An anemic model is a model without ...
"Anemic domain model is the use of a software domain model where the domain objects contain little or no business logic (validations, calculations, business rules etc.)."
Is a DTO an anemic model without business Logic? And, again, a balie object without its business Logic?
First of all let's split behavior in two: behavior for read and behavior for write so we speak the same language.
Is a DTO an anemic model without business Logic?
You cannot say that a DTO is anemic or not because a DTO is immutable and anemy makes sense only in the mutating/write side of an architecture (for example the Command side in CQRS) but if we force the term a little the yes, a DTO is anemic and has no behavior (neither read nor write) by definition: "DTO does not have any behavior except for storage and retrieval of its own data".
A Value object has behavior (behavior for read). For example, it implements the behavoir to test if two value objects are equal or not.
To extend the answer a little, Aggregate roots and nested Entities have behavior for the write side (all kinds of validations).
Related
When looking at the post "Should Entities in Domain Driven Design and Entity Framework be the same?" the accepted answer states that domain entities and EF Entities can only be the same when using code first. This so that the entities can remain "pure".
However, because of this inpediment: "Discussion on many-to-Many relationships (without CLR class for join table)" it is not possible to create an order entity with a collection of product entities without specifying a special entity for the association table (orderline entity).
I now see colleagues taking these association tables into their domain entities and i feel that is wrong because it hints towards coping with persistence and not towards being true to the domain. They are not "pure" anymore in my opinion.
Would you say that it is impossible to have the same Domain entities in EF Core because of the association table entities? How can i cope with this in EF Core?
But in a regular/classic Ordering domain there is a need for an orderline (or order-line-item or whatever you want to call it) because you need to store the quantity and the item price along the product ID.
In most DDD examples this item is a Value object from the DDD point of view and an Entity from the Persistence point of view. If you are wondering how a Value object could be an ORM Entity you should read Persisting Value Objects from the book Implementing Domain Driven Design by Vaughn Vernon.
There are, however cases when the Domain model does not fit 100% percent with the Persistence model. In such cases one needs to attach some meta information to the Domain models in order to match the Persistence models. In general you have two options:
you can add the metadata to some external files, like XML-files;
it has the advantage that it keeps the Domain model agnostic in regard to the persistence but
it has the disadvantage that one must remember to change the external files when the Domain model changes
you can annotate the Domain models
it has the advantage that it is easy to change at the same time the Domain model and the Persistence model by having the information in the same file; it follows the principle: "things that change together stay together" (Common Closure Principle)
it has the disadvantage that it pollutes the Domain model with Infrastructure concerns
If I have to choose, I tend to choose to annotate the Domain models, but you should make that decision by yourself.
While i am practicing DDD in my software projects, i have always faced the question of "Why should i implement my business rules in the entities? aren't they supposed to be pure data models?"
Note that, from my understanding of DDD, domain models could be consist of persistent models as well as value objects.
I have come up with a solution in which i separate my persistent models from my domain models. On the other hand we have data transfer objects (DTO), so we have 3 layers of data mapping. Database to persistence model, persistence model to domain models and domain models to DTOs. In my opinion, my solution is not an efficient one as too much hard effort must be put into it.
Therefore is there any better practice to achieve this goal?
Disclaimer: this answer is a little larger that the question but it is needed to understand the problem; also is 100% based on my experience.
What you are feeling is normal, I had the same feeling some time ago. This is because of a combination of architecture, programming language and used framework. You should try to choose the above tools as such that they give the code that is easiest to change. If you have to change 3 classes for each field added to an entity then this would be nightmare in a large project (i.e. 50+ entity types).
The problem is that you have multiple DTOs per entity/concept.
The heaviest architecture that I used was the Classic layered architecture; the strict version was the hardest (in the strict version a layer may access only the layer that is just before it; i.e. the User interface may access only the Application). It involved a lot of DTOs and translations as the data moved from the Infrastructure to the UI. The testing was also hard as I had to use a lot of mocking.
Then I inverted the dependency, the Domain will not depend on the Infrastructure. For this I defined interfaces in the Domain layer that were implemented in the Infrastructure. But I still needed to use mocking for them. Also, the Aggregates were not pure and they had side effects (because they called the Infrastructure, even it was abstracted by interfaces).
