 JSP:


 （7）停止:stop-dfs.sh

5）启动Yarn

（1）启动

<1>集群启动

Hadoop-NN-01启动Yarn，命令所在目录：$HADOOP_HOME/sbin

[zero@CentOS-Cluster-01 hadoop]$ start-yarn.sh

starting yarn daemons

starting resourcemanager, logging to /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/logs/yarn-zero-resourcemanager-CentOS-Cluster-01.out

Hadoop-DN-02: starting nodemanager, logging to /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/logs/yarn-zero-nodemanager-CentOS-Cluster-04.out

Hadoop-DN-03: starting nodemanager, logging to /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/logs/yarn-zero-nodemanager-CentOS-Cluster-05.out

Hadoop-DN-01: starting nodemanager, logging to /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/logs/yarn-zero-nodemanager-CentOS-Cluster-03.out

Hadoop-NN-02备机启动RM：

[zero@CentOS-Cluster-02 hadoop]$ yarn-daemon.sh start resourcemanager

starting resourcemanager, logging to /home/zero/hadoop/hadoop-2.3.0-cdh5.0.1/logs/yarn-zero-resourcemanager-CentOS-Cluster-02.o

<2>单进程启动

ResourceManager（Hadoop-NN-01，Hadoop-NN-02）：

[zero@CentOS-Cluster-01 hadoop-2.3.0-cdh5.0.1]$ yarn-daemon.sh start resourcemanager

DataNode（Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03）：

[zero@CentOS-Cluster-03 hadoop-2.3.0-cdh5.0.1]$ yarn-daemon.sh start nodemanager

（2）验证

<1>进程：

JobTracker：Hadoop-NN-01，Hadoop-NN-02

[zero@CentOS-Cluster-01 hadoop]$ jps

7454 NameNode

14684 Jps

14617 ResourceManager

7729 DFSZKFailoverController

TaskTracker：Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03

[zero@CentOS-Cluster-03 ~]$ jps

8965 Jps

5228 JournalNode

5137 DataNode

2514 QuorumPeerMain

8935 NodeManager
<2>页面

ResourceManger（Active）：8.8.8.11:23188



 

ResourceManager（Standby）：8.8.8.12:23188 



 

 

（3）停止

Hadoop-NN-01：stop-yarn.sh

Hadoop-NN-02：yarn-daeman.sh stop resourcemanager

  • 大小: 29.6 KB
  • 大小: 35.9 KB
  • 大小: 58.2 KB
  • 大小: 63.1 KB
  • 大小: 62.3 KB
  • 大小: 62.8 KB
  • 大小: 87.3 KB
  • 大小: 49 KB
  • 大小: 87.3 KB
分享到：
| Zookeeper-3.4.5-cdh5.0.1 单机模式、副本 ...
评论
4 楼 ShihLei 2018-06-29  
wangming520liwei 写道
上面的HA 架构图是不是来自 某个官网？  想问下还记得地址么？

太早了，记不得了，这个版本的hadoop应该都过时了，cloudera
3 楼 wangming520liwei 2018-06-14  
上面的HA 架构图是不是来自 某个官网？  想问下还记得地址么？
2 楼 ShihLei 2014-10-09  
hektor 写道
大哥 你这是5.0.1安装吗？ 明显目录都不对 5.0.1配置文件是在etc/hadoop下 

嗯，是写错了，校对的不彻底啊，直接把word版上传了，正确率能高些！
1 楼 hektor 2014-10-07  
大哥 你这是5.0.1安装吗？ 明显目录都不对 5.0.1配置文件是在etc/hadoop下 
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