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Hadoop 集群安装 -CDH5（5 台服务器集群）
CDH5包下载：http://archive.cloudera.com/cdh5/
架构设计：
主机规划：
|
IP |
Host |
部署模块 |
进程 |
|
192.168.254.151 |
Hadoop-NN-01 |
NameNode ResourceManager |
NameNode DFSZKFailoverController ResourceManager |
|
192.168.254.152 |
Hadoop-NN-02 |
NameNode ResourceManager |
NameNode DFSZKFailoverController ResourceManager |
|
192.168.254.153 |
Hadoop-DN-01 Zookeeper-01 |
DataNode NodeManager Zookeeper |
DataNode NodeManager JournalNode QuorumPeerMain |
|
192.168.254.154 |
Hadoop-DN-02 Zookeeper-02 |
DataNode NodeManager Zookeeper |
DataNode NodeManager JournalNode QuorumPeerMain |
|
192.168.254.155 |
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
目录规划：
|
名称 |
路径 |
|
$HADOOP_HOME |
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0 |
|
Data |
$ HADOOP_HOME/data |
|
Log |
$ HADOOP_HOME/logs |
集群安装：
一、关闭防火墙（防火墙可以以后配置）
二、安装JDK（略）
三、修改 HostName 并配置 Host（5 台）
[root@Linux01 ~]# vim /etc/sysconfig/network
[root@Linux01 ~]# vim /etc/hosts
192.168.254.151 Hadoop-NN-01
192.168.254.152 Hadoop-NN-02
192.168.254.153 Hadoop-DN-01 Zookeeper-01
192.168.254.154 Hadoop-DN-02 Zookeeper-02
192.168.254.155 Hadoop-DN-03 Zookeeper-03四、为了安全，创建 Hadoop 专门登录的用户（5台）
[root@Linux01 ~]# useradd hadoopuser
[root@Linux01 ~]# passwd hadoopuser
[root@Linux01 ~]# su – hadoopuser #切换用户五、配置 SSH 免密码登录（2台NameNode）
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-keygen --生成公私钥
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-copy-id -i ~/.ssh/id_rsa.pub hadoopuser@Hadoop-NN-01-I 表示 input
~/.ssh/id_rsa.pub 表示哪个公钥组
或者省略为：
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-copy-id Hadoop-NN-01（或写 IP：10.10.51.231）#将公钥扔到对方服务器
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-copy-id”-p 6000 Hadoop-NN-01”#如果带端口则这样写注意修改 Hadoop 的配置文件
vi Hadoop-env.sh
export HADOOP_SSH_OPTS=”-p 6000”[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh Hadoop-NN-01 #验证（退出当前连接命令：exit、logout）
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh Hadoop-NN-01 –p 6000 #如果带端口这样写六、配置环境变量：vi ~/.bashrc 然后 source ~/.bashrc（5 台）
[hadoopuser@Linux01 ~]$ vi ~/.bashrc
# hadoop cdh5
export HADOOP_HOME=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0
export PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/bin
[hadoopuser@Linux01 ~]$ source ~/.bashrc #生效七、安装 zookeeper（3 台DataNode）
1、解压
2、配置环境变量：vi ~/.bashrc
[hadoopuser@Linux01 ~]$ vi ~/.bashrc
# zookeeper cdh5
export ZOOKEEPER_HOME=/home/hadoopuser/zookeeper-3.4.5-cdh5.6.0
export PATH=$PATH:$ZOOKEEPER_HOME/bin
[hadoopuser@Linux01 ~]$ source ~/.bashrc #生效3、修改日志输出
[hadoopuser@Linux01 ~]$ vi $ZOOKEEPER_HOME/libexec/zkEnv.sh
56 行：找到如下位置修改语句：ZOO_LOG_DIR="$ZOOKEEPER_HOME/logs"4、修改配置文件
[hadoopuser@Linux01 ~]$ vi $ZOOKEEPER_HOME/conf/zoo.cfg
# zookeeper
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/home/hadoopuser/zookeeper-3.4.5-cdh5.6.0/data
clientPort=2181
# cluster
server.1=Zookeeper-01:2888:3888
server.2=Zookeeper-02:2888:3888
server.3=Zookeeper-03:2888:38885、设置myid
（1）Hadoop-DN -01：
mkdir $ZOOKEEPER_HOME/data
echo 1 > $ZOOKEEPER_HOME/data/myid（2）Hadoop-DN -02：
mkdir $ZOOKEEPER_HOME/data
echo 2 > $ZOOKEEPER_HOME/data/myid（3）Hadoop-DN -03：
mkdir $ZOOKEEPER_HOME/data
echo 3 > $ZOOKEEPER_HOME/data/myid6、各结点启动：
[hadoopuser@Linux01 ~]$ zkServer.sh start7、验证
