Hadoop YARN作业卡在地图0％处并减少0％ [英] Hadoop YARN job is getting stucked at map 0% and reduce 0%
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问题描述
我试图运行一个非常简单的作业来测试我的hadoop设置，所以我尝试使用Word Count Example，它被卡在0％内，所以我尝试了其他一些简单的作业，而每个作业都被卡住
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%
我正在使用hadoop版本-Hadoop 2.3.0-cdh5.0.2
我在Google上进行了快速研究，发现这种情况有所增加
yarn.scheduler.minimum-allocation-mb
yarn.nodemanager.resource.memory-mb
我有一个单节点群集，它在具有双核和8 GB Ram的Macbook中运行.
我的yarn-site.xml文件-
<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>
我的mapred-site.xml
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
只有1个属性. 尝试了几种排列和组合，但无法摆脱错误.
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
解决方案
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)."，但是您的mapreduce.map.memory.mb是8GB. 8GB是您真正要求的.
此外，您已将yarn.app.mapreduce.am.resource.mb设置为8GB.因此，您试图分配一个AM来控制8GB的作业以及几个8GB的映射器.
解决方案
要解决此问题，可以将AM的大小减小到1GB，然后将mapper的大小减小到.5GB，这对于玩耍尤其是字数计算来说是一个更合理的大小.
其他资源
您可以参考此说明由Clouera提供，以更详细地了解这些属性.
I am trying to run a very simple job to test my hadoop setup so I tried with Word Count Example , which get stuck in 0% , so i tried some other simple jobs and each one of them stuck
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%
I am using hadoop version- Hadoop 2.3.0-cdh5.0.2
I did quick research on Google and found to increase
yarn.scheduler.minimum-allocation-mb
yarn.nodemanager.resource.memory-mb
I am having single node cluster, running in my Macbook with dual core and 8 GB Ram.
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>
my mapred-site.xml
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
has only 1 property. tried several permutation and combinations but couldn't get rid of the error.
Log of the job
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
解决方案
Your settings appear to be incorrect.
The setting yarn.nodemanager.resource.memory-mb
is set to 2GB. This is the "amount of physical memory, in MB, that can be allocated for containers." But your mapreduce.map.memory.mb is 8GB. 8GB is what you're really requesting.
Additionally, you have set yarn.app.mapreduce.am.resource.mb to 8GB. As such, you're trying to allocate an AM which controls the job at 8GB plus several mappers at 8GB.
Solution
To solve the issue, you can drop the AM size to 1GB and then the mapper size to .5GB, which is a more reasonable size for playing around especially for word count.
Additional resources
You can refer to this instruction provided by Clouera to understand these properties in more detail.
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