I am building Microservices. One of my MicroService is using CQRS and Event sourcing. Integration events are raised in the system and i am saving my aggregates in event store also updating my read model.
My questions is why we need version in aggregate when we are updating the event stream against that aggregate ? I read we need this for consistency and events are to be replayed in sequence and we need to check version before saving (https://blog.leifbattermann.de/2017/04/21/12-things-you-should-know-about-event-sourcing/) I still can't get my head around this since events are raised and saved in order , so i really need concrete example to understand what benefit we get from version and why we even need them.
Many thanks,
Imran
Let me describe a case where aggregate versions are useful:
In our reSove framework aggregate version is used for optimistic concurrency control.
I'll explain it by example. Let's say InventoryItem aggregate accept commands AddItems and OrderItems. AddItems increases number of items in stock, OrderItems - decreases.
Suppose you have an InventoryItem aggregate #123 with one event - ITEMS_ADDED with quantity of 5. Aggregate #123 state say there are 5 items in stock.
So your UI is showing users that there are 5 items in stock. User A decide to order 3 items, user B - 4 items. Both issue OrderItems commands, almost at the same time, let's say user A is first by couple milliseconds.
Now, if you have a single instance of aggregate #123 in memory, in the single thread, you don't have a problem - first command from user A would succeed, event would be applied, state say quantity is 2, so second command from user B would fail.
In a distributed or serverless system where commands from A and B would be in separate processes, both commands would succeed and bring aggregate into incorrect state if we don't use some concurrency control. There several ways to do this - pessimistic locking, command queue, aggregate repository or optimistic locking.
Optimistic locking seems to be simplest and most practical solution:
We say that every aggregate has a version - number of events in its stream. So our aggregate #123 has version 1.
When aggregate emits an event, this event data has an aggregate version. In our case ITEMS_ORDERED events from users A and B will have event aggregate version of 2. Obviously, aggregate events should have versions to be sequentially increasing. So what we need to do is just put a database constraint that tuple {aggregateId, aggregateVersion} should be unique on write to event store.
Let's see how our example would work in a distributed system with optimistic concurrency control:
User A issues a command OrderItem for aggregate #123
Aggregate #123 is restored from events {version 1, quantity 5}
User B issues a command OrderItem for aggregate #123
Another instance of Aggregate #123 is restored from events (version 1, quantity 5)
Instance of aggregate for user A performs a command, it succeeds, event ITEMS_ORDERED {aggregateId 123, version 2} is written to event store.
Instance of aggregate for user B performs a command, it succeeds, event ITEMS_ORDERED {aggregateId 123, version 2} it attempts to write it to event store and fails with concurrency exception.
On such exception command handler for user B just repeats the whole procedure - then Aggregate #123 would be in a state of {version 2, quantity 2} and command will be executed correctly.
I hope this clears the case where aggregate versions are useful.