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https://issues.apache.org/jira/browse/ARROW-2367?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16432461#comment-16432461
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Krisztian Szucs edited comment on ARROW-2367 at 4/10/18 3:28 PM:
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What's the expected output? It should be able to hold `2^31 - 1` bytes?

According to my investigation 
https://github.com/apache/arrow/blob/f9c070162acd87caf031723fb8d7e9c9a7317c0e/cpp/src/arrow/builder.h#L44
 limits to `(2^31) - 1`


was (Author: kszucs):
What's the expected output?

> ListArray has trouble with sizes greater than kMaximumCapacity
> --------------------------------------------------------------
>
>                 Key: ARROW-2367
>                 URL: https://issues.apache.org/jira/browse/ARROW-2367
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 0.9.0
>            Reporter: Bryant Menn
>            Priority: Major
>
> When creating a Pandas dataframe with lists as elements as a column the 
> following error occurs when converting to a {{pyarrow.Table}} object.
> {code}
> Traceback (most recent call last):
> File "arrow-2227.py", line 16, in <module>
> arr = pa.array(df['strings'], from_pandas=True)
> File "array.pxi", line 177, in pyarrow.lib.array
> File "error.pxi", line 77, in pyarrow.lib.check_status
> File "error.pxi", line 77, in pyarrow.lib.check_status
> pyarrow.lib.ArrowInvalid: BinaryArray cannot contain more than 2147483646 
> bytes, have 2147483647
> {code}
> The following code was used to generate the error (adapted from ARROW-2227):
> {code}
> import pandas as pd
> import pyarrow as pa
> # Commented lines were used to test non-binary data types, both cause the 
> same error
> v1 = b'x' * 100000000
> v2 = b'x' * 147483646
> # v1 = 'x' * 100000000
> # v2 = 'x' * 147483646
> df = pd.DataFrame({
>      'strings': [[v1]] * 20 + [[v2]] + [[b'x']]
>      # 'strings': [[v1]] * 20 + [[v2]] + [['x']]
> })
> arr = pa.array(df['strings'], from_pandas=True)
> assert isinstance(arr, pa.ChunkedArray), type(arr)
> {code}
> Code was run using Python 3.6 with PyArrow installed from conda-forge on 
> macOS High Sierra.



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