[hadoopuser@Linux01 ~]$ jps
3051 Jps
2829 QuorumPeerMain8、状态
[hadoopuser@Linux01 ~]$ zkServer.sh status
JMX enabled by default
Using config: /home/zero/zookeeper/zookeeper-3.4.5-cdh5.0.1/bin/../conf/zoo.cfg
Mode: follower9、附录 zoo.cfg 各配置项说明
|
属性 |
意义 |
|
tickTime |
时间单元，心跳和最低会话超时时间为 tickTime 的两倍 |
|
dataDir |
数据存放位置，存放内存快照和事务更新日志 |
|
clientPort |
客户端访问端口 |
|
initLimit |
配 置 Zookeeper 接受客户端（这里所说的客户端不是用户连接 Zookeeper 服务器的客户端，而是 Zookeeper 服务器集群中连接到 Leader 的 Follower 服务器）初始化连接时最长能忍受多少个心跳时间间隔数。当已经超过 10 个心跳的时间（也就是 tickTime）长度后 Zookeeper 服务器还没有收到客户端的返回信息，那么表明这个客户端连接失败。总的时间长度就是 5*2000=10 秒。 |
|
syncLimit |
这个配置项标识 Leader 与 Follower 之间发送消息，请求和应答时间长度，最长不能超过多少个 |
|
server.id=host:port:port server.A=B：C：D |
集群结点列表： A：是一个数字，表示这个是第几号服务器； B：是这个服务器的 ip 地址； C：表示的是这个服务器与集群中的 Leader 服务器交换信息的端口； D：表示的是万一集群中的 Leader 服务器挂了，需要一个端口来重新进行选举，选出一个新的 Leader，而这个端口就是用来执行选举时服务器相互通信的端口。如果是伪集群的配置方式，由于 B 都是一样，所以不同的 Zookeeper 实例通信端口号不能一样，所以要给它们分配不同的端口号。 |
八、安装 Hadoop，并配置（只装1 台配置完成后分发给其它节点）
1、解压
2、修改配置文件
|
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 $HADOOP_HOME/etc/hadoop/hadoop-env.sh
#--------------------Java Env------------------------------
export JAVA_HOME="/usr/java/jdk1.8.0_73"
#--------------------Hadoop Env----------------------------
#export HADOOP_PID_DIR=${HADOOP_PID_DIR}
export HADOOP_PREFIX="/home/hadoopuser/hadoop-2.6.0-cdh5.6.0"
#--------------------Hadoop Daemon Options-----------------
# export HADOOP_NAMENODE_OPTS="-Dhadoop.security.logger=${HADOOP_SECURITY_LOGGER:-INFO,RFAS} -Dhdfs.audit.logger=${HDFS_AUDIT_LOGGER:-INFO,NullAppender} $HADOOP_NAMENODE_OPTS"
# export HADOOP_DATANODE_OPTS="-Dhadoop.security.logger=ERROR,RFAS $HADOOP_DATANODE_OPTS"
#--------------------Hadoop Logs---------------------------
#export HADOOP_LOG_DIR=${HADOOP_LOG_DIR}/$USER
#--------------------SSH PORT-------------------------------
export HADOOP_SSH_OPTS="-p 6000" #如果你修改了 SSH 登录端口，一定要修改此配置。 （2）修改 $HADOOP_HOME/etc/hadoop/hadoop-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.linuxidc.com/Linux/2016-05/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 $HADOOP_HOME/etc/hadoop/hdfs-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.linuxidc.com/Linux/2016-05/configuration.xsl"?>
<configuration>
<!--开启 web hdfs -->
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/data/dfs/name</value>
<description> namenode 存放 name table(fsimage)本地目录（需要修改）</description>
</property>
<property>
<name>dfs.namenode.edits.dir</name>
<value>${dfs.namenode.name.dir}</value>
<description>namenode 存放 transaction file(edits)本地目录（需要修改）</description>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/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>
<description>文件副本个数，默认为 3 </description>
</property>
<!-- 块大小（默认）-->
<property>
<name>dfs.blocksize</name>
<value>268435456</value>
< description>块大小 256M</description>
</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/hadoopuser/hadoop-2.6.0-cdh5.6.0/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/hadoopuser/.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>-->
<value>Hadoop-DN-01:2181,Hadoop-DN-02:2181,Hadoop-DN-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/hadoopuser/hadoop-2.6.0-cdh5.6.0/logs"
（5）修改 $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>
<!-- HBase 使用 start -->
<property>
