CQRS + EventSourcing. Change Aggregate Root history - domain-driven-design

I have following problem.
Given. CQRS + EventSourcing application.
How is that possible to change the state of the Aggregate root in history?
For example, accounting application, accounter wants to apply transation but with past date. The event which will be stored in Event Store will have the older date than recent events, but the sequense number of this event will be bigger.
Repository will restore the state of aggregate root by ordering events by sequence number. And if we will take the snapshot for this past date - we will have aggregate root without this event.
We can surely change the logic of repository to order events by date, but we use external framework for CQRS, and this is not desirable.
Are there some elegant solutions for this case?

What you're looking for is a bi-temporal implementation.
e.g. On dec 3rd we thought X == 12 (as-at), but on dec 5th we corrected the mistake and now know X == 14 on dec 3rd (as-of)
There are two ways to implement this
1) The event store holds as-at data and a projection holds as-of data (a possible variation is both an as-of and as-at projection as well)
2) The aggregate has an overloaded method indicating the desire for as-of vs as-at values from the event store. This will most likely involve using a custom secondary snapshot stream for as-of data values.
Your solution could very likely use both implementations as one is command focused and the other is query focused.
The as-of snapshots for the aggregate root in the second option would need to be rebuilt as corrective events are recieved.
Martin Folwler talks about this in this article
Note: The event store is still append only.

In accounting you'll probably end up in jail if you change past bookings. Don't change the past. Use compensating commands instead.
Sorry, but you brought up the accounting example, which is probably a domain that's very strict about fiddling with past data without making the changes explicit.
If the above doesn't apply to your domain you can easily apply new events on top of older ones that change the state (and possibly the history) of your domain objects.
Take a booking to an account for example. The event might have occurred today, but it can set the actual booking date to some time in the past.

You have stated that your business logic allows you to add a back-dated transaction; now I don't know why you'd want that, but there's nothing constraining your aggregate not to accept it. Of course the event will get a later event sequence number/version, but that's expected.
You don't need to fiddle with the infrastructure, repository or anything else to do this.

Accounting doesn't let you change history. It only lets you add entries. It's up to your business logic to interpret the dates on these events as you will. In this case, the sequence of events is not just a persistence trick as with event sourcing, but the actual content of the domain!

One solution to this is to think of the event as an explicit compensating action. For example, when your bank reverses a charge, they don't delete an existing transaction, they add a compensating transaction. This transaction may reference they transaction it wishes to compensate with respective dating. In this way, the events are a proper representation of reality.

Related

How to ensure data consistency between two different aggregates in an event-driven architecture?

I will try to keep this as generic as possible using the “order” and “product” example, to try and help others that come across this question.
The Structure:
In the application we have 3 different services, 2 services that follow the event sourcing pattern and one that is designed for read only having the separation between our read and write views:
- Order service (write)
- Product service (write)
- Order details service (Read)
The Background:
We are currently storing the relationship between the order and product in only one of the write services, for example within order we have a property called ‘productItems’ which contains a list of the aggregate Ids from Product for the products that have been added to the order. Each product added to an order is emitted onto Kafka where the read service will update the view and form the relationships between the data.
 
The Problem:
As we pull back by aggregate Id for the order and the product to update them, if a product was to be deleted, there is no way to disassociate the product from the order on the write side.
 
This in turn means we have inconsistency, that the order holds a reference to a product that no longer exists within the product service.
The Ideas:
Master the relationship on both sides, which means when the product is deleted, we can look at the associated orders and trigger an update to remove from each order (this would cause duplication of reference).
Create another view of the data that shows the relationships and use a saga to do a clean-up. When a delete is triggered, it will look up the view database, see the relationships within the data and then trigger an update for each of the orders that have the product associated.
Does it really matter having the inconsistencies if the Product details service shows the correct information? Because the view database will consume the product deleted event, it will be able to safely remove the relationship that means clients will be able to get the correct view of the data even if the write models appear inconsistent. Based on the order of the events, the state will always appear correct in the read view.
Another thought: as the aggregate Id is deleted, it should never be reused which means when we have checks on the aggregate such as: “is this product in the order already?” will never trigger as the aggregate Id will never be repurposed meaning the inconsistency should not cause an issue when running commands in the future.
Sorry for the long read, but these are all the ideas we have thought of so far, and I am keen to gain some insight from the community, to make sure we are on the right track or if there is another approach to consider.
 
