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ibm-research
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dp-bench

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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.

Error code:   FeaturesError
Exception:    ValueError
Message:      Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/ibm-research/dp-bench@d7ad1b47c1a189a1940f05177522a821174a3670/dp_bench.json.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 186, in _generate_tables
                  raise ValueError(
              ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/ibm-research/dp-bench@d7ad1b47c1a189a1940f05177522a821174a3670/dp_bench.json.

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DP-Bench: A Benchmark for Evaluating Data Product Creation Systems

The DP-Bench (shortened from Data Product Benchmark) is the first of its kind benchmark.

It contains -

Description of specific business use cases, which we call data product requests (DPRs)
Corresponding data products for each of these DPRs, which consist of a subset of database tables and columns which are relevant to the DPR as well as derived columns which are produced from existing columns in the database
Provenance (in SQL) for the derived columns in the data products
Actual DB schemas from which these data products were created
Natural language questions corresponding to each business usecase
Annotated topics for the DPRs and annotated topics for the data products.

For details about this benchmark and to cite it please refer to the following paper

Title: DP-Bench: A Benchmark for Evaluating Data Product Creation Systems
Authors: Faisal Chowdhury, Sola Shirai, Sarthak Dash, Nandana Mihindukulasooriya, Horst Samulowitz

arxiv(2025)

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