小贝子编程

Hadoop YARN作业被困在map 0%和reduce 0%



我正在尝试运行一个非常简单的工作来测试我的hadoop设置，所以我尝试了单词计数示例，它卡在0%，所以我尝试了其他一些简单的工作，其中每一个都卡住了

52191_0003/
14/07/14 23:55:51 INFO mapreduce.Job: Running job: job_1405376352191_0003
14/07/14 23:55:57 INFO mapreduce.Job: Job job_1405376352191_0003 running in uber mode : false
14/07/14 23:55:57 INFO mapreduce.Job:  map 0% reduce 0%

我使用hadoop版本- hadoop 2.3.0-cdh5.0.2

我在谷歌上快速搜索了一下，发现增加

yarn.scheduler.minimum-allocation-mb
yarn.nodemanager.resource.memory-mb

我有一个单节点集群，运行在我的Macbook双核和8gb内存。

my yarn-site.xml file -

<configuration>
<!-- Site specific YARN configuration properties -->
  <property>
  <property>
    <name>yarn.resourcemanager.hostname</name>
    <value>resourcemanager.company.com</value>
  </property>   
  <property>
    <description>Classpath for typical applications.</description>
    <name>yarn.application.classpath</name>
    <value>
        $HADOOP_CONF_DIR,
        $HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,
        $HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,
        $HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,
        $HADOOP_YARN_HOME/*,$HADOOP_YARN_HOME/lib/*
    </value>
  </property>
  <property>
    <name>yarn.nodemanager.local-dirs</name>
    <value>file:///data/1/yarn/local,file:///data/2/yarn/local,file:///data/3/yarn/local</value>
  </property>
  <property>
    <name>yarn.nodemanager.log-dirs</name>
    <value>file:///data/1/yarn/logs,file:///data/2/yarn/logs,file:///data/3/yarn/logs</value>
  </property>
  <property>
  </property>
    <name>yarn.log.aggregation.enable</name>
    <value>true</value> 
  <property>
    <description>Where to aggregate logs</description>
    <name>yarn.nodemanager.remote-app-log-dir</name>
    <value>hdfs://var/log/hadoop-yarn/apps</value>
  </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>
   <property>
    <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
    <value>org.apache.hadoop.mapred.ShuffleHandler</value>
  </property>
  </property>
  <property>
        <name>yarn.app.mapreduce.am.resource.mb</name>
        <value>8092</value>
    </property>
    <property>
        <name>yarn.app.mapreduce.am.command-opts</name>
        <value>-Xmx768m</value>
    </property>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
        <description>Execution framework.</description>
    </property>
    <property>
        <name>mapreduce.map.cpu.vcores</name>
        <value>4</value>
        <description>The number of virtual cores required for each map task.</description>
    </property>
    <property>
        <name>mapreduce.map.memory.mb</name>
        <value>8092</value>
        <description>Larger resource limit for maps.</description>
    </property>
    <property>
        <name>mapreduce.map.java.opts</name>
        <value>-Xmx768m</value>
        <description>Heap-size for child jvms of maps.</description>
    </property>
    <property>
        <name>mapreduce.jobtracker.address</name>
        <value>jobtracker.alexjf.net:8021</value>
    </property>
 <property>
    <name>yarn.scheduler.minimum-allocation-mb</name>
    <value>2048</value>
    <description>Minimum limit of memory to allocate to each container request at the Resource Manager.</description>
  </property>
  <property>
    <name>yarn.scheduler.maximum-allocation-mb</name>
    <value>8092</value>
    <description>Maximum limit of memory to allocate to each container request at the Resource Manager.</description>
  </property>
  <property>
    <name>yarn.scheduler.minimum-allocation-vcores</name>
    <value>2</value>
    <description>The minimum allocation for every container request at the RM, in terms of virtual CPU cores. Requests lower than this won't take effect, and the specified value will get allocated the minimum.</description>
  </property>
  <property>
    <name>yarn.scheduler.maximum-allocation-vcores</name>
    <value>10</value>
    <description>The maximum allocation for every container request at the RM, in terms of virtual CPU cores. Requests higher than this won't take effect, and will get capped to this value.</description>
  </property>
  <property>
    <name>yarn.nodemanager.resource.memory-mb</name>
    <value>2048</value>
    <description>Physical memory, in MB, to be made available to running containers</description>
  </property>
  <property>
    <name>yarn.nodemanager.resource.cpu-vcores</name>
    <value>4</value>
    <description>Number of CPU cores that can be allocated for containers.</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>
   <property>
    <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
    <value>org.apache.hadoop.mapred.ShuffleHandler</value>
  </property>
</configuration>
我mapred-site.xml

