Hi Doug,

That's fine at this point since it simplifies that task to some degree.
We'll work together to propose a few ideas for what the basic API might look
like and then refine it with input from other interested parties.

I will try to formulate it as an ML problem and as an optimization problem
so that researchers from those communities can engage it. I'll work up a
wiki page for the problem, we'll get some feedback on it, and then when
we're ready I can push it to various research groups.

On Mon, Dec 20, 2010 at 7:30 PM, Doug Judd <[email protected]> wrote:

> Hi Gordon,
>
> Thank you.  Any help from you and the folks in your network would be much
> appreciated.  Let me know if there is any more information you need from me
> or if you'd like to setup a meeting at some point to discuss.
>
> As far as the balance policy goes, I think for the first go-round we might
> want to have the system automatically balance when nodes are added and
> include a BALANCE command to be run manually if/when the system becomes out
> of balance.
>
> - Doug
>
>
> On Mon, Dec 20, 2010 at 10:38 AM, Gordon <[email protected]> wrote:
>
>> Hi Doug,
>>
>> Thanks for the nice writeup -- at this point we would like to start
>> carving out what the API would like to allow people to extend with their own
>> intelligent load balancing algorithms. Load balancing of this type is
>> recognized as a hard research problem(*) and I would like to see Hypertable
>> be used as central to that research.
>>
>> We'll need a set of abstractions and interfaces that allow a variety of
>> approaches that people might like to apply -- reinforcement learning,
>> constraint programming, or other AI style planning approaches. I'd like to
>> collect some feedback from a few different sources to see if we can solve
>> for the minimal interface that gives everyone the inputs and the controls
>> they need to devise a balancer. Then, we can produce an API recommendation.
>>
>> Also, we should add a bit more detail to talk about policy for calling the
>> balancer. Intelligence in the balancing strategy might probably better be
>> served by allowing the balancer policy itself to be learned or optimized.
>> For example, the system might be better left in a slightly unbalanced
>> condition rather than pay the balancing cost if it's learned that the
>> unbalanced condition is temporary.
>>
>> I'll point out the problem and this mailing list to folks doing research
>> in ML (particularly SysML or ML applied to systems management) but also from
>> the constraint computing field.
>>
>> (*) see for example:
>> http://www2.cs.uni-paderborn.de/cs/ag-monien/RESEARCH/LOADBAL/
>>
>>
>>
>> On Sun, Dec 19, 2010 at 9:15 PM, Doug Judd <[email protected]> wrote:
>>
>>> We're now 100% focused on load balancing.  This will handle the addition
>>> of new nodes as well as normal load imbalances.  I've come up with a design
>>> and have described it in the following document:
>>>
>>> http://code.google.com/p/hypertable/wiki/LoadBalancing
>>>
>>> Please read it and send your feedback.  Thanks!
>>>
>>> - Doug
>>>
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>>
>>
>>
>> --
>> Gordon Rios -- Cork Constraint Computation Centre
>> http://www.4c.ucc.ie/web/people.jsp?id=144
>> http://www.linkedin.com/in/gordonrios
>> Ireland: +353 86 089 2416
>> USA: +1 650 906 3473
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-- 
Gordon Rios -- Cork Constraint Computation Centre
http://www.4c.ucc.ie/web/people.jsp?id=144
http://www.linkedin.com/in/gordonrios
Ireland: +353 86 089 2416
USA: +1 650 906 3473

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