Hi guys! One question regarding Actors and map_batches:
I saw on Actors — Ray 2.7.1 that we may use
max_task_retries in a
@ray.remote decorator to allow an actor to be restarted on failures, but how can I pass these parameters when running
map_batches on a dataset pipeline?
Here is an example of an actor class and a call to
dataset.map_batches(ActorA, compute=ray.data.ActorPoolStrategy(1, 4), batch_size=100000) class ActorA: def __init__(self): # init actor here def __call__(self, batch): return self.potential_exception_method(batch) def potential_exception_method(self, batch): # logic here