What happened:
DataFrame collections like dask dataframes or dask-cudf cannot be persisted after release 2021.2.0. @wphicks triaged that after the merge of this PR the issue started to present: https://github.com/dask/distributed/pull/4406
What you expected to happen:
Persist to work (see reproducer)
Minimal Complete Verifiable Example:
import dask.dataframe as dd
import numpy as np
import pandas as pd
from dask.distributed import Client
from dask.distributed import LocalCluster
def persist_across_workers(client, objects, workers=None):
if workers is None:
# Default to all workers
workers = client.has_what().keys()
return client.persist(objects, workers={o: workers for o in objects})
if __name__ == "__main__":
cluster = LocalCluster()
client = Client(cluster)
X = np.ones((10000, 20))
X_df = pd.DataFrame(X)
X_dist = dd.from_pandas(X_df, npartitions=2)
X_f = persist_across_workers(client, X_dist)
Output:
distributed.protocol.core - CRITICAL - Failed to Serialize
Traceback (most recent call last):
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/protocol/core.py", line 39, in dumps
small_header, small_payload = dumps_msgpack(msg, **compress_opts)
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/protocol/core.py", line 184, in dumps_msgpack
payload = msgpack.dumps(msg, default=msgpack_encode_default, use_bin_type=True)
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/msgpack/__init__.py", line 35, in packb
return Packer(**kwargs).pack(o)
File "msgpack/_packer.pyx", line 292, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 298, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 295, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 264, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 264, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 289, in msgpack._cmsgpack.Packer._pack
TypeError: can not serialize 'dict_keys' object
distributed.comm.utils - ERROR - can not serialize 'dict_keys' object
Traceback (most recent call last):
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/comm/utils.py", line 32, in _to_frames
protocol.dumps(
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/protocol/core.py", line 39, in dumps
small_header, small_payload = dumps_msgpack(msg, **compress_opts)
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/protocol/core.py", line 184, in dumps_msgpack
payload = msgpack.dumps(msg, default=msgpack_encode_default, use_bin_type=True)
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/msgpack/__init__.py", line 35, in packb
return Packer(**kwargs).pack(o)
File "msgpack/_packer.pyx", line 292, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 298, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 295, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 264, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 264, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 289, in msgpack._cmsgpack.Packer._pack
TypeError: can not serialize 'dict_keys' object
distributed.batched - ERROR - Error in batched write
Traceback (most recent call last):
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/batched.py", line 93, in _background_send
nbytes = yield self.comm.write(
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/tornado/gen.py", line 762, in run
value = future.result()
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/comm/tcp.py", line 230, in write
frames = await to_frames(
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/comm/utils.py", line 52, in to_frames
return _to_frames()
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/comm/utils.py", line 32, in _to_frames
protocol.dumps(
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/protocol/core.py", line 39, in dumps
small_header, small_payload = dumps_msgpack(msg, **compress_opts)
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/distributed/protocol/core.py", line 184, in dumps_msgpack
payload = msgpack.dumps(msg, default=msgpack_encode_default, use_bin_type=True)
File "/home/galahad/miniconda3/envs/ns0208/lib/python3.8/site-packages/msgpack/__init__.py", line 35, in packb
return Packer(**kwargs).pack(o)
File "msgpack/_packer.pyx", line 292, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 298, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 295, in msgpack._cmsgpack.Packer.pack
File "msgpack/_packer.pyx", line 264, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 264, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 231, in msgpack._cmsgpack.Packer._pack
File "msgpack/_packer.pyx", line 289, in msgpack._cmsgpack.Packer._pack
TypeError: can not serialize 'dict_keys' object
Environment:
cc @jakirkham @pentschev @madsbk @wphicks
cc @ian-r-rose
Thanks for the nice example @dantegd. In https://github.com/dask/distributed/pull/4406 we removed the ability to pass Dask collections to priority=, workers= keywords as they were broken in many cases. Instead you can now use Dask's new dask.annotate machinery in these cases, which should hopefully be more robust.
For the above example, this means changing
client.persist(objects, workers={o: workers for o in objects})
to
with dask.annotate(workers=set(workers)):
return client.persist(objects)
Details:
import dask.dataframe as dd
import numpy as np
import pandas as pd
import dask
from dask.distributed import Client
from dask.distributed import LocalCluster
def persist_across_workers(client, objects, workers=None):
if workers is None:
# Default to all workers
workers = client.has_what().keys()
with dask.annotate(workers=set(workers)):
return client.persist(objects)
if __name__ == "__main__":
cluster = LocalCluster()
client = Client(cluster)
X = np.ones((10000, 20))
X_df = pd.DataFrame(X)
X_dist = dd.from_pandas(X_df, npartitions=2)
X_f = persist_across_workers(client, X_dist)
Should we improve the error message here then? Maybe drop this flag? Something else? As it is, this is not obviously unsupported based on the error message given (MsgPack unable to serialize something)
Yes, that's right @jrbourbeau .
@jakirkham I agree that an improved error message would be helpful. At the very least, we could do a better job ensuring that the shape of the priority/workers/etc makes sense (i.e., iterable for workers, number for priority, error if dict-of-collections)
@trivialfis you might be interested in this -- I think xgboost maybe does similar things ?
cc @hcho3 (from xgboost as well)
I think xgboost maybe does similar things ?
Good to know. Briefly looking through xgboost, they specify individual worker addresses in workers= without any Dask collections, so that shouldn't be impacted by any of the recent changes
@hcho3 is out for a bit, but it sounds like we're good on the xgboost front? @trivialfis, please feel free to hit me up if you need extra hands/eyes on that.
Good to know. Briefly looking through xgboost, they specify individual worker addresses in workers= without any Dask collections, so that shouldn't be impacted by any of the recent changes
Thanks for checking @jrbourbeau
Just checking in here, was there anything else we still need to do or is this ok to close now?
It was proposed we could improve the error message which is raised (https://github.com/dask/distributed/issues/4492#issuecomment-775523990). But otherwise I think things have already been fixed upstream in dask-cudf
I'm sorry for completely missing this thread until I tried to dig up some old emails...
Good to know. Briefly looking through xgboost, they specify individual worker addresses in workers= without any Dask collections, so that shouldn't be impacted by any of the recent changes
We do have a line that might be related https://github.com/dmlc/xgboost/blob/905fdd3e08d91077aada776346c7e49e4ff69334/python-package/xgboost/dask.py#L335 , copying it to here:
data = client.persist(data)
But we just use the default value for workers. So should be safe?
If you don't need the workers to be specified, would not specify them
Yeah, as John mentioned, you should be fine since you're not explicitly specifying a set of workers
@jakirkham @jrbourbeau Thanks for the advice!
Most helpful comment
@trivialfis you might be interested in this -- I think xgboost maybe does similar things ?