perf: Adopt bulk-NULL builders and NullBuffer::union_many in datafusion-spark

### Is your feature request related to a problem or challenge?

Two patterns from @neilconway's recent perf PRs are not yet applied throughout the `datafusion-spark` crate:

1. **Bulk-NULL builders** ([#21789](https://github.com/apache/datafusion/pull/21789), [#21849](https://github.com/apache/datafusion/pull/21849), [#21863](https://github.com/apache/datafusion/pull/21863), [#21847](https://github.com/apache/datafusion/pull/21847), [#21854](https://github.com/apache/datafusion/pull/21854), [#21877](https://github.com/apache/datafusion/pull/21877), [#21991](https://github.com/apache/datafusion/pull/21991), [#22029](https://github.com/apache/datafusion/pull/22029), [#21519](https://github.com/apache/datafusion/pull/21519), [#21366](https://github.com/apache/datafusion/pull/21366)) — when an output null mask equals (or is a `NullBuffer::union[_many]` of) the input null masks, precompute it once instead of maintaining it row-by-row with `append_null` / `BooleanBufferBuilder.append`.
2. **`NullBuffer::union_many`** ([#22070](https://github.com/apache/datafusion/pull/22070)) — replaces chains of 3+ binary `NullBuffer::union` calls with one clone + in-place `&=`.

An audit of the Spark crate turned up six sites where these patterns apply.

### Describe the solution you'd like

Apply the patterns at the following call sites. Each checkbox is one PR.

- [ ] **`datafusion/spark/src/function/math/width_bucket.rs:206-276, 313-432`** — `width_bucket` kernel has four nullable inputs (value, min, max, n_buckets). The macro generates the same code for Float64, Duration, IntervalYearMonth, IntervalMonthDayNano. Precompute `NullBuffer::union_many([v.nulls(), min.nulls(), max.nulls(), n.nulls()])` outside the loop, append placeholders for masked rows, reattach at the end.
- [ ] **`datafusion/spark/src/function/array/slice.rs:152-186`** — `calculate_start_end` runs two `Int64Builder`s in lockstep, both `append_null` when any of (values, start, length) is null. Precompute `union_many` of three input nulls, fill placeholders, reattach to both builders.
- [ ] **`datafusion/spark/src/function/string/substring.rs:371-401`** — `SparkSubstring`'s main loop. Three-input null union (array + start_array + optional length_array). Negative-length branch still needs row-level `append_empty`, but the null mask itself can be precomputed.
- [ ] **`datafusion/spark/src/function/datetime/make_dt_interval.rs:170-197`** — 1-4 nullable inputs wrapped in `Option<&ArrayRef>`. `union_many` over the `Some(...)` arrays' nulls.
- [ ] **`datafusion/spark/src/function/datetime/make_interval.rs:190-`** — same structure as `make_dt_interval`.
- [ ] **`datafusion/spark/src/function/string/format_string.rs:126-157`** — accumulates `Vec` then `StringArray::from(vec)`. Switch to `GenericStringBuilder` + `append_value(&str)`. Matches the `append_with` pattern from #22029.
- [ ] **`datafusion/spark/src/function/conversion/cast.rs:199-209, 226-236`** — `cast_int_to_timestamp` / `cast_float_to_timestamp` do per-row `append_null` / `append_value` where output nulls equal input nulls. Clone input nulls.

### Describe alternatives you've considered

Bundling all sites into a single PR. Splitting per file keeps each PR reviewable, especially the `width_bucket` macro change which touches four type variants.

### Additional context

Already use these patterns, skip:

- `datafusion/spark/src/function/spark/null_utils.rs:63` — uses `union_many`.
- `datafusion/spark/src/function/map/str_to_map.rs:212` — uses `union_many`.
- `datafusion/spark/src/function/hash/utils.rs` — fast-path null-count checks.

Considered and rejected:

- `datafusion/spark/src/function/string/elt.rs:115-139` — output null mask is data-dependent (which column's nulls to include depends on the runtime `idx` value).