Hadoop-2.2.0中国文献——MapReduce 下一代 —配置单节点集群

Mapreduce 包

你需从公布页面获得MapReduce tar包。若不能。你要将源代码打成tar包。

$ mvn clean install -DskipTests
$ cd hadoop-mapreduce-project
$ mvn clean install assembly:assembly -Pnative

注意：你须要安装有protoc 2.5.0。
忽略本地建立mapreduce。你能够在maven中省略-Pnative參数。
tar包应该在target/directory。
配置环境
如果你已经安装hadoop-common/hadoop-hdfs，而且输出了$HADOOP_COMMON_HOME/$HADOOP_HDFS_HOME，解压hadoop mapreduce 包，配置环境变量$HADOOP_MAPRED_HOME到要安装的文件夹。$HADOOP_YARN_HOME的配置和 $HADOOP_MAPRED_HOME一样.
注意：以下的操作如果你已经执行了hdfs。
设置配置信息
要启动ResourceManager and NodeManager, 你必须升级配置。如果你的 $HADOOP_CONF_DIR是配置文件夹。而且已经安装了HDFS和core-site.xml。还有2个配置文件你必须设置 mapred-site.xml 和yarn-site.xml.
设置 mapred-site.xml
加入以下的配置到你的mapred-site.xml.
<property>
    <name>mapreduce.cluster.temp.dir</name>
    <value></value>
    <description>No description</description>
    <final>true</final>
  </property>

  <property>
    <name>mapreduce.cluster.local.dir</name>
    <value></value>
    <description>No description</description>
    <final>true</final>
  </property>
设置 yarn-site.xml
加入以下的配置到你的yarn-site.xml.
<property>
    <name>yarn.resourcemanager.resource-tracker.address</name>
    <value>host:port</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>host:port</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>host:port</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>

设置 capacity-scheduler.xml
确保你放置根队列到capacity-scheduler.xml.
 <property>
    <name>yarn.scheduler.capacity.root.queues</name>
    <value>unfunded,default</value>
  </property>
  
  <property>
    <name>yarn.scheduler.capacity.root.capacity</name>
    <value>100</value>
  </property>
  
  <property>
    <name>yarn.scheduler.capacity.root.unfunded.capacity</name>
    <value>50</value>
  </property>
  
  <property>
    <name>yarn.scheduler.capacity.root.default.capacity</name>
    <value>50</value>
  </property>
执行守护进程
如果环境变量 $HADOOP_COMMON_HOME, $HADOOP_HDFS_HOME, $HADOO_MAPRED_HOME, $HADOOP_YARN_HOME,$JAVA_HOME 和 $HADOOP_CONF_DIR 已经设置正确。$$YARN_CONF_DIR 的设置同 $HADOOP_CONF_DIR。
执行ResourceManager 和 NodeManager 例如以下：
$ cd $HADOOP_MAPRED_HOME
$ sbin/yarn-daemon.sh start resourcemanager
$ sbin/yarn-daemon.sh start nodemanager
你应该启动和执行。你能够执行randomwriter例如以下：
$ $HADOOP_COMMON_HOME/bin/hadoop jar hadoop-examples.jar randomwriter out
祝你好运。