Projections in Event Sourcing: Build ANY model you want!

Projections in Event Sourcing are a way to derive the current state from an event stream. This can be done asynchronously as events are persisted to an event stream which can update a projection. You don’t need to replay all the events in an event stream to get to the current state for a UI every time you need to display data. This could be very inefficient if you have a lot of events in a stream. Rather, create a projection that represents the current state and keep it updated as events occur.

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Projections in Event Sourcing

Projections are a primary pattern you’ll likely use with Event Sourcing. It’s the answer to the most common question I get about event sourcing which is: How do you build out UI? If you have to replay all the events in an event stream to get to the current state, isn’t that very inefficient when it comes to displaying in a UI or reporting?

The answer, depending on your situation, could be yes. It could be very inefficient to have to replay an entire event stream to get to the current state.

This is where projections come in.

Data Transformation

Really a projection is transforming an event stream into another model. That other model could be almost anything depending on the events in your stream.

This is a stream of events for a specific product in a warehouse. Our event streams are per unique aggregate. In this case it’s for the product that’s identified with a SKU of ABC123

We can turn these series of events into a model that could be used for display purposes. The most obvious is probably to show users the current quantity on hand.

If we process these events we can derive these events into a current state that looks like this:

Our current state for the quantity is 59. If we process each event and keep track of the quantity (10 + 5 – 6 + 50) we would come to this final state.

The beauty of event sourcing is that you can create many different models. For example, we could also derive the event stream into this state:

Projections in Event Sourcing

In the above, we’re simply breaking out by keeping track of Received, Shipped, and Adjusted all separately.

As another example, we could keep track of product aging. Meaning how long is the oldest product in the warehouse from when it was received.

Event Consumers

Now before we get to actually building projections, you need to deliver/publish events to consumers that will process those events to update their projection of the current state.

There are a couple ways to accomplish this.

The first is to simply use a message broker that publishes events after they are saved to the event stream.

If you’re crossing a boundary, you likely don’t want to expose the event your persisting to your event stream. That would be leaking data internal to your domain. You’d likely want to transform that event into an integration event that you have versioning and contracts defined for.

The second option is if your consumers are within your boundary, and your database/event store supports it, is to use the event stream directly.

Products like EventStoreDB support two types of subscriptions: Persistent and Catch-up.

Subscriptions

Persistent subscriptions mean that you have competing consumers to a subscription group. As events occur, the event will be published to one consumer in the group that will process the message. This is similar to how you would use a message broker, except the event store is the broker. The event store keeps track of which subscription group has processed which message in the stream.

Catch-up subscriptions work a bit differently as the consumer must ask the event store to send events from a particular version onwards. The consumer must keep track of which message (version) of the stream it has processed. Once the consumer is caught up and processed all the messages that have occurred since the one it requested, the event store will send new messages to the consumer. Again, the consumer must keep track of which index/version it has processed because once it re-connects (for whatever reason) it needs to tell the event store where to start in the event stream.

Source Code

Developer-level members of my CodeOpinion YouTube channel get access to the full source in this post available in a git repo. Check out the membership for more info.

Building Projections

For my example, I’m using the first example I showed with a project that is keeping track of the current quantity for a product (by SKU).

I’m using Entity Framework and here’s my simple Entity and DbContext.

Every time a new event is appended to our event stream, it will publish this event which will be consumed by our ProjectionBuilder.ReceiveEvent()

ReceiveEvent() will determine which event type it is, then call the appropriate Apply() method. Each Apply() method fetches the appropriate record from our database, then updates the appropriate property/column. Then of course save the changes.

Now if we wanted to display the quantity on hand for a product, we would simply query DbContext by SKU and have to Subtract the Shipped from the Received amount. We do not need to go to the event store, reply to all the events to get to the current state. We already have it.

Demo App

I’ve created a simple console application that has all the code above in an interactive way. Developer-level members of my CodeOpinion YouTube channel get access to the full source and demo available in a git repo. Check out the membership for more info.

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Event Sourcing Example & Explained in plain English

What is Event Sourcing? It’s a way of storing data that is probably very different than what you’re used to. I’ll explain the differences and show ab event sourcing example that should clear up all the mystery around it.

YouTube

Check out my YouTube channel where I post all kinds of content that accompanies my posts including this video showing everything that is in this post.

Source Code

Developer-level members of my CodeOpinion YouTube channel get access to the full source in this post available in a git repo. Check out the membership for more info.

Current State

The vast majority of apps persist current state in a database. Regardless if you’re using a relational database (RDBMS) or a document store (NoSQL), you’re likely used to storing current state.

To illustrate this, here’s a table that represents products.

