[jira] [Created] (ARROW-7782) Losing index information when using write_to_dataset with partition_cols
Ludwik Bielczynski created ARROW-7782:
-
Summary: Losing index information when using write_to_dataset with
partition_cols
Key: ARROW-7782
URL: https://issues.apache.org/jira/browse/ARROW-7782
Project: Apache Arrow
Issue Type: Bug
Environment: pyarrow==0.15.1
Reporter: Ludwik Bielczynski
One cannot save the index when using {{pyarrow.parquet.write_to_dataset()}}
with given partition_cols arguments. Here I have created a minimal example
which shows the issue:
{code:java}
from pathlib import Path
import pandas as pd
from pyarrow import Table
from pyarrow.parquet import write_to_dataset
path = Path('/home/ludwik/Documents/YieldPlanet/research/trials')
file_name = 'trial_pq.parquet'
df = pd.DataFrame({"A": [1, 2, 3],
"B": ['a', 'a', 'b']
},
index=pd.Index(['a', 'b', 'c'], name='idx'))
table = Table.from_pandas(df)
write_to_dataset(table, str(path / file_name), partition_cols=['B'],
partition_filename_cb=None, filesystem=None)
{code}
The issue is rather important for pandas and dask users.
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[jira] [Created] (ARROW-1398) No support reading columns of type decimal(19,4)
Ludwik Bielczynski created ARROW-1398:
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Summary: No support reading columns of type decimal(19,4)
Key: ARROW-1398
URL: https://issues.apache.org/jira/browse/ARROW-1398
Project: Apache Arrow
Issue Type: Bug
Components: Python
Affects Versions: 0.6.0
Environment: Ubuntu 16.04, Python 3.6
Reporter: Ludwik Bielczynski
I have a localy saved parquet database created in spark from querrying an SQL
database. When I run:
{code:python}
import pyarrow.parquet as pq
path = "path/to/parquet/dataset"
dataset = pq.ParquetDataset(path)
dataset.read()
{code}
an error indicating that there is no support for reading columns of type
decimal(19,4). It's quite a common type used in SQL databases and I saw in the
source code that there is an implementation for decimals. I'm stuck trying to
figuring out a solution. Is there a walk around (conversion of decimals to
integers during reading)?
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