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Allow stealing of fast tasks in some situations #6115

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Allow stealing of fast tasks in some situations #6115

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2 changes: 1 addition & 1 deletion distributed/scheduler.py
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Expand Up @@ -3441,7 +3441,7 @@ def get_task_duration(self, ts: TaskState) -> double:
"""
duration: double = ts._prefix._duration_average
if duration >= 0:
return duration
return max(0.005, duration)
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This seems like a large change to occupancy calculations that would affect things beyond stealing.

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That's true. It's not unreasonable though. getitem tasks have durations like 62us, which I think is not reflective of general overhead. I think that it probably makes sense for us to set a minimum to our compute times more broadly.


s: set = self._unknown_durations.get(ts._prefix._name) # type: ignore
if s is None:
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5 changes: 2 additions & 3 deletions distributed/stealing.py
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Expand Up @@ -23,7 +23,7 @@
# submission which may include code serialization. Therefore, be very
# conservative in the latency estimation to suppress too aggressive stealing
# of small tasks
LATENCY = 0.1
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I don't think this is realistic, see #5390

LATENCY = 0.01
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This seems unrealistically fast to me (and goes against what the comment above is saying). We've talked about doing the opposite in other places #5324. If we need to artificially suppress the latency estimate, maybe that points to something else being wrong with the stealing heuristics.


logger = logging.getLogger(__name__)

Expand Down Expand Up @@ -199,8 +199,7 @@ def steal_time_ratio(self, ts):

ws = ts.processing_on
compute_time = ws.processing[ts]
if compute_time < 0.005: # 5ms, just give up
return None, None
compute_time = max(compute_time, 0.010)
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I've been down this road before, see #4920

I also noticed the way we measure bandwidths is very skewed which impacts this significantly, see #4962 (comment) Not sure if this is still relevant but it was big back then

I still think #4920 is worth getting in but I had to drop this back then because deadlocks popped up.


nbytes = ts.get_nbytes_deps()
transfer_time = nbytes / self.scheduler.bandwidth + LATENCY
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