MapReduce 作业卡在 Accepted 状态 [英] MapReduce jobs get stuck in Accepted state

问题描述

我有自己的 MapReduce 代码正在尝试运行，但它只是停留在 Accepted 状态.我尝试运行之前运行过的另一个示例 MR 作业并且成功.但是现在，这两个工作都处于 Accepted 状态.我尝试更改 mapred-site.xml 和 yarn-site.xml 中提到的各种属性 这里和here 但这也无济于事.有人可以指出可能出了什么问题.我正在使用 hadoop-2.2.0

I have my own MapReduce code that I'm trying to run, but it just stays at Accepted state. I tried running another sample MR job that I'd run previously and which was successful. But now, both the jobs stay in Accepted state. I tried changing various properties in the mapred-site.xml and yarn-site.xml as mentioned here and here but that didn't help either. Can someone please point out what could possibly be going wrong. I'm using hadoop-2.2.0

我已经为各种属性尝试了许多值，这里有一组值 -在mapred-site.xml中

I've tried many values for the various properties, here is one set of values- In mapred-site.xml

<property>
<name>mapreduce.job.tracker</name>
<value>localhost:54311</value>
</property> 

<property>
<name>mapreduce.job.tracker.reserved.physicalmemory.mb</name>
<value></value>
</property>

<property>
<name>mapreduce.map.memory.mb</name>
<value>256</value>
</property>

<property>
<name>mapreduce.reduce.memory.mb</name>
<value>256</value>
</property>


<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>400</value>
<source>mapred-site.xml</source>
</property>

在yarn-site.xml中

In yarn-site.xml

<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>400</value>
<source>yarn-site.xml</source>
</property>
<property>
<name>yarn.scheduler.capacity.maximum-am-resource-percent</name>
<value>.3</value>
</property>

推荐答案

我也有同样的效果，发现让系统每个工作节点有更多可用内存并减少应用程序所需的内存有帮助.

I've had the same effect and found that making the system have more memory available per worker node and reduce the memory required for an application helped.

我的 yarn-site.xml 中的设置(在我非常小的实验盒上):

The settings I have (on my very small experimental boxes) in my yarn-site.xml:

<property>
  <name>yarn.nodemanager.resource.memory-mb</name>
  <value>2200</value>
  <description>Amount of physical memory, in MB, that can be allocated for containers.</description>
</property>

<property>
  <name>yarn.scheduler.minimum-allocation-mb</name>
  <value>500</value>
</property>

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