Most DDD Books (e.g. Patterns and Principles of DDD) recommend strongly to load the whole aggregate when getting the data from the database. The reason for that is that aggregates are consistent boundaries.
But there common cases where this would result in overwhelming performance problems.
Here is a real example I am facing:
I have an aggregate root which is an workobject entity with its properties. There are other entities in this aggregate:
List of attached documents of the workobject. Each document is an entity.(The class document contains the metadata of the real document).
List of comments. Each comment is an entity`.
List of activities. Each activity is an entity which represents an activity that is done on this workobject.
List of ArchivedFiles. Each ArchivedFile is an entity which represents an document which is already archived in an external system. (The class ArchivedFile contains the metadata of the real archived file)
These entities belong to the aggregate, because changes on the workobject would mostly affect the state of these entities, too.
Now I have the following problem:
In the UI, there is a place where a user gets all the workobjects that are in his/her inbox. This could be more than 100 workobjects or even more. But it does not make sense to load the whole aggregate (comments,activies,documents) for each workobject at that point. This would slow down the application resulting in a terrible user experience.
The idea is to show just the properties of the workobject to the user in a datagrid. If a user makes a specific event like clicking on a specific workobject, a specific form is loaded where detailed information of the specific workobject is loaded. That would be an appropriate point to load the whole aggregate (i.e., comments,activies,documents). But most of the DDD-Books (e.g. Patterns and Principles of DDD) warn to not use lazy loading inside an aggregate, but to load the whole aggregate when loading the aggregate root.
How should we solve this problem by still respecting the DDD-rules?
How should we solve this problem by still respecting the DDD-rules?
Usual answer: don't use the aggregate pattern when the thing you want is a report.
Lazy loading is a "code smell" when performing domain dynamics; if you are leaving a lot of data behind when making a change, that strongly suggests that the information left behind belongs in a different aggregate.
But for an operation that is effectively read only, like a report? We're not going to be changing anything, so we don't need the constraint that ensure that our changes our correct, so we don't need the information we use to describe the constraint.
For more ideas about separating reads from writes, review the patterns described under the umbrella cqrs ("command query responsibility segregation").
Related
I'm having trouble getting my head around how to use the repository pattern with a more complex object model. Say I have two aggregate roots Student and Class. Each student may be enrolled in any number of classes. Access to this data would therefore be through the respective repositories StudentRepository and ClassRepository.
Now on my front end say I want to create a student details page that shows the information about the student, and a list of classes they are enrolled in. I would first have to get the Student from StudentRepository and then their Classes from ClassRepository. This makes sense.
Where I get lost is when the domain model becomes more realistic/complex. Say students have a major that is associated with a department, and classes are associated with a course, room, and instructors. Rooms are associated with a building. Course are associated with a department etc.. etc..
I could easily see wanting to show information from all these entities on the student details page. But then I would have to make a number of calls to separate repositories per each class the student is enrolled in. So now what could have been a couple queries to the database has increased massively. This doesn't seem right.
I understand the ClassRepository should only be responsible for updating classes, and not anything in other aggregate roots. But does it violate DDD if the values ClassRepository returns contains information from other related aggregate roots? In most cases this would only need to be a partial summary of those related entities (building name, course name, course number, instructor name, instructor email etc..).
But then I would have to make a number of calls to separate repositories per each class the student is enrolled in. So now what could have been a couple queries to the database has increased massively. This doesn't seem right.
Yup.
But does it violate DDD if the values ClassRepository returns contains information from other related aggregate roots?
Nobody cares about "violate DDD". What we care about is: do you still get the benefits of the repository pattern if you start pulling in data from other aggregates?
Probably not - part of the point of "aggregates" is that when writing the business code you don't have to worry to much about how storage is implemented... but if you start mixing locked data and unlocked data, your abstraction starts leaking into the domain code.
However: if you are trying to support reporting, or some other effectively read only function, you don't necessarily need the domain model at all -- it might make sense to just query your data store and present a representation of the answer.
This substitution isn't necessarily "free" -- the accuracy of the information will depend in part on how closely your stored information matches your in memory information (ie, how often are you writing information into your storage).
This is basically the core idea of CQRS: reads and writes are different, so maybe we should separate the two, so that they each can be optimized without interfering with the correctness of the other.
Can DDD repositories return data from other aggregate roots?
Short answer: No. If that happened, that would not be a DDD repository for a DDD aggregate (that said, nobody will go after you if you do it).
