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https://issues.apache.org/jira/browse/PARQUET-1869?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17123699#comment-17123699
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Wes McKinney commented on PARQUET-1869:
---------------------------------------
I'm pretty sure this is a problem with conversion from Arrow format to the
Parquet fixed-size-binary storage representation, so might move this issue to
the ARROW issue tracker. Either way we should definitely try to fix this before
the next major Arrow release
> [C++] Large decimal values don't roundtrip correctly
> ----------------------------------------------------
>
> Key: PARQUET-1869
> URL: https://issues.apache.org/jira/browse/PARQUET-1869
> Project: Parquet
> Issue Type: Test
> Components: parquet-cpp
> Reporter: Joris Van den Bossche
> Priority: Major
>
> Reproducer with python:
> {code}
> import decimal
> import pyarrow as pa
> import pyarrow.parquet as pq
> arr = pa.array([decimal.Decimal('9223372036854775808'),
> decimal.Decimal('1.111')])
> print(arr)
> pq.write_table(pa.table({'a': arr}), "test_decimal.parquet")
> result = pq.read_table("test_decimal.parquet")
> print(result.column('a'))
> {code}
> gives
> {code}
> # before writing
> <pyarrow.lib.Decimal128Array object at 0x7fd07d79a468>
> [
> 9223372036854775808.000,
> 1.111
> ]
> # after reading
> <pyarrow.lib.ChunkedArray object at 0x7fd0711e9f98>
> [
> [
> -221360928884514619.392,
> 1.111
> ]
> ]
> {code}
> I tried reading the file with a different parquet implementation (fastparquet
> python package), and that gives the same values on read, so the issue might
> possibly rather be on the write side.
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