dask 在 jupyterlab 上 运行 时存储文件在哪里
Where does dask store files while running on juputerlab
我 运行 正在使用 jupyterlab。我正在尝试在存储我的 python 文件的主目录中保存一些文件,并且它是 运行 正确但我无法找到我的文件保存位置。所以我在主目录中创建了一个名为 output 的文件夹以在其中保存文件,但是当我在其中保存文件时出现以下错误:
PermissionError: [Errno 13] Permission denied: b'/home/jovyan/Output/20190101_0200'
这是我的尝试:
from dask_gateway import Gateway
gateway = Gateway(
address="http://traefik-pangeo-dask-gateway/services/dask-gateway",
public_address="https://pangeo.aer-gitlab.com/services/dask-gateway",
auth="jupyterhub",
)
options = gateway.cluster_options()
options
cluster = gateway.new_cluster(
cluster_options=options,
)
cluster.adapt(minimum=10, maximum=50)
client = cluster.get_client()
cluster
client
def get_turb(file, name):
d=[name[0:4],name[4:6],name[6:8],name[9:11],name[11:13]]
f_zip = gzip.decompress(file)
yr=d[0]
mo=d[1]
da=d[2]
hr=d[3]
mn=d[4]
fs = s3fs.S3FileSystem(anon=True)
period = pd.Period(str(yr)+str('-')+str(mo)+str('-')+str(da), freq='D')
# period.dayofyear
dy=period.dayofyear
cc=[7,8,9,10,11,12,13,14,15,16] #look at the IR channels only for now
dat = xr.open_dataset(f_zip)
dd=dat[['recNum','trackLat','trackLon','altitude','maxEDR']]
dd=dd.to_dataframe()
dd = dd.sort_values(by=['maxEDR'])
dd = dd.dropna()
dd['num'] = np.arange(len(dd))
dd.to_csv('Output/edr.csv') <----- Saving the file
edr_files = []
for i in range(2):
print(names[i])
s3_ds = dask.delayed(get_turb)(filedata[i], names[i])
edr_files.append(s3_ds)
edr_files = dask.compute(*edr_files)
请让我知道我做错了什么或可能的解决方案。
而且当我尝试使用以下代码直接将文件保存在 S3 存储桶上时:
s3.Bucket('temp').upload_file(file_name+'.zip', file_name+'.zip')
它抛出了这个错误:
distributed.protocol.pickle - INFO - Failed to serialize <function get_temp at 0x7f20a9cb8550>. Exception: cannot pickle '_thread.lock' object
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
/srv/conda/envs/notebook/lib/python3.8/site-packages/distributed/worker.py in dumps_function(func)
3319 with _cache_lock:
-> 3320 result = cache_dumps[func]
3321 except KeyError:
/srv/conda/envs/notebook/lib/python3.8/site-packages/distributed/utils.py in __getitem__(self, key)
1572 def __getitem__(self, key):
-> 1573 value = super().__getitem__(key)
1574 self.data.move_to_end(key)
/srv/conda/envs/notebook/lib/python3.8/collections/__init__.py in __getitem__(self, key)
1009 return self.__class__.__missing__(self, key)
-> 1010 raise KeyError(key)
1011 def __setitem__(self, key, item): self.data[key] = item
KeyError: <function get_temp at 0x7f20a9cb8550>
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
/srv/conda/envs/notebook/lib/python3.8/site-packages/distributed/protocol/pickle.py in dumps(x, buffer_callback, protocol)
52 buffers.clear()
---> 53 result = cloudpickle.dumps(x, **dump_kwargs)
54 elif not _always_use_pickle_for(x) and b"__main__" in result:
/srv/conda/envs/notebook/lib/python3.8/site-packages/cloudpickle/cloudpickle_fast.py in dumps(obj, protocol, buffer_callback)
72 )
---> 73 cp.dump(obj)
74 return file.getvalue()
/srv/conda/envs/notebook/lib/python3.8/site-packages/cloudpickle/cloudpickle_fast.py in dump(self, obj)
562 try:
--> 563 return Pickler.dump(self, obj)
564 except RuntimeError as e:
TypeError: cannot pickle '_thread.lock' object
您似乎 运行 dask 和 jupyterlab 在 docker 中?