Then I moved the Domain to the very bottom. This made my Aggregates pure. I no longer needed to use mocking. But I still needed DTOs (returned by the Application layer to the UI and those used by the ORM).
Then I made the first leap: CQRS. This splits the models in two: the write model and the read model. The important thing is that you don't need to use DTOs for models anymore. The Aggregate (the write model) can be serialized as it is or converted to JSON and stored in almost any database. Vaughn Vernon has a blog post about this.
But the nicest are the Read models. You can create a read model for each use case. Being a model used only for read/query, it can be as simple/dump as possible. The read entities contain only query related behavior. With the right persistence they can be persisted as they are. For example, if you use MongoDB (or any document database), with a simple reflection based serializer you can have a very thin architecture. Thanks to the domain events, you won't need to use JOINS, you can have full data denormalization (the read entities include all the data they need).
The second leap is Event sourcing. With this you don't need a flat persistence for the Aggregates. They are rehydrated from the Event store each time they handle a command.
You still have DTOs (commands, events, read models) but there is only one DTO per entity/concept.
Regarding the elimination of DTOs used by the Presentation: you can use something like GraphSQL.
All the above can be made worse by the programming language and framework. Strong typed programming languages force you to create a type for each custom returned value. Some frameworks force you to return a custom serializable type in order to return them to REST over HTTP requests (in this way you could have self-described REST endpoints using reflection). In PHP you can simply use arrays with string keys as value to be returned by a REST controller.
P.S.
By DTO I mean a class with data and no behavior.
I'm not saying that we all should use CQRS, just that you should know that it exists.
Why should i implement my business rules in the entities? aren't they supposed to be pure data models?
Your persistence entities should be pure data models. Your domain entities describe behaviors. They aren't the same thing; it is a common pattern to have a bit of logic with in the repository to change one to the other.
The cleanest way I know of to manage things is to treat the persistent entity as a value object to be managed by the domain entity, and to use something like a data mapper for transitions between domain and persistence.
On the other hand we have data transfer objects (DTO), so we have 3 layers of data mapping. Database to persistence model, persistence model to domain models and domain models to DTOs. In my opinion, my solution is not an efficient one as too much hard effort must be put into it.
cqrs offers some simplification here, based on the idea that if you are implementing a query, you don't really need the "domain model" because you aren't actually going to change the supporting data. In which case, you can take the "domain model" out of the loop altogether.
DDD and data are very different things. The aggregate's data (an outcome) will be persisted somehow depending on what you're using. Personally I think in domain events so the resulting Domain Event is the DTO (technically it is) that can be stored directly in an Event Store (if you're using Event Sourcing) or act as a data source for your persistence model.
A domain model represents relevant domain behaviour with the domain state being the 'result'. An entity is concept which has an id, compared to a Value Object which represents a business semantic value only. An entity usually groups related value objects and consistency rules. Not all business rules are here , some of them make sense as a service.
Now, there is the case of a CRUD domain or CRUD modelling where basically all you have is some data structures plus some validation rules. No need to complicate your life here if the modeling is correct. Implement things as simple as possible.
Always think of DDD as a methodology to gather requirements and to structure information. Implementation as in code (design) is something different.
I am using Jimmy Bogard's lovely Automapper to map my API model to the POCO classes (domain model).
The API model does not contain certain attributes of the domain model which are necessary for the domain model to be in valid state. In this scenario, when Automapper finishes its job, I have a fully constructed domain model in an invalid state.
Not using Automapper is not an option because there are too many attributes to hand code.
So, here is my question:
How do I use automapper to create the object in this manner while leaving the domain model in a valid state.
Thanks
This is probably too long for a comment:
Although Jimmy's answer is correct it may imply that your design may not be as encapsulated as it could be since you are going to have to expose a lot of state. This may be why there are comments around "anemic" models and "not fit for purpose".
If you are focused on behaviour then you may have something, totally hypothetical, as follows to make your customer a Gold customer:
customer.MakeGold();
However, using state you would now have to expose attributes that allow you to map to a Gold status. Internally your customer may have checked certain other state to determine the validity of the Gold status whereas that validity check has now moved out of the domain in the way Jimmy says he makes sure that the state is correct before passing it to the domain.
This is not so much an auto-mapper issue as it is a design issue. It also seems to indicate that your API/Integration model may be more data-centric.
