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From rammohan ganapavarapu <rammohanga...@gmail.com>
Subject Re: ACCEPTED: waiting for AM container to be allocated, launched and register with RM
Date Fri, 19 Aug 2016 21:32:28 GMT
When i submit a job using yarn its seems working only with oozie its
failing i guess, not sure what is missing.

yarn jar
/uap/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.1.jar pi
20 1000
Number of Maps  = 20
Samples per Map = 1000
.
.
.
Job Finished in 19.622 seconds
Estimated value of Pi is 3.14280000000000000000

Ram

On Fri, Aug 19, 2016 at 11:46 AM, rammohan ganapavarapu <
rammohanganap@gmail.com> wrote:

> Ok, i have used yarn-utils.py to get the correct values for my cluster and
> update those properties and restarted RM and NM but still no luck not sure
> what i am missing, any other insights will help me.
>
> Below are my properties from yarn-site.xml and map-site.xml.
>
> python yarn-utils.py -c 24 -m 63 -d 3 -k False
>  Using cores=24 memory=63GB disks=3 hbase=False
>  Profile: cores=24 memory=63488MB reserved=1GB usableMem=62GB disks=3
>  Num Container=6
>  Container Ram=10240MB
>  Used Ram=60GB
>  Unused Ram=1GB
>  yarn.scheduler.minimum-allocation-mb=10240
>  yarn.scheduler.maximum-allocation-mb=61440
>  yarn.nodemanager.resource.memory-mb=61440
>  mapreduce.map.memory.mb=5120
>  mapreduce.map.java.opts=-Xmx4096m
>  mapreduce.reduce.memory.mb=10240
>  mapreduce.reduce.java.opts=-Xmx8192m
>  yarn.app.mapreduce.am.resource.mb=5120
>  yarn.app.mapreduce.am.command-opts=-Xmx4096m
>  mapreduce.task.io.sort.mb=1024
>
>
>     <property>
>       <name>mapreduce.map.memory.mb</name>
>       <value>5120</value>
>     </property>
>     <property>
>       <name>mapreduce.map.java.opts</name>
>       <value>-Xmx4096m</value>
>     </property>
>     <property>
>       <name>mapreduce.reduce.memory.mb</name>
>       <value>10240</value>
>     </property>
>     <property>
>       <name>mapreduce.reduce.java.opts</name>
>       <value>-Xmx8192m</value>
>     </property>
>     <property>
>       <name>yarn.app.mapreduce.am.resource.mb</name>
>       <value>5120</value>
>     </property>
>     <property>
>       <name>yarn.app.mapreduce.am.command-opts</name>
>       <value>-Xmx4096m</value>
>     </property>
>     <property>
>       <name>mapreduce.task.io.sort.mb</name>
>       <value>1024</value>
>     </property>
>
>
>
>      <property>
>       <name>yarn.scheduler.minimum-allocation-mb</name>
>       <value>10240</value>
>     </property>
>
>      <property>
>       <name>yarn.scheduler.maximum-allocation-mb</name>
>       <value>61440</value>
>     </property>
>
>      <property>
>       <name>yarn.nodemanager.resource.memory-mb</name>
>       <value>61440</value>
>     </property>
>
>
> Ram
>
> On Thu, Aug 18, 2016 at 11:14 PM, tkg_cangkul <yuza.rasfar@gmail.com>
> wrote:
>
>> maybe this link can be some reference to tune up the cluster:
>>
>> http://jason4zhu.blogspot.co.id/2014/10/memory-configuration
>> -in-hadoop.html
>>
>>
>> On 19/08/16 11:13, rammohan ganapavarapu wrote:
>>
>> Do you know what properties to tune?
>>
>> Thanks,
>> Ram
>>
>> On Thu, Aug 18, 2016 at 9:11 PM, tkg_cangkul <yuza.rasfar@gmail.com>
>> wrote:
>>
>>> i think that's because you don't have enough resource.  u can tune your
>>> cluster config to maximize your resource.
>>>
>>>
>>> On 19/08/16 11:03, rammohan ganapavarapu wrote:
>>>
>>> I dont see any thing odd except this not sure if i have to worry about
