Schema Management

Overview

SchemaCore validates, maps fields, and manages schemas through JSON-based definitions. It integrates with permissions and payment systems for data management.

Core Component

SchemaCore

• Lifecycle Management
  • Schema persistence and versioning
  • Field mapping coordination
  • Relationship tracking
  • Thread-safe operations
• Validation and Control
  • Validation rules
  • Permission integration
  • Payment configuration
  • Error recovery
• Processing
  • JSON schema parsing
  • Field validation and type checking
  • Field mapping rules processing
  • Relationship validation
• Integration
  • Error context preservation
  • Field mapping interpretation
  • Relationship validation
  • Payment requirement parsing

Schema Definition

JSON Structure

{
  "name": "UserProfile",
  "version": "1.0",
  "fields": {
    "id": {
      "type": "string",
      "required": true,
      "permissions": {
        "read": "public",
        "write": "owner"
      }
    },
    "email": {
      "type": "string",
      "required": true,
      "permissions": {
        "read": "trusted",
        "write": "owner"
      },
      "payment": {
        "baseCost": 0.001,
        "trustScaling": true
      }
    }
  }
}

Features

Management Flow

flowchart LR
    subgraph Input
        J[JSON Schema] --> V[Validation]
        V --> P[Permission Check]
        P --> T[Field Mapping Rules]
    end
    subgraph Processing
        T --> SC[SchemaCore]
        SC --> VM[Validation]
    end
    subgraph Output
        VM --> S[Schema Storage]
        S --> R[Relationship Tracking]
        R --> PM[Payment Integration]
    end

Component Architecture

classDiagram
    class SchemaCore {
        -schemas: Mutex<Map>
        -schemas_dir: PathBuf
        +load_schema()
        +unload_schema()
        +get_schema()
        +list_schemas()
        +schema_exists()
        +load_schemas_from_disk()
        +map_fields()
        +interpret_schema()
        +load_schema_from_json()
        +load_schema_from_file()
    }

Field Mapping System

graph TD
    S1[Source Schema] --> |Field Mapping| TM[Field Mapper]
    S2[Target Schema] --> |Validation Rules| TM
    TM --> |Type Conversion| TC[Type Checker]
    TM --> |Permission Mapping| PM[Permission Manager]
    TM --> |Payment Calculation| PC[Payment Calculator]
    TC --> |Validated| OUT[Output Schema]
    PM --> |Verified| OUT
    PC --> |Configured| OUT

Implementation

Validation Process

1. Parse JSON schema definition
2. Validate field types and constraints
3. Check permission configurations
4. Verify payment settings
5. Validate relationships
6. Process field mapping rules
7. Store schema version

Field Mapping

• Type Mappings
  • Basic type conversions
  • Complex field mappings
  • Custom type handlers
• Permission Mappings
  • Access level inheritance
  • Trust distance calculations
  • Payment requirement mapping
• Relationship Tracking
  • Field dependencies
  • Schema version links
  • Field mapping path tracking

Error Handling

• Validation errors
• Field mapping failure recovery
• Permission conflict resolution
• Payment requirement validation
• Relationship consistency checks

Best Practices

1. Schema Design

• Use clear field names
• Define explicit types
• Set permissions
• Configure payments
• Document relationships

2. Version Management

• Maintain versions
• Track breaking changes
• Update relationships
• Migrate data safely
• Test field mappings

3. Security

• Validate inputs
• Check permissions
• Verify payment configs
• Track access patterns
• Monitor field mappings

4. Performance

• Cache schemas
• Optimize field mappings
• Batch updates
• Monitor memory
• Profile operations

Extension Points

• Validation rules
• Field mapping pipelines
• Type converters
• Payment calculators
• Permission handlers

Advanced Schema Evolution

FoldDB includes automated schema evolution capabilities:

Schema Field Mapping Process

flowchart LR
    S1[Source Schema] --> |Analysis| AE[Analysis Engine]
    AE --> |Suggestions| T[Field Mapping Rules]
    T --> |Validation| V[Validator]
    V --> |Feedback| AE
    AE --> |Optimized| S2[Target Schema]

Evolution Capabilities

Automated Field Mapping

• Mapping Generation: Generates field mappings from schema structures
• Type Inference: Determines appropriate type conversions between schemas
• Relationship Discovery: Identifies relationships between fields across schemas
• Optimization: Recommends schema improvements based on usage patterns

Impact Analysis

• Change Prediction: Forecasts issues before schema changes
• Dependency Tracking: Maps affected components when schemas change
• Risk Assessment: Evaluates data integrity risks with field mappings
• Compatibility: Ensures backward compatibility with existing applications

Migration Automation

• Script Generation: Creates migration scripts for schema evolution
• Data Field Mapping: Handles data conversions between versions
• Validation Rules: Generates validation for migrated data
• Rollback Planning: Creates safety mechanisms for failed migrations

Adaptive System

• Pattern Analysis: Uses past schema changes to improve future field mappings
• Usage Optimization: Adapts recommendations based on query patterns
• Continuous Improvement: Refines suggestions through feedback loops
• Cross-Schema Learning: Applies insights across similar scenarios

Component Integration

The evolution system integrates with schema management components:

• SchemaCore: Field mapping suggestion capabilities and validation for changes
• ValidationManager: Automated validation rule generation
• SchemaEvolutionPlanner: Schema planning

Benefits

• Development Speed: Automates schema field mapping tasks
• Error Prevention: Identifies issues before production impact
• Performance: Suggests improvements based on usage
• Evolution: Simplifies versioning and migration
• Data Quality: Ensures consistent validation across changes