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.
Related
I am confused about how to treat strictly UI-related things, that won't be used in the business logic in the domain model: how to properly store them in the database?
If for example I have an aggregate which is an entity and the main purpose of this model is to do something with an important thing, should I include a title in the model even though it does not contribute to the business logic in any way? Does it matter if I want to store the title in the same table I store other data for my entity (e.g. important things)?
#Entity
MyAggregate:
id: ID
title: str
importantThing: ImportantThing
def doSomethingWithImportantThing():
...
And if I don't include a title in the model, then how to properly store it using Repository pattern? If I keep the title within my model my Repository could look like so:
#Repository
MyAggregateRepository:
def create(myAggregate: MyAggregate):
...
What would happen to repository if I remove title from the model? Should it transform like so:
#Repository
MyAggregateRepository:
def create(myAggregate: MyAggregate, title: str):
...
The rule of thumb is to keep only things that are necessary for making decisions and protecting invariants inside the aggregate state. Otherwise, aggregates get polluted by alien concerns and convert to a messy one-to-one representation of an over-growing database table or document.
As any rule, it has exceptions. I don't think it's a good idea going overboard from the start and splitting the entity prematurely.
However, if you feel that things get messy and you can see patterns that a group of fields are used in a group of functions, while another group of fields is solely used in a different set of functions, you might get an idea that your aggregate deserves splitting.
The repository pattern is largely relevant for executing commands. Its main purpose is to handle the aggregate persistence. When implementing queries, consider using CQRS and write queries that you need to write, it doesn't have to be the repository that handles queries. Queries are also idempotent and have no side effect (except the performance), so it is rather safe not to think about the domain model as such when writing queries. It's better to name your queries using the Ubiquitous Language though.
Things that are purely UI-related typically don't belong in the domain unless the domain is related to managing UI-related items, such as in the case of a localisation domain.
Data that belongs in the domain would stay in the domain. For instance, if there is a comment on an AccountTransaction, or some such, then that would be in the language used by the users of the system and not something that one could localize. However, if that transaction has a Type indicator that is either Debit or Credit then you wouldn't want to necessarily use a string representation but rather codify that; even if the "code" is Debit and Credit or Dr/Cr. However, the front-end would use some l10n or i18n mechanism to display the text for the Type in the relevant language.
Hopefully I understood your question correctly.
Keep title within the bounds of your model. There are a few reasons for this.
The utility of title is kept within the bounds of the model itself, since it does not serve any other purpose in the domain layer. It serves as "identity" that is merely local to the model itself, and then gets surfaced in the UI.
The title is not necessary for creating the aggregate, since it has no business logic intent. If it did, it would represent a tighter coupling between the model and the creation of the aggregate, which is typically undesirable.
title seems to be an aggregate invariant that you'd only want the aggregate root to be concerned with, and not a concern from a perspective of external access or creation.
Ultimately, this keeps your design cleaner.
We're refactoring our solution to a Domain Driven Design structure. Our consultants which implement the software, should be able to customize some behavior of the application (for specific customers needs). For example they want to add custom defined properties to the presentation (user input forms) and save the custom data together with the entities defined in our DDD projects.
However, the domain objects should preferably not contain a customData property. I don't want to mix those and let the domain object know that there's something like custom data. I'm saving en fetching the entities by Repositories.
How do I make this scenario possible? One possible solution would be:
Query the entity by using his Repository
And query separately the CustomPropertiesRepository by entity ID.
Combine the two queries objects.
When saving the forms. It will be splitted again using two repositories
The disadvantage of this, is that I have to query twice though it should be one document.
Any advice on this problem?
in general dynamic properties are better suited for data-centric design and in my opinion this practice is not suitable for DDD.
in DDD the code must reflect the knowledge of the domain, it must be simple and explicit.
before thinking of the best way to persist a dynamic property, you must solve the problem at the design level:
1-There are three possible artifacts for a property: aggregate root, entity or object value.
2-usually a dynamic property brings with it a functional need (calculation, validation ... etc), where you will implement this functionality? whether in the aggregate root or in a domain service you will be compelled to compile your code and here the dynamic propriety loses its meaning, unless you think use a Business rules engine, and there you introduce another new paradigm with its whole complication, and some of your business logic would be outside aggregates and domain services.
In many case, I need write a lot of class work with CRUD for some class. For example CRUD with pure object User, Book, Tag.
I usually make a directory named models, put all the CRUD classed into the models folder.
But I feel that the word model is not show essence. Is the word model well-defined in computer science? It means the pure object of User, or the means of CRUD of User?
I also use another name services for more complex logic, For example UserService may require other models than UserModel. But the word service is often conflict with some other case like an online service, backend service.
Are there any good names for the model and service in my case? BTW, I am most using Node.js; it may not conflict with the general conventions used in Node.js.
Ultimately, it will come down to what makes the code the most understandable both to you and to someone down the road who may have occasion to work on your code. If 'model' and 'services' convey the thought of what lies within in an obvious way to anyone coming in to the code, then they are probably fine. As far as standards, I don't know if there is a 'defined' set of names you have to use. In MVC, for example, you will use 'Models' as one of your folders in order to store all of the actual models you will be feeding your views, and this is understood in the MVC architecture that those names (Models, Views, Controllers) are the standard.
I agree with you that Model is a little ambiguous. Sometimes it is used to indicate domain objects such as User/Book/Tag, but sometimes it is used to indicate objects that deal with business logic, such as "Buying a book","Authenticating a user".