Thank you in advance for your help.
Event sourcing suites very well human and specifically human-paced processes. It helps a lot to imagine that every event in an event-sourced system is delivered by some clerk printed on a sheet of paper. Than it will be much easier to figure out the suitable solution.
What's the purpose of an order? So that your back-office personnel would secure the necessary units at a warehouse, then customer would do a payment and you start shipping process.
So, I guess, after an order is placed, some back-office system can process it and confirm that it can be taken into work and invoicing. Or it can return the order with remarks that this and that line are no longer available, so that a customer could agree to the reduced order or pick other options.
Another option is, since the probability of a customer ordering a discontinued item is low, just not do this check. But if at the shipping it still occurs - then issue a refund and some coupon for inconvenience. Why is it low? Because the goods are added from an online catalogue, which reflects the current state. The availability check can be done on the 'Submit' button click. So, an inconsistency may occur if an item is discontinued the same minute (or second) the order has been submitted. And usually the actual decision to discontinue is made up well before the information was updated in the Product service due to some external reasons.
Hence, I suggest to use eventual consistency. Since an event-sourced entity should only be responsible for its own consistency and not try to fulfil someone else's responsibility.

Inferring the user intention from the event stream in an event store. Is this even a correct thing to do?

We are using an event store that stores a single aggregate - a user's order (imagine an Amazon order than can be updated at any moment by both a client or someone in the e-commerce company before it actually gets dispatched).
For the first time we're going to allow our company's employees to see the order's history, as until now they could only see its current state.
We are now realizing that the events that form up the aggregate root don't really show the intent or what the user actually did. They only serve to build the current state of the order when applied sequencially to an empty order. The question is: should they?
Imagine a user that initially had one copy of book X and then removed it and added 2 again. Should we consider this as an event "User added 1 book" or events "User removed 1 book" + "User added 2 books" (we seem to have followed this approach)?
In some cases we have one initial event that then is followed by other events. I, developer, know for sure that all these events were triggered by a single command, but it seems incredibly brittle for me to make that kind of assumptions when generating on the fly this "order history" functionality for the user to see. But if I don't treat them, at least in the order history feature as a single action, it will seem like there were lots of order amendments when in fact there was just one, big one.
Should I have "macro" events that contain "micro events" inside? Should I just attach the command's id to the event so I can then easily inferr what event happened at the same and which ones not (an alternative would be relying on timestamps.. but that's disgusting).
What's the standard approch to deal with this kind of situations? I would like to be able to look at any time to the aggregate's history and generate this report (I don't want to build the report incrementally every time the order is updated).
Thanks
Command names should ideally be descriptive of intent. Which should mean it's possible to create event names which make the original intent clear. As a rule of thumb, the events in the event stream should be understandable to the relevant members of the business. It's a good rule of thumb. It should contain stuff like 'cartUpdated' etc.
Given the above, I would have expected that the showing the event stream should be fine. But I totally get why it may not be ideal in some circumstances. I.e. it may be too detailed. In which case maybe create a 'summeriser' read model fed the events.
It is common to include the command’s ID in the resulting events’ metadata, along with an optional correlation ID (useful for long running processes). This then makes it easier to build the order history projection. Alternatively, you could just use the event time stamps to correlate batches in whatever way you want (perhaps you might only want one entry even for multiple commands, if they happened in a short window).
Events (past tense) do not always capture human - or system - user intent. Commands (imperative mood) do. As all command data cannot always be easily retraced from the events it generated, keeping a structured log of commands looks like a good option here.

How to implement Commands and Events for complex form using Event Sourcing?

