[大数据]解决运行MapReduce时遇到:Container killed on request. Exit code is 143

背景描述：解决运行MapReduce时遇到:Container killed on request. Exit code is 143
问题分析：内存分配不足 需要对MapReduce和yarn的xml文件参数进行调整
在这里修改：

[master@hadoop102 hadoop]$ vim mapred-site.xml

增加内容为：

<property>
    <name>mapreduce.map.memory.mb</name>
    <value>1500</value>
    <description>每个Map任务的物理内存限制</description>
</property>
 
<property>
    <name>mapreduce.reduce.memory.mb</name>
    <value>3000</value>
    <description>每个Reduce任务的物理内存限制</description>
</property>
 
<property>
    <name>mapreduce.map.java.opts</name>
    <value>-Xmx1200m</value>
</property>
 
<property>
    <name>mapreduce.reduce.java.opts</name>
    <value>-Xmx2600m</value>
</property>
<property>
    <name>mapreduce.framework.name</name>
    <value>yarn</value>
</property>

然后修改yarn-site.xml 添加以下内容

[master@hadoop102 hadoop]$ vim yarn-site.xml

<property>
    <name>yarn.nodemanager.resource.memory-mb</name>
    <value>22528</value>
    <discription>每个节点可用内存,单位MB</discription>
</property>
 
<property>
    <name>yarn.scheduler.minimum-allocation-mb</name>
    <value>1500</value>
    <discription>单个任务可申请最少内存，默认1024MB</discription>
</property>
 
<property>
    <name>yarn.scheduler.maximum-allocation-mb</name>
    <value>16384</value>
    <discription>单个任务可申请最大内存，默认8192MB</discription>
</property>

然后分发到hadoop103 104上，再重启集群 ,即可执行

stop-all.sh
start-all.sh