dotnet-cqrs/PHASE_7_SUMMARY.md

# Phase 7: Advanced Features - Implementation Summary

**Status**: ✅ **COMPLETED**

Phase 7 adds three advanced features to the Svrnty.CQRS event streaming framework: Event Sourcing Projections, SignalR Integration, and Saga Orchestration.

---

## 📊 Phase 7.1: Event Sourcing Projections

### Overview
Build materialized read models from event streams using the catch-up subscription pattern with checkpointing and automatic recovery.

### Key Components

#### Abstractions (`Svrnty.CQRS.Events.Abstractions/Projections/`)
- **`IProjection<TEvent>`** - Typed projection interface for specific event types
- **`IDynamicProjection`** - Dynamic projection handling multiple event types via pattern matching
- **`IResettableProjection`** - Optional interface for projections that support rebuilding
- **`IProjectionCheckpointStore`** - Persistent checkpoint storage interface
- **`IProjectionEngine`** - Core projection execution engine interface
- **`IProjectionRegistry`** - Thread-safe projection definition registry
- **`ProjectionOptions`** - Configuration: batch size, retry policy, polling interval

#### Core Implementation (`Svrnty.CQRS.Events/Projections/`)
- **`ProjectionEngine`** (~300 lines)
  - Catch-up subscription pattern
  - Exponential backoff retry: `delay = baseDelay × 2^attempt`
  - Batch processing with configurable size
  - Per-event or per-batch checkpointing
  - Continuous polling for new events
- **`ProjectionRegistry`** - Thread-safe ConcurrentDictionary-based registry
- **`InMemoryProjectionCheckpointStore`** - Development storage
- **`ProjectionHostedService`** - Auto-start background service

#### PostgreSQL Storage (`Svrnty.CQRS.Events.PostgreSQL/`)
- **Migration**: `007_ProjectionCheckpoints.sql`
  - Composite primary key: `(projection_name, stream_name)`
  - Tracks: last offset, events processed, error state
- **`PostgresProjectionCheckpointStore`**
  - UPSERT-based atomic updates: `INSERT ... ON CONFLICT ... DO UPDATE`
  - Thread-safe for concurrent projection instances

#### Sample Implementation (`Svrnty.Sample/Projections/`)
- **`UserStatistics.cs`** - Read model tracking user additions/removals
- **`UserStatisticsProjection.cs`** - Dynamic projection processing UserWorkflow events
- **Endpoint**: `GET /api/projections/user-statistics`

### Configuration Example
```csharp
services.AddProjections(useInMemoryCheckpoints: !usePostgreSQL);

if (usePostgreSQL)
{
    services.AddPostgresProjectionCheckpointStore();
}

services.AddDynamicProjection<UserStatisticsProjection>(
    projectionName: "user-statistics",
    streamName: "UserWorkflow",
    configure: options =>
    {
        options.BatchSize = 50;
        options.AutoStart = true;
        options.MaxRetries = 3;
        options.CheckpointPerEvent = false;
        options.PollingInterval = TimeSpan.FromSeconds(1);
    });
```

### Key Features
- ✅ Idempotent event processing
- ✅ Automatic checkpoint recovery on restart
- ✅ Exponential backoff retry on failures
- ✅ Projection rebuilding support
- ✅ Both typed and dynamic projections
- ✅ In-memory (dev) and PostgreSQL (prod) storage

---

## 🔄 Phase 7.2: SignalR Integration

### Overview
Real-time event streaming to browser clients via WebSockets using ASP.NET Core SignalR.

### Key Components

#### Package: `Svrnty.CQRS.Events.SignalR`
- **`EventStreamHub.cs`** (~220 lines)
  - Per-connection subscription tracking with `ConcurrentDictionary<connectionId, subscriptions>`
  - Independent Task per subscription with CancellationToken
  - Automatic cleanup on disconnect
  - Batch reading with configurable offset

