For some reason I'm really struggling to find the right design here. I feel
OK about my "channel job" actor which creates as children a job tracker, a
worker pull master, and some workers. It builds a work list of time periods
(currently assumed to be from one channel) which it sends to the child
worker-pull master. The tracker sends a job complete message to the job
actor and the job actor stops itself. So I guess the job actor it's a bit
like a per-request actor where the request is not a web request, but a
request to process a channel.

But now I have millions of channels to process. I can paginate them or
organize them in other ways, like location. I'd like to start as many
channel jobs in parallel as possible and get a good distribution across
location. How can I throttle this job creation or is there some other
pattern I'm missing? Should I just turn the millions of channels into
millions of messages to a router and hope I can beef up the number of
routees? Should I re-apply worker pull where each worker works on a chunk
of channels?  If so, where do I get the Future in overide def
doWork():Future[_] from? By ask?ing the list of per-channel jobs their
status?

Sorry if I'm being dense.


On Tue, Jul 1, 2014 at 6:08 PM, Richard Rodseth <[email protected]> wrote:

> I've had some success using the worker pull pattern to process time series
> data in a particular "channel". A channel job actor builds the queue of
> time chunks for a work pull master and workers work on chunks of time.
>
> Now I wish to process multiple (possibly millions of) channels in parallel
> and am wondering whether to a) repeat the pattern, treating a page  of
> channels as the work queue item, where the page workers would spawn a
> channel job per channel, or b) use something else like routers or balancing
> dispatcher. Any tips?

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