IN LIST: centralize primitive filters and optimize Decimal128

[geoffreyclaude]

Which issue does this PR close?

• Part of Further improve performance of IN list evaluation #19241.
• Stacked on #23014.
• Next in stack: #24102.

Rationale for this change

#23014 adds fast direct comparisons for short primitive IN lists. For longer lists, DataFusion uses a bitmap, a hash set, or another specialized filter when one exists, and otherwise uses the general filter.

#24102 needs to make that same choice after reading FixedSizeBinary values as same-width primitive keys. Today, the choice is part of the native primitive path, so #24102 would have to repeat its limits and fallback rules.

This PR moves that choice beside the primitive filters and makes it reusable. The limits count only non-null list values. A separate commit uses one PrimitiveHashSetFilter<T, K> for the existing integer and floating-point hash-set paths. Integers keep their native keys; Float32 and Float64 keep their bitwise keys, including distinct signed zeros and NaN encodings. Filter selection and SQL behavior are unchanged.

The only new lookup path is for Decimal128. Lists with at most four non-null values still use direct comparisons. Larger lists now use a hash set over the stored i128 values instead of the general Arrow filter. Values are not rescaled, and the existing precision, scale, and null rules are unchanged. #24102 also uses this path for 16-byte FixedSizeBinary values.

What changes are included in this PR?

• Makes primitive filter selection reusable by IN LIST: reuse primitive filters for FixedSizeBinary #24102.
• Uses one primitive hash-set implementation for integer and floating-point values, while preserving their existing key semantics.
• Uses PrimitiveHashSetFilter<Decimal128Type> for Decimal128 lists with more than four non-null values.
• Adds four Decimal128 benchmark cases at list sizes 5 and 64.

Are these changes tested?

Tests cover the direct-comparison boundary, an all-null list, and bitwise float hash keys, including signed zero and distinct NaN encodings. Existing end-to-end Decimal tests cover hits, misses, nulls, IN, and NOT IN.

Are there any user-facing changes?

No. SQL results and public APIs are unchanged.

Benchmark snapshot

The benchmark uses list size 5, the first size above the direct-comparison limit, and a larger size of 64. Each size is measured with 0% and 50% matches. Filter construction is outside the timed loop.

A previous automated run measured this lookup strategy before the work was split from #24102. The current code still probes a hash set of stored i128 values, and filter construction remains outside the timed loop.

Compared baselines: #23014 -> this PR

Benchmark	Before	After	Change
primitive/decimal128/large_list/list=5/match=0%	18.1 us	15.2 us	-16.0% (1.19x faster)
primitive/decimal128/large_list/list=5/match=50%	38.6 us	19.2 us	-50.3% (2.01x faster)
primitive/decimal128/large_list/list=64/match=0%	17.6 us	15.2 us	-13.6% (1.16x faster)
primitive/decimal128/large_list/list=64/match=50%	37.1 us	23.5 us	-36.7% (1.58x faster)

[codecov-commenter]

Codecov Report

❌ Patch coverage is 73.33333% with 40 lines in your changes missing coverage. Please review.
✅ Project coverage is 81.14%. Comparing base (426b351) to head (510bf3e).
⚠️ Report is 106 commits behind head on main.

Files with missing lines	Patch %	Lines
...l-expr/src/expressions/in_list/primitive_filter.rs	73.79%	23 Missing and 15 partials ⚠️
.../physical-expr/src/expressions/in_list/strategy.rs	0.00%	0 Missing and 2 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #24283      +/-   ##
==========================================
+ Coverage   80.91%   81.14%   +0.23%     
==========================================
  Files        1102     1112      +10     
  Lines      377102   386940    +9838     
  Branches   377102   386940    +9838     
==========================================
+ Hits       305143   313998    +8855     
- Misses      53769    54439     +670     
- Partials    18190    18503     +313     

☔ View full report in Codecov by Harness.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.