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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'customer_id'}) and 1 missing columns ({'product_id'}).

This happened while the csv dataset builder was generating data using

zip://rel-amazon__user-churn.csv::hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235109Z/preds-classification.zip, ['hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235109Z/preds-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235109Z/preds-regression.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235124Z/rt-j-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235124Z/rt-j-regression.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235141Z/preds-rt-plurel-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235141Z/preds-rt-plurel-regression.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235156Z/rt-plurel-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235156Z/rt-plurel-regression.zip']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 784, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
                  pa_table = table_cast(pa_table, self._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
              customer_id: int64
              timestamp: string
              churn: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 629
              to
              {'product_id': Value('int64'), 'timestamp': Value('string'), 'churn': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'customer_id'}) and 1 missing columns ({'product_id'}).
              
              This happened while the csv dataset builder was generating data using
              
              zip://rel-amazon__user-churn.csv::hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235109Z/preds-classification.zip, ['hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235109Z/preds-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235109Z/preds-regression.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235124Z/rt-j-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235124Z/rt-j-regression.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235141Z/preds-rt-plurel-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235141Z/preds-rt-plurel-regression.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235156Z/rt-plurel-classification.zip', 'hf://datasets/rishabh-ranjan/relbench-submissions@60523c8bf73a4de8d57403227d4a87c6e3ae61bf/20261004T235156Z/rt-plurel-regression.zip']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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product_id
int64
timestamp
string
churn
float64
487,515
2016-01-01
0.333015
42,955
2016-01-01
0.344168
33,626
2016-01-01
0.566671
413,030
2016-01-01
0.344361
14,589
2016-01-01
0.331498
341,379
2016-01-01
0.343452
487,771
2016-01-01
0.318432
26,284
2016-01-01
0.333503
483,539
2016-01-01
0.341747
86,082
2016-01-01
0.414425
174,933
2016-01-01
0.491544
10,025
2016-01-01
0.577242
484,781
2016-01-01
0.343672
166,873
2016-01-01
0.346016
104,759
2016-01-01
0.54961
396,037
2016-01-01
0.429364
179,273
2016-01-01
0.463839
371,426
2016-01-01
0.333178
96,333
2016-01-01
0.497717
401,922
2016-01-01
0.450113
162,864
2016-01-01
0.420109
85,686
2016-01-01
0.362377
13,060
2016-01-01
0.561621
386,601
2016-01-01
0.594316
438,224
2016-01-01
0.360799
102,678
2016-01-01
0.347703
504,170
2016-01-01
0.347316
155,836
2016-01-01
0.644337
354,900
2016-01-01
0.451258
444,986
2016-01-01
0.322686
25,967
2016-01-01
0.339937
148,772
2016-01-01
0.53312
171,231
2016-01-01
0.459961
34,383
2016-01-01
0.429773
51,144
2016-01-01
0.646851
4,668
2016-01-01
0.357175
155,639
2016-01-01
0.641956
450,922
2016-01-01
0.37981
300,435
2016-01-01
0.465881
88,072
2016-01-01
0.502672
202,736
2016-01-01
0.390272
205,923
2016-01-01
0.577665
42,353
2016-01-01
0.386763
101,351
2016-01-01
0.377713
350,686
2016-01-01
0.365372
219,033
2016-01-01
0.555247
481,916
2016-01-01
0.515011
258,657
2016-01-01
0.332473
6,044
2016-01-01
0.327399
159,064
2016-01-01
0.353763
413,157
2016-01-01
0.359814
17,439
2016-01-01
0.393356
179,435
2016-01-01
0.35209
439,945
2016-01-01
0.458991
461,025
2016-01-01
0.58818
5,538
2016-01-01
0.470275
354,863
2016-01-01
0.353149
326,330
2016-01-01
0.332961
134,428
2016-01-01
0.495203
412,866
2016-01-01
0.376996
102,750
2016-01-01
0.499787
258,911
2016-01-01
0.372648
81,084
2016-01-01
0.332636
119,882
2016-01-01
0.607547
28,804
2016-01-01
0.332527
208,073
2016-01-01
0.418519
461,852
2016-01-01
0.589273
306,349
2016-01-01
0.316739
212,316
2016-01-01
0.41696
79,361
2016-01-01
0.458913
224,599
2016-01-01
0.447881
241,889
2016-01-01
0.474953
104,342
2016-01-01
0.593727
353,782
2016-01-01
0.355551
102,381
2016-01-01
0.449672
33,586
2016-01-01
0.348645
270,015
2016-01-01
0.652961
80,629
2016-01-01
0.334589
227,215
2016-01-01
0.483126
104,976
2016-01-01
0.472037
471,078
2016-01-01
0.469881
438,641
2016-01-01
0.348313
480,940
2016-01-01
0.486413
105,000
2016-01-01
0.493557
236,960
2016-01-01
0.356279
107,240
2016-01-01
0.323327
438,939
2016-01-01
0.372163
114,413
2016-01-01
0.37088
320,935
2016-01-01
0.451893
14,298
2016-01-01
0.419239
215,134
2016-01-01
0.394405
426,384
2016-01-01
0.373562
14,163
2016-01-01
0.340156
389,859
2016-01-01
0.456315
337,821
2016-01-01
0.390272
59,002
2016-01-01
0.334807
337,867
2016-01-01
0.354014
399,070
2016-01-01
0.579162
273,607
2016-01-01
0.4924
351,176
2016-01-01
0.46014
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