In the context of event replay, snapshots refer to a technique for improving the efficiency of replaying events for aggregates that have a large number of events associated with them. Rather than replaying all events from the beginning of time to reconstruct the current state of the aggregate, a snapshot is taken periodically and stored alongside the events. This snapshot represents the state of the aggregate at the time it was taken.

When replaying events, the snapshot is used as a starting point instead of the beginning of time, and only events that occurred after the snapshot are replayed. This can significantly reduce the amount of work required to reconstruct the current state of the aggregate.

The frequency at which snapshots are taken depends on factors such as the size of the aggregate, the rate at which events are generated, and the available computing resources. Snapshots are usually taken after a certain number of events have been processed or after a certain amount of time has elapsed since the last snapshot.

In summary, snapshots are a technique used to optimize event replay in event-sourced systems by reducing the amount of work required to reconstruct the current state of an aggregate.

Example

Let’s say we have an event-sourced aggregate Order with a large number of events associated with it. The Order has a list of OrderLineItem objects, which themselves have a list of Product objects.

Without snapshots, during event replay we would need to load and process every single event for the Order, its OrderLineItems, and its Products. This could take a significant amount of time and consume a lot of resources.

Snapshots provide a way to optimize this process. We can take a “snapshot” of the aggregate’s current state at certain points in time and save it to a separate store, along with the ID of the last event processed. Then, during event replay, we can start from the latest snapshot and only process the events that have occurred since then.

For example, we might take a snapshot of an Order after it has been updated with a new OrderLineItem, and then save it to a snapshot store. If we need to replay events for that Order, we can start from the snapshot and only process events that occurred after that point.

This approach can significantly reduce the amount of time and resources required for event replay, especially for aggregates with a large number of events.