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

只有一个属性。尝试了几种排列和组合，但无法消除错误。

作业日志

 23:55:55,694 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2014-07-14 23:55:55,697 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2014-07-14 23:55:55,699 INFO [main] org.apache.hadoop.yarn.client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8030
2014-07-14 23:55:55,769 INFO [main] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: maxContainerCapability: 8092
2014-07-14 23:55:55,769 INFO [main] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: queue: root.abhishekchoudhary
2014-07-14 23:55:55,775 INFO [main] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Upper limit on the thread pool size is 500
2014-07-14 23:55:55,777 INFO [main] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: yarn.client.max-nodemanagers-proxies : 500
2014-07-14 23:55:55,787 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: job_1405376352191_0003Job Transitioned from INITED to SETUP
2014-07-14 23:55:55,789 INFO [CommitterEvent Processor #0] org.apache.hadoop.mapreduce.v2.app.commit.CommitterEventHandler: Processing the event EventType: JOB_SETUP
2014-07-14 23:55:55,800 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: job_1405376352191_0003Job Transitioned from SETUP to RUNNING
2014-07-14 23:55:55,823 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1405376352191_0003_m_000000 Task Transitioned from NEW to SCHEDULED
2014-07-14 23:55:55,824 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1405376352191_0003_m_000001 Task Transitioned from NEW to SCHEDULED
2014-07-14 23:55:55,824 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1405376352191_0003_m_000002 Task Transitioned from NEW to SCHEDULED
2014-07-14 23:55:55,825 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1405376352191_0003_m_000003 Task Transitioned from NEW to SCHEDULED
2014-07-14 23:55:55,826 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1405376352191_0003_m_000000_0 TaskAttempt Transitioned from NEW to UNASSIGNED
2014-07-14 23:55:55,827 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1405376352191_0003_m_000001_0 TaskAttempt Transitioned from NEW to UNASSIGNED
2014-07-14 23:55:55,827 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1405376352191_0003_m_000002_0 TaskAttempt Transitioned from NEW to UNASSIGNED
2014-07-14 23:55:55,827 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1405376352191_0003_m_000003_0 TaskAttempt Transitioned from NEW to UNASSIGNED
2014-07-14 23:55:55,828 INFO [Thread-49] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: mapResourceReqt:8092
2014-07-14 23:55:55,858 INFO [eventHandlingThread] org.apache.hadoop.mapreduce.jobhistory.JobHistoryEventHandler: Event Writer setup for JobId: job_1405376352191_0003, File: hdfs://localhost/tmp/hadoop-yarn/staging/abhishekchoudhary/.staging/job_1405376352191_0003/job_1405376352191_0003_1.jhist
2014-07-14 23:55:56,773 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Before Scheduling: PendingReds:0 ScheduledMaps:4 ScheduledReds:0 AssignedMaps:0 AssignedReds:0 CompletedMaps:0 CompletedReds:0 ContAlloc:0 ContRel:0 HostLocal:0 RackLocal:0
2014-07-14 23:55:56,799 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerRequestor: getResources() for application_1405376352191_0003: ask=1 release= 0 newContainers=0 finishedContainers=0 resourcelimit=<memory:0, vCores:0> knownNMs=1

根据消息Connecting to ResourceManager at /0.0.0.0:8030，你确定你的ResourceManager应该在0.0.0.0:8030(默认值)?如果没有，您应该在yarn-site.xml中添加以下内容:

<property>
  <name>yarn.resourcemanager.hostname</name>
  <value>MASTER ADDRESS</value>
</property>
<property>
  <name>yarn.resourcemanager.resource-tracker.address</name>
  <value>${yarn.resourcemanager.hostname}:8025</value>
</property>
<property>
  <name>yarn.resourcemanager.scheduler.address</name>
  <value>${yarn.resourcemanager.hostname}:8030</value>
</property>
<property>
  <name>yarn.resourcemanager.address</name>
  <value>${yarn.resourcemanager.hostname}:8040</value>
</property>
<property>
  <name>yarn.resourcemanager.webapp.address</name>
  <value>${yarn.resourcemanager.hostname}:8088</value>
</property>
<property>
  <name>yarn.resourcemanager.admin.address</name>
  <value>${yarn.resourcemanager.hostname}:8033</value>
</property>

用主节点的地址替换MASTER ADDRESS。你可以单独修改资源管理器的webapp、admin等地址

您的设置似乎不正确。

设置yarn.nodemanager.resource.memory-mb设置为"2GB"。这是可以为容器分配的"物理内存量，以MB为单位。"但是你的mapreduce.map.memory.mb是8GB。8GB才是你真正需要的。

另外，您已经将yarn.app.mapreduce.am.resource.mb设置为8GB。因此，您正在尝试分配一个控制8GB作业的AM以及8GB的几个映射器。

<

解决方案/strong>

为了解决这个问题，您可以将AM的大小降低到1GB，然后将mapper的大小降低到.5GB，这是一个更合理的大小，特别是对于单词计数。

额外资源

您可以参考Clouera提供的说明来更详细地了解这些属性

我不知道你是否只是在创建这个问题时犯了复制/粘贴错误，但是看看你的yarn-site.xml，它从两个<property>标签开始。我不确定Hadoop的xml解析器是否会实际应用这些嵌套的<property>标签。

我正在使用Apache Hadoop 2.7.2版本，所以它可能像"苹果到橘子"的比较，但是我遇到了同样的沉默卡住状态前几天。在大多数情况下，这种长时间的"沉默"表明调度器无法为应用程序分配足够的资源。

在我使用类似配置的特定情况下，增加属性yarn.nodemanager.resource的值。yarn-site.xml中的Memory-mb 就可以了。

您还可以在这里检查资源分配的其他属性

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