I would like to implement CQRS and ES using Axon framework
I've got a pretty complex HTML form which represents recruitment process with six steps.
ES would be helpful to generate historical statistics for selected dates and track changes in form.
Admin can always perform several operations:
assign person responsible for each step
provide notes for each step
accept or reject candidate on every step
turn on/off SMS or email notifications
assign tags
Form update (difference only) is sent from UI application to backend.
Assuming I want to make changes only for servers side application, question is what should be a Command and what should be an Event, I consider three options:
Form patch is a Command which generates Form Update Event
Drawback of this solution is that each event handler needs to check if changes in form refers to this handler ex. if email about rejection should be sent
Form patch is a Command which generates several Events ex:. Interviewer Assigned, Notifications Turned Off, Rejected on technical interview
Drawback of this solution is that some events could be generated and other will not because of breaking constraints ex: Notifications Turned Off will succeed but Interviewer Assigned will fail due to assigning unauthorized user. Maybe I should check all constraints before commands generation ?
Form patch is converted to several Commands ex: Assign Interviewer, Turn Off Notifications and each command generates event ex: Interviewer Assigned, Notifications Turned Off
Drawback of this solution is that some commands can fail ex: Assign Interviewer can fail due to assigning unauthorized user. This will end up with inconsistent state because some events would be stored in repository, some will not. Maybe I should check all constraints before commands generation ?
The question I would call your attention to: are you creating an authority for the information you store, or are you just tracking information from the outside world?
Udi Dahan wrote Race Conditions Don't Exist; raising this interesting point
A microsecond difference in timing shouldn’t make a difference to core business behaviors.
If you have an unauthorized user in your system, is it really critical to the business that they be authorized before they are assigned responsibility for a particular step? Can the system really tell that the "fault" is that the responsibility was assigned to the wrong user, rather than that the user is wrongly not authorized?
Greg Young talks about exception reports in warehouse systems, noting that the responsibility of the model in that case is not to prevent data changes, but to report when a data change has produced an inconsistent state.
What's the cost to the business if you update the data anyway?
If the semantics of the message is that a Decision Has Been Made, or that Something In The Real World Has Changed, then your model shouldn't be trying to block that information from being recorded.
FormUpdated isn't a particularly satisfactory event, for the reason you mention; you have to do a bunch of extra work to cast it in domain specific terms. Given a choice, you'd prefer to do that once. It's reasonable to think in terms of translating events from domain agnostic forms to domain specific forms as you go along.
HttpRequestReceived ->
FormSubmitted ->
InterviewerAssigned
where the intermediate representations are short lived.
I can see one big drawback of the first option. One of the biggest advantage of CQRS/ES with Axon is scalability. We can add new features without worring about regression bugs. Adding new feature is the result of defining new commands, event and handlers for both of them. None of them should not iterfere with ones existing in our system.
FormUpdate as a command require adding extra logic in one of the handler. Adding new attribute to patch and in consequence to command will cause changes in current logic. Scalability is no longer advantage in that case.
VoiceOfUnreason is giving a very good explanation what you should think about when starting with such a system, so definitely take a look at his answer.
The only thing I'd like to add, is that I'd suggest you take the third option.
With the examples you gave, the more generic commands/events don't tell that much about what's happening in your domain. The more granular events far better explain what exactly has happened, as the event message its name already points it out.
Pulling Axon Framework in to the loop, I can also add a couple of pointers.
From a command message perspective, it's safe to just take a route and not over think it to much. The framework quite easily allows you to adjust the command structure later on. In Axon Framework trainings it is typically suggested to let a command message take the form of a specific action you're performing. So 'assigning a person to a step would typically be a AssignPersonToStepCommand, as that is the exact action you'd like the system to perform.
From events it's typically a bit nastier to decide later on that you want fine grained or generic events. This follows from doing Event Sourcing. Since the events are your source of truth, you'll thus be required to deal with all forms of events you've got in your system.
Due to this I'd argue that the weight of your decision should lie with how fine grained your events become. To loop back to your question: in the example you give, I'd say option 3 would fit best.