On the other hand, if you are mapping to, say, command-style value objects that are handed to the domain it may not be as bad as that :)
// map my APIActivationDetails to Activate --- however automapper does this :)
var activate = AutoMapper.Map<Activate>().From(apiActivationDetails);
customer.Activate(activate);
Come to think of it... this seems to be what Jimmy is saying :P
"to map my API model to the POCO classes (domain model)"
Why would you ever want to map command object (your API model) attributes to domain objects? If that's what you are aiming for you will mostly end up with over-engineered CRUD, but certainly not a DDD solution.
Behaviors should be explicitly declared on aggregates and aggregates are responsible for mutating their own internal state according to the business invariants they protect.
That way, domain model clients can clearly state their intention and this intention isin't lost through the business process.
You shouldn't try to shove data into aggregates, instead you should ask them to perform a task.
I validate the API model before it gets mapped into my domain model, whether I'm using AutoMapper or not. The API model represents a command or action, so I'm validating the command before I apply it to my entity, not mutate my entity and then try to validate it afterwards. This also means all my validation attributes are on my API model.
From what I've read and implemented, DTO is the object that hold a subset of value from a Data model, in most cases these are immutable objects.
What about the case where I need to pass either new value or changes back to the database?
Should I work directly with the data model/actual entity from my DAL in my Presentation layer?
Or should I create a DTO that can be passed from the presentation layer to the business layer then convert it to an entity, then be updated in the DB via an ORM call. Is this writing too much code? I'm assuming that this is needed if the presentation layer has no concept of the data model. If we are going with this approach, should I fetch the object again at the BLL layer before committing the change?
A few thoughts :
DTO is a loaded term, but as it stands for Data Transfer Object, I see it more as a purely technical, potentially serializable container to get data through from one point to another, usually across tiers or maybe layers. Inside a layer that deals with business concerns, such as the Domain layer in DDD, these little data structures that circulate tend to be named Value Objects instead, because they have a business meaning and are part of the domain's Ubiquitous Language. There are all sorts of subtle differences between DTO's and Value Objects, such as you usually don't need to compare DTO's, while comparison and equality is an important concern in VO's (two VO's are equal if their encapsulated data is equal).
DDD has an emphasis on the idea of rich domain model. That means you usually don't simply map DTO's one-to-one to domain entities, but try to model business actions as intention-revealing methods in your entities. For instance, you wouldn't use setters to modify a User's Street, City and ZipCode but rather call a moveTo(Address newAddress) method instead, Address being a Value Object declared in the Domain layer.
DTO's usually don't reach the Domain layer but go through the filter of an Application layer. It can be Controllers or dedicated Application Services. It's Application layer objects that know how to turn DTO's they got from the client, into the correct calls to Domain layer Entities (usually Aggregate Roots loaded from Repositories). Another level of refinement above that is to build tasked-based UIs where the user doesn't send data-centric DTO's but Commands that reflect their end goal.
So, mapping DTO's to Entities is not really the DDD way of doing things, it denotes more of a CRUD-oriented approach.
Should I work directly with the data model/actual entity from my DAL in my Presentation layer?
This is okay for small to medium projects. But when you have a large project with more than 5 developers where different layers are assigned to different teams, then the project benefits from using a DTO to separate the Data Layer from the Presentation Layer.
With a DTO in the middle, any changes in the presentation layer won't affect the data layer (vice versa)
Or should I create a DTO that can be passed from the presentation layer to the business layer then convert it to an entity, then be updated in the DB via an ORM call. Is this writing too much code? I'm assuming that this is needed if the presentation layer has no concept of the data model. If we are going with this approach, should I fetch the object again at the BLL layer before committing the change?
For creating a new entity, then that is the usual way to go (for example "new user"). For updating an existing entity, you don't convert a DTO to an entity, rather you fetch the existing entity, map the new values then initiate an ORM update.
UpdateUser(UserDto userDto)
{
// Fetch
User user = userRepository.GetById(userDto.ID);
// Map
user.FirstName = userDTO.FirstName;
user.LastName = userDTO.LastName;
// ORM Update
userRepository.Update(user);
userRepository.Commit();
}
For large projects with many developers, the disadvantage of writing too much code is minimal compared to the huge advantage of decoupling it provides.
