Datasets:
ArrowInvalid issue when saving to disk
Hi!
Thank you very much for the dataset!
I'm attempting to save the dataset to disk using the following,
from datasets import load_dataset
ds = load_dataset("biglam/blbooks-parquet")
for k in ds.keys():
ds[k].to_json(
f"/data/blbooks/blbooks_{k}.jsonl",
batch_size=128,
force_ascii=False,
)
I've encountered this exception at the saving to disk stage
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/users/nus/rng/.conda/envs/peft-38/lib/python3.8/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/home/users/nus/rng/.conda/envs/peft-38/lib/python3.8/site-packages/datasets/io/json.py", line 123, in _batch_json
json_str = batch.to_pandas().to_json(path_or_buf=None, orient=orient, lines=lines, **to_json_kwargs)
File "pyarrow/array.pxi", line 837, in pyarrow.lib._PandasConvertible.to_pandas
File "pyarrow/table.pxi", line 4114, in pyarrow.lib.Table._to_pandas
File "/home/users/nus/rng/.local/lib/python3.8/site-packages/pyarrow/pandas_compat.py", line 820, in table_to_blockmanager
blocks = _table_to_blocks(options, table, categories, ext_columns_dtypes)
File "/home/users/nus/rng/.local/lib/python3.8/site-packages/pyarrow/pandas_compat.py", line 1168, in _table_to_blocks
result = pa.lib.table_to_blocks(options, block_table, categories,
File "pyarrow/table.pxi", line 2771, in pyarrow.lib.table_to_blocks
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Casting from timestamp[s] to timestamp[ns] would result in out of bounds timestamp: -9751017600
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "download_dataset.py", line 75, in <module>
download()
File "download_dataset.py", line 66, in download
ds[k].to_json(
File "/home/users/nus/rng/.conda/envs/peft-38/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 4861, in to_json
return JsonDatasetWriter(self, path_or_buf, batch_size=batch_size, num_proc=num_proc, **to_json_kwargs).write()
File "/home/users/nus/rng/.conda/envs/peft-38/lib/python3.8/site-packages/datasets/io/json.py", line 105, in write
written = self._write(file_obj=buffer, orient=orient, lines=lines, **self.to_json_kwargs)
File "/home/users/nus/rng/.conda/envs/peft-38/lib/python3.8/site-packages/datasets/io/json.py", line 152, in _write
for json_str in hf_tqdm(
File "/home/users/nus/rng/.local/lib/python3.8/site-packages/tqdm/std.py", line 1178, in __iter__
for obj in iterable:
File "/home/users/nus/rng/.conda/envs/peft-38/lib/python3.8/multiprocessing/pool.py", line 868, in next
raise value
pyarrow.lib.ArrowInvalid: Casting from timestamp[s] to timestamp[ns] would result in out of bounds timestamp: -9751017600
Is there a way to bypass this error?
Thank you!
Hi
@RaymondAISG
, according to the pandas documentation, to_json() accepts a date_unit argument
You could try setting that to 's' and see if that helps
If what
@shamikbose89
suggested doesn't work and you don't mind a slightly hacky approach you could also cast the date to a string. That should make it possible to save to JSON i.e.
from datasets import load_dataset
from datasets import Value
ds = load_dataset("biglam/blbooks-parquet")
ds = ds.cast_column("date", Value("string"))
for k in ds.keys():
ds[k].to_json(
f"/data/blbooks/blbooks_{k}.jsonl",
batch_size=128,
force_ascii=False,
)
Hi
@shamikbose89
,
Thank you for your reply! I've tried adding the date_unit argument to to_json(), unfortunately it still returns the same error.
Hi
@davanstrien
,
Thank you for your reply! Your solution works and I'm able to save the dataset now, thank you for the dataset again.