Long answer: Your problem is that you are trying to use tools made to safely modify data (aggregates and repositories) to solve a problem reading data for presentation purposes. An aggregate is a consistency boundary. Its goal is to implement a process and encapsulate the data required for that process. The repository's goal is to read and atomically update a single aggregate. It is not meant to implement queries needed for data presentation to users.
Also, note that the model you present is not a model based on aggregates. If you break that model into aggregates you'll have multiple clusters of entities without "lines" between them. For example, a Student aggregate might have a collection of ClassEnrollments and a Class aggregate a collection of Atendees (that's just an example, note that modeling many to many relationships with aggregates can be a bit tricky). You'll have one repository for each aggregate, which will fully load the aggregate when executing an operation and transactionally update the full aggregate.
Now to your actual question: how do you implement queries for data presentation that require data from multiple aggregates? well, you have multiple options:
As you say, do multiple round trips using your existing repositories. Load a student and from the list of ClassEnrollments, load the classes that you need.
Use CQRS "lite". Aggregates and respositories will only be used for update operations and for query operations implement Queries, which won't use repositories, but access the DB directly, therefore you can join tables from multiple aggregates (Student->Enrollments->Atendees->Classes)
Use "full" CQRS. Create read models optimised for your queries based on the data from your aggregates.
My preferred approach is to use CQRS lite and only create a dedicated read model when it's really needed.
In the Guide/eBook: .NET Microservices: Architecture for Containerized .NET Applications (related to the eShopOnContainers) in the chapter "Designing the infrastructure persistence layer" (page 213) is explained in general how an aggregate root can perform CUD operations against a persistent data source.
Two important starting points are mentioned :
An aggregate is ignorant of methods of persistency and infrastructure following the Persistence Ignorance and the Infrastructure Ignorance principles (page 218). An aggregate is determined by the business and not by the infrastructure.
One should only define one repository per aggregate root to maintain transactional consistency between the objects within the aggregate (page 213)
Unfortunately, in all further examples that are mentioned the aggregate root and all underlying objects that fall under it are within one and the same persistent data source.
The pattern then is as follows:
A repository is created containing that aggregate
In this repository a Unit of Work is injected during creation. This Unit of Work contains methods such as SaveChangesAsync, SaveEntitiesAsync, Update
and so on.
In a command, the Unit of Work manages the transactions to
this one data source such as a database or similar.
I want to expand this pattern that the aggregate can write its data over 2 or more physical data sources depending on the underlying object type.
Starting from starting point 1, it is perfectly justified to have a root aggregate and its underlying object to be updated to different data sources depending on the type of underlying object. Examples mentioned are : a Database and an XML file, a database and a NOSQL 'database',a database and a service, a database and an IoT device. Because an aggregate must be ignorant to methods of persistence and infrastructure, to my opinion there is no need to argue about the design of the aggregate. I think nowhere in the book it is written that a aggregate root should persist within one data source.
At the same time, starting point 2 also seems perfectly justified. Because the complete set of objects within the aggregate root is edited, and the successful persistence of the entire package is coordinated from one repository and (preferably) from one Unit of Work.
The question is:
How deals Domain Driven Design if within the aggregate - depending on the type of the underlying object - it is hydrated over different data sources?
Should I use one custom Unit of Work and make the decision where to write to within this UoW ?
I'm aware of the next question , but having studied the code I think it only deals with inheritance of repositories that deal with different data sources, but still serving one data source at the time and that is not what I'm after.
I want to expand this pattern that the aggregate can write its data over 2 or more physical data sources depending on the underlying object type.
Why do you want to do that on purpose?
In most cases, the persistence implementation is chosen to serve the domain, rather than the other way around. So the happy path typically involves choosing a persistence solution that can record the state of the entire aggregate, and storing the entire thing within a single transaction.
So if you find yourself trying to store an aggregate in two different places, you should take a hard careful look at why.
One common answer is that you want to be able to query the aggregate state efficiently. cqrs is a common solution here - rather than persisting the aggregate in two different data stores, you persist it to one and replicate it to another. The queries can run very efficiently against the replica (although there is of course some additional latency between a change to the aggregate and the reflection of that change in the query results).
Another common answer is that you really have two aggregates that reference each other. Nothing wrong with storing two aggregates in different places. You may be better served by making the distinction between the two explicit in your code.
Dan Pritchett
Jimmy Bogard
How deals Domain Driven Design if within the aggregate - depending on the type of the underlying object - it is hydrated over different data sources?
