My dask code seems to be working in multithreading mode but fails in multiprocessing mode

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The code fails when I try to do a groupby using dask:

other_df = ddf.groupby(
            by=[self.phone_field, self.state_field]).\
                    apply(lambda x: self.
                        obtain_cluster_nos_weighted_levenshtein(x.copy()),
                            meta={self.address_id_field: "f8",
                                  self.add_clust_field: "i8"}).compute(scheduler='processes')

This is the traceback:

  File "/home/ec2-user/anaconda3/lib/python3.7/site-packages/dask/local.py", line 461, in fire_task
    dumps((dsk[key], data)),
  File "/home/ec2-user/anaconda3/lib/python3.7/site-packages/cloudpickle/cloudpickle_fast.py", line 102, in dumps
    cp.dump(obj)
  File "/home/ec2-user/anaconda3/lib/python3.7/site-packages/cloudpickle/cloudpickle_fast.py", line 563, in dump
    return Pickler.dump(self, obj)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 437, in dump
    self.save(obj)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 774, in save_tuple
    save(element)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 789, in save_tuple
    save(element)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/site-packages/cloudpickle/cloudpickle_fast.py", line 745, in save_function
    *self._dynamic_function_reduce(obj), obj=obj
  File "/home/ec2-user/anaconda3/lib/python3.7/site-packages/cloudpickle/cloudpickle_fast.py", line 687, in _save_reduce_pickle5
    save(state)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 774, in save_tuple
    save(element)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 859, in save_dict
    self._batch_setitems(obj.items())
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 885, in _batch_setitems
    save(v)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 774, in save_tuple
    save(element)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 549, in save
    self.save_reduce(obj=obj, *rv)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 638, in save_reduce
    save(args)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 774, in save_tuple
    save(element)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 549, in save
    self.save_reduce(obj=obj, *rv)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 662, in save_reduce
    save(state)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 504, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 859, in save_dict
    self._batch_setitems(obj.items())
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 885, in _batch_setitems
    save(v)
  File "/home/ec2-user/anaconda3/lib/python3.7/pickle.py", line 524, in save
    rv = reduce(self.proto)
NotImplementedError: object proxy must define __reduce_ex__()

I'm guessing this has something to do with pickling before assigning to workers. This issue pops up only when scheduler='processes'. For multithreading, it executes fine. How can I resolve this?

1 Answers

It seems it isn't a good idea to call a class method for multiprocessing. I declared self.obtain_cluster_nos_weighted_levenshtein as a standalone function and my problem was solved.

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