Let's say I've got a domain class, which has functions, that are to be called in a sequence. Each function does its job but if the previous step in the sequence is not done yet, it throws an error. The other way is that each function completes the step required for it to run, and then executes its own logic. I feel that this way is not a good practice, since I am adding multiple responsibilities, and the caller wont know what all operations can happen when he invokes a method.
My question is, how to handle dependent scenarios in DDD. Is it the responsibility of the caller to invoke the methods in the right sequence? Or do we make the methods handle the dependent operations before it's own logic?
Is it the responsibility of the caller to invoke the methods in the right sequence?
It's ok if those methods have a business meaning. For example the client may book a flight, and then book a hotel room. Both of those is something the client understands, and it is the client's logic to call them in this sequence. On the other hand, inserting the reservation into the database, then committing (or whatever) is technical. The client should not have to deal with that at all. Or "initializing" an object, then calling other methods, then calling "close".
Requiring a sequence of technical calls is a form of temporal coupling, it is considered a bad practice, and is not directly related to DDD.
The solution is to model the problem better. There is probably a higher level use-case the caller wants achieved with this call sequence. So instead of publishing the individual "steps" required, just support the higher use-case as a whole.
In general you should always design with the goal to get any sequence of valid calls to actually mean something (as far as the language allows).
Update: A possible model for the mentioned "File" domain:
public interface LocalFile {
RemoteFile upload();
}
public interface RemoteFile {
RemoteFile convert(...);
LocalFile download();
}
From my point of view, what you are describing is the orchestration of domain model operations. That's the job of the application layer, the layer upon domain model. You should have an application service that would call the domain model methods in the right sequence, and it also should take into account whether some step has left any task undone, and in such case, tell the next step to perform it.
TLDR; Scroll to the bottom for the answer, but the backstory will give some good context.
If the caller into your domain must know the order in which to call things, then you have missed an opportunity to encapsulate business logic in your domain, which is a symptom of an anemic domain.
#RobertBräutigam made a very good point:
Requiring a sequence of technical calls is a form of temporal coupling, it is considered a bad practice, and is not directly related to DDD.
This is true, but it is worse when you do it with your domain model because non-domain concerns get intermixed with domain concerns. Intent becomes lost in a sea of non business logic. If you can, you look for a higher-order aggregate that encapsulates the ordering. To borrow Robert's example, rather than booking a flight then a hotel room, and forcing that on the client, you could have a Vacation aggregate take both and validate it.
I know that sounds wrong in your case, and I suspect you're right. There's a clear dependency that can't happen all at once, so we can't be the end of the story. When you have a clear dependency with intermediate transactions that must occur before the "final" state, we have... orchestration (think sagas, distributed transactions, domain events and all that goodness).
What you describe with file operations spans across transactions. The manipulation (state change) of a domain is transactional at each point in a distributed transaction, but is not transactional overall. So when #choquero70 says
you are describing is the orchestration of domain model operations. That's the job of the application layer, the layer upon domain model.
that's also correct. Orchestration is key. Each step must manipulate the state of the domain once, and once only, and leave it in a valid state, but it OK for there to be multiple steps.
Each of those individual points along the timeline are valid moments in the state of your domain.
So, back to your model. If you expose a single interface with multiple possible calls to all steps, then you leave yourself open to things being called out of order. Make this impossible or at least improbable. Orchestration is not just about what to do, but what to prevent from happening. Create smaller interfaces/classes to avoid accidentally increasing the "surface area" of what could be misused accidentally.
In this way, you are guiding the caller on what to do next by feeding them valid intermediate states. But, and this is the important part, the burden on what to call in what order is not on the caller. Sure, the caller could know what to do, but why force it.
Your basic algorithm is the same: upload, transform, download.
Is it the responsibility of the caller to invoke the methods in the right sequence?
Not exactly. Is the responsibility of the caller to choose from legitimate choices given the state of your domain. It's "your" responsibility to present these choices via business methods on your correctly modeled moment/interval aggregate suitable for the caller to use.
Or do we make the methods handle the dependent operations before it's own logic?
If you've setup orchestration correctly, this won't be necessary. But it does make sense to validate anyway.
On a side note, each step of the orchestration you do should be very linear in nature. I tell my developers to be suspicious of an orchestration step that has an if statement in it. If there's an if it's likely better to be part of another orchestration step or encapsulated in business logic.
