Reputation: 12396
I have a HDF5 file that I would like to load into a list of Dask DataFrames. I have set this up using a loop following an abbreviated version of the Dask pipeline approach. Here is the code:
import pandas as pd
from dask import compute, delayed
import dask.dataframe as dd
import os, h5py
@delayed
def load(d,k):
ddf = dd.read_hdf(os.path.join(d,'Cleaned.h5'), key=k)
return ddf
if __name__ == '__main__':
d = 'C:\Users\User\FileD'
loaded = [load(d,'/DF'+str(i)) for i in range(1,10)]
ddf_list = compute(*loaded)
print(ddf_list[0].head(),ddf_list[0].compute().shape)
I get this error message:
C:\Python27\lib\site-packages\tables\group.py:1187: UserWarning: problems loading leaf ``/DF1/table``::
HDF5 error back trace
File "..\..\hdf5-1.8.18\src\H5Dio.c", line 173, in H5Dread
can't read data
File "..\..\hdf5-1.8.18\src\H5Dio.c", line 543, in H5D__read
can't initialize I/O info
File "..\..\hdf5-1.8.18\src\H5Dchunk.c", line 841, in H5D__chunk_io_init
unable to create file chunk selections
File "..\..\hdf5-1.8.18\src\H5Dchunk.c", line 1330, in H5D__create_chunk_file_map_hyper
can't insert chunk into skip list
File "..\..\hdf5-1.8.18\src\H5SL.c", line 1066, in H5SL_insert
can't create new skip list node
File "..\..\hdf5-1.8.18\src\H5SL.c", line 735, in H5SL_insert_common
can't insert duplicate key
End of HDF5 error back trace
Problems reading the array data.
The leaf will become an ``UnImplemented`` node.
% (self._g_join(childname), exc))
The message mentions a duplicate key. I iterated over the first 9 files to test out the code and, in the loop, I am using each iteration to assemble a different key that I use with dd.read_hdf
. Across all iterations, I'm keeping the filename is the same - only the key is being changed.
I need to use dd.concat(list,axis=0,...)
in order to vertically concatenate the contents of the file. My approach was to load them into a list first and then concatenate them.
I have installed PyTables and h5Py and have Dask version 0.14.3+2
.
With Pandas 0.20.1
, I seem to get this to work:
for i in range(1,10):
hdf = pd.HDFStore(os.path.join(d,'Cleaned.h5'),mode='r')
df = hdf.get('/DF{}' .format(i))
print df.shape
hdf.close()
Is there a way I can load this HDF5 file into a list of Dask DataFrames? Or is there another approach to vertically concatenate them together?
Upvotes: 2
Views: 2685
Reputation: 57251
Dask.dataframe is already lazy, so there is no need to use dask.delayed to make it lazier. You can just call dd.read_hdf
repeatedly:
ddfs = [dd.read_hdf(os.path.join(d,'Cleaned.h5'), key=k)
for k in keys]
ddf = dd.concat(ddfs)
Upvotes: 5