perf(spark): restore Catalyst fast-paths for row-writer bulk insert key generation

### Problem

`HoodieDatasetBulkInsertHelper.prepareForBulkInsert` invokes the configured `KeyGenerator` for every row via `df.queryExecution.toRdd.mapPartitions { iter => iter.map { row => keyGenerator.getRecordKey(row, schema); keyGenerator.getPartitionPath(row, schema); ... } }`. This forces an RDD round-trip and per-row reflection-based keygen invocation on every record, even for the keygens (NonpartitionedKeyGenerator, SimpleKeyGenerator) where the record-key and partition-path values can be sourced directly from input columns.

Before the original row-writer PR ([#5470](https://github.com/apache/hudi/pull/5470)) consolidated the path, these two keygens were handled with `withColumn(col(field).cast(String))` projections — pure Catalyst, free codegen, no row materialization. Collapsing the dispatch onto an RDD `mapPartitions` regressed bulk-insert throughput for the common SimpleKeyGen and NonpartitionedKeyGen cases. Related: #18969 (same module, drop-partition-columns hot path).

### Proposed fix

Restore tiered dispatch in `prepareForBulkInsert`:

- **Tier 1 — `NonpartitionedKeyGenerator`** (single record-key field): emit `col(rk).cast(String)` + `lit("")` as Catalyst columns.
- **Tier 2 — `SimpleKeyGenerator`** (single record-key + single partition-path, URL-encoding off, slash-separated dates off): emit `col(rk).cast(String)` and a partition-path expression mirroring `PartitionPathFormatterBase#combine`, including the `handleEmpty -> __HIVE_DEFAULT_PARTITION__` substitution and hive-style `field=` prefixing.
- **Tier 3 — everything else** (multi-field keys, ComplexKeyGenerator, TimestampBased, Custom, Simple with URL-encode or slash-sep): anonymous `functions.udf` over a struct of input columns calling the canonical `BuiltinKeyGenerator.getRecordKey(Row)` / `getPartitionPath(Row)` — i.e. the same Avro-aligned formatter the read side and Tier 3 callers already share. UDFs are not registered against the SparkSession (no leak across writes).
- **Auto record key generation** keeps the existing RDD path; it needs `TaskContext.partitionId` and a stateful per-task counter, which can't be expressed cleanly as a driver-side closure.

The Tier 3 UDF goes through `getRecordKey(Row)` / `getPartitionPath(Row)`, which use the `String` formatter (`combinePartitionPath`), so all three formatter flags (hive-style, URL encode, slash-separated dates) are honored for the keygens that fall through. The Tier 2 fast-path encodes only the default+hive-style flag combinations (URL encoding has no efficient pure-Catalyst equivalent, and the 1.2.0+ slash-separated branch in the formatter exercises a separate code path we'd rather not encode twice).

### Test coverage

New tests added to `TestHoodieDatasetBulkInsertHelper`:

- **Parity against canonical Avro keygen**, parameterized across 11 cases — every supported keygen class plus the SimpleKeyGen flag combinations: default, hive-style only, slash-sep (Tier 3), hive+slash (Tier 3), URL-encode (Tier 3), hive+URL (Tier 3), ComplexKeyGen single/multi, TimestampBased, Custom.
- **Non-string record key cast** — verifies Tier 1/2 cast `ts: long` correctly.
- **Logical plan inspection** — Tier 1/2 plans contain no `ScalaUDF` (i.e. they actually benefit from Catalyst codegen, not silently fall to Tier 3).
- **Empty partition value** — confirms `__HIVE_DEFAULT_PARTITION__` substitution under both default and hive-style flags.
- **Driver session timezone propagation** — Tier 3 UDF respects `spark.sql.session.timeZone` set on the driver (guards against executor JVM default leakage on TimestampBasedKeyGenerator).

### Out of scope (followups)

- The `dropPartitionColumns = true` path inside `BulkInsertDataInternalWriterHelper.write` does the partition-column strip per-row in a Java loop with a `HashSet` lookup. Lifting that into `prepareForBulkInsert` would let us also avoid materialising columns that are about to be dropped — see #18969 for the adjacent discussion.
- The auto-keygen path could shed its `toRdd` round-trip with a custom Catalyst `Expression` for `partitionId + monotonic rowId`. Out of scope here.

### PR

Patch will be linked here once opened.