See my post about Why use a DTO
My opinion is that DTOs represent the contracts (or messages, if you will) that form the basis for interaction between an Aggregate Root and the outside world. They are defined in the domain, and the AR needs to be able to both handle incoming instances and provide outgoing instances. (Note that in most cases, the DTO instances will be either provided by the AR or handled by the AR, but not both, because having one DTO that flows both ways is usually a violation of separation of concerns.)
At the same time, the AR is responsible for providing the business logic through which the data contained in the DTOs are processed. The presentation layer (or any other actor including the data access layer, for that matter) is free to put whatever gibberish it wants into a DTO and request that the AR process it, and the AR must be able to interpret the contents of the DTO as gibberish and raise an exception.
Because of this requirement, it is never appropriate to simply map a DTO back to its Entity counterpart.
The DTO must always be processed through the logic in the AR in order to affect changes in the Entity that may bring it to the state described by the DTO.
When you are developing an architecture in OO/DDD style and modeling some domain entity e.g. Order entity you are putting whole logic related to order into Order entity.
But when the application becomes more complicated, Order entity collects more and more logic and this class becomes really huge.
Comparing with anemic model, yes its obviously an anti-pattern, but all that huge logic is separated in different services.
Is it ok to deal with huge domain entities or i understand something wrong?
When you are trying to create rich domain models, focus entities on identity and lifecyle, and thus try to avoid them becoming bloated with either properties or behavior.
Domain services potentially are a place to put behavior, but I tend to see a lot of domain service methods with behavior that would be better assigned to value objects, so I wouldn't start refactoring by moving the behavior to domain services. Domain services tend to work best as straightforward facades/adaptors in front of connections to things outside of the current domain model (i.e. masking infrastructure concerns).
You can also put behavior in Application services, but ask yourself whether that behavior belongs outside of the domain model or not. As a general rule, try to focus application services more on orchestration-style tasks that cross entities, domain services, repositories.
When you encounter a bloated entity then the first thing to do is look for sets of cohesive set of entity properties and related behavior, and make these implicit concepts explicit by extracting them into value objects. The entity can then delegate its behavior to these value objects.
Since we all tend to be more comfortable with entities, try to be more biased towards value objects so that you get the benefits of immutability, encapsulation and composability that value objects provide - moving you towards a more supple design.
Value objects enable you to incorporate a more functional style (eg. side-effect-free functions) into your domain model and thus free up your entities from having to deal with the complexity of adding complicated behavior to the burden of managing identity and lifecycle. See the pattern summaries for entities and value objects in Eric Evan's http://domainlanguage.com/ddd/patterns/ and the Blue Book for more details.
When you are developing an architecture in OO/DDD style and modeling
some domain entity e.g. Order entity you are putting whole logic
related to order into Order entity. But when the application becomes
more complicated, Order entity collects more and more logic and this
class becomes really huge.
Classes that have a tendency to become huge, are often the classes with overlapping responsibilities. Order is a typical example of a class that could have multiple responsibilities and that could play different roles in your application.
Given the context the Order appears in, it might be an Entity with mutable state (i.e. if you're managing Order's commercial condition, during a negotiation phase) but if you're application is managing logistics, an Order might play a different role: and an immutable Value Object might be the best implementation in the logistic context.
Comparing with anemic model, yes its
obviously an anti-pattern, but all that huge logic is separated in
different services.
...and separation is a good thing. :-)
I have got a feeling that the original model is probably data-centric and data serving different purposes (order creation, payment, order fulfillment, order delivery) is piled up in the same container (the Order class). Can't really say it from here, but it's a very frequent pattern. Not all of this data is useful for the same purpose at the same time.
Often, a bloated class like the one you're describing is a smell of a missing separation between Bounded Contexts, and/or an incomplete Aggregate separation within the same bounded context. I'd have a look to:
things that change together;
things that change for the same reason;
information needed to fulfill behavior;
and try to re-define aggregate boundaries accordingly. And also to:
different purposes for the application;
different stakeholders;
different implicit models/languages;
when it comes to discover the involved contexts.
In a large application you might have more than one model, thus leading to more than a single representation of a single domain concept, at least for concepts that are playing many roles.
This is complementary to Paul's approach.
It's fine to use services in DDD. You will commonly see services at the Domain, Application or Infrastructure layers.
Eric uses these guidelines in his book for spotting when to use services:
The operation relates to a domain concept that is not a natural part of an ENTITY or VALUE OBJECT.
The interface is defined in terms of other elements in the domain model
The operation is stateless