My question here is quite straight as mentioned in the subject.
However, please allow me to give some brief explanation here about my innocent thoughts.
I've been using Axon for approximately 10 months now. I used to design my project structure based on the Hexagonal architecture with two top level packages respectively for domain and infrastructure.
Furthermore, domain package will contain different domain objects (as explained in the DDD concept) such as follow:
Aggregate (this will be an Axon aggregate class).
Repository (in my case, this will be a Spring Data Repository interface).
Entity (in my case, this contains any lookup entity that i used for set-based consistency validation as written here).
Service Port (collection of Input and Ouput port interfaces).
Commands (representing Axon Command object).
As for Events, I used to put them on a different module that I compiled as a jar file, so I can share it to other developers whom going to use the same event in their project.
I've noticed recently that all of my commands and events were basically anemic models (an anti pattern that we should avoid).
Is there any good practice on this ? Or, Is it something that intentionally used by design ?
I've been thinking to put my Command classes within my Aggregate class (as an inner classes). At least by using this approach I won't end-up with having so many anemic models scattered outside. Any thoughts ?
Commands are designed to be behavior and input structures mirroring the external world. They don't necessarily mirror an aggregate's structure.
They are not even connected clearly to one single aggregate, at times. Enclosing them within aggregates can be a code smell because you are then thinking in terms of resources and UI organization, instead of transaction boundaries and entity groups.
You are also violating the open-closed principle. Changes in volatile layers like user interface and request structures will make you edit the Aggregate class, and that is not good design.
On a more general note...
At times, this debate of anemic vs. non-anemic (or dry vs. non-dry) can push you in the direction of premature - and incorrect - optimization. Try avoiding this trap because you will end up optimising at the code level, but your domain will suffer.
DDD and CQRS guidelines align with principles that help you keep complexity at bay over the long term. Things kept distinct and separate help you achieve this.
First of all, in DDD, your domain had to be free of any frameworks, just use pure language library.
Then, mixing Commands and Aggregates cannot be a good solution. I think Commands belongs to Port while Aggregates belongs to the Hexagone.
Finally, DDD highlights the discovery of the domain thanks to the experts. Did you do that ? If not, if you're only using the Tacticts pattern, you'll miss one of the most important part of DDD.
Related
I am trying to learn about details of domain driven design and i came to this question.
I found many examples with:
Defining repository interface within the domain
Defining repository implementation somewhere else
Inject repository interface into aggregate root
On the other hand, there are examples that strictly go against it and do all repository related stuff from service.
I cannot find authoritive answer and explanation: is it considered a bad practice and if so - why?
I cannot find authoritive answer and explanation: is it considered a bad practice and if so - why?
Yes, mostly because a number of different concerns get confused.
Aggregates define a consistency boundary; any change of state should be restricted to a collection of related entities that are all part of the same aggregate. So once you have looked up the first one (the "root" entity), you should be able to achieve the change without needing to examine any data other than this graph of domain entities and the arguments that you have been passed.
Put another way, Repository is a plumbing concern, not a domain concern. Your domain entities are responsible for expressing your domain, without infrastructure concerns getting mixed in.
To have, for example, Aggregate.Save() method that would inside use IRepository interface to save.
Aggregate.Save() definitely indicates a problem. Well, two problems, to be precise: Save probably isn't part of your ubiquitous language, and for that matter its likely that Aggregate isn't either.
Save isn't a domain concern, it's a persistence concern - it just copies data from your in memory representation (volatile storage) to a durable representation (stable storage). Your domain model shouldn't need to know anything about that.
One of the reasons you found "many examples with" is that getting these concerns separated correctly is hard; meaning you really need to think deeply about the problem to tease them apart. Most examples don't, because teasing things apart isn't critical when you always deploy everything together.
I'm breaking my system into (at least) two bounded-contexts: study-design and survey-planning.
There's a concept named "subject" (potential subject for interviewing) in the study-design context. We also maintain associations between subjects and populations in that domain.
Now, in the survey-planning, we also need (some) information about the subject (for example: for planning a visit, or even for anticipated selection of questionnaire, in case the population the subject belongs to is known beforehand).
So, I need that "subject" in both contexts.
What approach should I pick? Having a shared kernel, as explained in Eric Evans DDD book? I don't mind (at least for now) having the two contexts sharing the same database.
