Jonathan Pou

08/04/2022, 9:01 PM
Hello! Has anyone been using Prefect 2.0 with Dask managed with Coiled? I am having issues with distributing a dataframe across multiple Dask workers within the same cluster. The cluster is deployed with 4 workers but the dataframe is only being loaded in 1 of the workers, leaving the 3 others idle. When I run the same script outside of a Prefect task & flow, it runs as expected - the dataframe gets distributed across the cluster for later use. I also tested another scenario where the cluster is deployed with only 1 worker, but with autoscaling enabled by passing adapt_kwargs={"maximum": 10} to DaskTaskRunner. In this scenario, it seems like the autoscaling request is ignored as the cluster remains of size 1. Lastly, is there a way to return the standard output of a print() statement executed on a remote dask cluster back to the Prefect logger?
from prefect import flow, task
from prefect_dask.task_runners import DaskTaskRunner
import dask

coiled_executor = DaskTaskRunner(
		"n_workers" : 4,
		"software": "ttibi-dev",
		"shutdown_on_close": True,
	adapt_kwargs={"maximum": 10}

def some_data_manipulation():
	df = dask.datasets.timeseries(
		"2000", "2020", partition_freq="2w"
	df.groupby("name").aggregate({"x": "sum", "y": "max"}).compute()
	return df

def test_flow():

if __name__ == "__main__":	
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08/04/2022, 9:13 PM
Do you know if it also only sends work to a single worker if using a non-coiled Dask cluster? Unfortunately there are some issues around retrieving logs from Dask right now, investigating a fix is on the backlog.
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Jonathan Pou

08/04/2022, 9:33 PM
I just tried running it on a local Dask cluster and I'm running into the same issue. The dataframe is only trying to load on a single worker. Understood, thanks!!

Andrew Huang

08/04/2022, 10:19 PM
opened an issue here: please feel free to add more information (e.g. expected vs actual output / dashboard)
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Sam Dyson

08/09/2022, 11:09 PM
We ran into a similar problem in the past and we think that this is actually expected behaviour. Your prefect task is serialized and sent to the dask cluster as a single Dask task, but Dask workers do not automatically get a client to connect to the full cluster. Thus, it will attempt to do the work within the worker itself. You need to get a
inside the task which will let the worker submit jobs to the cluster. I found this documentation helpful:


08/10/2022, 3:05 PM
Thanks Sam! Thatโ€™s a helpful reminder.
@Andrew Huang Iโ€™d document the correct pattern here and mark that as expected.
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