Related
I am trying to understand which of the following two options is the right approach and why.
Say we have GetHotelInfo(hotel_id) API that is being invoked from the Web till the Controller.
The logic of the GetHotelInfo is:
Invoke GetHotelPropertyData() (Location, facilities…)
Invoke GetHotelPrice(hotel_id, dates…)
Invoke GetHotelReviews(hotel_id)
Once all results come back, process and merge the data and return 1 object that contains all relevant data of the hotel.
Option 1:
Create 3 different repositories (HotelPropertyRepo, HotelPriceRepo,
HotelReviewsRepo)
Create GetHotelInfo usecase that will use these 3 repositories and
return the final result.
Option 2:
Create 3 different repositories (HotelPropertyRepo, HotelPriceRepo,
HotelReviewsRepo)
Create 3 different usecases (GetHotelPropertyDataUseCase,
GetHotelPriceUseCase, GetHotelReviewsUseCase)
Create GetHotelInfoUseCase that will orchestrate the previous 3
usecases. (It can also be a controller, but that’s a different topic)
Let’s say that right now only GetHotelInfo is being exposed to the Web but maybe in the future, I will expose some of the inner requests as well.
And would the answer be different if the actual logic of GetHotelInfo is not a combination of 3 endpoints but rather 10?
You can see a similar method (called Get()) in "Clean Architecture with GO" from Manato Kuroda
Manato points out that:
following Acyclic Dependencies Principle (ADP), the dependencies only point inward in the circle, not point outward and no circulation.
that Controller and Presenter are dependent on Use Case Input Port and Output Port which is defined as an interface, not as specific logic (the details). This is possible (without knowing the details in the outer layer) thanks to the Dependency Inversion Principle (DIP).
That is why, in example repository manakuro/golang-clean-architecture, Manato creates for the Use cases layer three directories:
repository,
presenter: in charge of Output Port
interactor: in charge of Input Port, with a set of methods of specific application business rules, depending on repository and presenter interface.
You can use that example, to adapt your case, with GetHotelInfo declared first in hotel_interactor.go file, and depending on specific business method declared in hotel_repository, and responses defined in hotel_presenter
Is expected Interactors (Use Case class) call other interactors. So, both approaches follow Clean Architecture principles.
But, the "maybe in the future" phrase goes against good design and architecture practices.
We can and should think the most abstract way so that we can favor reuse. But always keeping things simple and avoiding unnecessary complexity.
And would the answer be different if the actual logic of GetHotelInfo is not a combination of 3 endpoints but rather 10?
No, it would be the same. However, as you are designing APIs, in case you need the combination of dozens of endpoints, you should start considering put a GraphQL layer instead of adding complexity to the project.
Clean is not a well-defined term. Rather, you should be aiming to minimise the impact of change (adding or removing a service). And by "impact" I mean not only the cost and time factors but also the risk of introducing a regression (breaking a different part of the system that you're not meant to be touching).
To minimise the "impact of change" you would split these into separate services/bounded contexts and allow interaction only through events. The 'controller' would raise an event (on a shared bus) like 'hotel info request', and each separate service (property, price, and reviews) would respond independently and asynchronously (maybe on the same bus), leaving the controller to aggregate the results and return them to the client, which could be done after some period of time. If you code the result aggregator appropriately it would be possible to add new 'features' or remove existing ones completely independently of the others.
To improve on this you would then separate the read and write functionality of each context into its own context, each responding to appropriate events. This will allow you to optimise and scale the write function independently of the read function. We call this CQRS.
I am new to domain driven design and there is one thing that is bothering me when I'm writing domain model. How to handle domain validation?
I am designing library management system where user can search through books and see if book is on the stock.
If it is not, user can create request for book so some kind of queue is created. Rule is that we don't have any book in stock. Right now I have information about quantity inside book entity and that is not a problem but what if i have different bounded context for requesting books and book catalog. Then I must somehow contact another vertical/service and ask (validate) that book quantity is zero before creating book aggregate.
Also I am checking if user have valid membership card, is book already borrowed by him, do user have active requests for any book.
Things that bother me.
I need to know what exactly to include in aggregate before passing it to domain model because of validations. I am not sure that is safest approach because my validations accuracy will depend from specification/query, etc.