Or... should I go pure microservice? Meaning: those two can't / shouldn't share database..., and in that case I might have to go the mirroring / duplicating route through event passing: https://www.infoq.com/news/2014/11/sharing-data-bounded-contexts
Any thoughts on which one is better, for the above situation?
Thanks!
The context for microservices is distributed systems. In any other situation it would probably be overkill. Shared kernel will eventually split. That is usually the case. You may start from it. Nothing wrong with that. However, it will not stay there.
I recommend that you choose a event-driven solution, but not necessarily to use microservices. You could build an event-driven monolith in order to spend much less time on synchronizing the two models. When the application grows too big then you split the monolith into microservices. You could use CQRS to split event more the models into write and read. If you use event-sourcing things get even more interesting.
In my experience, with shared kernel, the models become god objects, one-size-fits-all kind of objects.
In my opinion, you have three entities:
study
survey
person
It is pretty intuitive to see that each of these is its own aggregate root. So then we are talking about inter-root relationships. In my experience, those are meaningful entities on their own, and cleanest and most future proof by far is to treat those relationships as independent aggregate roots.
The relationship between a study and a person is perhaps called TestSubject, and the relationship between a person and a survey could be called Interviewee or something similar. In another context, the person could be an employee for a company, and then the Employee would be its own aggregate root. Information that only relates to the relationship and not to the person or the study say, should be limited to this relationship specific aggregate root. This could for instance be the start date at which the subject started to take part in the test, and the end date (when he dropped out, if he or she dropped out prematurely, etc.)
As for storage, all aggregate roots should define their own separate repositories as interfaces and know only those interfaces, but the implementation of those interfaces is free to choose to use the same database or different ones, or even different kinds, local or distributed, etc. So this holds for these 'relational' aggregate roots as well. But you should almost force yourself to use different databases and preferably even different technologies (e.g. one EntityFramework, the other MongoDb) when you start with this, to force yourself to make sure your interfaces are properly defined and independent of implementation.
And yes, big fan of CQRS as well here, and Event/Command Sourcing as well. There are many light-weight implementations possible that allow you to upscale, but are very easy to get into and afford you almost completely linear (=predictable) complexity.
You can start with microservices that share a monolithic data source, but only use partial domain entities and value objects
I have seen ORM use a unit of work to commit multiple repositories in a single step.
I have also seen DDD and the use of aggregate roots saved via repositories, when using event stores persistence conceptually becomes quite clear to understand.
I always need to write data access code and whilst I am familiar with ORM, I am new to domain driven design and event sourcing - event sourcing is great, but does come with a lot of infrastructure.
Ultimately I would like to some rules to help decide at what point (code size, number of database entities) when DDD+ES becomes worth the extra effort over CRUD systems.
To help decide my questions are as follows:
I haven't seen aggregate roots combined in to a single unit of work, is this avoided? If so what problems can this cause?
In DDD a customer entity may have addresses and phones embedded within it (value objects), whereas in ORM there is a unit of work with customer, phone and address repositories. What is the best way to explain and understand these different approaches?
Can ORM use multiple different unit of works (each referencing relevant and related repositories/tables) to represent an aggregate root?
What are the pain/warning signs to look out for with impedance mismatch from my domain to ORM, at which point we may consider switching to an event store?
An aggregate defines a consistency boundary. In NoSQL databases, it is usually not possible to commit multiple entities per transaction. Therefore, in DDD with NoSQL, it is desirable to only have a single aggregate in a unit of work while updates to entities external to the aggregate at hand are delivered in an eventually consistent manner.
If addresses and phones are value objects then they shouldn't have repositories. In the ORM, they would be mapped as components of a parent entity not a separate mapping.
I'm not sure what you'd achieve this way?
One pain point that naturally leads to event sourcing is the need to preserve all state changes in an aggregate. Furthermore, event sourcing and the concept of domain events in general provide a different domain modelling methodology focused on behavior rather than state. I'd consider ES when there is potential business value in preserving all state changes. If you are willing to make the initial infrastructure investment, ES can in many ways be simpler by avoiding ORM madness. Think of CRUD as event sourcing with only 4 event types, or even 2 (read, update). Beyond the most basic domains, it is desirable to have more context beyond changes to data which leads you to ES.