Badly, just like everybody else.
I have seen lot of discussions regarding this topic but i couldn't get a convincing answer. The general advice is not to have repository inside a domain object. What about an aggregate root? Isnt it right to give the root the responsibility to manipulate the composed objects?
For example, i have a microservice which takes care of invoices. Invoice is an aggregate root which has the different products. There is no requirement for this service to give details about individual products. I have 2 tables, one to store invoice details and other to store products of those invoices. I have two repositories corresponding to the tables. I have injected product repository inside the invoice domain object. Is it wrong to do so?
I see some mistakes according to DDD principles in your question. Let me try to clarify some concepts to give you hand.
First, you mentioned you have an Aggregate Root which is Invoice, and then two different repositories. Having an Aggregate Root means that any change on the Entities that the Aggregate consists of should be performed via the Aggregate Root. Why? That's because you need to satisfy some business rule (invariant) that applies on the relation of those Entities. For instance, given the next business rule:
Winning auction bids must always be placed before the auction ends. If a winning bid is placed after an auction ends, the domain is in an invalid state because an invariant has been broken and the model has failed to correctly apply domain rules.
Here there is an aggregate consisting of Auction and Bids where the Auction is the Aggregate Root.
If you have a BidsRepository, you could easily do:
var newBid = new Bid(money);
BidsRepository->save(newBid);
And you were saving a Bid without passing the defined business rule. However, having the repository just for the Aggregate Root you are enforcing your design because you need to do something like:
var newBid = new Bid(money);
auction.placeBid(newBid);
auctionRepository.save(auction);
Therefore, you can check your invariant within the method placeBid and nobody can skip it if they want to place a new Bid. Afterwards you can save the info into as many tables as you want, that is an implementation detail.
Second, you said if it's wrong injecting the repository into a Domain class. Here a quick explanation:
The repository should depend on the object it returns, not the other way around. The reason for this is that your "domain object" (more on that later) can exist (and should be testable) without being loaded or saved (that is, having a dependency on a repository).
Basically your design says that in order to have an invoice, you need to provide a MySQL/Mongo/XXX instance connection which is an infrastructure detail. Your domain should not know anything about how it is persisted. Your domain knows about the behavior like in the scenario of the Auction and Bids.
These concepts just help you to create code easier to maintain as well as help you to apply best practices such as SRP (Single Responsibility Principle).
Yes, I think it is wrong.
Domain should match real business model and should not care how data is persisted. Even if data internally are stored in multiple tables, this should not affect domain objects in any way.
When you are loading aggregate root, you should load related entities as well in one go. For example, this can easily be achieved with Include keyword in Entity Framework if you are on .NET. By loading all the data you ensure that you have full representation of business entity at any given time and you don't have to query database anymore.
Any changes in related entities should be persisted together with aggregate root in one atomic operation (usually using transactions).
I'm currently designing a backend for a social networking-related application in REST. I'm very intrigued by the DDD principle. Now let's assume I have a User object who has a Collection of Friends. These can be thousands if the app and the user would become very successful. Every Friend would have some properties as well, it is basically a User.
Looking at the DDD Cargo application example, the fully expanded Cargo-object is stored and retrieved from the CargoRepository from time to time. WOW, if there is a list in the aggregate-root, over time this would trigger a OOM eventually. This is why there is pagination, and lazy-loading if you approach the problem from a data-centric point of view. But how could you cope with these large collections in a persistence-unaware DDD?
As #JefClaes mentioned in the comments: You need to determine whether your User AR indeed requires a collection of Friends.
Ownership does not necessarily imply that a collection is necessary.
Take an Order / OrderLine example. An OrderLine has no meaning without being part of an Order. However, the Customer that an Order belongs to does not have a collection of Orders. It may, possibly, have a collection of ActiveOrders if a customer is limited to a maximum number (or amount) iro active orders. Keeping a collection of historical orders would be unnecessary.
I suspect the large collection problem is not limited to DDD. If one were to receive an Order with many thousands of lines there may be design trade-offs but the order may much more likely be simply split into smaller orders.
In your case I would assert that the inclusion / exclusion of a Friend has very little to do with the consistency of the User AR.
Something to keep in mind is that as soon as you start using you domain model for querying your start running into weird sorts of problems. So always try to think in terms of some read/query model with a simple query interface that can access your data directly without using your domain model. This may simplify things.
So perhaps a Relationship AR may assist in this regard.
If some paging or optimization techniques are the part of your domain, it's nothing wrong to design domain classes with this ability.