<name>mapred.remote.os</name>
<value>Linux</value>
</property>
<property>
<name>mapreduce.app-submission.cross-platform</name>
<value>true</value>
</property>
<property>
<name>mapreduce.application.classpath</name>
<value>
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/etc/hadoop,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/lib/*,
/usr/local/hbase/lib/*
</value>
</property>
<!-- HBase 使用 end -->
</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>-->
<value>Hadoop-DN-01:2181,Hadoop-DN-02:2181,Hadoop-DN-03:2181</value>
</property>
<property>
<name>yarn.resourcemanager.zk.state-store.address</name>
<!--<value>Zookeeper-01:2181,Zookeeper-02:2181,Zookeeper-03:2181</value>-->
<value>Hadoop-DN-01:2181,Hadoop-DN-02:2181,Hadoop-DN-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>
<!-- HBase 使用 start -->
<property>
<name>mapreduce.application.classpath</name>
<value>
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/etc/hadoop,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/lib/*,
/usr/local/hbase/lib/*
</value>
</property>
<!-- HBase 使用 end -->
</configuration> （7）修改 $HADOOP_HOME/etc/hadoop/slaves
Hadoop-DN-01
Hadoop-DN-02
Hadoop-DN-033、分发程序
#因为我的 SSH 登录修改了端口，所以使用了 -P 6000
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-NN-02:/home/hadoopuser
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-01:/home/hadoopuser
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-02:/home/hadoopuser
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-03:/home/hadoopuser更多详情见请继续阅读下一页的精彩内容：http://www.linuxidc.com/Linux/2016-05/131867p2.htm
4、启动HDFS
（1）启动JournalNode：
[Hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ hadoop-daemon.sh start journalnode starting journalnode, logging to /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/logs/hadoop-puppet-journalnode-BigData-03.out验证JournalNode：
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ jps
5652 QuorumPeerMain
9076 Jps
9029 JournalNode停止JournalNode：
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ hadoop-daemon.sh stop journalnode stoping journalnode（2）NameNode 格式化：
结点 Hadoop-NN-01：hdfs namenode -format
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ hdfs namenode -format（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。
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ scp -P 6000 -r data/ hadoopuser@Hadoop-NN-02:/home/hadoopuser/hadoop-2.6.0-cdh5.6.0（4）初始化ZFCK：
创建 ZNode，记录状态信息。
结点 Hadoop-NN-01：hdfs zkfc -formatZK
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ hdfs zkfc -formatZK（5）启动
集群启动法：Hadoop-NN-01：start-dfs.sh
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ start-dfs.sh单进程启动法：
<1>NameNode（Hadoop-NN-01，Hadoop-NN-02）：hadoop-daemon.sh start namenode
<2>DataNode（Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03）：hadoop-daemon.sh start datanode
<3>JournalNode（Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03）：hadoop-daemon.sh start journalnode
<4>ZKFC（Hadoop-NN-01，Hadoop-NN-02）：hadoop-daemon.sh start zkfc
（6）验证
<1> 进程
NameNode：jps
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ jps
9329 JournalNode
9875 NameNode
10155 DFSZKFailoverController
10223 JpsDataNode：jps
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ jps
9498 Jps
9019 JournalNode
9389 DataNode
5613 QuorumPeerMain<2> 页面:
