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Right now the way concurrency works in our test can be kind of hard to understand. We specify a ConcurrentPaymentJobs value ( typically from 1 to 50).
This is the number of payment "jobs" a client maintains. A payment job is the process of
opening a virtual channel
sending a few payments on it
close the virtual channel
We run these jobs in their own go-routine which means the client handles concurrent API calls (which it handles fine).
I think this model works fine although may be resource intensive for large ConcurrentPaymentJobs values as we're spinning up a go routine for each job.
However I'm not sure this model reflects how we'd expect it to be used in retrieval market. It's also hard to quickly describe what this value means. It would be nice if the way we controlled load (concurrent or otherwise) was simple to explain and understand.
In the context of a retrieval market is there a better way to model load on a client? Is there any way we could simplify our model so it's easy to describe and understand?
The text was updated successfully, but these errors were encountered:
Right now the way concurrency works in our test can be kind of hard to understand. We specify a
ConcurrentPaymentJobs
value ( typically from1
to50
).This is the number of payment "jobs" a client maintains. A payment job is the process of
We run these jobs in their own
go-routine
which means the client handles concurrent API calls (which it handles fine).I think this model works fine although may be resource intensive for large
ConcurrentPaymentJobs
values as we're spinning up a go routine for each job.However I'm not sure this model reflects how we'd expect it to be used in retrieval market. It's also hard to quickly describe what this value means. It would be nice if the way we controlled load (concurrent or otherwise) was simple to explain and understand.
In the context of a retrieval market is there a better way to model load on a client? Is there any way we could simplify our model so it's easy to describe and understand?
The text was updated successfully, but these errors were encountered: