What this PR does / why we need it:

This PR adds comprehensive support for complex data types in Feast and implements schema validation across all compute engines:

Commit 1 (970650b): Fix Map/Dict support and implement schema validation

• Fixed Map/Dict type support across offline stores, online stores, and type mappings
• Added enable_validation parameter to FeatureView, BatchFeatureView, and StreamFeatureView
• Implemented schema validation nodes in Local, Ray, and Spark compute engines (missing columns, type mismatch warnings)
• Added Spark and Milvus map type mappings
• Updated documentation for Map type backend mappings

Commit 2 (ac28d4d): Add JSON and Struct complex data types

• Added JSON, JSON_LIST, STRUCT, STRUCT_LIST to the protobuf ValueType enum and Value message
• Introduced Json primitive type and Struct class (schema-aware structured type with named, typed fields)
• Implemented full type mapping pipeline: Feast ↔ Proto ↔ PyArrow ↔ backend-native types (PostgreSQL, BigQuery, Snowflake, Redshift, Spark, MSSQL, Athena, DynamoDB, Milvus)
• Added JSON well-formedness validation at both proto conversion level (always active) and validation node level (when enable_validation=True)
• Implemented Spark-native type validation using from_feast_to_spark_type() and _spark_types_compatible() — eliminates the PyArrow-to-Spark type mismatch gap
• Persisted Struct field schemas through the registry via Field tags (feast:struct_schema)
• Added Go SDK type conversion support for JSON and Struct types
• Added automatic serialization/deserialization for JSON type (Python dict/list ↔ JSON string)
• Single _validate_schema() method per engine (missing columns + type checks + JSON content validation)

Commit 3 (a131b73): Modified default template with different types

• Added Json, Map and Struct in driver template