>>> it or not.
>>>
>>> 2016-08-19 03:29:26,621 INFO [main] org.apache.hadoop.yarn.client.RMProxy:
>>> Connecting to ResourceManager at /0.0.0.0:8030
>>> 2016-08-19 03:29:27,646 INFO [main] org.apache.hadoop.ipc.Client:
>>> Retrying connect to server: 0.0.0.0/0.0.0.0:8030. Already tried 0
>>> time(s); retry policy is RetryUpToMaximumCo
>>> untWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
>>> 2016-08-19 03:29:28,647 INFO [main] org.apache.hadoop.ipc.Client:
>>> Retrying connect to server: 0.0.0.0/0.0.0.0:8030. Already tried 1
>>> time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10,
>>> sleepTime=1000 MILLISECONDS)
>>>
>>>
>>> its keep printing this log ..in app container logs.
>>>
>>> On Thu, Aug 18, 2016 at 8:20 PM, tkg_cangkul <yuza.rasfar@gmail.com>
>>> wrote:
>>>
>>>> maybe u can check the logs from port 8088 on your browser. that was RM
>>>> UI. just choose your job id and then check the logs.
>>>>
>>>> On 19/08/16 10:14, rammohan ganapavarapu wrote:
>>>>
>>>> Sunil,
>>>>
>>>> Thanks you for your input, below are my server metrics for RM. Also
>>>> attached RM UI for capacity scheduler resources. How else i can find?
>>>>
>>>> {
>>>>       "name": "Hadoop:service=ResourceManage
>>>> r,name=QueueMetrics,q0=root",
>>>>       "modelerType": "QueueMetrics,q0=root",
>>>>       "tag.Queue": "root",
>>>>       "tag.Context": "yarn",
>>>>       "tag.Hostname": "hadoop001",
>>>>       "running_0": 0,
>>>>       "running_60": 0,
>>>>       "running_300": 0,
>>>>       "running_1440": 0,
>>>>       "AppsSubmitted": 1,
>>>>       "AppsRunning": 0,
>>>>       "AppsPending": 0,
>>>>       "AppsCompleted": 0,
>>>>       "AppsKilled": 0,
>>>>       "AppsFailed": 1,
>>>>       "AllocatedMB": 0,
>>>>       "AllocatedVCores": 0,
>>>>       "AllocatedContainers": 0,
>>>>       "AggregateContainersAllocated": 2,
>>>>       "AggregateContainersReleased": 2,
>>>>       "AvailableMB": 64512,
>>>>       "AvailableVCores": 24,
>>>>       "PendingMB": 0,
>>>>       "PendingVCores": 0,
>>>>       "PendingContainers": 0,
>>>>       "ReservedMB": 0,
>>>>       "ReservedVCores": 0,
>>>>       "ReservedContainers": 0,
>>>>       "ActiveUsers": 0,
>>>>       "ActiveApplications": 0
>>>>     },
>>>>
>>>> On Thu, Aug 18, 2016 at 6:49 PM, Sunil Govind <sunil.govind@gmail.com>
>>>> wrote:
>>>>
>>>>> Hi
>>>>>
>>>>> It could be because of many of reasons. Also I am not sure about which
>>>>> scheduler your are using, pls share more details such as RM log etc.
>>>>>
>>>>> I could point out few reasons
>>>>>  - Such as "Not enough resource is cluster" can cause this
>>>>>  - If using Capacity Scheduler, if queue capacity is maxed out, such
>>>>> case can happen.
>>>>>  - Similarly if max-am-resource-percent is crossed per queue level,
>>>>> then also AM container may not be launched.
>>>>>
>>>>> you could check RM log to get more information if AM container is
>>>>> laucnhed.
>>>>>
>>>>> Thanks
>>>>> Sunil
>>>>>
>>>>> On Fri, Aug 19, 2016 at 5:37 AM rammohan ganapavarapu <
>>>>> rammohanganap@gmail.com> wrote:
>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> When i submit a MR job, i am getting this from AM UI but it never
get
>>>>>> finished, what am i missing ?
>>>>>>
>>>>>> Thanks,
>>>>>> Ram
>>>>>>
>>>>>
>>>>
>>>>
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>>>> For additional commands, e-mail: user-help@hadoop.apache.org
>>>>
>>>>
>>>>
>>>
>>>
>>
>>
>

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