Aggregate Root including tremendous number of children

I wonder how to model Calendar using DDD and CQRS. My problem consist in increasing number of events. I consider Calendar as Aggregate Root which contains Events (Calendar Events). I dont want to use ReadSide in my Commands but I need way to check events collisions at domain level.
I wonder how to model Calendar using DDD and CQRS. My problem consist in increasing number of events.
The most common answer to "long lived" aggregates is to break that lifetime into episodes. An example of this would be the temporary accounts that an accountant will close at the end of the fiscal year.
In your specific case, probably not "the Calendar" so much as "the February calendar", the "the March calendar", and so on, at whatever grain is appropriate in your domain.
Im not sure if Im right about DDD aproach in terms of validation. I believe the point is not to allow the model to enter into invalid state
Yes, but invalid state is a tricky thing to define. Udi Dahan offered this observation
A microsecond difference in timing shouldn’t make a difference to core business behaviors.
More succinctly, processing command A followed by processing command B produces a valid state, then it should also be true that you end up processing command B first, and then A.
Let's choose your "event collisions" example. Suppose we handle two commands scheduleMeeting(A) and scheduleMeeting(B), and the domain model understands that A and B collide. Riddle: how do we make sure the calendar stays in a valid state?
Without loss of generality, we can flip a coin to decide which command arrives first. My coin came up tails, so command B arrives first.
on scheduleMeeting(B):
publish MeetingScheduled(B)
Now the command for meeting A arrives. If your valid calendars do not permit conflicts, then your implementation needs to look something like
on scheduleMeeting(A):
throw DomainException(A conflicts with B)
On the other hand, if you embrace the idea that the commands arrive shouldn't influence the outcome, then you need to consider another approach. Perhaps
on scheduleMeeting(A)
publish MeetingScheduled(A)
publish ConflictDetected(A,B)
That is, the Calendar aggregate is modeled to track not only the scheduled events, but also the conflicts that have arisen.
See also: aggregates and RFC 2119
Event could also an be an Aggregate root. I don't know your business constraint but I think that if two Events colide you could notify the user somehow to take manual actions. Otherwise, if you really really need them not to colide you could use snapshots to speed up the enormous Calendar AR.
I dont want to use ReadSide in my Commands but I need way to check events collisions at domain level.
You cannot query the read model inside the aggregate command handler. For the colision detection I whould create a special DetectColisionSaga that subscribes to the EventScheduled event and that whould check (possible async if are many Events) if a colision had occurred and notify the user somehow.

CQRS aggregates

I'm new to the CQRS/ES world and I have a question. I'm working on an invoicing web application which uses event sourcing and CQRS.
My question is this - to my understanding, a new command coming into the system (let's say ChangeLineItemPrice) should pass through the domain model so it can be validated as a legal command (for example, to check if this line item actually exists, the price doesn't violate any business rules, etc). If all goes well (the command is not rejected) - then the appropriate event is created and stored (for example LineItemPriceChanged)
The thing I didn't quite get is how do I keep this aggregate in memory to begin with, before trying to apply the command. If I have a million invoices in the system, should I playback the whole history every time I want to apply a command? Do I always save the event without any validations and do the validations when constructing the view models / projections?
If I misunderstood any part of the process I would appreciate your feedback.
Thanks for your help!
You are not alone, this is a common misunderstanding. Let me answer the validation part first:
There are 2 types of validation which take place in this kind of system. The first is the kind where you look for valid email addresses, numeric only or required fields. This type is done before the command is even issued. A command which contains these sorts of problems should not be raised as commands (for belt and braces you can check at the domain side but this is not a domain concern and you are better off just preventing this scenario).
The next type of validation is when it is a domain concern. It could be the kind of thing you mention where you check prices are within a set of specified parameters. This is a domain concept the business people would understand, do and be able to articulate.
The next phase is for the domain to apply the state change and raise the associated events. These are then persisted and on success, published for the rest of the app.
All of this is can be done with the aggregate in memory. The actions are coordinated with a domain service which handles the command. It loads the aggregate, apply's all it's past events (or loads a snapshot) then issues the command. On success of the command it requests all the new uncommitted events and tries to persist them. On success it publishes the new events.
As you see it only loads the events for that specific aggregate. Even with a lot of events this process is lightning fast. If performance is a problem there are strategies such as keeping aggregates in memory or snapshotting which you can apply.
To your last point about validating events. As they can only be generated by your aggregate they are trustworthy.
If you want more detail check out my overview of CQRS and ES here. And take a look at my post about how to build aggregate roots here.
Good luck - I hope they help!
It is right that you have to replay the event to 'rehydrate' the domain aggregate. But you don't have to replay all events for all invoices. If you store the entity id of the root aggregate in the events, you can just select and replay the events that with the relevant id.
Then, how do you find the relevant aggregate root id? One of the read repositories should contain the relevant information to get the id, based on a set of search criteria.

Resources