#### Hub Methods
```csharp
// Client-callable methods
Task SubscribeToStream(string streamName, long? startFromOffset = null)
Task UnsubscribeFromStream(string streamName)

// Server-to-client callbacks
await Clients.Caller.SendAsync("SubscriptionConfirmed", streamName);
await Clients.Client(connectionId).SendAsync("EventReceived", streamName, eventData);
await Clients.Caller.SendAsync("Error", errorMessage);
```

### Registration Example
```csharp
// Server-side
services.AddEventStreamHub();
app.MapEventStreamHub("/hubs/events");

// Client-side (JavaScript)
const connection = new signalR.HubConnectionBuilder()
    .withUrl("/hubs/events")
    .build();

connection.on("EventReceived", (streamName, event) => {
    console.log("Received event:", event);
});

await connection.start();
await connection.invoke("SubscribeToStream", "UserWorkflow", 0);
```

### Key Features
- ✅ WebSocket-based real-time streaming
- ✅ Multiple concurrent subscriptions per connection
- ✅ Start from specific offset (catch-up + real-time)
- ✅ Automatic connection cleanup
- ✅ Thread-safe subscription management

---

## 🔀 Phase 7.3: Saga Orchestration

### Overview
Long-running business processes with compensation pattern (not two-phase commit). Steps execute sequentially; on failure, completed steps compensate in reverse order.

### Key Components

#### Abstractions (`Svrnty.CQRS.Events.Abstractions/Sagas/`)

**Core Interfaces:**
```csharp
public interface ISaga
{
    string SagaId { get; }
    string CorrelationId { get; }
    string SagaName { get; }
}

public interface ISagaStep
{
    string StepName { get; }
    Task ExecuteAsync(ISagaContext context, CancellationToken cancellationToken);
    Task CompensateAsync(ISagaContext context, CancellationToken cancellationToken);
}

public interface ISagaContext
{
    ISaga Saga { get; }
    SagaState State { get; }
    ISagaData Data { get; }
    T? Get<T>(string key);
    void Set<T>(string key, T value);
}
```

**State Machine:**
```
NotStarted → Running → Completed
                  ↓
            Compensating → Compensated
                  ↓
              Failed
```

**`ISagaOrchestrator`** - Lifecycle management:
- `StartSagaAsync<TSaga>()` - Initialize and execute
- `ResumeSagaAsync()` - Resume paused saga
- `CancelSagaAsync()` - Trigger compensation
- `GetStatusAsync()` - Query saga state

**`ISagaStateStore`** - Persistent state storage:
- `SaveStateAsync()` - UPSERT saga state
- `LoadStateAsync()` - Restore saga state
- `GetByCorrelationIdAsync()` - Multi-saga workflows
- `GetByStateAsync()` - Query by state

#### Core Implementation (`Svrnty.CQRS.Events/Sagas/`)

**`SagaOrchestrator.cs`** - Core execution engine:
- Fire-and-forget execution pattern
- Sequential step execution with checkpointing
- Reverse-order compensation on failure
- Saga instance reconstruction from snapshots
- Uses ActivatorUtilities for DI-enabled saga construction

**`SagaRegistry.cs`** - Thread-safe definition storage:
- ConcurrentDictionary-based
- Type-to-definition mapping
- Name-to-definition mapping
- Name-to-type mapping

**`SagaData.cs`** - In-memory data storage:
- Dictionary-based key-value store
- Type conversion support via `Convert.ChangeType`
- Serializable for persistence

**`InMemorySagaStateStore.cs`** - Development storage:
- ConcurrentDictionary for state
- Correlation ID indexing
- State-based queries

#### PostgreSQL Storage (`Svrnty.CQRS.Events.PostgreSQL/`)

**Migration**: `008_SagaState.sql`
```sql
CREATE TABLE saga_states (
    saga_id TEXT PRIMARY KEY,
    correlation_id TEXT NOT NULL,
    saga_name TEXT NOT NULL,
    state INT NOT NULL,
    current_step INT NOT NULL,
    total_steps INT NOT NULL,
    completed_steps JSONB NOT NULL,
    data JSONB NOT NULL,
    ...
);

CREATE INDEX idx_saga_states_correlation_id ON saga_states (correlation_id);
CREATE INDEX idx_saga_states_state ON saga_states (state);
```