Some solutions I've thought about
If User is aggregate root, you can populate your UserRepository with method GetUserWithFriends(int userId, int firstFriendNo, int lastFriendNo) encapsulating specific user object construction. In same way you can also populate user model with some counters and etc.
On the other side, it is possible to implement lazy loading for User instance's _friends field. Thus, User instance can itself decide which "part" of friends list to load.
Finally, you can use UserRepository to get all friends of certain user with respect to paging or other filtering conditions. It doesn't violate any DDD principles.
DDD is too big to talk that it's not for CRUD. Programming in a DDD way you should always take into account some technical limitations and adapt your domain to satisfy them.
Do not prematurely optimize. If you are afraid of large stress, then you have to benchmark your application and perform stress tests.
You need to have a table like so:
friends
id, user_id1, user_id2
to handle the n-m relation. Index your fields there.
Also, you need to be aware whether friends if symmetrical. If so, then you need a single row for two people if they are friends. If not, then you might have one row, showing that a user is friends with the other user. If the other person considers the first a friend as well, you need another row.
Lazy-loading can be achieved by hidden (AJAX) requests so users will have the impression that it is faster than it really is. However, I would not worry about such problems for now, as later you can migrate the content of the tables to a new structure which is unkown now due to the infinite possible evolutions of your project.
Your aggregate root can have a collection of different objects that will only contain a small subset of the information, as reference to the actual business objects. Then when needed, items can be used to fetch the entire information from the underlying repository.
In "DDD" what is the best patterns for handling different versions of your entities, e.g. Entities in a list vs the full object. I would like to avoid the overhead of getting properties I do not need when displaying the entities in a list
Would you have a separate entity type used in lists or just fill up your full entity type partially?
Would you use inheritance?
I understand your urge to create "views" of models in the domain, but would recommend against it. Personally, I use the entire entity inside of the domain, regardless of the situation. The entity is the entity, and anything less or more just does not feel clean. That does not mean that I can't use a reference to the entity to help focus my use of the items in the list, though.
The entity does not cross the domain boundary in my implementation. Instead, I return a type of DTO and have application services that can abstract a view from it. This allows, for example, allowing a presenter to generate the correct view model from a DTO and provide it to the view. I don't know if you are talking about operations in the domain services or in the application services, but there are a couple of things you can do that could be applied to either (or both).
You can do certain things to reduce the performance penalty of working with the entire entity in the domain layers, as well. One thing to look at is implementing some sort of cache-aside implementation. When an entity is requested, check to see if it is cached. If it is, return the cached version. If it isn't, pull it and then cache it before returning. When the entity is updated, evict it from the cache and do your update. I have purposely created my concrete repository implementations to be cache-aware to facilitate this. One other thing to consider using an approach like this is that it is beneficial to do as many fine-grained operations as possible. While that seems illogical at first, if entities are commonly "gotten" from your data store, it is easy to set up some logging to measure the number of cache hits to cache misses.
Coming full circle, to your question... Most lists I deal with are small, so I incur the penalty of loading up the entity in its entirety. Assuming that most use cases will involve the user drilling into one or more of the items, they are pre-cached because of the cache-aside implementation. The number of items is fluid, but I generally apply this approach to anything less than twenty five entities in a list.
For larger lists, I just use IDs. Most likely, the use case here is some sort of search result. Search results are commonly paged, for example, and this does not fit into the above pattern. Instead, I use the larger list of IDs as a sliding range window of entities I am interested in that I then pass to a GetRangeById() method that all of my repositories have - written to purposely take a list of identifiers and load them one at a time so they are cached. In essence, this will take a larger lightweight list and zero in just on the area I am interested in at a given point in time.
With an approach like this, the important thing to realize is that it is highly scalable. It might not baseline as fast as a non-cached approach with small sets of data, but will perform better with larger sets of data. There is an implied performance overhead of operation at play here, but it degrades at a slower rate than a standard "load 'em up" pattern, as well.
You can use CQRS pattern to separate query processing and command processing. And you can do it even on a single database. In such a case you would map you view models directly to the tables in databse (via NHibernate for example). Commands (writes) would go through real domain model and would be persisted in the DB. Queries (like get me a list of entities) would bypass the domain a go straight do DB. There is no point in querying domain object because you actually don't invoke any business logic in them, just retrieving some data.
You can also extend this solution to full-featured CQRS by having separate stores for command side and for query side. Query side would be synchronized by means of replication or pub/sub messaging.