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https://issues.apache.org/jira/browse/ARROW-7087?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

François Blanchard updated ARROW-7087:
--------------------------------------
    Description: 
There is an unexpected behavior with the method 
*[write_to_dataset|https://github.com/apache/arrow/blob/10a3b716a5ca227c8d97e6f6b27976df14678263/python/pyarrow/parquet.py#L1373]*
 in *pyarrow/parquet.py*

When we write a table that contains metadata then metadata are replaced by 
pandas metadata. This happens only if we defined *partition_cols*.

 

To be more explicit here is an example code: 
{code:python}
from pyarrow.parquet import write_to_dataset
import pyarrow as pa
import pyarrow.parquet as pd

columnA = pa.array(['a', 'b', 'c'], type=pa.string())
columnB = pa.array([1, 1, 2], type=pa.int32())

# Build table from collumns
table = pa.Table.from_arrays([columnA, columnB], names=['columnA', 'columnB'], 
metadata={'data': 'test'})
print table.schema.metadata
"""
Metadata is set as expected

>> OrderedDict([('data', 'test')])
"""

# Write table in parquet format partitioned per columnB
write_to_dataset(table, '/path/to/test', partition_cols=['columnB'])

# Load data from parquet files
ds = pd.ParquetDataset('/path/to/test')
load_table = pq.read_table(ds.pieces[0].path)
print load_table.schema.metadata
"""
Metadata with the key `data` is missing


>> OrderedDict([('pandas', '{"creator": {"version": "0.14.1", "library": 
>> "pyarrow"}, "pandas_version": "0.22.0", "index_columns": [], "columns": 
>> [{"metadata": null, "field_name": "columnA", "name": "columnA", 
>> "numpy_type": "object", "pandas_type": "unicode"}], "column_indexes": []}')])
"""{code}
 
  
  

  was:
There is an unexpected behavior with the method 
*[write_to_dataset|https://github.com/apache/arrow/blob/10a3b716a5ca227c8d97e6f6b27976df14678263/python/pyarrow/parquet.py#L1373]*
 in *pyarrow/parquet.py*

When we write a table that contains metadata then metadata are replaced by 
pandas metadata. This happens only if we defined *partition_cols*.

 

To be more explicit here is an example code: 
{code:python}
from pyarrow.parquet import write_to_dataset
import pyarrow as pa
import pyarrow.parquet as pd

columnA = pa.array(['a', 'b', 'c'], type=pa.string())
columnB = pa.array([1, 1, 2], type=pa.int32())

# Build table from collumns
table = pa.Table.from_arrays([columnA, columnB], names=['columnA', 'columnB'], 
metadata={'data': 'test'})
print table.schema.metadata
"""
Metadata is set as expected

>> OrderedDict([('data', 'test')])
"""

# Write table in parquet format partitioned per columnB
write_to_dataset(table, '/path/to/test', partition_cols=['columnB'])

# Load data from parquet files
ds = pd.ParquetDataset('/path/to/test')
load_table = pq.read_table(ds.pieces[0].path)
print load_table.schema.metadata
"""
Metadata with the key `data` are missing


>> OrderedDict([('pandas', '{"creator": {"version": "0.14.1", "library": 
>> "pyarrow"}, "pandas_version": "0.22.0", "index_columns": [], "columns": 
>> [{"metadata": null, "field_name": "columnA", "name": "columnA", 
>> "numpy_type": "object", "pandas_type": "unicode"}], "column_indexes": []}')])
"""{code}
 
  
  


> [Pyarrow] Table Metadata disappear when we write a partitioned dataset
> ----------------------------------------------------------------------
>
>                 Key: ARROW-7087
>                 URL: https://issues.apache.org/jira/browse/ARROW-7087
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 0.14.1
>            Reporter: François Blanchard
>            Priority: Major
>
> There is an unexpected behavior with the method 
> *[write_to_dataset|https://github.com/apache/arrow/blob/10a3b716a5ca227c8d97e6f6b27976df14678263/python/pyarrow/parquet.py#L1373]*
>  in *pyarrow/parquet.py*
> When we write a table that contains metadata then metadata are replaced by 
> pandas metadata. This happens only if we defined *partition_cols*.
>  
> To be more explicit here is an example code: 
> {code:python}
> from pyarrow.parquet import write_to_dataset
> import pyarrow as pa
> import pyarrow.parquet as pd
> columnA = pa.array(['a', 'b', 'c'], type=pa.string())
> columnB = pa.array([1, 1, 2], type=pa.int32())
> # Build table from collumns
> table = pa.Table.from_arrays([columnA, columnB], names=['columnA', 
> 'columnB'], metadata={'data': 'test'})
> print table.schema.metadata
> """
> Metadata is set as expected
> >> OrderedDict([('data', 'test')])
> """
> # Write table in parquet format partitioned per columnB
> write_to_dataset(table, '/path/to/test', partition_cols=['columnB'])
> # Load data from parquet files
> ds = pd.ParquetDataset('/path/to/test')
> load_table = pq.read_table(ds.pieces[0].path)
> print load_table.schema.metadata
> """
> Metadata with the key `data` is missing
> >> OrderedDict([('pandas', '{"creator": {"version": "0.14.1", "library": 
> >> "pyarrow"}, "pandas_version": "0.22.0", "index_columns": [], "columns": 
> >> [{"metadata": null, "field_name": "columnA", "name": "columnA", 
> >> "numpy_type": "object", "pandas_type": "unicode"}], "column_indexes": 
> >> []}')])
> """{code}
>  
>   
>   



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