我在不同的机器上安装了一个带有调度程序的容器和几个工作容器。 因此，我正在尝试运行下一个代码（只是我的问题的最小示例）：
import os
import numpy as np
import dask.distributed as dds
import dask.dataframe as dd
import pandas as pd
client = dds.Client('ADDRESS_HERE')
df = pd.DataFrame({
'column': ['val1', 'val2', 'val1', 'val3'] * 30
})
df_dask = dd.from_pandas(df, npartitions=2)
df_unique = df_dask[['column']].dropna().drop_duplicates()
df_unique.compute()
但是最终的.compute()方法引发以下异常：
---------------------------------------------------------------------------
CancelledError Traceback (most recent call last)
<ipython-input-6-9ab9b046d151> in <module>
----> 1 df_unique.compute()
/usr/local/lib/python3.6/dist-packages/dask/base.py in compute(self, **kwargs)
163 dask.base.compute
164 """
--> 165 (result,) = compute(self, traverse=False, **kwargs)
166 return result
167
/usr/local/lib/python3.6/dist-packages/dask/base.py in compute(*args, **kwargs)
434 keys = [x.__dask_keys__() for x in collections]
435 postcomputes = [x.__dask_postcompute__() for x in collections]
--> 436 results = schedule(dsk, keys, **kwargs)
437 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
438
/usr/local/lib/python3.6/dist-packages/distributed/client.py in get(self, dsk, keys, restrictions, loose_restrictions, resources, sync, asynchronous, direct, retries, priority, fifo_timeout, actors, **kwargs)
2543 should_rejoin = False
2544 try:
-> 2545 results = self.gather(packed, asynchronous=asynchronous, direct=direct)
2546 finally:
2547 for f in futures.values():
/usr/local/lib/python3.6/dist-packages/distributed/client.py in gather(self, futures, errors, direct, asynchronous)
1843 direct=direct,
1844 local_worker=local_worker,
-> 1845 asynchronous=asynchronous,
1846 )
1847
/usr/local/lib/python3.6/dist-packages/distributed/client.py in sync(self, func, asynchronous, callback_timeout, *args, **kwargs)
760 else:
761 return sync(
--> 762 self.loop, func, *args, callback_timeout=callback_timeout, **kwargs
763 )
764
/usr/local/lib/python3.6/dist-packages/distributed/utils.py in sync(loop, func, callback_timeout, *args, **kwargs)
331 if error[0]:
332 typ, exc, tb = error[0]
--> 333 raise exc.with_traceback(tb)
334 else:
335 return result[0]
/usr/local/lib/python3.6/dist-packages/distributed/utils.py in f()
315 if callback_timeout is not None:
316 future = gen.with_timeout(timedelta(seconds=callback_timeout), future)
--> 317 result[0] = yield future
318 except Exception as exc:
319 error[0] = sys.exc_info()
/usr/local/lib/python3.6/dist-packages/tornado/gen.py in run(self)
733
734 try:
--> 735 value = future.result()
736 except Exception:
737 exc_info = sys.exc_info()
CancelledError:
distributed.client - ERROR - Failed to reconnect to scheduler after 10.00 seconds, closing client
distributed.utils - ERROR -
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/distributed/utils.py", line 662, in log_errors
yield
File "/usr/local/lib/python3.6/dist-packages/distributed/client.py", line 1290, in _close
await gen.with_timeout(timedelta(seconds=2), list(coroutines))
concurrent.futures._base.CancelledError
distributed.utils - ERROR -
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/distributed/utils.py", line 662, in log_errors
yield
File "/usr/local/lib/python3.6/dist-packages/distributed/client.py", line 1019, in _reconnect
await self._close()
File "/usr/local/lib/python3.6/dist-packages/distributed/client.py", line 1290, in _close
await gen.with_timeout(timedelta(seconds=2), list(coroutines))
concurrent.futures._base.CancelledError
任何想法都可能是这个问题的根源吗？
UPD。似乎这是部署缓慢的问题，但我仍然不知道这个问题的根源。