Active 结点：http://192.168.254.151:50070
（7）停止：stop-dfs.sh
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ stop-dfs.sh5、启动Yarn
（1）启动
<1> 集群启动
Hadoop-NN-01 启动 Yarn，命令所在目录：$HADOOP_HOME/sbin
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ start-yarn.shHadoop-NN-02 备机启动 RM：
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ yarn-daemon.sh start resourcemanager<2> 单进程启动
ResourceManager（Hadoop-NN-01，Hadoop-NN-02）：yarn-daemon.sh start resourcemanager
DataNode（Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03）：yarn-daemon.sh start nodemanager
（2）验证
<1> 进程：
JobTracker：Hadoop-NN-01，Hadoop-NN-02
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ jps
9329 JournalNode
9875 NameNode
10355 ResourceManager
10646 Jps
10155 DFSZKFailoverControllerTaskTracker：Hadoop-DN-01，Hadoop-DN-02，Hadoop-DN-03
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ jps
9552 NodeManager
9680 Jps
9019 JournalNode
9389 DataNode
5613 QuorumPeerMain<2> 页面
ResourceManger（Active）：192.168.254.151:23188
ResourceManager（Standby）：192.168.254.152:23188
（3）停止
Hadoop-NN-01：stop-yarn.sh
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ stop-yarn.sh
Hadoop-NN-02：yarn-daemon.sh stop resourcemanager
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ yarn-daeman.sh stop resourcemanager附：Hadoop 常用命令总结
#第 1 步 启动 zookeeper
[hadoopuser@Linux01 ~]$ zkServer.sh start
[hadoopuser@Linux01 ~]$ zkServer.sh stop #停止
#第 2 步 启动 JournalNode：
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ hadoop-daemon.sh start journalnode starting journalnode, logging to /home/hadoopuser/hadoop-dir/hadoop-2.6.0-cdh5.6.0/logs/hadoop-puppet-journalnode-BigData-03.out #两个 namenode
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ hadoop-daemon.sh stop journalnode stoping journalnode #停止
#第 3 步 启动 DFS：
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ start-dfs.sh
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ stop-dfs.sh #停止
#第 4 步 启动 Yarn：
#Hadoop-NN-01 启动 Yarn
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ start-yarn.sh
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ stop-yarn.sh #停止
#Hadoop-NN-02 备机启动 RM
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ yarn-daemon.sh start resourcemanager
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ yarn-daemon.sh stop resourcemanager #停止
#如果安装了 HBase
#Hadoop-NN-01 启动 HBase 的 Thrift Server：
[hadoopuser@Linux01 bin]$ hbase-daemon.sh start thrift
[hadoopuser@Linux01 bin]$ hbase-daemon.sh stop thrift #停止
#Hadoop-NN-01 启动 HBase：
[hadoopuser@Linux01 bin]$ hbase/bin/start-hbase.sh
[hadoopuser@Linux01 bin]$ hbase/bin/stop-hbase.sh #停止
#如果安装了 RHive
#Hadoop-NN-01 启动 Rserve：
[hadoopuser@Linux01 ~]$ Rserve --RS-conf /usr/local/lib64/R/Rserv.conf #停止 直接 kill
#Hadoop-NN-01 启动 hive 远程服务（rhive 是通过 thrift 连接 hiveserver 的，需要要启动后台 thrift 服务）：
[hadoopuser@Linux01 ~]$ nohup hive --service hiveserver2 & #注意这里是 hiveserver2
附：Hadoop 常用环境变量配置
# JAVA
export JAVA_HOME=/usr/java/jdk1.8.0_73
export PATH=$PATH:$JAVA_HOME/bin
export CLASSPATH=.:$JAVA_HOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
# MYSQL
export PATH=/usr/local/mysql/bin:/usr/local/mysql/lib:$PATH
# Hive
export HIVE_HOME=/home/hadoopuser/hive
export PATH=$PATH:$HIVE_HOME/bin
# Hadoop
export HADOOP_HOME=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0
