perf: reduce Parquet runtime filter schema guard overhead #6123

What is the problem the feature request solves?

The conservative Parquet runtime-filter schema guard in #6067 preserves conversion errors, but it also disables reader pruning for adaptations that can be proved infallible and adds work for fully eligible wide scans.

The focused native release benchmark at c48d39f07, documented in PR #6067, found:

The promotion and nested fixtures use 16 files and 128 row groups. The wide fixture uses 128 small files and 64 columns. Measurements use warm local caches, the standard optimized release profile, and 14 measured samples per case/mode. Timing includes native planning and execution. Nested column pruning remains effective; the struct case loses row-group pruning.

Describe the potential solution

1. Establish which schema adaptations are infallible and allow reader filtering through those adaptations. Start with permitted INT32-to-BIGINT promotion and projection of a subset of a struct's fields. Use an explicit conversion-safety contract so the decision stays aligned with the existing Spark adapter.
2. Avoid one inner.rewrite call per required column per file when the logical and physical schemas already match and adapter semantics establish that the fast path is safe. Keep unresolved-column handling, partition exclusions, case and field-ID resolution, and missing/default-column behavior correct.

Acceptance criteria:

• Preserve the schema-conversion and timestamp-overflow errors covered by fix: preserve Parquet conversion errors during join filtering #6067, including nested timestamps, mixed files, static predicates, empty files, and supplied file statistics.
• Keep unresolved names ineligible and preserve the partition and column-resolution regressions.
• Preserve static pruning, missing/default values, and supported name/field-ID mappings.
• Compare the changes using the same direct, promotion, nested, wide selective, and wide non-pruning fixtures with runtime filtering both enabled and disabled. Report query time, requested data bytes, and row groups read.

Additional context

Requested in this review. This follow-up covers the schema guard's pruning eligibility and per-file checking cost. #5775 tracks TopK fusion and reader pushdown.