[C++] compute.cumulative_max initializes incorrectly for non-integer types #51194
Description
Describe the bug, including details regarding any error messages, version, and platform.
the initial value is documented to be
the minimum value of input type (so that any other value will replace the start as the new maximum)
but since it uses std::numeric_limits<T>::min(), for floating-point types like double, this actually initializes with the smallest positive value of the input type. so any input with a prefix of values <=0 will yield incorrect results. this also impacts pandas.cummax()
GPT-6 Astra helped identify the bug
import pyarrow as pa
import pyarrow.compute as pc
import pandas as pd
values = [-2.5, 2.5]
arrow_result = pc.cumulative_max(pa.array(values, type=pa.float64())).to_pylist()
pandas_result = pd.Series(values, dtype="float64[pyarrow]").cummax().tolist()
expected = [-2.5, 2.5]
print("expected running maximum:", expected)
print("pyarrow cumulative_max: ", arrow_result)
print("pandas cummax (arrow): ", pandas_result)
print("pandas cummax (numpy): ", pd.Series(values).cummax().tolist())
assert arrow_result == expected, "cumulative_max seeded with the smallest positive float">>> expected
[-2.5, 2.5]
>>> arrow_result
[2.2250738585072014e-308, 2.5]
>>> pandas_result
[2.2250738585072014e-308, 2.5]Component(s)
C++
Activity
[-]`compute.cumulative_max` initializes incorrectly for non-integer types[/-][+][C++] `compute.cumulative_max` initializes incorrectly for non-integer types[/+]Adarsh-Me commentedon Sep 6, 2026
take
GH-51194: [C++] Fix cumulative_max/min default start for floating-poi…
pitrou commentedon Sep 7, 2026
Issue resolved by pull request 51203
#51203