mishbahr opened a new issue #11967:
URL: https://github.com/apache/arrow/issues/11967
I'm writing some DataFrame to binary parquet format with one or more entire
null object columns.
If I then load the parquet dataset with `use_legacy_dataset=False`
```python
parquet_dataset = pq.ParquetDataset(root_path, use_legacy_dataset=False,
**kwargs)
type(parquet)
pyarrow.parquet._ParquetDatasetV2
```
It returns an `_ParquetDatasetV2` instance and when I check the schema.
```python
type(parquet_dataset.schema)
pyarrow.lib.Schema
```
If I load the same file but with `use_legacy_dataset=True`
```python
parquet_dataset2 = pq.ParquetDataset(root_path, use_legacy_dataset=True,
**kwargs)
```
The schema for the file is an instance of `ParquetSchema`
```python
type(parquet_dataset2.schema)
pyarrow._parquet.ParquetSchema
```
This is as I would expect and I'm aware that I can get the "arrow schema"
like this.
```python
arrow_schema = parquet_dataset2.schema.to_arrow_schema()
type(arrow_schema)
pyarrow.lib.Schema
```
i.e same format as when I use `use_legacy_dataset=False`
For an instance of `ParquetSchema`, I can get details of any column. e.g
```python
parquet_dataset2.schema[13]
<ParquetColumnSchema>
name: col13
path: col13
max_definition_level: 1
max_repetition_level: 0
physical_type: INT96
logical_type: None
converted_type (legacy): NONE
```
Here the "physical_type" for this column is INT96.
```python
parquet.schema[13].physical_type
'INT32'
```
For an instance of `pyarrow.lib.Schema`, if I get the "data type" for the
same column.
```python
parquet_dataset.schema.field("col13").type
DataType(null)
```
i.e with no information about what the "data type" is supposed to be.
This information is available in the Parquet file. But how do I access it?
Is there way to convert instance of `pyarrow.lib.Schema` ->
`pyarrow._parquet.ParquetSchema`?
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