也许你应该添加一些标志,比如 fellowing:
--user root \
-v new-longhorn-volume:/home/jovyan \
-e CHOWN_HOME=yes \
-e CHOWN_HOME_OPTS='-R' \
尝试使用 s3fs 而不是 boto3 在 S3 上上传文件。这可能有用。
我 运行 正在使用 jupyterlab。我正在尝试在存储我的 python 文件的主目录中保存一些文件,并且它是 运行 正确但我无法找到我的文件保存位置。所以我在主目录中创建了一个名为 output 的文件夹以在其中保存文件,但是当我在其中保存文件时出现以下错误:
PermissionError: [Errno 13] Permission denied: b'/home/jovyan/Output/20190101_0200'
这是我的尝试:
from dask_gateway import Gateway
gateway = Gateway(
address="http://traefik-pangeo-dask-gateway/services/dask-gateway",
public_address="https://pangeo.aer-gitlab.com/services/dask-gateway",
auth="jupyterhub",
)
options = gateway.cluster_options()
options
cluster = gateway.new_cluster(
cluster_options=options,
)
cluster.adapt(minimum=10, maximum=50)
client = cluster.get_client()
cluster
client
def get_turb(file, name):
d=[name[0:4],name[4:6],name[6:8],name[9:11],name[11:13]]
f_zip = gzip.decompress(file)
yr=d[0]
mo=d[1]
da=d[2]
hr=d[3]
mn=d[4]
fs = s3fs.S3FileSystem(anon=True)
period = pd.Period(str(yr)+str('-')+str(mo)+str('-')+str(da), freq='D')
# period.dayofyear
dy=period.dayofyear
cc=[7,8,9,10,11,12,13,14,15,16] #look at the IR channels only for now
dat = xr.open_dataset(f_zip)
dd=dat[['recNum','trackLat','trackLon','altitude','maxEDR']]
dd=dd.to_dataframe()
dd = dd.sort_values(by=['maxEDR'])
dd = dd.dropna()
dd['num'] = np.arange(len(dd))
dd.to_csv('Output/edr.csv') <----- Saving the file
edr_files = []
for i in range(2):
print(names[i])
s3_ds = dask.delayed(get_turb)(filedata[i], names[i])
edr_files.append(s3_ds)
edr_files = dask.compute(*edr_files)
请让我知道我做错了什么或可能的解决方案。
而且当我尝试使用以下代码直接将文件保存在 S3 存储桶上时:
s3.Bucket('temp').upload_file(file_name+'.zip', file_name+'.zip')
它抛出了这个错误:
distributed.protocol.pickle - INFO - Failed to serialize <function get_temp at 0x7f20a9cb8550>. Exception: cannot pickle '_thread.lock' object
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
/srv/conda/envs/notebook/lib/python3.8/site-packages/distributed/worker.py in dumps_function(func)
3319 with _cache_lock:
-> 3320 result = cache_dumps[func]
3321 except KeyError:
/srv/conda/envs/notebook/lib/python3.8/site-packages/distributed/utils.py in __getitem__(self, key)
1572 def __getitem__(self, key):
-> 1573 value = super().__getitem__(key)
1574 self.data.move_to_end(key)
/srv/conda/envs/notebook/lib/python3.8/collections/__init__.py in __getitem__(self, key)
1009 return self.__class__.__missing__(self, key)
-> 1010 raise KeyError(key)
1011 def __setitem__(self, key, item): self.data[key] = item
KeyError: <function get_temp at 0x7f20a9cb8550>
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
/srv/conda/envs/notebook/lib/python3.8/site-packages/distributed/protocol/pickle.py in dumps(x, buffer_callback, protocol)
52 buffers.clear()
---> 53 result = cloudpickle.dumps(x, **dump_kwargs)
54 elif not _always_use_pickle_for(x) and b"__main__" in result:
/srv/conda/envs/notebook/lib/python3.8/site-packages/cloudpickle/cloudpickle_fast.py in dumps(obj, protocol, buffer_callback)
72 )
---> 73 cp.dump(obj)
74 return file.getvalue()
/srv/conda/envs/notebook/lib/python3.8/site-packages/cloudpickle/cloudpickle_fast.py in dump(self, obj)
562 try:
--> 563 return Pickler.dump(self, obj)
564 except RuntimeError as e:
TypeError: cannot pickle '_thread.lock' object
您似乎 运行 dask 和 jupyterlab 在 docker 中?
也许你应该添加一些标志,比如 fellowing:
--user root \
-v new-longhorn-volume:/home/jovyan \
-e CHOWN_HOME=yes \
-e CHOWN_HOME_OPTS='-R' \
尝试使用 s3fs 而不是 boto3 在 S3 上上传文件。这可能有用。