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）
安装文档：http://www.cnblogs.com/hunttown/p/5807383.html
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/core-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> <description>该值来自于hdfs-site.xml中的配置</description> </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 $HADOOP_HOME/etc/hadoop/hdfs-site.xml
<?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <!--开启web hdfs --> <property> <name>dfs.webhdfs.enabled</name> <value>true</value> </property> <property> <name>dfs.namenode.name.dir</name> <value>/home/hadoopuser/hadoop-2.6.0-cdh5.6.0/data/dfs/name</value> <description> namenode 存放name table(fsimage)本地目录（需要修改）</description> </property> <property> <name>dfs.namenode.edits.dir</name> <value>${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 $HADOOP_HOEM/etc/hadoop/mapred-site.xml
<configuration> <!-- 配置JVM大小 --> <property> <name>mapred.child.java.opts</name> <value>-Xmx1000m</value> <final>true</final> <description>final=true表示禁止用户修改JVM大小</description> </property> <!-- 配置 MapReduce Applications --> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <!-- JobHistory Server ============================================================== --> <!-- 配置 MapReduce JobHistory Server 地址 ，默认端口10020 --> <property> <name>mapreduce.jobhistory.address</name> <value>0.0.0.0:10020</value> </property> <!-- 配置 MapReduce JobHistory Server web ui 地址， 默认端口19888 --> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>0.0.0.0:19888</value> </property> </configuration>
HBase的配置：
<!-- HBase使用 start --> <property> <name>mapred.remote.os</name> <value>Linux</value> </property> <property> <name>mapreduce.app-submission.cross-platform</name> <value>true</value> </property> <property> <name>mapreduce.application.classpath</name> <value> /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/etc/hadoop, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/common/lib/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/hdfs/lib/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/mapreduce/lib/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/*, /home/hadoopuser/hadoop-2.6.0-cdh5.6.0/share/hadoop/yarn/lib/*, /usr/local/hbase/lib/* </value> </property> <!-- HBase使用 end -->
另：JVM配置也可以这么写：
<property> <name>mapred.task.java.opts</name> <value>-Xmx2000m</value> </property> <property> <name>mapred.child.java.opts</name> <value>${mapred.task.java.opts} -Xmx1000m</value> <final>true</final> <description>相同的jvm arg写在一起，比如"-Xmx2000m -Xmx1000m"，后面的会覆盖前面的，也就是说最终“-Xmx1000m”才会生效。</description> </property>
另：如果要分别配置map和reduce的JVM大小，可以这么写
<property> <name>mapred.map.child.java.opts</name> <value>-Xmx512M</value> </property> <property> <name>mapred.reduce.child.java.opts</name> <value>-Xmx1024M</value> </property>
（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> </configuration>
HBase的配置：
<!-- 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 -->
（7）修改 $HADOOP_HOME/etc/hadoop/slaves
Hadoop-DN-01 Hadoop-DN-02 Hadoop-DN-03
3、分发程序
#因为我的SSH登录修改了端口，所以使用了 -P 6000 scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-NN-02:/home/hadoopuser scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-01:/home/hadoopuser scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-02:/home/hadoopuser scp -P 6000 -r /home/hadoopuser/hadoop-2.6.0-cdh5.6.0 hadoopuser@Hadoop-DN-03:/home/hadoopuser
4、启动HDFS
（1）启动JournalNode：
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ 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 Jps
DataNode：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.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：$HADOOP_HOME/sbin
[hadoopuser@Linux01 hadoop-2.6.0-cdh5.6.0]$ start-yarn.sh
Hadoop-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 DFSZKFailoverController
TaskTracker：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