【原】centos6.5下hadoop cdh4.6 安装

1、架构准备：

namenode 10.0.0.2

secondnamenode 10.0.0.3

datanode1 10.0.0.4

datanode2 10.0.0.6

datanode3 10.0.0.11

2、安装用户：cloud-user

3、[namenode]namenode到其他节点ssh无密码登录：

ssh-keygen (一路回车)

ssh-copy-id cloud-user@10.0.0.3

ssh-copy-id cloud-user@10.0.0.4

ssh-copy-id cloud-user@10.0.0.6

ssh-copy-id cloud-user@10.0.0.11

4、[ALL]cdh源的准备：

wget http://archive.cloudera.com/cdh4/redhat/5/x86_64/cdh/RPM-GPG-KEY-cloudera

sudo rpm --import RPM-GPG-KEY-cloudera

cd /etc/yum.repos.d/ && sudo wget http://archive.cloudera.com/cdh4/one-click-install/redhat/6/x86_64/cloudera-cdh-4-0.x86_64.rpm

sudo yum --nogpgcheck localinstall cloudera-cdh-4-0.x86_64.rpm

cd /etc/yum.repos.d/ && sudo wget http://archive.cloudera.com/gplextras/redhat/6/x86_64/gplextras/cloudera-gplextras4.repo

sudo yum clean all && sudo yum makecache

5、[ALL]java的安装：这里用的是jdk-6u45-linux-x64-rpm.bin

chmod +x jdk-6u45-linux-x64-rpm.bin && sudo ./jdk-6u45-linux-x64-rpm.bin

6、 [ALL]添加java的环境变量：

　　　 /etc/profile中添加：

1 export JAVA_HOME=/usr/java/jdk1.6.0_45
2 export JRE_HOME=$JAVA_HOME/jre   
3 export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib:$CLASSPATH 
4 export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH
5 export HADOOP_MAPRED_HOME=/usr/lib/hadoop-mapreduce

　　　使之生效：source /etc/profile

7、安装cdh包：

sudo yum install -y hadoop-yarn-resourcemanager hadoop-mapreduce-historyserver hadoop-yarn-proxyserver hadoop-hdfs-namenode //仅在namenode上安装

sudo yum install -y hadoop-hdfs-namenode //仅在secondnamenode上安装

sudo yum install -y hadoop-yarn-nodemanager hadoop-hdfs-datanode hadoop-mapreduce //在datanode1,datanode2,datanode3 上安装

sudo yum install -y hadoop-lzo-cdh4 //在所有节点上安装

8、[ALL]配置hadoop：

sudo service iptables stop && sudo service ip6tables stop

sudo echo -e "namenode secondnamenode" >> /etc/hadoop/conf/masters && sudo echo -e "datanode1 datanode2 datanode3" >> /etc/hadoop/conf/slaves

sudo cp -r /etc/hadoop/conf.dist /etc/hadoop/conf.my_cluster && sudo alternatives --verbose --install /etc/hadoop/conf hadoop-conf /etc/hadoop/conf.my_cluster 50 && sudo alternatives --set hadoop-conf /etc/hadoop/conf.my_cluster

　　 core-site.xml:

<property>
     <name>fs.defaultFS</name>
     <value>hdfs://sdc</value>
</property>
<property>
     <name>ha.zookeeper.quorum</name>
     <value>datanode1:2181,datanode2:2181,datanode3:2181</value>
</property>
<property>
     <name>fs.trash.interval</name>
     <value>10080</value>
</property>
<property>
     <name>fs.trash.checkpoint.interval</name>
     <value>10080</value>
</property>
<property>
     <name>hadoop.native.lib</name>
     <value>true</value>
</property>
<property>
     <name>hadoop.proxyuser.mapred.groups</name>
     <value>*</value>
</property>
<property>
     <name>hadoop.proxyuser.mapred.hosts</name>
     <value>*</value>
</property>
<property> 
   <name>hadoop.proxyuser.oozie.hosts</name> 
   <value>10.0.0.2</value> 
</property> 
<property> 
   <name>hadoop.proxyuser.oozie.groups</name> 
   <value>*</value> 
</property> 
<property>
   <name>io.compression.codecs</name>
   <value>org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.BZip2Codec,com.hadoop.compression.lzo.LzoCodec,com.hadoop.compression.lzo.LzopCodec,org.apache.hadoop.io.compress.SnappyCodec</value>
</property>

　　hdfs-site.xml:

