Event Processing

Understanding how reducers process events is crucial for building effective read models. This guide covers the event processing model, method patterns, and advanced techniques.

Event Processing Model

Event Method Discovery

Reducers use convention-based method discovery. Chronicle automatically finds and invokes methods that:

Match the event type name (e.g., OnOrderCreated for OrderCreated events)
Accept the event type as the first parameter
Accept the current read model state (nullable) as the second parameter
Optionally accept EventContext as the third parameter

public record OrderSummary(Guid OrderId, decimal Total, DateTimeOffset LastUpdated);

public class OrderSummaryReducer : IReducerFor<OrderSummary>
{
    public OrderSummary OnOrderCreated(OrderCreated @event, OrderSummary? current, EventContext context)
    {
        return new OrderSummary(@event.OrderId, 0m, context.Occurred);
    }

    public OrderSummary OnItemAdded(ItemAdded @event, OrderSummary? current, EventContext context)
    {
        if (current is null) return null!; // Skip if no order exists

        return current with
        {
            Total = current.Total + @event.Price,
            LastUpdated = context.Occurred
        };
    }
}

Event Source Isolation

Each reducer method is called for a single event source:

Events for the same event source (e.g., the same order) are processed sequentially
The current parameter contains the current state for that specific event source
Each event source has its own independent state

Sequential Processing

Events are guaranteed to be processed in sequence order:

Events are ordered by their sequence number
Each method is called once per event
The return value becomes the current parameter for the next event

Method Signatures

Basic Synchronous Pattern

The simplest pattern accepts the event and current state:

public TReadModel OnEventName(EventType @event, TReadModel? current)
{
    // Process event and return new state
    return newState;
}

Pattern with Event Context

Access event metadata by adding EventContext parameter:

public TReadModel OnEventName(EventType @event, TReadModel? current, EventContext context)
{
    // Access occurred time, correlation ID, etc.
    return newState;
}

Async Patterns

Both patterns support async methods:

// Async without context
public Task<TReadModel> OnEventName(EventType @event, TReadModel? current)
{
    return Task.FromResult(newState);
}

// Async with context
public async Task<TReadModel> OnEventName(EventType @event, TReadModel? current, EventContext context)
{
    // Perform async operations
    return await ComputeStateAsync(@event, current);
}

Event Context

The EventContext provides metadata about the event:

public record EventContext
{
    public EventSequenceNumber SequenceNumber { get; }
    public EventSourceId EventSourceId { get; }
    public EventType EventType { get; }
    public DateTimeOffset Occurred { get; }
    public CorrelationId CorrelationId { get; }
    public CausationId CausationId { get; }
    public Identity CausedBy { get; }
    // ... and more
}

Using Event Context

public OrderSummary OnOrderPlaced(OrderPlaced @event, OrderSummary? current, EventContext context)
{
    return new OrderSummary(
        OrderId: @event.OrderId,
        Total: @event.Amount,
        PlacedAt: context.Occurred,
        PlacedBy: context.CausedBy.ToString(),
        CorrelationId: context.CorrelationId);
}

Current State Parameter

The current parameter represents the previously computed state for this event source.

First Event

When processing the first event for an event source:

current is null
Initialize your read model with appropriate values
You can return null! to skip creating state for certain events

public Analytics OnDataRecorded(DataRecorded @event, Analytics? current, EventContext context)
{
    if (current is null)
    {
        // First event - initialize state
        return new Analytics(
            EventCount: 1,
            FirstEventTime: context.Occurred,
            LastEventTime: context.Occurred,
            TotalValue: @event.Value);
    }

    // Update existing state
    return current with
    {
        EventCount = current.EventCount + 1,
        LastEventTime = context.Occurred,
        TotalValue = current.TotalValue + @event.Value
    };
}

Subsequent Events

For subsequent events:

current contains the state from the previous event
Use record's with expression to create modified copies
Return the new state

Processing Patterns

Pattern 1: Accumulation

Accumulate values across events:

public record Statistics(decimal Sum, int Count, decimal Average);

public class StatisticsReducer : IReducerFor<Statistics>
{
    public Statistics OnMetricRecorded(MetricRecorded @event, Statistics? current)
    {
        var sum = (current?.Sum ?? 0) + @event.Value;
        var count = (current?.Count ?? 0) + 1;

        return new Statistics(sum, count, sum / count);
    }
}

Pattern 2: State Transitions

Track state changes through events:

public record OrderStatus(string State, DateTimeOffset LastUpdated);

public class OrderStatusReducer : IReducerFor<OrderStatus>
{
    public OrderStatus OnOrderCreated(OrderCreated @event, OrderStatus? current, EventContext context)
        => new OrderStatus("Created", context.Occurred);

    public OrderStatus OnOrderPaid(OrderPaid @event, OrderStatus? current, EventContext context)
        => new OrderStatus("Paid", context.Occurred);

    public OrderStatus OnOrderShipped(OrderShipped @event, OrderStatus? current, EventContext context)
        => new OrderStatus("Shipped", context.Occurred);

    public OrderStatus OnOrderDelivered(OrderDelivered @event, OrderStatus? current, EventContext context)
        => new OrderStatus("Delivered", context.Occurred);

    public OrderStatus OnOrderCancelled(OrderCancelled @event, OrderStatus? current, EventContext context)
        => new OrderStatus("Cancelled", context.Occurred);
}

