This repository has been archived by the owner on Nov 3, 2020. It is now read-only.
Hanging in waiter.acquire(True, timeout) #96
Comments
|
I realised the workers produced logs in Anyway, it looks like this is the problem: So looking at the version of Compared to the version on the worker My local version of distributed is while on the work it is: I ran And it now works! |
|
Glad to hear that this was resolved. In the future you might try
client.get_versions(check=True)
…On Wed, Jun 28, 2017 at 10:14 AM, Mike Smith ***@***.***> wrote:
I realised the workers produced logs in /var/log/dask-worker.log (I don't
know if this is because I added distributed.worker: debug to
.dask/config.yaml).
Anyway, it looks like this is the problem:
tornado.application - ERROR - Future <tornado.concurrent.Future object at 0x7f95d1e4f588> exception was never retrieved: Traceback (most recent call last):
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1024, in run
yielded = self.gen.send(value)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/core.py", line 239, in handle_comm
+ str(msg))
TypeError: Bad message type. Expected dict, got
[{'key': 'cv-parameters-ffeaf7708bc5a807e04134ba8785cabf', 'op': 'release-task'}, {'key': 'array-ae6a72ba4372b6e6a66362a12d606e12', 'op': 'release-task'}]
distributed.utils - ERROR - too many values to unpack (expected 2)
Traceback (most recent call last):
File "/opt/anaconda/lib/python3.5/site-packages/distributed/utils.py", line 381, in log_errors
yield
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/numpy.py", line 98, in deserialize_numpy_ndarray
is_custom, dt = header['dtype']
ValueError: too many values to unpack (expected 2)
distributed.protocol.core - CRITICAL - Failed to deserialize
Traceback (most recent call last):
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/core.py", line 121, in loads
value = _deserialize(head, fs)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/serialize.py", line 161, in deserialize
return f(header, frames)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/numpy.py", line 98, in deserialize_numpy_ndarray
is_custom, dt = header['dtype']
ValueError: too many values to unpack (expected 2)
distributed.worker - ERROR - too many values to unpack (expected 2)
Traceback (most recent call last):
File "/opt/anaconda/lib/python3.5/site-packages/distributed/worker.py", line 1040, in compute_stream
msgs = yield comm.read()
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1015, in run
value = future.result()
File "/opt/anaconda/lib/python3.5/site-packages/tornado/concurrent.py", line 237, in result
raise_exc_info(self._exc_info)
File "<string>", line 3, in raise_exc_info
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1024, in run
yielded = self.gen.send(value)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/comm/tcp.py", line 169, in read
msg = from_frames(frames, deserialize=self.deserialize)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/comm/utils.py", line 30, in from_frames
return protocol.loads(frames, deserialize=deserialize)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/core.py", line 121, in loads
value = _deserialize(head, fs)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/serialize.py", line 161, in deserialize
return f(header, frames)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/numpy.py", line 98, in deserialize_numpy_ndarray
is_custom, dt = header['dtype']
ValueError: too many values to unpack (expected 2)
distributed.core - ERROR - too many values to unpack (expected 2)
Traceback (most recent call last):
File "/opt/anaconda/lib/python3.5/site-packages/distributed/core.py", line 260, in handle_comm
result = yield result
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1015, in run
value = future.result()
File "/opt/anaconda/lib/python3.5/site-packages/tornado/concurrent.py", line 237, in result
raise_exc_info(self._exc_info)
File "<string>", line 3, in raise_exc_info
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1021, in run
yielded = self.gen.throw(*exc_info)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/worker.py", line 1040, in compute_stream
msgs = yield comm.read()
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1015, in run
value = future.result()
File "/opt/anaconda/lib/python3.5/site-packages/tornado/concurrent.py", line 237, in result
raise_exc_info(self._exc_info)
File "<string>", line 3, in raise_exc_info
File "/opt/anaconda/lib/python3.5/site-packages/tornado/gen.py", line 1024, in run
yielded = self.gen.send(value)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/comm/tcp.py", line 169, in read
msg = from_frames(frames, deserialize=self.deserialize)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/comm/utils.py", line 30, in from_frames
return protocol.loads(frames, deserialize=deserialize)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/core.py", line 121, in loads
value = _deserialize(head, fs)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/serialize.py", line 161, in deserialize
return f(header, frames)
File "/opt/anaconda/lib/python3.5/site-packages/distributed/protocol/numpy.py", line 98, in deserialize_numpy_ndarray
is_custom, dt = header['dtype']
ValueError: too many values to unpack (expected 2)
So looking at the version of ~/anaconda3/lib/python3.6/
site-packages/distributed/protocol/numpy.py,
def deserialize_numpy_ndarray(header, frames):
with log_errors():
if len(frames) > 1:
frames = merge_frames(header, frames)
if header.get('pickle'):
return pickle.loads(frames[0])
dt = header['dtype']
if isinstance(dt, tuple):
dt = list(dt)
x = np.ndarray(header['shape'], dtype=dt, buffer=frames[0],
strides=header['strides'])
x = stride_tricks.as_strided(x, strides=header['strides'])
return x
Compared to the version on the worker /opt/anaconda/lib/python3.5/
site-packages/distributed/protocol/numpy.py:
def deserialize_numpy_ndarray(header, frames):
with log_errors():
if len(frames) > 1:
frames = merge_frames(header, frames)
if header.get('pickle'):
return pickle.loads(frames[0])
is_custom, dt = header['dtype']
if is_custom:
dt = pickle.loads(dt)
else:
dt = np.dtype(dt)
x = np.ndarray(header['shape'], dtype=dt, buffer=frames[0],
strides=header['strides'])
return x
My local version of distributed is
Python 3.6.1 |Anaconda 4.4.0 (64-bit)| (default, May 11 2017, 13:09:58)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import distributed
>>> distributed.__version__
'1.16.3'
while on the work it is:
Python 3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:53:06)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import distributed
>>> distributed.__version__
'1.17.1'
I ran conda update distributed on my local machine. Updating:
distributed: 1.16.3-py36_0 --> 1.17.1-py36_0
And it now works!
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
<#96 (comment)>, or mute
the thread
<https://github.com/notifications/unsubscribe-auth/AASszJE5MC5LrS8-KQMXKiRkCzTgne-vks5sIl_HgaJpZM4OF53v>
.
|
|
|
This project is ancient and probably not supported any longer. I recommend looking through https://docs.dask.org/en/latest/setup/cloud.html In particular, many AWS users seem to like Dask on EMR. |
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
My python script hangs (inside
search.fit). When I stop it, I find that it's blocked on line 299,gotit = waiter.acquire(True, timeout). I'm not 100% sure what's happened, but I can run it happily from the remote jupyter notebook (over the workers). I wonder if it's a python/pickle compatibility issue. I've just upgraded from 14.04 to 16.04 on the local machine, while the remote workers etc are all on 14.04 (due to #38). The version of python is slightly different, and I wonder if that's causing the problem?On workers: Python 3.5.2 (ubuntu 14.04)
On local: Python 3.6.1 (ubuntu 16.04)
I don't know if that's the problem... I'll investigate more (I wonder how to get a bit more info from the workers??)
The text was updated successfully, but these errors were encountered: