Datasets:

---

Siilhouette

/

bcp-cache

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
corpus_fingerprint: string
num_documents: int64
doc_ids: string
completed_rows: int64
metadata: struct<corpus_fingerprint: string, pooling: string, normalize: bool, torch_dtype: string, storage_dt (... 35 chars omitted)
  child 0, corpus_fingerprint: string
  child 1, pooling: string
  child 2, normalize: bool
  child 3, torch_dtype: string
  child 4, storage_dtype: string
  child 5, doc_max_length: int64
complete: bool
encoding_fingerprint_fields: list<item: string>
  child 0, item: string
embedding_dim: int64
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 493
to
{'encoding_fingerprint_fields': List(Value('string')), 'metadata': {'corpus_fingerprint': Value('string'), 'pooling': Value('string'), 'normalize': Value('bool'), 'torch_dtype': Value('string'), 'storage_dtype': Value('string'), 'doc_max_length': Value('int64')}, 'embedding_dim': Value('int64'), 'completed_rows': Value('int64'), 'complete': Value('bool')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 339, in _generate_tables
                  yield Key(shard_idx, 0), self._cast_table(pa_table)
                                           ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              corpus_fingerprint: string
              num_documents: int64
              doc_ids: string
              completed_rows: int64
              metadata: struct<corpus_fingerprint: string, pooling: string, normalize: bool, torch_dtype: string, storage_dt (... 35 chars omitted)
                child 0, corpus_fingerprint: string
                child 1, pooling: string
                child 2, normalize: bool
                child 3, torch_dtype: string
                child 4, storage_dtype: string
                child 5, doc_max_length: int64
              complete: bool
              encoding_fingerprint_fields: list<item: string>
                child 0, item: string
              embedding_dim: int64
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 493
              to
              {'encoding_fingerprint_fields': List(Value('string')), 'metadata': {'corpus_fingerprint': Value('string'), 'pooling': Value('string'), 'normalize': Value('bool'), 'torch_dtype': Value('string'), 'storage_dtype': Value('string'), 'doc_max_length': Value('int64')}, 'embedding_dim': Value('int64'), 'completed_rows': Value('int64'), 'complete': Value('bool')}
              because column names don't match