This is a great idea. I think, if I understand you correctly, adding a
fourth implementation type is intended to address this. The extra type
is going to act something like an orchestrator, trying to
intelligently manage the Map, Combine, and Reduce functions over
distributed computing facilities and heterogeneous data sources. Like
you said, this component could shape the deployment of computations
based on things like cloud load, time of day, locality of resources
and so on.
I should probably make this more clear in my proposal.
Thank you for the comment/suggestion!
Chris
On Mar 30, 2008, at 12:50 AM, Robert Burrell Donkin wrote:
On Sun, Mar 30, 2008 at 5:06 AM, Chris Trezzo <[EMAIL PROTECTED]>
wrote:
Hello everyone,
I have posted a rough draft proposal for the project entitled
"Simplify the development of Map/Reduce applications and their
integration with various sources of information."
The draft is located here: http://www.cse.ucsd.edu/~ctrezzo/gsocapplication.html
Any comments/suggestions would be highly appreciated.
just throwing out an idea...
but would it be possible/beneficial to wrap Map/Reduce resources using
SCAs the other way round as well?
for example, take an abstract service which performs some possibly
intensive analytic computation. at smaller scales or development, the
analytic components might be assembled into a simple web service
running on a single container. at the the largest scales, the work may
need to be farmed out to one of a number of clouds.
perhaps an active management layer might be able to make decisions to
route the processing to different possibly hetrogeneous resources
based on data and meta-data (cloud load, time of day and so on) . for
example, during local night these computations might be directed to a
grid formed on general purpose PCs used during the day.
(who usually just lurks...)
- robert
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