Event Sourcing

If we were to have some behavior in our system that is to receive product into the warehouse, we would increment the quantity value. So for example, if we received more quantity for SKU ABC123, we would update quantity value. If we shipped product out of the warehouse, we would decrease the quantity value.

One question to ask from the table above, how did we get to the current state of Quantity of 59 for product ABC123?

Because we only record current state, we have no way to know with absolutely certainty how we got to that number.

Yes, if added logging you could infer with some degree of certainty how you got to a particular state. However, it would not be guaranteed because it actually requires you to write logs in every place that you’re changing state, include outside of your application. This could be incredibly difficult. Ultimately your current state is the point of truth, no matter how you got to that state.

Event Sourcing

Event Sourcing is a different approach to storing data. Instead of storing the current state, you’re instead going to be storing events. Events represent the state transitions of things that have occurred in your system.

They are facts.

To illustrate the exact same product of SKU ABC123 that had a current state quantity of 59, this is how we would be storing this data using event sourcing.

It’s important to note that events are persisted in what is called an event stream. Event streams are generally per unique aggregate. So in my example, a single product SKU. The above is the stream of events for SKU ABC123.

With the above events, we can see that we Received a quantity of 10. Then we Received 5 more. Followed up by having Shipped out 6. Finally there some extra quantity that was magically found in the warehouse so it was adjusted by another 50. This got us to our current state of 59.

Event Sourcing Implementation

First is to define the events that occur that we want to record. Events are facts that something has occurred. They are generally the result of a state changes from commands. Here’ are the 3 events I’ve defined in our the event stream.

Next comes our aggregate. It is responsible for creating events that will get persisted to the event stream. The aggregate exposes methods to perform commands/actions to our domain. If our business logic passes, then we’ve confirmed that an event has occured.

When an event is added, we call the appropriate Apply() method. These methods are to keep track of the current state within our aggregate so we can perform the relevant business logic (which throws an InvalidDomainException).

Repository

For demo purposes, I’m not using an actual database to store our event stream, but rather just in-memory dictionary and list to illustrate. The important part is your repository is responsible two things, building your aggregate and saving the events from your aggregate.

When you want to build/get a WarehouseProduct from the Repository, it will get the events from the event stream, then call ApplyEvent() for each existing event. This is replaying all the events in the aggregate to get back to current state.

Then after you have called commands like ShipProduct/ReceiveProduct/AdjustInventory, the new events will get appended to the event stream from the Repositories Save() method.

Projections

The current state used in the aggregate is called a projection. It represents the current state of the event stream. I’ve covered more about projections and how they are used in UI and reporting to build many different models from your event stream.

Demo App

I’ve created a simple console application that has all the code above in an interactive way. Developer-level members of my CodeOpinion YouTube channel get access to the full source and demo available in a git repo. Check out the membership for more info.

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Event Sourcing: Projections with Liquid Projections

Liquid Projections

Projections are an important yet pretty simple concept when working with event-centric or event sourcing systems. The concept is to build a state from a stream of events. In my previous post, Event Sourcing with SQL Stream Store, I made a pretty basic projection to keep the current account balance. In this post, I’ll use Liquid Projections to accomplish the same task.

I recommend checking out my post on SQL Stream Store as I’m using the same example/demo application in this post.

Liquid Projections

Liquid Projection is a library for building projections. The concept and API are pretty simple, and I’ll cover the basics in this post.

First I’ll update my Demo Application to use the Liquid Projections NuGet package.

Event Map

The first building block is creating an event map. The idea is to map an event to an action that we want to be invoked when the event occurs. We can use the EventMapBuild<TContext> to create all of our event mappings. The TContext can be anything but I’ll be using it to mutate the state that represents the current balance.

As a refresher from my previous post, here is the Balance

Now using the EventMapBuilder<Balance> to handle the Deposited and Withdrawn events.

You’ll notice call Build() on the EventMapBuilder<Balance> which will return us the EventMap<Balance>. At this point, you can call Handle() to pass in the events incoming from our subscription with our current Balance.

Conditions

There are also some nice additions such as providing conditions for when to execute a map. For example, if you wanted to handle only deposited events where the amount was greater than 100.

Inheritance

There is also support for inheritance, which means since my Deposited and Withdrawn events inherit from the AccountEvent base class, I could also have done

Event Store Integration

The next on my list is write this up directly with to something like Event Store or SQL Stream Store. Stay tuned.

Check out Liquid Projections on GitHub for more.

All the source code shown in this post is available on GitHub.

If you’d like a more detailed contented related to various aspects of event sourcing, let me know in the comments or on twitter.

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