[jira] [Commented] (ARROW-6339) [Python][C++] Rowgroup statistics for pd.NaT array ill defined

["Florian Jetter (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-6339?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16914949#comment-16914949 ] 

Florian Jetter commented on ARROW-6339:
---------------------------------------

The same is true for other null values, e.g.
{code:python}
df = pd.DataFrame({
    "t": pd.Series([pd.NaT], dtype="datetime64[ns]"),
    "f": [pd.np.nan],
    "o": [None],
})
{code}

The statistics are _mostly_ initialised to zero but not all the times.

> [Python][C++] Rowgroup statistics for pd.NaT array ill defined
> --------------------------------------------------------------
>
>                 Key: ARROW-6339
>                 URL: https://issues.apache.org/jira/browse/ARROW-6339
>             Project: Apache Arrow
>          Issue Type: Bug
>    Affects Versions: 0.14.1
>            Reporter: Florian Jetter
>            Priority: Minor
>
> When initialising an array with NaT only values the row group statistic is corrupt returning either random values or raises integer out of bound exceptions.
> {code:python}
> import io
> import pandas as pd
> import pyarrow as pa
> import pyarrow.parquet as pq
> df = pd.DataFrame({"t": pd.Series([pd.NaT], dtype="datetime64[ns]")})
> buf = pa.BufferOutputStream()
> pq.write_table(pa.Table.from_pandas(df), buf, version="2.0")
> buf = io.BytesIO(buf.getvalue().to_pybytes())
> parquet_file = pq.ParquetFile(buf)
> # Asserting behaviour is difficult since it is random and the state is ill defined. 
> # After a few iterations an exception is raised.
> while True:
>     parquet_file.metadata.row_group(0).column(0).statistics.max
> {code}



--
This message was sent by Atlassian Jira
(v8.3.2#803003)