Pattern 3: Collection Building

Build collections from events:

public record Activity(string Type, DateTimeOffset Timestamp, string Description);
public record CustomerActivityLog(List<Activity> Activities);

public class CustomerActivityLogReducer : IReducerFor<CustomerActivityLog>
{
    public CustomerActivityLog OnCustomerAction(CustomerAction @event, CustomerActivityLog? current, EventContext context)
    {
        var activities = current?.Activities ?? new List<Activity>();

        activities.Add(new Activity(
            @event.Type,
            context.Occurred,
            @event.Description));

        return new CustomerActivityLog(activities);
    }
}

Pattern 4: Time-Based Aggregation

Aggregate events within time windows:

public record HourlyMetrics(Dictionary<int, decimal> MetricsByHour);

public class HourlyMetricsReducer : IReducerFor<HourlyMetrics>
{
    public HourlyMetrics OnMetricRecorded(MetricRecorded @event, HourlyMetrics? current, EventContext context)
    {
        var metricsByHour = current?.MetricsByHour ?? new Dictionary<int, decimal>();
        var hour = context.Occurred.Hour;

        if (!metricsByHour.ContainsKey(hour))
            metricsByHour[hour] = 0;

        metricsByHour[hour] += @event.Value;

        return new HourlyMetrics(metricsByHour);
    }
}

Pattern 5: Conditional Processing

Skip processing based on conditions:

public record Account(Guid AccountId, decimal Balance, bool IsActive);

public class AccountReducer : IReducerFor<Account>
{
    public Account OnAccountOpened(AccountOpened @event, Account? current, EventContext context)
    {
        return new Account(@event.AccountId, 0m, true);
    }

    public Account OnDepositMade(DepositMade @event, Account? current, EventContext context)
    {
        // Skip if account doesn't exist or is not active
        if (current is null || !current.IsActive) return null!;

        return current with { Balance = current.Balance + @event.Amount };
    }

    public Account OnAccountClosed(AccountClosed @event, Account? current, EventContext context)
    {
        if (current is null) return null!;

        return current with { IsActive = false };
    }
}

Error Handling

Handling Invalid State

Return null! to skip creating/updating state:

public OrderSummary OnItemAdded(ItemAdded @event, OrderSummary? current, EventContext context)
{
    // Can't add items if order doesn't exist
    if (current is null) return null!;

    return current with
    {
        Total = current.Total + @event.Price
    };
}

Recording Errors in State

Include error information in your read model:

public record ValidationResult(bool IsValid, List<string> Errors);

public class ValidationResultReducer : IReducerFor<ValidationResult>
{
    public ValidationResult OnInvalidDataDetected(InvalidDataDetected @event, ValidationResult? current)
    {
        var errors = current?.Errors ?? new List<string>();
        errors.Add(@event.Reason);

        return new ValidationResult(false, errors);
    }
}

Performance Optimization

Minimize Object Creation

Leverage record types with with expressions:

// Efficient - only creates new object when needed
public Stats OnMetricRecorded(MetricRecorded @event, Stats? current)
{
    if (current is null)
        return new Stats(Count: 1, Sum: @event.Value);

    return current with
    {
        Count = current.Count + 1,
        Sum = current.Sum + @event.Value
    };
}

Reuse Collections

Be mindful of collection modifications:

public record ItemList(List<Item> Items);

public ItemList OnItemAdded(ItemAdded @event, ItemList? current)
{
    // Reuse existing list
    var items = current?.Items ?? new List<Item>();
    items.Add(new Item(@event.ItemId, @event.Name));

    return new ItemList(items);
}

Best Practices

Use record types - Prefer immutable record types for read models
Keep logic pure - Avoid side effects; only compute state from events
Handle null safely - Always check current for null on first event
Use with expressions - Leverage record's with for clean state updates
Return null! to skip - Use null! to skip creating/updating state
Access context when needed - Use EventContext for metadata like timestamps
Name methods clearly - Use descriptive method names that match event types
Test thoroughly - Unit test with various event sequences and edge cases

Table of Contents

Event Processing