Ok… gotcha… wasn’t sure that YARN just looked at the heap size allocation and 
ignored the off heap. 

WRT over all OS memory… this would be one reason why I’d keep a decent amount 
of swap around. (Maybe even putting it on a fast device like an .m2 or PCIe 
flash drive…. 

> On Sep 22, 2016, at 9:56 AM, Sean Owen <so...@cloudera.com> wrote:
> It's looking at the whole process's memory usage, and doesn't care
> whether the memory is used by the heap or not within the JVM. Of
> course, allocating memory off-heap still counts against you at the OS
> level.
> On Thu, Sep 22, 2016 at 3:54 PM, Michael Segel
> <msegel_had...@hotmail.com> wrote:
>> Thanks for the response Sean.
>> But how does YARN know about the off-heap memory usage?
>> That’s the piece that I’m missing.
>> Thx again,
>> -Mike
>>> On Sep 21, 2016, at 10:09 PM, Sean Owen <so...@cloudera.com> wrote:
>>> No, Xmx only controls the maximum size of on-heap allocated memory.
>>> The JVM doesn't manage/limit off-heap (how could it? it doesn't know
>>> when it can be released).
>>> The answer is that YARN will kill the process because it's using more
>>> memory than it asked for. A JVM is always going to use a little
>>> off-heap memory by itself, so setting a max heap size of 2GB means the
>>> JVM process may use a bit more than 2GB of memory. With an off-heap
>>> intensive app like Spark it can be a lot more.
>>> There's a built-in 10% overhead, so that if you ask for a 3GB executor
>>> it will ask for 3.3GB from YARN. You can increase the overhead.
>>> On Wed, Sep 21, 2016 at 11:41 PM, Jörn Franke <jornfra...@gmail.com> wrote:
>>>> All off-heap memory is still managed by the JVM process. If you limit the
>>>> memory of this process then you limit the memory. I think the memory of the
>>>> JVM process could be limited via the xms/xmx parameter of the JVM. This can
>>>> be configured via spark options for yarn (be aware that they are different
>>>> in cluster and client mode), but i recommend to use the spark options for
>>>> the off heap maximum.
>>>> https://spark.apache.org/docs/latest/running-on-yarn.html
>>>> On 21 Sep 2016, at 22:02, Michael Segel <msegel_had...@hotmail.com> wrote:
>>>> I’ve asked this question a couple of times from a friend who didn’t 
>>>> know
>>>> the answer… so I thought I would try here.
>>>> Suppose we launch a job on a cluster (YARN) and we have set up the
>>>> containers to be 3GB in size.
>>>> What does that 3GB represent?
>>>> I mean what happens if we end up using 2-3GB of off heap storage via
>>>> tungsten?
>>>> What will Spark do?
>>>> Will it try to honor the container’s limits and throw an exception or 
>>>> will
>>>> it allow my job to grab that amount of memory and exceed YARN’s
>>>> expectations since its off heap?
>>>> Thx
>>>> -Mike
>>>> [œÝXœØÜšX™H K[XZ[ ˆ \Ù\‹][œÝXœØÜšX™P Ü \šË˜\ XÚ K›Ü™ÃBƒ

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