export HADOOP_CONF_DIR=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/etc/hadoop
export HADOOP_CMD=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/bin/hadoop
export HADOOP_STREAMING=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/tools/lib/hadoop-streaming-2.6.0-cdh5.6.0.jar
export JAVA_LIBRARY_PATH=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/lib/native/
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
# R
export R_HOME=/usr/local/lib64/R
export PATH=$PATH:$R_HOME/bin
export RHIVE_DATA=/usr/local/lib64/R/rhive/data
export CLASSPATH=.:/usr/local/lib64/R/library/rJava/jri
export LD_LIBRARY_PATH=/usr/local/lib64/R/library/rJava/jri
export RServe_HOME=/usr/local/lib64/R/library/Rserve
# thrift
export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig/
# HBase
export HBASE_HOME=/usr/local/hbase
export PATH=$PATH:$HBASE_HOME/bin
# Zookeeper
export ZOOKEEPER_HOME=/home/hadoopuser/zookeeper-3.4.5-cdh5.6.0
export PATH=$PATH:$ZOOKEEPER_HOME/bin
# Sqoop2
export SQOOP2_HOME=/home/hadoopuser/sqoop2-1.99.5-cdh5.6.0
export CATALINA_BASE=$SQOOP2_HOME/server
export PATH=$PATH:$SQOOP2_HOME/bin
# Scala
export SCALA_HOME=/usr/local/scala
export PATH=$PATH:${SCALA_HOME}/bin
# Spark
export SPARK_HOME=/home/hadoopuser/spark-1.5.0-cdh5.6.0
export PATH=$PATH:${SPARK_HOME}/bin
# Storm
export STORM_HOME=/home/hadoopuser/apache-storm-0.9.6
export PATH=$PATH:$STORM_HOME/bin
#kafka
export KAFKA_HOME=/home/hadoopuser/kafka_2.10-0.9.0.1
export PATH=$PATH:$KAFKA_HOME/bin更多 Hadoop 相关信息见Hadoop 专题页面 http://www.linuxidc.com/topicnews.aspx?tid=13
本文永久更新链接地址：http://www.linuxidc.com/Linux/2016-05/131867.htm
Hadoop 集群安装 -CDH5（5 台服务器集群）
CDH5包下载：http://archive.cloudera.com/cdh5/
架构设计：
主机规划：
|
IP |
Host |
部署模块 |
进程 |
|
192.168.254.151 |
Hadoop-NN-01 |
NameNode ResourceManager |
NameNode DFSZKFailoverController ResourceManager |
|
192.168.254.152 |
Hadoop-NN-02 |
NameNode ResourceManager |
NameNode DFSZKFailoverController ResourceManager |
|
192.168.254.153 |
Hadoop-DN-01 Zookeeper-01 |
DataNode NodeManager Zookeeper |
DataNode NodeManager JournalNode QuorumPeerMain |
|
192.168.254.154 |
Hadoop-DN-02 Zookeeper-02 |
DataNode NodeManager Zookeeper |
DataNode NodeManager JournalNode QuorumPeerMain |
|
192.168.254.155 |
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
目录规划：
|
名称 |
路径 |
|
$HADOOP_HOME |
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0 |
|
Data |
$ HADOOP_HOME/data |
|
Log |
$ HADOOP_HOME/logs |
集群安装：
一、关闭防火墙（防火墙可以以后配置）
二、安装JDK（略）
三、修改 HostName 并配置 Host（5 台）
[root@Linux01 ~]# vim /etc/sysconfig/network
[root@Linux01 ~]# vim /etc/hosts
192.168.254.151 Hadoop-NN-01
192.168.254.152 Hadoop-NN-02
192.168.254.153 Hadoop-DN-01 Zookeeper-01
192.168.254.154 Hadoop-DN-02 Zookeeper-02
192.168.254.155 Hadoop-DN-03 Zookeeper-03四、为了安全，创建 Hadoop 专门登录的用户（5台）
[root@Linux01 ~]# useradd hadoopuser
[root@Linux01 ~]# passwd hadoopuser
[root@Linux01 ~]# su – hadoopuser #切换用户五、配置 SSH 免密码登录（2台NameNode）
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-keygen --生成公私钥
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-copy-id -i ~/.ssh/id_rsa.pub hadoopuser@Hadoop-NN-01-I 表示 input
~/.ssh/id_rsa.pub 表示哪个公钥组
或者省略为：
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-copy-id Hadoop-NN-01（或写 IP：10.10.51.231）#将公钥扔到对方服务器
