FoldDB Concurrency Management

What is Concurrency Management?

FoldDB's concurrency management system ensures data consistency and thread safety across all operations. Through atomic operations, mutex locks, and version control, the system provides reliable concurrent access to data while preventing conflicts and maintaining data integrity.

Key Features

The concurrency management system provides three primary capabilities:

How Concurrency Management Works

Thread Safety Implementation

FoldDB implements thread safety through these mechanisms:

• Mutex locks - Control access to shared resources
• Atomic operations - Ensure indivisible execution
• Immutable data - Prevent modification after creation
• Lock-free algorithms - Enable concurrent access where possible

Schema Access Pattern

When accessing schema information, the system follows this sequence:

1. Client requests lock from Mutex
2. Mutex acquires lock
3. Mutex allows SchemaManager access
4. SchemaManager modifies Schema
5. Operation completes
6. SchemaManager releases lock
7. Mutex releases lock to Client

sequenceDiagram
    participant C as Client
    participant M as Mutex
    participant SM as SchemaManager
    participant S as Schema

    C->>M: Request Lock
    M->>M: Acquire Lock
    M->>SM: Allow Access
    SM->>S: Modify Schema
    S-->>SM: Operation Complete
    SM-->>M: Release Lock
    M-->>C: Lock Released

Data Operations Pattern

When performing data operations, the system follows this sequence:

1. Client sends read request to AtomRef
2. AtomRef retrieves latest Atom version
3. Latest Atom returns data to Client
4. Client sends update request to AtomRef
5. Client creates new Atom version
6. New Atom links to previous version
7. AtomRef updates pointer to new version

sequenceDiagram
    participant C as Client
    participant AR as AtomRef
    participant A1 as Atom v1
    participant A2 as Atom v2

    C->>AR: Read Request
    AR->>A2: Get Latest
    A2-->>C: Return Data
    C->>AR: Update Request
    C->>A2: Create New Version
    A2->>A1: Link Previous
    AR->>A2: Update Pointer

Component Architecture

The concurrency components interact in this structure:

classDiagram
    class Mutex {
        +acquire()
        +release()
        +tryLock()
    }
    class SchemaManager {
        -mutex: Mutex
        +modifySchema()
        +readSchema()
    }
    class AtomRef {
        +atomicUpdate()
        +lockFreeRead()
    }
    SchemaManager --> Mutex
    SchemaManager --> Schema
    AtomRef --> Atom

Safety Mechanisms

Deadlock Prevention

The system prevents deadlocks through:

• Resource ordering - Acquires resources in consistent order
• Timeout mechanisms - Prevents indefinite waiting
• Lock hierarchy - Establishes clear lock acquisition order
• Deadlock detection - Identifies potential deadlock situations

Race Condition Handling

The system handles race conditions through:

• Atomic compare-and-swap - Ensures consistent updates
• Version verification - Validates data version before updates
• Retry mechanisms - Attempts operations again after conflicts
• Conflict resolution - Resolves conflicting changes

Performance Optimization

1. Optimization Strategies

The system optimizes performance through:

• Minimized lock contention - Reduces waiting for locks
• Efficient resource utilization - Maximizes resource usage
• Lock-free algorithms - Avoids locks when possible
• Optimistic concurrency control - Assumes conflicts are rare

2. Scalability Features

The system supports scalability through:

• Parallel operation support - Enables simultaneous operations
• Resource pooling - Manages shared resources efficiently
• Connection management - Handles multiple connections
• Load distribution - Spreads work across resources

Best Practices

Development Guidelines

Follow these guidelines when developing with FoldDB:

1. Use appropriate lock granularity
2. Implement proper error handling
3. Monitor lock contention
4. Test concurrent scenarios
5. Document thread safety requirements

Operation Recommendations

Follow these recommendations when operating FoldDB:

1. Minimize critical section size
2. Use appropriate isolation levels
3. Handle timeouts properly
4. Implement retry strategies
5. Monitor system performance