[Vector Index] CREATE INDEX ... USING vector_index DDL + index definition wiring

Part of #18676. RFC-104 / [design PR](https://github.com/chrevanthreddy/hudi/pull/1).

## Scope

User-facing entry point that triggers the bootstrap pipeline from sub-issue 5.

## Tasks

- Extend `hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/IndexCommands.scala` to recognize `vector_index` index type.
- Extend `hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/index/HoodieSparkIndexClient.java` to:
- Accept SQL options: `vectorColumn` (required), `numClusters` (optional, default from config), `fgPerCluster` (optional, default from config).
- Validate the column exists on the table and is of type `array` or `array`.
- Persist user-supplied params into `HoodieIndexDefinition` (so the bootstrap can read them back).
- Invoke `ScheduleIndexActionExecutor` → metadata writer bootstrap path.

Example DDL the change must support:

```sql
CREATE INDEX my_vec_idx ON hudi_tbl
USING vector_index (embedding)
OPTIONS (numClusters = '128', fgPerCluster = '2');
```

## Tests

- Negative test: missing `vectorColumn` option → clear error.
- Negative test: non-array column → clear error.
- Positive test: valid DDL parses and persists the `HoodieIndexDefinition` correctly.

## Depends on

- Sub-issues 1, 5 (need partition type + bootstrap implementation)

## Out of scope

`DROP INDEX` and `REFRESH INDEX` for vector indexes (later milestone).

Start in IndexCommands.scala to trace how index types are parsed, then inspect HoodieSparkIndexClient.java and the existing index-definition and scheduling paths. Add the vector_index DDL flow with the named options and validation, and cover missing vectorColumn, non-array columns, and valid definition persistence with tests for the stated cases.

Written by the indexing model from the issue text.