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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError Exception: CastError Message: Couldn't cast reference_datetime: string site_id: string datetime: timestamp[us, tz=UTC] family: string variable: string observation: double crps: double logs: double mean: double median: double sd: double quantile97.5: double quantile02.5: double quantile90: double quantile10: double to {'reference_datetime': Value(dtype='string', id=None), 'site_id': Value(dtype='string', id=None), 'datetime': Value(dtype='timestamp[us, tz=UTC]', id=None), 'family': Value(dtype='string', id=None), 'variable': Value(dtype='string', id=None), 'pubDate': Value(dtype='string', id=None), 'observation': Value(dtype='float64', id=None), 'crps': Value(dtype='float64', id=None), 'logs': Value(dtype='float64', id=None), 'mean': Value(dtype='float64', id=None), 'median': Value(dtype='float64', id=None), 'sd': Value(dtype='float64', id=None), 'quantile97.5': Value(dtype='float64', id=None), 'quantile02.5': Value(dtype='float64', id=None), 'quantile90': Value(dtype='float64', id=None), 'quantile10': Value(dtype='float64', id=None)} because column names don't match Traceback: Traceback (most recent call last): File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 263, in query pa_table = pa.concat_tables( File "pyarrow/table.pxi", line 5245, in pyarrow.lib.concat_tables File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: Schema at index 5 was different: reference_datetime: string site_id: string datetime: timestamp[us, tz=UTC] family: string variable: string pubDate: string observation: double crps: double logs: double mean: double median: double sd: double quantile97.5: double quantile02.5: double quantile90: double quantile10: double vs reference_datetime: string site_id: string datetime: timestamp[us, tz=UTC] family: string variable: string observation: double crps: double logs: double mean: double median: double sd: double quantile97.5: double quantile02.5: double quantile90: double quantile10: double During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 101, in get_rows_content pa_table = rows_index.query(offset=0, length=rows_max_number) File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 412, in query return self.parquet_index.query(offset=offset, length=length) File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 270, in query raise SchemaMismatchError("Parquet files have different schema.", err) libcommon.parquet_utils.SchemaMismatchError: ('Parquet files have different schema.', ArrowInvalid('Schema at index 5 was different: \nreference_datetime: string\nsite_id: string\ndatetime: timestamp[us, tz=UTC]\nfamily: string\nvariable: string\npubDate: string\nobservation: double\ncrps: double\nlogs: double\nmean: double\nmedian: double\nsd: double\nquantile97.5: double\nquantile02.5: double\nquantile90: double\nquantile10: double\nvs\nreference_datetime: string\nsite_id: string\ndatetime: timestamp[us, tz=UTC]\nfamily: string\nvariable: string\nobservation: double\ncrps: double\nlogs: double\nmean: double\nmedian: double\nsd: double\nquantile97.5: double\nquantile02.5: double\nquantile90: double\nquantile10: double')) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute compute_first_rows_from_parquet_response( File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 113, in compute_first_rows_from_parquet_response return create_first_rows_response( File "/src/libs/libcommon/src/libcommon/viewer_utils/rows.py", line 134, in create_first_rows_response rows_content = get_rows_content(rows_max_number) File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 108, in get_rows_content raise SplitParquetSchemaMismatchError( libcommon.exceptions.SplitParquetSchemaMismatchError: Split parquet files being processed have different schemas. Ensure all files have identical column names. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/utils.py", line 126, in get_rows_or_raise return get_rows( File "/src/services/worker/src/worker/utils.py", line 64, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/utils.py", line 103, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1388, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__ for key, pa_table in self.generate_tables_fn(**self.kwargs): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 94, in _generate_tables yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 74, in _cast_table pa_table = table_cast(pa_table, self.info.features.arrow_schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2194, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast reference_datetime: string site_id: string datetime: timestamp[us, tz=UTC] family: string variable: string observation: double crps: double logs: double mean: double median: double sd: double quantile97.5: double quantile02.5: double quantile90: double quantile10: double to {'reference_datetime': Value(dtype='string', id=None), 'site_id': Value(dtype='string', id=None), 'datetime': Value(dtype='timestamp[us, tz=UTC]', id=None), 'family': Value(dtype='string', id=None), 'variable': Value(dtype='string', id=None), 'pubDate': Value(dtype='string', id=None), 'observation': Value(dtype='float64', id=None), 'crps': Value(dtype='float64', id=None), 'logs': Value(dtype='float64', id=None), 'mean': Value(dtype='float64', id=None), 'median': Value(dtype='float64', id=None), 'sd': Value(dtype='float64', id=None), 'quantile97.5': Value(dtype='float64', id=None), 'quantile02.5': Value(dtype='float64', id=None), 'quantile90': Value(dtype='float64', id=None), 'quantile10': Value(dtype='float64', id=None)} because column names don't match
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Snapshot of the Ecological Forecasting Initiative NEON Forecasting Challenge
Includes probabilistic forecasts, observations, and skill scores across all submitted forecasts over 5 challenge themes.
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