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh-copy-id”-p 6000 Hadoop-NN-01”#如果带端口则这样写注意修改 Hadoop 的配置文件
vi Hadoop-env.sh
export HADOOP_SSH_OPTS=”-p 6000”[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh Hadoop-NN-01 #验证（退出当前连接命令：exit、logout）
[hadoopuser@Linux05 hadoop-2.6.0-cdh5.6.0]$ ssh Hadoop-NN-01 –p 6000 #如果带端口这样写六、配置环境变量：vi ~/.bashrc 然后 source ~/.bashrc（5 台）
[hadoopuser@Linux01 ~]$ vi ~/.bashrc
# hadoop cdh5
export HADOOP_HOME=/home/hadoopuser/hadoop-2.6.0-cdh5.6.0
export PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/bin
[hadoopuser@Linux01 ~]$ source ~/.bashrc #生效七、安装 zookeeper（3 台DataNode）
1、解压
2、配置环境变量：vi ~/.bashrc
[hadoopuser@Linux01 ~]$ vi ~/.bashrc
# zookeeper cdh5
export ZOOKEEPER_HOME=/home/hadoopuser/zookeeper-3.4.5-cdh5.6.0
export PATH=$PATH:$ZOOKEEPER_HOME/bin
[hadoopuser@Linux01 ~]$ source ~/.bashrc #生效3、修改日志输出
[hadoopuser@Linux01 ~]$ vi $ZOOKEEPER_HOME/libexec/zkEnv.sh
56 行：找到如下位置修改语句：ZOO_LOG_DIR="$ZOOKEEPER_HOME/logs"4、修改配置文件
[hadoopuser@Linux01 ~]$ vi $ZOOKEEPER_HOME/conf/zoo.cfg
# zookeeper
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/home/hadoopuser/zookeeper-3.4.5-cdh5.6.0/data
clientPort=2181
# cluster
server.1=Zookeeper-01:2888:3888
server.2=Zookeeper-02:2888:3888
server.3=Zookeeper-03:2888:38885、设置myid
（1）Hadoop-DN -01：
mkdir $ZOOKEEPER_HOME/data
echo 1 > $ZOOKEEPER_HOME/data/myid（2）Hadoop-DN -02：
mkdir $ZOOKEEPER_HOME/data
echo 2 > $ZOOKEEPER_HOME/data/myid（3）Hadoop-DN -03：
mkdir $ZOOKEEPER_HOME/data
echo 3 > $ZOOKEEPER_HOME/data/myid6、各结点启动：
[hadoopuser@Linux01 ~]$ zkServer.sh start7、验证
[hadoopuser@Linux01 ~]$ jps
3051 Jps
2829 QuorumPeerMain8、状态
[hadoopuser@Linux01 ~]$ zkServer.sh status
JMX enabled by default
Using config: /home/zero/zookeeper/zookeeper-3.4.5-cdh5.0.1/bin/../conf/zoo.cfg
Mode: follower9、附录 zoo.cfg 各配置项说明
|
属性 |
意义 |
|
tickTime |
时间单元，心跳和最低会话超时时间为 tickTime 的两倍 |
|
dataDir |
数据存放位置，存放内存快照和事务更新日志 |
|
clientPort |
客户端访问端口 |
|
initLimit |
配 置 Zookeeper 接受客户端（这里所说的客户端不是用户连接 Zookeeper 服务器的客户端，而是 Zookeeper 服务器集群中连接到 Leader 的 Follower 服务器）初始化连接时最长能忍受多少个心跳时间间隔数。当已经超过 10 个心跳的时间（也就是 tickTime）长度后 Zookeeper 服务器还没有收到客户端的返回信息，那么表明这个客户端连接失败。总的时间长度就是 5*2000=10 秒。 |
|
syncLimit |
这个配置项标识 Leader 与 Follower 之间发送消息，请求和应答时间长度，最长不能超过多少个 |
|
server.id=host:port:port server.A=B：C：D |
集群结点列表： A：是一个数字，表示这个是第几号服务器； B：是这个服务器的 ip 地址； C：表示的是这个服务器与集群中的 Leader 服务器交换信息的端口； D：表示的是万一集群中的 Leader 服务器挂了，需要一个端口来重新进行选举，选出一个新的 Leader，而这个端口就是用来执行选举时服务器相互通信的端口。如果是伪集群的配置方式，由于 B 都是一样，所以不同的 Zookeeper 实例通信端口号不能一样，所以要给它们分配不同的端口号。 |
八、安装 Hadoop，并配置（只装1 台配置完成后分发给其它节点）
1、解压
2、修改配置文件
|
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 $HADOOP_HOME/etc/hadoop/hadoop-env.sh
#--------------------Java Env------------------------------
export JAVA_HOME="/usr/java/jdk1.8.0_73"
#--------------------Hadoop Env----------------------------
#export HADOOP_PID_DIR=${HADOOP_PID_DIR}
export HADOOP_PREFIX="/home/hadoopuser/hadoop-2.6.0-cdh5.6.0"
#--------------------Hadoop Daemon Options-----------------
# export HADOOP_NAMENODE_OPTS="-Dhadoop.security.logger=${HADOOP_SECURITY_LOGGER:-INFO,RFAS} -Dhdfs.audit.logger=${HDFS_AUDIT_LOGGER:-INFO,NullAppender} $HADOOP_NAMENODE_OPTS"
# export HADOOP_DATANODE_OPTS="-Dhadoop.security.logger=ERROR,RFAS $HADOOP_DATANODE_OPTS"
#--------------------Hadoop Logs---------------------------
#export HADOOP_LOG_DIR=${HADOOP_LOG_DIR}/$USER
