Mapreduce 包
你需从发布页面获得MapReduce tar包。若不能，你要将源码打成tar包。
$ mvn clean install -DskipTests
$ cd hadoop-mapreduce-project
$ mvn clean install assembly:assembly -Pnative |
注意：你需要安装有protoc 2.5.0。忽略本地建立mapreduce，你可以在maven中省略-Pnative参数。tar包应该在target/directory。配置环境
假设你已经安装hadoop-common/hadoop-hdfs，并且输出了$HADOOP_COMMON_HOME/$HADOOP_HDFS_HOME，解压hadoop mapreduce 包，配置环境变量$HADOOP_MAPRED_HOME到要安装的目录。$HADOOP_YARN_HOME的配置和 $HADOOP_MAPRED_HOME一样.注意：下面的操作假设你已经运行了hdfs。设置配置信息
要启动ResourceManager and NodeManager, 你必须升级配置。假设你的 $HADOOP_CONF_DIR是配置目录，并且已经安装了HDFS和core-site.xml。还有2个配置文件你必须设置 [code]mapred-site.xml
和
yarn-site.xml
.
设置 mapred-site.xml
添加下面的配置到你的
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>[/code] |
设置 yarn-site.xml
添加下面的配置到你的
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> |
运行守护进程
假设环境变量 $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。运行ResourceManager 和 NodeManager 如下：
$ cd $HADOOP_MAPRED_HOME
$ sbin/yarn-daemon.sh start resourcemanager
$ sbin/yarn-daemon.sh start nodemanager |
你应该启动和运行。你可以运行randomwriter如下：
$ $HADOOP_COMMON_HOME/bin/hadoop jar hadoop-examples.jar randomwriter out |
祝你好运。
