If you're using Jupyterhub, however, then there are spawners which have
some ways to control the resources available to each user. For example,
Systemdspawner:

https://github.com/jupyterhub/systemdspawner

On 7 February 2017 at 11:02, MinRK <[email protected]> wrote:

>
>
> On Mon, Feb 6, 2017 at 3:54 PM, <[email protected]> wrote:
>
>> Hi,
>>         We know user can create as many notebook instances as they can in
>> one jupyter notebook server client, and when we want to integrate spark's
>> pyspark into jupyter notebook, which means using the ipykernel, when every
>> each notebook instance is created, then a pyspark shell(or to say a driver)
>> is initialized, since we run that in spark client mode, so all the started
>> drivers would run on same host. And when some user in crazy mode, like
>> creating many many notebook instances, then many drivers would all start in
>> one host, which will lead to being lack of available resource  easily.
>>        So I am wondering if Jupyter notebook has some mechanism to deal
>> with or avoid such kind of that issue?
>>
>
> Jupyter itself has no mechanism to deal with this. It would have to be
> done at the library level - i.e. check for other instances and do one of:
>
> - connect to running instances if possible
> - refuse to start if too many are running
> - etc.
>
> -Min
>
>
>>
>> Many thanks in advance!
>>
>> Best Regards
>> Sherry
>>
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