[core][spark][flink] Fix nested data evolution isolation - #9564

Purpose

Follow up #8334 so sub-field-level nested data evolution is completely opt-in and preserves legacy data-evolution behavior while disabled.

Changes

• Gate nested path parsing, projection, conflict detection, read planning, and partial writes in Core, Flink, and Spark behind data-evolution.nested-field.enabled.
• Preserve literal top-level column names containing dots and retain the legacy top-level write metadata encoding while the option is disabled.
• Support both a persisted false-to-true rollout and per-operation enablement through dynamic table options. Dynamic enablement affects only the copied table instance and does not persist the option; persisted true-to-false changes or removal remain rejected, and data-evolution.enabled=true is required.
• Preserve row cardinality and every ROW ancestor nullness for projected or newly added nested leaves.
• Separate format reader mappings by requested shape, physical projected schema, and effective nested mode.
• Detect persisted enablement from file schemas so readers retained across ALTER TABLE false-to-true safely read later nested partial files.
• Inject the nested-field option into row-id column conflict detection instead of reading the latest schema inside the checker.

Compatibility

Upgrade every reader, writer, compactor, and maintenance component before enabling the option. Downgrading after nested sub-field metadata has been committed is unsafe.

Tests

• Core targeted suite: 48 tests passed.
• Conflict detection suite: 50 tests passed.
• API option-aware TableSchema tests: 2 tests passed.
• SchemaValidation and DataEvolutionUtils targeted tests: 4 tests passed.
• Flink nested MERGE INTO integration suite: 14 tests passed.
• Spark 3 nested MERGE INTO suite: 15 tests passed.
• Spark 4 module compiled with JDK 17.
• Spotless checks passed for all changed modules.