#--------------------SSH PORT-------------------------------
export HADOOP_SSH_OPTS="-p 6000" #如果你修改了 SSH 登录端口，一定要修改此配置。 （2）修改 $HADOOP_HOME/etc/hadoop/hadoop-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.linuxidc.com/Linux/2016-05/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 $HADOOP_HOME/etc/hadoop/hdfs-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.linuxidc.com/Linux/2016-05/configuration.xsl"?>
<configuration>
<!--开启 web hdfs -->
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/data/dfs/name</value>
<description> namenode 存放 name table(fsimage)本地目录（需要修改）</description>
</property>
<property>
<name>dfs.namenode.edits.dir</name>
<value>${dfs.namenode.name.dir}</value>
<description>namenode 存放 transaction file(edits)本地目录（需要修改）</description>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/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>
<description>文件副本个数，默认为 3 </description>
</property>
<!-- 块大小（默认）-->
<property>
<name>dfs.blocksize</name>
<value>268435456</value>
< description>块大小 256M</description>
</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/hadoopuser/hadoop-2.6.0-cdh5.6.0/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/hadoopuser/.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>-->
<value>Hadoop-DN-01:2181,Hadoop-DN-02:2181,Hadoop-DN-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/hadoopuser/hadoop-2.6.0-cdh5.6.0/logs"
（5）修改 $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>
<!-- HBase 使用 start -->
<property>
<name>mapred.remote.os</name>
<value>Linux</value>
</property>
<property>
<name>mapreduce.app-submission.cross-platform</name>
<value>true</value>
</property>
<property>
<name>mapreduce.application.classpath</name>
<value>
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/etc/hadoop,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/lib/*,
/usr/local/hbase/lib/*
</value>
</property>
<!-- HBase 使用 end -->
</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>-->
<value>Hadoop-DN-01:2181,Hadoop-DN-02:2181,Hadoop-DN-03:2181</value>
</property>
<property>
<name>yarn.resourcemanager.zk.state-store.address</name>
<!--<value>Zookeeper-01:2181,Zookeeper-02:2181,Zookeeper-03:2181</value>-->
<value>Hadoop-DN-01:2181,Hadoop-DN-02:2181,Hadoop-DN-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>
<!-- HBase 使用 start -->
<property>
<name>mapreduce.application.classpath</name>
<value>
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/etc/hadoop,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/lib/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/*,
/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/lib/*,
/usr/local/hbase/lib/*
</value>
</property>
<!-- HBase 使用 end -->
</configuration> （7）修改 $HADOOP_HOME/etc/hadoop/slaves
Hadoop-DN-01
Hadoop-DN-02
Hadoop-DN-033、分发程序
#因为我的 SSH 登录修改了端口，所以使用了 -P 6000
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-NN-02:/home/hadoopuser
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-01:/home/hadoopuser
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-02:/home/hadoopuser
scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-03:/home/hadoopuser更多详情见请继续阅读下一页的精彩内容：http://www.linuxidc.com/Linux/2016-05/131867p2.htm
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