Details
-
Bug
-
Status: Open
-
Major
-
Resolution: Unresolved
-
5.0.0
-
None
-
None
-
OS: Windows 10, CentOS 7
Description
We use pandas(with pyarrow engine) to write out parquet files and those outputs will be consumed by other applications such as Java apps using org.apache.parquet.hadoop.ParquetFileReader. We found that some empty dataframes would get incorrect schema for string columns in other applications. After some investigation, we narrow down the issue to the schema inference by pyarrow:
In [1]: import pandas as pd In [2]: df = pd.DataFrame([['a', 1, 1.0]], columns=['a', 'b', 'c']) In [3]: import pyarrow as pa In [4]: pa.Schema.from_pandas(df) Out[4]: a: string b: int64 c: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 562 In [5]: pa.Schema.from_pandas(df.head(0)) Out[5]: a: null b: int64 c: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 560 In [6]: pa._version_ Out[6]: '5.0.0'
As you can see, the column 'a' which should be string type if inferred as null type and is converted to int32 while writing to parquet files.
Is this an expected behavior? Or do we have any workaround for this issue? Could anyone take a look please. Thanks!