Datasets:

---

Q-RAG

/

fullwiki-retrieval-dateset

Like 0

Follow

Q-RAG 7

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
corpus: struct<mtime_ns: int64, path: string, size_bytes: int64>
  child 0, mtime_ns: int64
  child 1, path: string
  child 2, size_bytes: int64
dtype: string
last_offset: int64
rows: int64
schema_version: int64
shape: list<item: int64>
  child 0, item: int64
created_at: string
updated_at: string
embedding_complete: bool
completed_rows: int64
build_identity: struct<corpus: struct<require_id: bool, sha256: string, size_bytes: int64, validate_id_matches_row:  (... 225 chars omitted)
  child 0, corpus: struct<require_id: bool, sha256: string, size_bytes: int64, validate_id_matches_row: bool>
      child 0, require_id: bool
      child 1, sha256: string
      child 2, size_bytes: int64
      child 3, validate_id_matches_row: bool
  child 1, encoder: struct<api: string, max_length: int64, model: string, model_dtype: string, normalization: string, re (... 25 chars omitted)
      child 0, api: string
      child 1, max_length: int64
      child 2, model: string
      child 3, model_dtype: string
      child 4, normalization: string
      child 5, requested_revision: string
  child 2, schema_version: int64
  child 3, shards: struct<cache_dtype: string, rows_per_shard: int64>
      child 0, cache_dtype: string
      child 1, rows_per_shard: int64
truncation_estimate: struct<estimated_truncation_rate: double, max_observed_tokens: int64, sampled_passages: int64, would (... 17 chars omitted)
  child 0, estimated_truncation_rate: double
  child 1, max_observed_tokens: int64
  child 2, sampled_passages: int64
  child 3, would_truncate: int64
dimension: int64
resolved_model_revision: string
total_rows: int64
to
{'build_identity': {'corpus': {'require_id': Value('bool'), 'sha256': Value('string'), 'size_bytes': Value('int64'), 'validate_id_matches_row': Value('bool')}, 'encoder': {'api': Value('string'), 'max_length': Value('int64'), 'model': Value('string'), 'model_dtype': Value('string'), 'normalization': Value('string'), 'requested_revision': Value('string')}, 'schema_version': Value('int64'), 'shards': {'cache_dtype': Value('string'), 'rows_per_shard': Value('int64')}}, 'completed_rows': Value('int64'), 'created_at': Value('string'), 'dimension': Value('int64'), 'embedding_complete': Value('bool'), 'resolved_model_revision': Value('string'), 'total_rows': Value('int64'), 'truncation_estimate': {'estimated_truncation_rate': Value('float64'), 'max_observed_tokens': Value('int64'), 'sampled_passages': Value('int64'), 'would_truncate': Value('int64')}, 'updated_at': Value('string')}
because column names don't match
Traceback:    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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                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: struct<mtime_ns: int64, path: string, size_bytes: int64>
                child 0, mtime_ns: int64
                child 1, path: string
                child 2, size_bytes: int64
              dtype: string
              last_offset: int64
              rows: int64
              schema_version: int64
              shape: list<item: int64>
                child 0, item: int64
              created_at: string
              updated_at: string
              embedding_complete: bool
              completed_rows: int64
              build_identity: struct<corpus: struct<require_id: bool, sha256: string, size_bytes: int64, validate_id_matches_row:  (... 225 chars omitted)
                child 0, corpus: struct<require_id: bool, sha256: string, size_bytes: int64, validate_id_matches_row: bool>
                    child 0, require_id: bool
                    child 1, sha256: string
                    child 2, size_bytes: int64
                    child 3, validate_id_matches_row: bool
                child 1, encoder: struct<api: string, max_length: int64, model: string, model_dtype: string, normalization: string, re (... 25 chars omitted)
                    child 0, api: string
                    child 1, max_length: int64
                    child 2, model: string
                    child 3, model_dtype: string
                    child 4, normalization: string
                    child 5, requested_revision: string
                child 2, schema_version: int64
                child 3, shards: struct<cache_dtype: string, rows_per_shard: int64>
                    child 0, cache_dtype: string
                    child 1, rows_per_shard: int64
              truncation_estimate: struct<estimated_truncation_rate: double, max_observed_tokens: int64, sampled_passages: int64, would (... 17 chars omitted)
                child 0, estimated_truncation_rate: double
                child 1, max_observed_tokens: int64
                child 2, sampled_passages: int64
                child 3, would_truncate: int64
              dimension: int64
              resolved_model_revision: string
              total_rows: int64
              to
              {'build_identity': {'corpus': {'require_id': Value('bool'), 'sha256': Value('string'), 'size_bytes': Value('int64'), 'validate_id_matches_row': Value('bool')}, 'encoder': {'api': Value('string'), 'max_length': Value('int64'), 'model': Value('string'), 'model_dtype': Value('string'), 'normalization': Value('string'), 'requested_revision': Value('string')}, 'schema_version': Value('int64'), 'shards': {'cache_dtype': Value('string'), 'rows_per_shard': Value('int64')}}, 'completed_rows': Value('int64'), 'created_at': Value('string'), 'dimension': Value('int64'), 'embedding_complete': Value('bool'), 'resolved_model_revision': Value('string'), 'total_rows': Value('int64'), 'truncation_estimate': {'estimated_truncation_rate': Value('float64'), 'max_observed_tokens': Value('int64'), 'sampled_passages': Value('int64'), 'would_truncate': Value('int64')}, 'updated_at': Value('string')}
              because column names don't match