Hi Henry,

Are there any applications (on different queues rather than longrun queue)
are running in the same time ? I think FairScheduler is going to assign
more resources to your "longrun" as long as there no other applications are
running in the other queues.

Thanks
Yehia


On 12 August 2014 20:30, Henry Hung <ythu...@winbond.com> wrote:

>  Hi Everyone,
>
>
>
> I’m using Hadoop-2.2.0 with fair scheduler in my YARN cluster, but
> something is wrong with the fair scheduler.
>
>
>
> Here is my fair-scheduler.xml looks like:
>
>
>
> <allocations>
>
>   <queue name="longrun">
>
>     <maxResources>15360 mb, 5 vcores</maxResources>
>
>     <weight>0.5</weight>
>
>     <minMaps>2</minMaps>
>
>     <maxMaps>5</maxMaps>
>
>     <minReduces>1</minReduces>
>
>   </queue>
>
> </allocations>
>
>
>
> I create a “longrun” queue to ensure that huge MR application can only use
> 5 resources. My YARN setup for each resource memory is 3072 MB:
>
>
>
>   <property>
>
>     <name>mapreduce.map.memory.mb</name>
>
>     <value>3072</value>
>
>   </property>
>
>   <property>
>
>     <name>mapreduce.reduce.memory.mb</name>
>
>     <value>3072</value>
>
>   </property>
>
>
>
> When the huge application started, it works just fine and scheduler
> restrict it to only run 5 maps in parallel.
>
> But after running for some time, the application run 10 maps in parallel.
>
> The scheduler page show that the “longrun” queue used 66%, exceed the fair
> share 30%.
>
>
>
> Can anyone tell me why the application can get more than it deserved?
>
> Is the problem with my configuration? Or there is a bug?
>
>
>
> Best regards,
>
> Henry Hung
>
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