to_bytes silently rescales a Decimal with a negative scale
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评估
调研方向
从 pyiceberg.conversions.to_bytes 入口点和 decimal_to_unscaled 开始，然后运行针对 DecimalType(10, 2) 提供的 Decimal 复现代码。完成标准是：不匹配的有符号 scale 被拒绝，而不是重新缩放；已经匹配类型 scale 的值仍能正确往返转换；检查对 pyiceberg/manifest.py 和 pyiceberg/io/pyarrow.py 的影响。
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描述
to_bytes for DecimalType takes the absolute value of the exponent before comparing it
against the type's scale:
_, digits, exponent = value.as_tuple()
exponent = abs(int(exponent))
if exponent != primitive_type.scale:
raise ValueError(...)
A Decimal carries the negated scale as its exponent, so a value with a negative scale
passes this check as if it had the matching positive one. decimal_to_unscaled then uses
only the digits, and the exponent is dropped:
sign, digits, _ = value.as_tuple()
return int(Decimal((sign, digits, 0)).to_integral_value())
The value is written four orders of magnitude off, with no error.
Reproduction
from decimal import Decimal
from pyiceberg.conversions import to_bytes, from_bytes
from pyiceberg.types import DecimalType
t = DecimalType(10, 2)
print(from_bytes(t, to_bytes(t, Decimal("1E+2")))) # 0.01, expected 100.00
print(from_bytes(t, to_bytes(t, Decimal("5E+1")))) # 0.50 for decimal(10, 1) -> 0.5, expected 50.0
This is not an exotic input. Decimal.normalize() produces exactly this form:
Decimal("100").normalize() # Decimal('1E+2')
so a value that has been normalized, or that comes out of arithmetic that trims trailing
zeros, hits it.
Impact
to_bytes writes the lower_bounds and upper_bounds of a data file
(pyiceberg/manifest.py, _write_data_file_statistics), and the same conversion is used
in pyiceberg/io/pyarrow.py. A bound written as 0.01 instead of 100.00 makes scan
planning prune files that do hold matching rows, so a query silently returns fewer rows
than it should.
Values with a positive scale are unaffected: Decimal("100.00") round-trips correctly.
Suggested fix
Compare the signed scale, -exponent, against primitive_type.scale, so a mismatching
value is rejected instead of being silently rescaled. Rescaling the value to the type's
scale would be the other option, but that widens the contract of a function that today
requires an exact match.
Happy to open a PR.
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