GH-50645: [C++][Compute] Optimize min/max_element_wise with word at a time validity handling

[Kanishk-Dendukuri]

Rationale for this change

The variadic min_element_wise / max_element_wise kernels (ScalarMinMax in scalar_compare.cc) fold arguments using a multi pass approach: an antiextreme sentinel fill, a separate validity bitmap pass (BitmapOr/BitmapAnd), and a per element value pass with a per-element validity branch.

This can be rewritten as a single word at a time pass (handling validity 64 bits at a time) that fuses validity and value computation and keeps fully-valid words branchless. That removes the redundant passes and the per-element mispredicting branch, giving a measured ~2-7x speedup on numeric types, with no behavioral change.

What changes are included in this PR?

Rewrote the numeric ScalarMinMax fold to a word at a time algorithm (CombineWordwise / CombineArrays / FoldArrayIntoOutput), with an all-valid branchless fast path and an all null skip.

Added a random, sliced/offset test (MinMaxElementWiseRandom) covering the new word loop across null densities and offsets.

Benchmarks

archery benchmark diff (this branch vs main), 5 reps; throughput, change %:

benchmark	null	baseline	contender	change %
ArrayArray Int64	50%	285.338M/s	2.429G/s	+751.4%
ArrayArray Int64	0.01%	808.895M/s	3.594G/s	+344.3%
ArrayArray Int64	1%	645.295M/s	2.823G/s	+337.5%
ArrayArray Int64	10%	610.443M/s	2.433G/s	+298.5%
ArrayArray Int64	0%	1.422G/s	5.447G/s	+283.1%
ArrayArray Int64	100%	5.696G/s	14.671G/s	+157.6%
ArrayScalar Int64	50%	1.075G/s	2.748G/s	+155.7%
ArrayScalar Int64	1%	1.657G/s	3.387G/s	+104.4%
ArrayScalar Int64	10%	1.628G/s	2.758G/s	+69.4%
ArrayScalar Int64	0.01%	2.300G/s	3.817G/s	+66.0%
ArrayScalar Int64	0%	2.482G/s	3.782G/s	+52.4%
ArrayScalar Int64	100%	8.625G/s	10.134G/s	+17.5%

Are these changes tested?

Yes. All existing ElementWise tests pass, plus a new MinMaxElementWiseRandom typed test that cross checks the kernel against a reference across lengths (65/128/200), null densities (0–100%), offsets (0/1/3/7), both skip_nulls, and min/max, over all numeric types.

Are there any user-facing changes?

No

AI Usage

Parts of the code, tests, and this description were written with AI assistance.

Closes #50645

• GitHub Issue: [C++][Compute] Optimize min/max_element_wise with word at a time validity handling #50645

[Reranko05]

Can you run python -m pre_commit run clang-format --files cpp/src/arrow/compute/kernels/scalar_compare.cc cpp/src/arrow/compute/kernels/scalar_compare_test.cc to fix the formatting issues?