<property>
     <name>dfs.replication</name>
     <value>3</value>
</property>
<property>
     <name>dfs.nameservices</name>
     <value>sdc</value>
</property>
<property>
     <name>dfs.ha.namenodes.sdc</name>
     <value>nn1,nn2</value>
</property>
<!--配置rpc通信地址：dfs.namenode.rpc-address.[nameservice ID].-->
<property>
     <name>dfs.namenode.rpc-address.sdc.nn1</name>
     <value>namenode:8020</value>
</property>
<property>
     <name>dfs.namenode.rpc-address.sdc.nn2</name>
     <value>secondnamenode:8020</value>
</property>
<!--配置http通信地址：dfs.namenode.http-address.[nameservice ID] -->
<property>
     <name>dfs.namenode.http-address.sdc.nn1</name>
     <value>namenode:50070</value>
</property>
<property>
     <name>dfs.namenode.http-address.sdc.nn2</name>
     <value>secondnamenode:50070</value>
</property>
<property>
     <name>dfs.namenode.shared.edits.dir</name>
     <value>qjournal://datanode1:8485;datanode2:8485;datanode3:8485/sdc</value>
</property>
<property>
     <name>dfs.permissions.superusergroup</name>
     <value>hadoop</value>
</property>
<property> 
     <name>dfs.permissions</name> 
     <value>false</value> 
</property> 
<property> 
     <name>dfs.permissions.enabled</name> 
     <value>false</value> 
</property>
<property>
     <name>dfs.journalnode.edits.dir</name>
     <value>/data/1/dfs/jn</value>
</property>
<!--配置客户端failover，解决客户端故障转移-->
<property>
     <name>dfs.client.failover.proxy.provider.sdc</name> 
     <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
     <name>dfs.namenode.name.dir</name>
     <value>file:///data/1/dfs/nn,/nfsmount/dfs/nn</value>
</property>
<!--配置：Fencing，
这里dfs.ha.fencing.methods实现的方法有两种sshfence和shell，我下面实现的是sshfence，dfs.ha.fencing.ssh.private-key-files这个是ssh的key file ,于在Active 节点切换期间的安全机制，确保在任何时间都只有一个NameNode 处于活跃状态。在故障切换期间，haadmin 命令确保在将其它NameNode 转换为Active 状态之前Active 节点处在Standby 状态，或其进程已被终止。
至少应该配置一个，因为没有默认配置，因此如果配置则HA 机制将会失效。
如果要实现自定义的安全机制，参照org.apache.hadoop.ha.NodeFencer
-->
<property>
     <name>dfs.ha.fencing.methods</name>
     <value>sshfence</value>
</property>
<property>
     <name>dfs.ha.fencing.ssh.private-key-files</name>
     <value>/home/cloud-user/.ssh/id_rsa</value>
</property>
<!--启用失败自动切换-->
<property>
     <name>dfs.ha.automatic-failover.enabled</name>
     <value>true</value>
</property>
<!--配置zk集群信息-->
<property>
     <name>ha.zookeeper.quorum</name>
     <value>datanode1:2181,datanode2:2181,datanode3:2181</value>
</property>
<property>
     <name>dfs.datanode.data.dir</name>
     <value>file:///data/1/dfs/dn,/data/2/dfs/dn,/data/3/dfs/dn</value>
</property>
<property>
     <name>dfs.webhdfs.enabled</name>
     <value>true</value>
</property>
<property> 
     <name>dfs.ha.fencing.ssh.connect-timeout</name> 
     <value>10000</value> 
</property>

　　mapred-site.xml:

<property>
     <name>mapreduce.framework.name</name>
     <value>yarn</value>
</property>
<property>
     <name>yarn.app.mapreduce.am.staging-dir</name>
     <value>/user</value>
</property>
<property>
     <name>mapreduce.jobhistory.address</name>
     <value>namenode:10020</value>
</property>
<property>
     <name>mapreduce.jobhistory.webapp.address</name>
     <value>namenode:19888</value>
</property>

　　yarn-site.xml:

<property>
     <name>yarn.resourcemanager.resource-tracker.address</name>
     <value>namenode:8031</value>
</property>
<property>
     <name>yarn.resourcemanager.address</name>
     <value>namenode:8032</value>
</property>
<property>
     <name>yarn.resourcemanager.scheduler.address</name>
     <value>namenode:8030</value>
</property>
<property>
     <name>yarn.resourcemanager.admin.address</name>
     <value>namenode:8033</value>
</property>
<property>
     <name>yarn.resourcemanager.webapp.address</name>
     <value>namenode:8088</value>
</property>
<property>
     <name>yarn.web-proxy.address</name>
     <value>namenode:8100</value>
</property>
<property>
     <description>Classpath for typical applications.</description>
     <name>yarn.application.classpath</name>
     <value>
     $HADOOP_CONF_DIR,
     $HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,
     $HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,
     $HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,
     $YARN_HOME/*,$YARN_HOME/lib/*
     </value>
</property>
<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>
     <name>yarn.nodemanager.local-dirs</name>
     <value>file:///data/1/yarn/local,file:///data/2/yarn/local,file:///data/3/yarn/local</value>
</property>
<property>
     <name>yarn.nodemanager.log-dirs</name>
     <value>file:///data/1/yarn/logs,file:///data/2/yarn/logs,file:///data/3/yarn/logs</value>
</property>
<property>
     <description>Where to aggregate logs</description>
     <name>yarn.nodemanager.remote-app-log-dir</name>
     <value>hdfs://var/log/hadoop-yarn/apps</value>
</property>

