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Dataloader in multi-threaded environments

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#71 10 comentarios 0 reacciones 1 asignado Ver en GitHub

@Cito ya está trabajando en esto.

Desde el 10/12/2019.

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Descripción

discussion help wanted investigate

Hi,

I've been thinking a bit about how we could implement the Dataloader pattern in v3 while still running in multi-threaded mode. Since v3 does not support Syrus's Promise library, we need to come up with a story for batching in async mode, as well as in multi-threaded environments. There are many libraries that do not support asyncio and there are many cases where it does not make sense to go fully async.

As far as I understand, the only way to batch resolver calls from a single frame of execution would be to use loop.call_soon. But since asyncio is not threadsafe, that means we would need to run a separate event loop in each worker thread. We would need to wrap the graphql call with something like this:

def run_batched_query(...):
    loop = asyncio.new_event_loop()
    execution_future = graphql(...)
    loop.run_until_complete(result_future)
    return execution_future.result()

Is that completely crazy? If yes, do you see a less hacky way? I'm not very familiar with asyncio so I would love to get feedback.

Cheers

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