What's common to both uses is that "Model" is clearly separated from UI, that is handled entirely by the Views and the Controllers.
Another useful name is Entities. In Robert Martin's work on Object Oriented Design, he speaks of use-case-driven design, and distinguishes between three kinds of objects: Entity Objects, Interactor objects and Boundary objects.
Entity objects are useful in multiple use-cases. For example, in a book selling system, entities can be Book/User/Recommendation/Review.
Interactor objects implement use-cases, and they typically use multiple entity objects. For example, Purchase_Book/Login/Search_Books can be such objects.
Boundary objects are used for transferring data across module boundaries, and are used for building interfaces between parts of the system, which should be decoupled from one-another. For example, a controller may need to create a Purchase_Book object, and in order to create it, it needs to pass data about what book ID needs to be purchased, by what user ID, etc... and this data can be packed in a boundary object called Purchase_Request.
While Interactor and Boundary require more explanation, I find that the word Entities is meaningful and can be grasped intuitively without reading any explanation.
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
I've got a question on my mind that has been stirring for months as I've read about DDD, patterns and many other topics of application architecture. I'm going to frame this in terms of an MVC web application but the question is, I'm sure, much broader. and it is this: Does the adherence to domain entities create rigidity and inefficiency in an application?
The DDD approach makes complete sense for managing the business logic of an application and as a way of working with stakeholders. But to me it falls apart in the context of a multi-tiered application. Namely there are very few scenarios when a view needs all the data of an entity or when even two repositories have it all. In and of itself that's not bad but it means I make multiple queries returning a bunch of properties I don't need to get a few that I do. And once that is done the extraneous information either gets passed to the view or there is the overhead of discarding, merging and mapping data to a DTO or view model. I have need to generate a lot of reports and the problem seems magnified there. Each requires a unique slicing or aggregating of information that SQL can do well but repositories can't as they're expected to return full entities. It seems wasteful, honestly, and I don't want to pound a database and generate unneeded network traffic on a matter of principle. From questions like this Should the repository layer return data-transfer-objects (DTO)? it seems I'm not the only one to struggle with this question. So what's the answer to the limitations it seems to impose?
Thanks from a new and confounded DDD-er.
What's the real problem here? Processing business rules and querying for data are 2 very different concerns. That realization leads us to CQRS - Command-Query Responsibility Segregation. What's that? You just don't use the same model for both tasks: Domain Model is about behavior, performing business processes, handling command. And there is a separate Reporting Model used for display. In general, it can contain a table per view. These tables contains only relevant information so you can get rid of DTO, AutoMapper, etc.
How these two models synchronize? It can be done in many ways:
Reporting model can be built just on top of database views
Database replication
Domain model can issue events containing information about each change and they can be handled by denormalizers updating proper tables in Reporting Model
as I've read about DDD, patterns and many other topics of application architecture
Domain driven design is not about patterns and architecture but about designing your code according to business domain. Instead of thinking about repositories and layers, think about problem you are trying to solve. Simplest way to "start rehabilitation" would be to rename ProductRepository to just Products.
Does the adherence to domain entities create rigidity and inefficiency in an application?
Inefficiency comes from bad modeling. [citation needed]
The DDD approach makes complete sense for managing the business logic of an application and as a way of working with stakeholders. But to me it falls apart in the context of a multi-tiered application.
Tiers aren't layers
Namely there are very few scenarios when a view needs all the data of an entity or when even two repositories have it all. In and of itself that's not bad but it means I make multiple queries returning a bunch of properties I don't need to get a few that I do.
Query that data as you wish. Do not try to box your problems into some "ready-made solutions". Instead - learn from them and apply only what's necessary to solve them.
Each requires a unique slicing or aggregating of information that SQL can do well but repositories can't as they're expected to return full entities.
http://ayende.com/blog/3955/repository-is-the-new-singleton
So what's the answer to the limitations it seems to impose?
"seems"
Btw, internet is full of things like this (I mean that sample app).
To understand what DDD is, read blue book slowly and carefully. Twice.
If you think that fully fledged DDD is too much effort for your scenario then maybe you need to take a step down and look at something closer to Active Record.
I use DDD but in my scenario I have to support multiple front-ends; a couple web sites and a WinForms app, as well as a set of services that allow interaction with other automated processes. In this case, the extra complexity is worth it. I use DTO's to transfer a representation of my data to the various presentation layers. The CPU overhead in mapping domain entities to DTO's is small - a rounding error when compared to net work calls and database calls. There is also the overhead in managing this complexity. I have mitigated this to some extent by using AutoMapper. My Repositories return fully populated domain objects. My service layer will map to/from DTO's. Here we can flatten out the domain objects, combine domain objects, etc. to produce a more tabulated representation of the data.
Dino Esposito wrote an MSDN Magazine article on this subject here - you may find this interesting.
So, I guess to answer your "Why" question - as usual, it depends on your context. DDD maybe too much effort. In which case do something simpler.
Each requires a unique slicing or aggregating of information that SQL can do well but repositories can't as they're expected to return full entities.
Add methods to your repository to return ONLY what you want e.g. IOrderRepository.GetByCustomer
It's completely OK in DDD.
You may also use Query object pattern or Specification to make your repositories more generic; only remember not to use anything which is ORM-specific in interfaces of the repositories(e.g. ICriteria of NHibernate)