Vectorize the lower-bound check in native date_trunc for fine units #6717

What / Why

#5956 adds a check to timestamp_trunc_upstream in native/spark-expr/src/kernels/temporal.rs, ahead of the fine-unit fast path (MILLISECOND, SECOND, MINUTE, and HOUR and DAY when the array has no timezone). It scans every physical value for one that would underflow when truncated:

if array.values().iter().any(|micros| *micros < lower) {
    return timestamp_trunc_fine_boundary(array, granularity, unit);
}

The check is needed, but iter().any exits early and doesn't vectorize. In the timestamp_trunc benchmark from that PR, UTC SECOND, MINUTE, HOUR and DAY on 8192 rows without nulls went from about 7.7 µs to about 10 µs per batch compared with the kernel without the check (release build without LTO). That is still far faster than the chrono kernel the PR replaces, so this is headroom rather than a regression against a release.

Suggested fix

Take the minimum of the values buffer with a fold, or with arrow::compute::min over a null-free view of the same buffer, and compare it with lower once. Both vectorize. The check should keep looking at physical values, null slots included, as it does now, because DataFusion's fine-unit path subtracts from those too.

To measure, run cargo bench --bench timestamp_trunc -- 'timestamp_trunc/UTC/(DAY|HOUR|MINUTE|SECOND)/8192' in native/spark-expr before and after.

This depends on #5956 merging first.