1.  虚机的环境准备不详细列出，保证个虚机之间可以ping通，以及无密码登录。

环境准备阶段。

下载hadoop，http://apache.fayea.com/hadoop/common/stable/hadoop-2.6.0.tar.gz

安装jdk，jdk 1.7.0_71

2.  切换到hadoop用户，解压hadoop-2.6.0.tar.gz。

cd /data0/
tar zxvf hadoop-2.6.0.tar.gz

配置环境变量

vi ~/.bashrc
export JAVA_HOME=/usr/java/jdk1.7.0_71
export HADOOP_HOME=/data0/hadoop-2.6.0
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export PATH=$JAVA_HOME/bin:$HADOOP_HOME/bin:$PATH
export CLASSPATH=.:$JAVA_HOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jarsource ~/.bashrc

3.  配置分布式环境，hadoop的配置文件主要有core-site.xml，mapred-site.xml, hdfs-site.xml 、 yarn-site.xml文件。

core-site.xml

<configuration><property><name>hadoop.tmp.dir</name><value>/data0/hadoop/tmp</value><description>Abase for other temporary directories.</description></property><property><name>fs.defaultFS</name><value>hdfs://master:9000</value></property><property><name>io.file.buffer.size</name><value>4096</value></property><property><name>ha.zookeeper.quorum</name><value>master:2181,slave2:2181,slave3:2181</value></property>
</configuration>

mapred-site.xml

<configuration><property><name>mapreduce.framework.name</name><value>yarn</value></property><property><name>mapreduce.jobtracker.http.address</name><value>master:50030</value></property><property><name>mapreduce.jobhistory.address</name><value>master:10020</value></property><property><name>mapreduce.jobhistory.webapp.address</name><value>master:19888</value></property><property><name>mapreduce.job.queuename</name><value>hadoop</value></property></configuration>

hdfs-site.xml

<configuration><property><name>dfs.nameservices</name><value>ns1</value></property><property><name>dfs.namenode.secondary.http-address</name><value>master:50090</value></property><property><name>dfs.namenode.name.dir</name><value>/data0/hadoop/dfs/name</value></property><property><name>dfs.datanode.data.dir</name><value>/data0/hadoop/dfs/data</value></property><property><name>dfs.replication</name><value>1</value></property><property><name>dfs.webhdfs.enabled</name><value>true</value></property><property><name>dfs.permissions</name><value>false</value></property>
</configuration>

yarn-site.xml

<configuration><!-- Site specific YARN configuration properties --><property><name>yarn.nodemanager.aux-services</name><value>mapreduce_shuffle</value></property><property><name>yarn.resourcemanager.address</name><value>master:8032</value></property><property><name>yarn.resourcemanager.scheduler.address</name><value>master:8030</value></property><property><name>yarn.resourcemanager.resource-tracker.address</name><value>master:8031</value></property><property><name>yarn.resourcemanager.admin.address</name><value>master:8033</value></property><property><name>yarn.resourcemanager.webapp.address</name><value>master:8088</value></property><property><name>yarn.resourcemanager.scheduler.class</name><value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value></property><property><name>yarn.scheduler.fair.allocation.file</name><value>/data0/hadoop-2.6.0/etc/hadoop/fair-scheduler.xml</value></property><property><name>yarn.nodemanager.resource.memory-mb</name><value>4096</value></property><property><name>yarn.nodemanager.resource.cpu-vcores</name><value>4</value></property>
</configuration>

配置公平调度器

fair-scheduler.xml

<allocations><queue name="default"><minResources>0 mb,0vcores</minResources><maxResources>16384 mb,16vcores</maxResources><maxRunningApps>5</maxRunningApps><weight>1.0</weight></queue><user name="default"><maxRunningApps>5</maxRunningApps></user><queue name="hadoop"><minResources>1024 mb, 4 vcores</minResources><maxResources>4096 mb, 8 vcores</maxResources><maxRunningApps>200</maxRunningApps><minSharePreemptionTimeout>300</minSharePreemptionTimeout><weight>1.0</weight><!--<schedulingPolicy>fifo</schedulingPolicy>--></queue><user name="hadoop"><maxRunningApps>400</maxRunningApps></user><queue name="hive"><minResources>1024 mb, 1 vcores</minResources><maxResources>8092 mb, 8 vcores</maxResources><maxRunningApps>200</maxRunningApps><minSharePreemptionTimeout>300</minSharePreemptionTimeout><weight>1.0</weight><!--<schedulingPolicy>fifo</schedulingPolicy>--></queue><user name="hadoop"><maxRunningApps>400</maxRunningApps></user><userMaxAppsDefault>40</userMaxAppsDefault><fairSharePreemptionTimeout>6000</fairSharePreemptionTimeout>
</allocations>

hadoop-env.sh ，yarn-env.sh 导入JAVA_HOME

export JAVA_HOME=/usr/java/jdk1.7.0_71

vi masersmastervi slavesslave1
slave2
slave3

将配置好的环境打包

tar zcvf hadoop-2.6.0.tar.gz hadoop-2.6.0
scp  hadoop-2.6.0.tar.gz hadoop@slave2:/data0
scp  hadoop-2.6.0.tar.gz hadoop@slave3:/data0

分别登录到另外两台机器，解压hadoop包，并配置环境变量。

最后，格式化hdfs，启动hadoop集群,在master节点上执行如下命令，

hadoop namenode -format
cd $HADOOP_HOME/sbin
./start-all.shjps查看后台进程
25337 QuorumPeerMain
1075 HMaster
1694 Jps
25619 DataNode
25494 NameNode
25973 NodeManager
25839 ResourceManager
1470 Main

web查看hdfs，http://192.168.137.117:50070/

查看集群，http://192.168.137.117:8088

至此，hadoop的集群就搭建完成了。