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)
After reading Evan's and Nilsson's books I am still not sure how to manage Data access in a domain driven project. Should the CRUD methods be part of the repositories, i.e. OrderRepository.GetOrdersByCustomer(customer) or should they be part of the entities: Customer.GetOrders(). The latter approach seems more OO, but it will distribute Data Access for a single entity type among multiple objects, i.e. Customer.GetOrders(), Invoice.GetOrders(), ShipmentBatch.GetOrders() ,etc. What about Inserting and updating?
CRUD-ish methods should be part of the Repository...ish. But I think you should ask why you have a bunch of CRUD methods. What do they really do? What are they really for? If you actually call out the data access patterns your application uses I think it makes the repository a lot more useful and keeps you from having to do shotgun surgery when certain types of changes happen to your domain.
CustomerRepo.GetThoseWhoHaventPaidTheirBill()
// or
GetCustomer(new HaventPaidBillSpecification())
// is better than
foreach (var customer in GetCustomer()) {
/* logic leaking all over the floor */
}
"Save" type methods should also be part of the repository.
If you have aggregate roots, this keeps you from having a Repository explosion, or having logic spread out all over: You don't have 4 x # of entities data access patterns, just the ones you actually use on the aggregate roots.
That's my $.02.
DDD usually prefers the repository pattern over the active record pattern you hint at with Customer.Save.
One downside in the Active Record model is that it pretty much presumes a single persistence model, barring some particularly intrusive code (in most languages).
The repository interface is defined in the domain layer, but doesn't know whether your data is stored in a database or not. With the repository pattern, I can create an InMemoryRepository so that I can test domain logic in isolation, and use dependency injection in the application to have the service layer instantiate a SqlRepository, for example.
To many people, having a special repository just for testing sounds goofy, but if you use the repository model, you may find that you don't really need a database for your particular application; sometimes a simple FileRepository will do the trick. Wedding to yourself to a database before you know you need it is potentially limiting. Even if a database is necessary, it's a lot faster to run tests against an InMemoryRepository.
If you don't have much in the way of domain logic, you probably don't need DDD. ActiveRecord is quite suitable for a lot of problems, especially if you have mostly data and just a little bit of logic.
Let's step back for a second. Evans recommends that repositories return aggregate roots and not just entities. So assuming that your Customer is an aggregate root that includes Orders, then when you fetched the customer from its repository, the orders came along with it. You would access the orders by navigating the relationship from Customer to Orders.
customer.Orders;
So to answer your question, CRUD operations are present on aggregate root repositories.
CustomerRepository.Add(customer);
CustomerRepository.Get(customerID);
CustomerRepository.Save(customer);
CustomerRepository.Delete(customer);
I've done it both ways you are talking about, My preferred approach now is the persistent ignorant (or PONO -- Plain Ole' .Net Object) method where your domain classes are only worried about being domain classes. They do not know anything about how they are persisted or even if they are persisted. Of course you have to be pragmatic about this at times and allow for things such as an Id (but even then I just use a layer super type which has the Id so I can have a single point where things like default value live)
The main reason for this is that I strive to follow the principle of Single Responsibility. By following this principle I've found my code much more testable and maintainable. It's also much easier to make changes when they are needed since I only have one thing to think about.
One thing to be watchful of is the method bloat that repositories can suffer from. GetOrderbyCustomer.. GetAllOrders.. GetOrders30DaysOld.. etc etc. One good solution to this problem is to look at the Query Object pattern. And then your repositories can just take in a query object to execute.
I'd also strongly recommend looking into something like NHibernate. It includes a lot of the concepts that make Repositories so useful (Identity Map, Cache, Query objects..)
Even in a DDD, I would keep Data Access classes and routines separate from Entities.
Reasons are,
Testability improves
Separation of concerns and Modular design
More maintainable in the long run, as you add entities, routines
I am no expert, just my opinion.
The annoying thing with Nilsson's Applying DDD&P is that he always starts with "I wouldn't do that in a real-world-application but..." and then his example follows. Back to the topic: I think OrderRepository.GetOrdersByCustomer(customer) is the way to go, but there is also a discussion on the ALT.Net Mailing list (http://tech.groups.yahoo.com/group/altdotnet/) about DDD.