[jira] [Resolved] (ARROW-12482) [Doc][Python] Mention CSVStreamingReader pitfalls with type inference

["Antoine Pitrou (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-12482?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Antoine Pitrou resolved ARROW-12482.
------------------------------------
    Fix Version/s: 4.0.0
       Resolution: Fixed

Issue resolved by pull request 10132
[https://github.com/apache/arrow/pull/10132]

> [Doc][Python] Mention CSVStreamingReader pitfalls with type inference
> ---------------------------------------------------------------------
>
>                 Key: ARROW-12482
>                 URL: https://issues.apache.org/jira/browse/ARROW-12482
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Documentation, Python
>    Affects Versions: 3.0.0
>            Reporter: Oleksandr Shevchenko
>            Assignee: Antoine Pitrou
>            Priority: Major
>              Labels: CSVParser, CSVReader, pull-request-available
>             Fix For: 4.0.0
>
>          Time Spent: 1.5h
>  Remaining Estimate: 0h
>
> Looks like Arrow infer type for the first batch and apply it for all subsequent batches. But information might be not enough to infer the type correctly for the whole file. For our particular case, Arrow infers some field in the schema as date32 from the first batch but the next batch has an empty field value that can’t be converted to date32.
> When I increase the batch size to have such a value in the first batch Arrow set string type (not sure why not nullable date32) for such a field since it can’t be converted to date32 and the whole file is read successfully.
> This problem can be easily reproduced by using the following code and attached dataset:
> {code:java}
> import pyarrow as pa
> import pyarrow._csv as pa_csv
> import pyarrow._fs as pa_fs
> read_options: pa_csv.ReadOptions = pa_csv.ReadOptions(block_size=5_000_000)
> parse_options: pa_csv.ParseOptions = pa_csv.ParseOptions(newlines_in_values=True)
> convert_options: pa_csv.ConvertOptions = pa_csv.ConvertOptions(timestamp_parsers=[''])
> with pa_fs.LocalFileSystem().open_input_file("dataset.csv") as file:
>  reader = pa_csv.open_csv(
>  file, read_options=read_options, parse_options=parse_options, convert_options=convert_options
>  )
>  for batch in reader:
>  table_batch = pa.Table.from_batches([batch])
>  table_batch
> {code}
> Error message:
> {code:java}
>  for batch in reader:
>  File "pyarrow/ipc.pxi", line 497, in __iter__
>  File "pyarrow/ipc.pxi", line 531, in pyarrow.lib.RecordBatchReader.read_next_batch
>  File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status
>  pyarrow.lib.ArrowInvalid: In CSV column #23: CSV conversion error to date32[day]: invalid value ''
> {code}
>  
>  When we use block_size `10_000_000` file can be read successfully since we have the problematic value in the first batch.
> An error occurs when I try to attach dataset, so you can download it from Google Drive [here|https://drive.google.com/file/d/1Vt1yN02dyVumsou_kFs7GTnKT46eE6ja/view?usp=sharing]



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