do-me commented on issue #14229:
URL: https://github.com/apache/arrow/issues/14229#issuecomment-1826259855
Same here. I'm trying to load a 6GB parquet file with 3 cols two string cols
and one with embeddings (array) in pandas with
```python
df = pd.read_parquet("test.parquet")
```
```
File size in bytes: 6207538015 bytes
File size in kilobytes: 6062048.84 KB
```
Tried with pandas 2.0.3 and latest 2.1.3 on Windows (32Gb RAM) and Ubuntu
(128Gb RAM):
```
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
File <timed exec>:4
File ~/anaconda3/lib/python3.11/site-packages/pandas/io/parquet.py:509, in
read_parquet(path, engine, columns, storage_options, use_nullable_dtypes,
dtype_backend, **kwargs)
506 use_nullable_dtypes = False
507 check_dtype_backend(dtype_backend)
--> 509 return impl.read(
510 path,
511 columns=columns,
512 storage_options=storage_options,
513 use_nullable_dtypes=use_nullable_dtypes,
514 dtype_backend=dtype_backend,
515 **kwargs,
516 )
File ~/anaconda3/lib/python3.11/site-packages/pandas/io/parquet.py:227, in
PyArrowImpl.read(self, path, columns, use_nullable_dtypes, dtype_backend,
storage_options, **kwargs)
220 path_or_handle, handles, kwargs["filesystem"] = _get_path_or_handle(
221 path,
222 kwargs.pop("filesystem", None),
223 storage_options=storage_options,
224 mode="rb",
225 )
226 try:
--> 227 pa_table = self.api.parquet.read_table(
228 path_or_handle, columns=columns, **kwargs
229 )
230 result = pa_table.to_pandas(**to_pandas_kwargs)
232 if manager == "array":
File ~/anaconda3/lib/python3.11/site-packages/pyarrow/parquet/core.py:2973,
in read_table(source, columns, use_threads, metadata, schema,
use_pandas_metadata, read_dictionary, memory_map, buffer_size, partitioning,
filesystem, filters, use_legacy_dataset, ignore_prefixes, pre_buffer,
coerce_int96_timestamp_unit, decryption_properties, thrift_string_size_limit,
thrift_container_size_limit)
2962 # TODO test that source is not a directory or a list
2963 dataset = ParquetFile(
2964 source, metadata=metadata,
read_dictionary=read_dictionary,
2965 memory_map=memory_map, buffer_size=buffer_size,
(...)
2970 thrift_container_size_limit=thrift_container_size_limit,
2971 )
-> 2973 return dataset.read(columns=columns, use_threads=use_threads,
2974 use_pandas_metadata=use_pandas_metadata)
2976 warnings.warn(
2977 "Passing 'use_legacy_dataset=True' to get the legacy behaviour
is "
2978 "deprecated as of pyarrow 8.0.0, and the legacy implementation
will "
2979 "be removed in a future version.",
2980 FutureWarning, stacklevel=2)
2982 if ignore_prefixes is not None:
File ~/anaconda3/lib/python3.11/site-packages/pyarrow/parquet/core.py:2601,
in _ParquetDatasetV2.read(self, columns, use_threads, use_pandas_metadata)
2593 index_columns = [
2594 col for col in _get_pandas_index_columns(metadata)
2595 if not isinstance(col, dict)
2596 ]
2597 columns = (
2598 list(columns) + list(set(index_columns) - set(columns))
2599 )
-> 2601 table = self._dataset.to_table(
2602 columns=columns, filter=self._filter_expression,
2603 use_threads=use_threads
2604 )
2606 # if use_pandas_metadata, restore the pandas metadata (which gets
2607 # lost if doing a specific `columns` selection in to_table)
2608 if use_pandas_metadata:
File ~/anaconda3/lib/python3.11/site-packages/pyarrow/_dataset.pyx:369, in
pyarrow._dataset.Dataset.to_table()
File ~/anaconda3/lib/python3.11/site-packages/pyarrow/_dataset.pyx:2818, in
pyarrow._dataset.Scanner.to_table()
File ~/anaconda3/lib/python3.11/site-packages/pyarrow/error.pxi:144, in
pyarrow.lib.pyarrow_internal_check_status()
File ~/anaconda3/lib/python3.11/site-packages/pyarrow/error.pxi:115, in
pyarrow.lib.check_status()
OSError: List index overflow.
```
The weird thing is that this that I processed 20 of these files with
different file sizes and even bigger ones than this one (with 7GB) worked.
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