**`PostgresSagaStateStore.cs`**:
- JSONB storage for steps and data
- UPSERT for atomic state updates
- Indexed queries by correlation ID and state

#### Sample Implementation (`Svrnty.Sample/Sagas/`)

**`OrderFulfillmentSaga`** - 3-step workflow:

1. **Reserve Inventory**
   - Execute: Reserve items in inventory system
   - Compensate: Release reservation

2. **Authorize Payment**
   - Execute: Get payment authorization from payment gateway
   - Compensate: Void authorization
   - **Failure Point**: Simulated via `FailPayment` flag for testing

3. **Ship Order**
   - Execute: Create shipment and get tracking number
   - Compensate: Cancel shipment

**Test Scenario: Payment Failure**
```
[Start] → Reserve Inventory ✅ → Authorize Payment ❌
                ↓
        Compensating...
                ↓
        Void Payment (skipped - never completed)
                ↓
        Release Inventory ✅
                ↓
        [Compensated]
```

### HTTP Endpoints
```
POST /api/sagas/order-fulfillment/start
  Body: {
    "orderId": "ORD-123",
    "items": [...],
    "amount": 99.99,
    "shippingAddress": "123 Main St",
    "simulatePaymentFailure": false
  }
  Response: { "sagaId": "guid", "correlationId": "ORD-123" }

GET /api/sagas/{sagaId}/status
  Response: {
    "sagaId": "guid",
    "state": "Running",
    "progress": "2/3",
    "currentStep": 2,
    "totalSteps": 3,
    "data": {...}
  }

POST /api/sagas/{sagaId}/cancel
  Response: { "message": "Saga cancellation initiated" }
```

### Registration Example
```csharp
// Infrastructure
services.AddSagaOrchestration(useInMemoryStateStore: !usePostgreSQL);

if (usePostgreSQL)
{
    services.AddPostgresSagaStateStore();
}

// Saga definition
services.AddSaga<OrderFulfillmentSaga>(
    sagaName: "order-fulfillment",
    configure: definition =>
    {
        definition.AddStep(
            stepName: "ReserveInventory",
            execute: OrderFulfillmentSteps.ReserveInventoryAsync,
            compensate: OrderFulfillmentSteps.CompensateReserveInventoryAsync);

        definition.AddStep(
            stepName: "AuthorizePayment",
            execute: OrderFulfillmentSteps.AuthorizePaymentAsync,
            compensate: OrderFulfillmentSteps.CompensateAuthorizePaymentAsync);

        definition.AddStep(
            stepName: "ShipOrder",
            execute: OrderFulfillmentSteps.ShipOrderAsync,
            compensate: OrderFulfillmentSteps.CompensateShipOrderAsync);
    });
```

### Key Features
- ✅ Compensation pattern (not 2PC)
- ✅ Sequential execution with checkpointing
- ✅ Reverse-order compensation
- ✅ Persistent state across restarts
- ✅ Correlation ID for multi-saga workflows
- ✅ State-based queries
- ✅ Pause/resume support
- ✅ Manual cancellation
- ✅ In-memory (dev) and PostgreSQL (prod) storage

---

## 📦 New Packages Created

### Svrnty.CQRS.Events.SignalR
- **Purpose**: Real-time event streaming to browser clients
- **Dependencies**: ASP.NET Core SignalR, Svrnty.CQRS.Events.Abstractions
- **Key Type**: `EventStreamHub`

---

## 🗄️ Database Migrations

### 007_ProjectionCheckpoints.sql
```sql
CREATE TABLE projection_checkpoints (
    projection_name TEXT NOT NULL,
    stream_name TEXT NOT NULL,
    last_processed_offset BIGINT NOT NULL DEFAULT -1,
    last_updated TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    events_processed BIGINT NOT NULL DEFAULT 0,
    last_error TEXT NULL,
    last_error_at TIMESTAMPTZ NULL,
    CONSTRAINT pk_projection_checkpoints PRIMARY KEY (projection_name, stream_name)
);
```

