IN LIST: add UInt8 bitmap filter

[geoffreyclaude]

Which issue does this PR close?

• Part of Further improve performance of IN list evaluation #19241.
• Stacked on IN LIST: clean up generic static filtering #21927.
• Next in stack: IN LIST: add UInt16 bitmap filter #23012.
• Extracted from Optimize IN performance with specialized implementations #19390.

Rationale for this change

IN LIST evaluates expressions like x IN (1, 3, 7). The list on the right is fixed, so DataFusion can precompute a small lookup structure once and then reuse it for every input row.

For UInt8, there are only 256 possible values: 0 through 255. That means the lookup can be a tiny checklist with one bit per possible value:

• If the list contains 3, set bit 3.
• If the list contains 7, set bit 7.
• To check whether an input value is present, read that one bit.

So instead of hashing each input value or comparing it against the list, membership becomes one indexed bit test. The bitmap is only 32 bytes, because 256 bits = 32 bytes.

This PR adds the first specialized primitive path in the stack as a concrete UInt8 filter. The UInt16 version is added in #23012, and the shared bitmap abstraction is introduced only after both concrete implementations are visible in #23035.

What changes are included in this PR?

• Adds UInt8BitmapFilter, a 32-byte bitmap built from the non-null constants in the IN list.
• Routes UInt8 constant-list filtering to that bitmap path.
• Keeps the same SQL null behavior as the generic path for both IN and NOT IN.
• Moves shared dictionary-needle handling into static_filter.rs, so specialized filters can reuse it consistently.
• Adds focused tests for UInt8 null handling and dictionary-encoded needles.

Are these changes tested?

Yes.

• cargo fmt --all
• cargo test -p datafusion-physical-expr bitmap_filter_u8 --lib
• cargo test -p datafusion-physical-expr in_list_int_types --lib
• cargo clippy -p datafusion-physical-expr --all-targets --all-features -- -D warnings

Are there any user-facing changes?

No. This is an internal performance optimization only.

Local benchmark snapshot

Benchmark command:

cargo bench -p datafusion-physical-expr --profile release-nonlto --bench in_list_strategy -- --save-baseline <name>

Method: compare adjacent saved baselines using raw Criterion sample minima (min(time / iters)). Lower is better; changes within +/-5% are treated as noise. These numbers were not rerun after splitting the bitmap abstraction into #23035.

Compared baselines: #21927 -> #23011

Relevant scope: UInt8 narrow-integer rows.

Summary: 5 relevant rows, 5 faster, 0 slower, 0 within +/-5%.

Benchmark	Before	After	Change
narrow_integer/u8/list=16/match=0%	20.39 us	3.94 us	-80.7% (5.18x faster)
narrow_integer/u8/list=16/match=50%	38.38 us	3.98 us	-89.6% (9.65x faster)
narrow_integer/u8/list=4/match=0%	18.18 us	3.93 us	-78.4% (4.62x faster)
narrow_integer/u8/list=4/match=50%	34.63 us	3.96 us	-88.6% (8.75x faster)
nulls/narrow_integer/u8/list=16/match=50%/nulls=20%	37.12 us	4.16 us	-88.8% (8.93x faster)