feat(variant): add Spark 4.0 VARIANT type and Parquet read support

[oarap]

Introduce TypeKind::VARIANT as Spark-compatible STRUCT<value VARBINARY, metadata VARBINARY> and wire it through vectors, serde, and Spark SQL functions.

• Add VARIANT type and VariantVector/VariantValue plumbing.
• Implement Spark VARIANT dictionary parsing and decoding for both bit-coded and compact encodings (compact string length and unordered start-offset tables).
• Support variant_get / parse_json over Spark VARIANT payloads.
• Improve Parquet reader integration, including ScanSpec child ordering mismatch correction for (value, metadata).
• Add Spark-generated VARIANT Parquet fixtures and Parquet reader/unit test coverage.

What problem does this PR solve?

Issue Number: close #xxx

Type of Change

• 🐛 Bug fix (non-breaking change which fixes an issue)
• ✨ New feature (non-breaking change which adds functionality)
• 🚀 Performance improvement (optimization)
• ⚠️ Breaking change (fix or feature that would cause existing functionality to change)
• 🔨 Refactoring (no logic changes)
• 🔧 Build/CI or Infrastructure changes
• 📝 Documentation only

Description

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Performance Impact

• No Impact: This change does not affect the critical path (e.g., build system, doc, error handling).

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  After:   8.2s  (+20%)
  

• Negative Impact: Explained below (e.g., trade-off for correctness).

Release Note

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Release Note:

Release Note:
- Fixed a crash in `substr` when input is null.
- optimized `group by` performance by 20%.

Checklist (For Author)

• I have added/updated unit tests (ctest).
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• I have run clang-format / linters.
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Breaking Changes

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