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From hari <harib...@gmail.com>
Subject Re: YARN creates only 1 container
Date Fri, 04 Jul 2014 00:36:38 GMT
Just an update on this: turns out that in 2.2.0 version, the container
count is implemented by using the memory
resource, even though there are configs for vcores. Things might have
changed since
then.

Thanks for the suggestions. yarn.xml was a typo, should have been
yarn-site.xml.

About the heap size, it shouldn't be a problem unless the memory allocation
footprint of the
container exceeds or reaches close to the configured heap size. This
happened when
those settings were used. For other cases, the memory values were
different.

On Wed, Jul 2, 2014 at 6:27 PM, Adam Kawa <kawa.adam@gmail.com> wrote:

> You also might want to increase values for mapreduce.{map,reduce}.memory.mb
> to 1280 or 1536 or so (assuming that mapreduce.{map,reduce}.java.opts =
> -Xmx1024m).
>
> mapreduce.{map,reduce}.memory.mb is logical size of the container and it
> should be larger than mapreduce.{map,reduce}.java.opts that specifies the
> heap for JVM running the actual task.
>
>
> 2014-06-27 5:43 GMT+02:00 Wangda Tan <wheeleast@gmail.com>:
>
> It should be yarn-site.xml not yarn.xml.
>> yarn.xml will not be added to $CLASSPATH
>>
>> Thanks,
>> Wangda
>>
>>
>>  On Wed, May 28, 2014 at 8:56 AM, hari <haribaha@gmail.com> wrote:
>>
>>> The issue was not related the configuration related to containers. Due
>>> to
>>> misconfiguration, the Application master was not able to contact
>>> resourcemanager
>>> causing in the 1 container problem.
>>>
>>> However, the total containers allocated still is not as expected. The
>>> configuration settings
>>> should have resulted in 16 containers per node, but it is allocating 64
>>> containers per node.
>>>
>>> Reiterating the config parameters here again:
>>>
>>> mapred-site.xml
>>> mapreduce.map.cpu.vcores = 1
>>> mapreduce.reduce.cpu.vcores = 1
>>> mapreduce.map.memory.mb = 1024
>>> mapreduce.reduce.memory.mb = 1024
>>> mapreduce.map.java.opts = -Xmx1024m
>>> mapreduce.reduce.java.opts = -Xmx1024m
>>>
>>> yarn.xml
>>> yarn.nodemanager.resource.memory-mb = 65536
>>>  yarn.nodemanager.resource.cpu-vcores = 16
>>> yarn.scheduler.minimum-allocation-mb = 1024
>>> yarn.scheduler.maximum-allocation-mb  = 2048
>>> yarn.scheduler.minimum-allocation-vcores = 1
>>> yarn.scheduler.maximum-allocation-vcores = 1
>>>
>>> Is there anything else that might be causing this problem ?
>>>
>>> thanks,
>>> hari
>>>
>>>
>>>
>>>
>>>
>>> On Tue, May 27, 2014 at 3:31 AM, hari <haribaha@gmail.com> wrote:
>>>
>>>> Hi,
>>>>
>>>> When using YARN 2.2.0 version, only 1 container is created
>>>> for an application in the entire cluster.
>>>> The single container is created at an arbitrary node
>>>> for every run. This happens when running any application from
>>>> the examples jar (e.g., wordcount). Currently only one application is
>>>> run at a time. The input datasize is > 200GB.
>>>>
>>>> I am setting custom values that affect concurrent container count.
>>>> These config parameters were mostly taken from:
>>>>
>>>> http://blog.cloudera.com/blog/2014/04/apache-hadoop-yarn-avoiding-6-time-consuming-gotchas/
>>>> These wasn't much description elsewhere on how the container count
>>>> would be
>>>> decided.
>>>>
>>>> The settings are:
>>>>
>>>> mapred-site.xml
>>>> mapreduce.map.cpu.vcores = 1
>>>> mapreduce.reduce.cpu.vcores = 1
>>>> mapreduce.map.memory.mb = 1024
>>>> mapreduce.reduce.memory.mb = 1024
>>>> mapreduce.map.java.opts = -Xmx1024m
>>>> mapreduce.reduce.java.opts = -Xmx1024m
>>>>
>>>> yarn.xml
>>>> yarn.nodemanager.resource.memory-mb = 65536
>>>> yarn.nodemanager.resource.cpu-vcores = 16
>>>>
>>>> From these settings, each node should be running 16 containers.
>>>>
>>>> Let me know if there might be something else affecting the container
>>>> count.
>>>>
>>>> thanks,
>>>> hari
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>
>>
>

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