### 008_SagaState.sql
```sql
CREATE TABLE saga_states (
    saga_id TEXT PRIMARY KEY,
    correlation_id TEXT NOT NULL,
    saga_name TEXT NOT NULL,
    state INT NOT NULL,
    current_step INT NOT NULL,
    total_steps INT NOT NULL,
    completed_steps JSONB NOT NULL DEFAULT '[]'::jsonb,
    data JSONB NOT NULL DEFAULT '{}'::jsonb,
    started_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    last_updated TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    completed_at TIMESTAMPTZ NULL,
    error_message TEXT NULL
);

CREATE INDEX idx_saga_states_correlation_id ON saga_states (correlation_id);
CREATE INDEX idx_saga_states_state ON saga_states (state);
```

---

## 🎯 Testing the Implementation

### Test Projection
```bash
# Start the application
cd Svrnty.Sample
dotnet run

# Query projection status
curl http://localhost:6001/api/projections/user-statistics
```

### Test SignalR (JavaScript)
```javascript
const connection = new signalR.HubConnectionBuilder()
    .withUrl("http://localhost:6001/hubs/events")
    .build();

connection.on("EventReceived", (streamName, event) => {
    console.log(`[${streamName}] ${event.EventType}:`, event.Data);
});

await connection.start();
await connection.invoke("SubscribeToStream", "UserWorkflow", 0);
```

### Test Saga - Success Path
```bash
curl -X POST http://localhost:6001/api/sagas/order-fulfillment/start \
  -H "Content-Type: application/json" \
  -d '{
    "orderId": "ORD-001",
    "items": [
      {
        "productId": "PROD-123",
        "productName": "Widget",
        "quantity": 2,
        "price": 49.99
      }
    ],
    "amount": 99.98,
    "shippingAddress": "123 Main St, City, ST 12345",
    "simulatePaymentFailure": false
  }'

# Check status
curl http://localhost:6001/api/sagas/{sagaId}/status
```

### Test Saga - Compensation Path
```bash
curl -X POST http://localhost:6001/api/sagas/order-fulfillment/start \
  -H "Content-Type: application/json" \
  -d '{
    "orderId": "ORD-002",
    "items": [...],
    "amount": 99.98,
    "shippingAddress": "123 Main St",
    "simulatePaymentFailure": true
  }'

# Console output will show:
# [SAGA] Reserving inventory for order ORD-002...
# [SAGA] Inventory reserved: {guid}
# [SAGA] Authorizing payment for order ORD-002: $99.98...
# [ERROR] Payment authorization failed: Insufficient funds
# [SAGA] COMPENSATING: Releasing inventory reservation {guid}...
# [SAGA] COMPENSATING: Inventory released
# [SAGA] Saga 'order-fulfillment' compensation completed
```

---

## 📊 Build Status

**Solution Build**: ✅ **SUCCESS**
- **Projects**: 12 (including new SignalR package)
- **Errors**: 0
- **Warnings**: 20 (package pruning + API deprecation warnings)
- **Build Time**: ~2 seconds

---

## 🎓 Key Design Patterns

### Event Sourcing Projections
- **Pattern**: Catch-up Subscription
- **Retry**: Exponential Backoff
- **Persistence**: Checkpoint-based Recovery

### SignalR Integration
- **Pattern**: Observer (Pub/Sub)
- **Lifecycle**: Per-Connection Management
- **Concurrency**: CancellationToken-based

### Saga Orchestration
- **Pattern**: Saga (Compensation-based)
- **Execution**: Sequential with Checkpointing
- **Recovery**: Reverse-order Compensation
- **Not Used**: Two-Phase Commit (2PC)

---

## 📝 Next Steps

Phase 7 is complete! The framework now includes:
1. ✅ Event Sourcing Projections for building read models
2. ✅ SignalR Integration for real-time browser notifications
3. ✅ Saga Orchestration for long-running workflows

All implementations support both in-memory (development) and PostgreSQL (production) storage backends.

**Future Enhancements:**
- Projection snapshots for faster rebuilds
- Saga timeout handling
- SignalR backpressure management
- Distributed saga coordination
- Projection monitoring dashboard