linux(centos5.8)环境下Hadoop 2.0.2单机部署以及Eclipse环境搭建

Hadoop 2.0.2-alpha单机部署

（1）新建hadoop用户以及hadoop用户组

首先取得root权限新

$ su -

建用户hadoop组

# groupadd hadoop

新建用户hadoop，放入hadoop组中，并设置主目录为/home/hadoop

# useradd -g hadoop -d /home/hadoop hadoop

修改密码

# passwd hadoop

其中删除用户命令为userdel，删除用户组命令为groupdel，查看用户和分组信息可以cat /etc/groups 或cat /etc/passwd

回到新建用户目录

# su hadoop

$ cd

（2）下载和配置hadoop

下载hadoop文件

$ wget http://mirror.bjtu.edu.cn/apache/hadoop/common/hadoop-2.0.2-alpha/hadoop-2.0.2-alpha.tar.gz
下载完成后解压

$ tar xzvf hadoop-2.0.2-alpha.tar.gz

新建一个叫hadoop的文件夹，建立软链接，以便以后使用其他版本

$ ln -sf hadoop-2.0.2-alpha hadoop

配置系统环境变量

$ su -

# vim /etc/profile

在最后加上以下几行

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export HADOOP_PREFIX="/home/hadoop/hadoop"
PATH="$PATH:$HADOOP_PREFIX/bin:$HADOOP_PREFIX/sbin"
export HADOOP_MAPRED_HOME=${HADOOP_PREFIX}
export HADOOP_COMMON_HOME=${HADOOP_PREFIX}
export HADOOP_HDFS_HOME=${HADOOP_PREFIX}
export YARN_HOME=${HADOOP_PREFIX}
export HADOOP_CONF_DIR="${HADOOP_PREFIX}/etc/hadoop"

重新启动系统
# reboot

重启后使用hadoop用户登录，进入/home/hadoop/hadoop/etc/hadoop中进行配置

$ cd /home/hadoop/hadoop/etc/hadoop/

修改hadoop-env.sh

修改JAVA_HOME，这里JAVA_HOME的路径必须指定为真实的路径，不能引用${JAVA_HOME}，否则运行的时候会有错误JAVA_HOME is not set

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export JAVA_HOME=／user/java/jdk1.6.0_35

修改core-site.xml

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<configuration>
<property>
<name>fs.default.name</name>
<value>hdfs://localhost:9000</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>/tmp/hadoop/hadoop-${user.name}</value>
</property>
</configuration>

修改hdfs-site.xml

其中，/home/hadoop/dfs/name，/home/hadoop/dfs/data都是文件系统中的目录，需要先新建

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<configuration>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:/home/hadoop/dfs/name</value>
<description>Determines where on the local filesystem the DFS name node
should store the name table. If this is a comma-delimited list
of directories then the name table is replicated in all of the
directories, for redundancy. </description>
<final>true</final>
</property>

<property>
<name>dfs.datanode.data.dir</name>
<value>file:/home/hadoop/dfs/data</value>
<description>Determines where on the local filesystem an DFS data node
should store its blocks. If this is a comma-delimited
list of directories, then data will be stored in all named
directories, typically on different devices.
Directories that do not exist are ignored.
</description>
<final>true</final>
</property>

<property>
<name>dfs.replication</name>
<value>1</value>
</property>

<property>
<name>dfs.permissions</name>
<value>false</value>
</property>
</configuration>

修改mapred-site.xml

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<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>

<property>
<name>mapred.system.dir</name>
<value>file:/home/hadoop/mapred/system</value>
<final>true</final>
</property>

<property>
<name>mapred.local.dir</name>
<value>file:/home/hadoop/mapred/local</value>
<final>true</final>
</property>
</configuration>

修改yarn-site.xml

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<configuration>

<!-- Site specific YARN configuration properties -->
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>localhost:8081</value>
<description>host is the hostname of the resource manager and
port is the port on which the NodeManagers contact the Resource Manager.
</description>
</property>

<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>localhost:8082</value>
<description>host is the hostname of the resourcemanager and port is the port
on which the Applications in the cluster talk to the Resource Manager.
</description>
</property>

<property>
<name>yarn.resourcemanager.scheduler.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value>
<description>In case you do not want to use the default scheduler</description>
</property>

<property>
<name>yarn.resourcemanager.address</name>
<value>localhost:8083</value>
<description>the host is the hostname of the ResourceManager and the port is the port on
which the clients can talk to the Resource Manager. </description>
</property>

<property>
<name>yarn.nodemanager.local-dirs</name>
<value></value>
<description>the local directories used by the nodemanager</description>
</property>

<property>
<name>yarn.nodemanager.address</name>
<value>0.0.0.0:port</value>
<description>the nodemanagers bind to this port</description>
</property>

<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>10240</value>
<description>the amount of memory on the NodeManager in GB</description>
</property>

<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/app-logs</value>
<description>directory on hdfs where the application logs are moved to </description>
</property>

<property>
<name>yarn.nodemanager.log-dirs</name>
<value></value>
<description>the directories used by Nodemanagers as log directories</description>
</property>

<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce.shuffle</value>
<description>shuffle service that needs to be set for Map Reduce to run </description>
</property>
</configuration>

（3）启动hdfs以及yarn

完成以上配置后可以检测是否配置成

首先格式化namenode

$ hdfs namenode -format

然后启动hdfs

$ start-dfs.sh

或者

$ hadoop-daemon.sh start namenode

$ hadoop-daemon.sh start datanode

接着启动yarn daemons

$ start-yarn.sh

或者

$ yarn-daemon.sh start resourcemanager

$ yarn-daemon.sh start nodemanager

启动完成后可以进入http://localhost:50070/dfshealth.jsp 查看dfs状态，如下图所示

转载请注明：http://blog.csdn.net/lawrencesgj/article/details/8240571

Eclipse环境配置

（1）下载eclipse插件并导入到eclipse中

到http://wiki.apache.org/hadoop/EclipsePlugIn上下载对应的eclipse插件，然后eclipse的plugin目录中，我的环境是/usr/share/eclipse/plugins

（2）使用hadoop用户启动eclipse

$ su hadoop

$ eclipse&

（3）配置eclipse

启动后在视图中调出mapreduce视图，并点击右下角new hadoop的大象图标，如下图



填写安装目录以及用户明后Vaildate Location 就可以看到发现hadoop2.02了！这里我自己花了一点时间摸索，要完成关键是用hadoop用户启动eclipse，之前用系统的用户一直验证不成功。。

（3）新建mapreduce project

如无意外，在File>>New>>Project下面就会看到有Mapreduce Project，点击后需要配置hadoop install directory，如果用mapreduce框架配置为/home/hadoop/hadoop/share/hadoop/mapreduce，如果用yarn框架配置为/home/hadoop/hadoop/share/hadoop/yarn即可。

转载请注明：http://blog.csdn.net/lawrencesgj/article/details/8240571



一开始因为没有用hadoop用户打开eclipse所以这里费了不少时间，后来才醒悟过来。这样我们就新建了一个mapreduce项目了！

参考：
http://ipjmc.iteye.com/blog/1703112 http://slaytanic.blog.51cto.com/2057708/885198 http://hadoop.apache.org/docs/r2.0.2-alpha/hadoop-yarn/hadoop-yarn-site/SingleCluster.html http://wiki.apache.org/hadoop/EclipseEnvironment