9、建立配置所需文件目录：

1 sudo mkdir -p /data/1/yarn/local /data/2/yarn/local /data/3/yarn/local /data/4/yarn/local && sudo mkdir -p /data/1/yarn/logs /data/2/yarn/logs /data/3/yarn/logs /data/4/yarn/logs && sudo chown -R yarn:yarn /data/1/yarn/local /data/2/yarn/local /data/3/yarn/local /data/4/yarn/local && sudo chown -R yarn:yarn /data/1/yarn/logs /data/2/yarn/logs /data/3/yarn/logs /data/4/yarn/logs
2 datanode:
3 sudo mkdir -p /data/1/dfs/jn && sudo chown -R hdfs:hdfs /data/1/dfs/jn
4 Namenode:
5 sudo mkdir -p /data/1/dfs/nn /nfsmount/dfs/nn && sudo  chown -R hdfs:hdfs /data/1/dfs/nn /nfsmount/dfs/nn &&sudo  chmod 700 /data/1/dfs/nn /nfsmount/dfs/nn
6 Datanode:
7 sudo mkdir -p /data/1/dfs/dn /data/2/dfs/dn /data/3/dfs/dn /data/4/dfs/dn && sudo chown -R hdfs:hdfs /data/1/dfs/dn /data/2/dfs/dn /data/3/dfs/dn /data/4/dfs/dn

10、[datanode]在datanode上安装zookeeper：

　　sudo yum install -y zookeeper

配置/etc/zookeeper/conf/zoo.cfg：

tickTime=2000
dataDir=/var/lib/zookeeper/
clientPort=2181
initLimit=5
syncLimit=2
server.1=datanode1:2888:3888
server.2=datanode2:2888:3888
server.3=datanode3:2888:3888

　　配置id：
　　sudo echo 1 > /var/lib/zookeeper/myid //仅在namenode1上执行
　　sudo echo 2 > /var/lib/zookeeper/myid //仅namenode2上执行
　　sudo echo 3 > /var/lib/zookeeper/myid //namenode3上执行
　　sudo chown -R zookeeper:zookeeper /var/lib/zookeeper //在所有datanode上

　　启动zookeeper：
　　sudo /usr/lib/zookeeper/bin/zkServer.sh start
　　查看状态：
　　sudo /usr/lib/zookeeper/bin/zkServer.sh status

11、namenode上格式化ZooKeeper集群：

sudo -u hdfs hdfs zkfc -formatZK

12、[datanode]安装并启动JournalNode集群：

sudo yum install -y hadoop-hdfs-journalnode
sudo service hadoop-hdfs-journalnode start

13、[namenode]namenode上格式化namenode并启动：

sudo -u hdfs hdfs namenode -format

sudo service hadoop-hdfs-namenode start

14、[secondnamenode]同步数据到secondnamenode上并启动：
sudo -u hdfs hdfs namenode -bootstrapStandby
sudo service hadoop-hdfs-namenode start

15、[datanode]启动所有的datanode：

sudo service hadoop-hdfs-datanode start

16、[namenode]启动yarn服务：

     sudo service hadoop-yarn-resourcemanager start
     sudo service hadoop-mapreduce-historyserver start
     sudo service hadoop-yarn-proxyserver start

17、[datanode]datanode上启动yarn：

sudo service hadoop-yarn-nodemanager start

18、[namenode + secondnamenode]安装并启动ZooKeeperFailoverCotroller：

　　　sudo yum install -y hadoop-hdfs-zkfc
sudo service hadoop-hdfs-zkfc start

19、[ALL]检测状态：

sudo /usr/java/jdk1.6.0_45/bin/jps

20、建立hdfs文件目录(有些是以后用到的)：

　　 sudo -u hdfs hadoop fs -chmod 777 /user

sudo -u hdfs hadoop fs -mkdir /user/history

     sudo -u hdfs hadoop fs -chmod -R 1777 /user/history
     sudo -u hdfs hadoop fs -chown mapred:hadoop /user/history
     sudo -u hdfs hadoop fs -mkdir /var/log/hadoop-yarn
     sudo -u hdfs hadoop fs -chown yarn:mapred /var/log/hadoop-yarn

     sudo -u hdfs hadoop fs -mkdir /tmp
     sudo -u hdfs hadoop fs -chmod -R 1777 /tmp
     sudo -u hdfs hadoop fs -mkdir /user/hive
     sudo -u hdfs hadoop fs -mkdir /user/hive/warehouse
     sudo -u hdfs hadoop fs -chown -R hive /user/hive
     sudo -u hdfs hadoop fs -chmod -R 1777 /user/hive/warehouse

     sudo -u hdfs hadoop fs -mkdir /tmp/hadoop-mapred
     sudo -u hdfs hadoop fs -mkdir /tmp/hive-hive

     sudo -u hdfs hadoop fs -chmod -R 777 /tmp/hadoop-mapred
     sudo -u hdfs hadoop fs -chmod -R 777 /tmp/hive-hive

     sudo -u hdfs hadoop fs -mkdir /user/cloud-user
     sudo -u hdfs hadoop fs -chown cloud-user:cloud-user /user/cloud-user
21、测试map-reduce：　

　　 cd /usr/lib/hadoop-mapreduce

hadoop jar hadoop-mapreduce-examples-2.0.0-cdh4.6.0.jar pi 2 10

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原文地址：https://www.cnblogs.com/yuandianliws/p/3716602.html