Another very important thing. When application layer method start with execution and something is not valid client will get only validation messages for code that was executed and there is good chance there is more things that are preventing code for execution. This can be really inconvenient if user is filling some form.
First thoughts for solving this problem.
I have command/handler architecture and I am using MediatR so I am thinking to move domain validations between command and handler and that will solve my problems for now but that approach will spread domain knowledge across bounded context and domain model will not be smart enough to guard from not valid actions. More precise I will need to think before executing application method (handler) what I need to validate.
So I am really curious. Is there any clear way of handling domain validations inside domain model?
Is there any clear way of handling domain validations inside domain model?
Yes; they require work and careful thinking.
One aspect of careful thinking is to distinguish message validation from domain logic. Message validation is an isolated thing, a message is valid or not according to the schema of the message -- are all of the required fields present, is the data in the right form, are the numbers in the allowed range, and so on. Really, we're asking the question "did the client fill out the form correctly?"
Integrating a valid message with previously known information (aka, the "state" of the domain model) is a domain logic concern. State is chosen deliberately - the domain model is a state machine for the bookkeeping of your domain.
Depending on your domain, and the information that is available, there can be states that mean that the client doesn't get what they want. "The road less traveled" doesn't mean that things are invalid.
Furthermore, if your system is distributed (different pieces of data are the responsibility of different authorities), then any locally cached copies of that data are necessarily stale, and may be out of date. See Pat Helland's Memories, Guesses, and Apologies. That we will sometimes produce an incorrect answer is an inevitable consequence of distributing the work. If we're responsible, then we performed a cost benefit analysis to ensure that the expected benefits of distributing the work offset the expected risks.
Let's assume we host two microservices: RealEstate and Candidate.
The RealEstate service is responsible for managing rental properties, landlords and so forth.
The Candidate service provides commands to apply for a rental property.
There would be a CandidateForRentalProperty command which requires the RentalPropertyId and all necessary Candidate information.
Now the crucial point: Different types of RentalPropertys require a different set of Candidate information.
Therefore the commands and aggregates got splitten up:
Commands: CandidateForParkingLot, CandidateForFlat, and so forth.
Aggregates: ParkingLotCandidature, FlatCandidature, and so forth.
The UI asks the read model to decide which command has to be called.
It's reasonable for me to validate the Candidate information and all the business logic involved with that in the Candidate domain layer, but leave out validation whether the correct command got called based on the given RentalPropertyId. Reason: Multiple aggregates are involved in this validation.
The microservice should be autonomous and it's read model consumes events from the RealEstate domain, hence it's not guaranteed to be up to date. We don't want to reject candidates based on that but rather use eventual consistency.
Yes, this could lead to inept Candidate information used for a certain kind of RentalProperty. Someone could just call the CandidateForFlat command with a parking lot rental property id.
But how do we handle the cases in which this happens?
The RealEstate domain does not know anything about Candidates.
Would there be an event handler which checks if there is something wrong and execute an appropriate command to compensate?
On the other hand, this "mapping" is domain logic and I'd like to accomodate it in the domain layer. But I don't know who's accountable for this kind of compensating measures. Would the Candidate aggregate be informed, like IneptApplicationTypeUsed or something like that?
As an aside - commands are usually imperative verbs. ApplyForFlat might be a better spelling than CandidateForFlat.
The pattern you are probably looking for here is that of an exception report; when the candidate service matches a CandidateForFlat message with a ParkingLot identifier, then the candidate service emits as an output a message saying "hey, we've got a problem here".
If a follow up message fixes the problem -- the candidate service gets an updated message that fixes the identifier in the CandidateForFlat message, or the candidate service gets an update from real estate announcing that the identifier actually points to a Flat, then the candidate service can emit another message "never mind, the problem has been fixed"
I tend to find in this pattern that the input commands to the service are really all just variations of handle(Event); the user submitted, the http request arrived; the only question is whether or not the microservice chooses to track that event. In other words, the "command" stream is just another logical event source that the microservice is subscribed to.
As you said, validation of commands should be performed at the point of command generation - at client side - where read models are available.
Command processing is performed by aggregate, so it cannot and should not check validity or existence of other aggregates. So it should trust a command issuer.
If commands comes from an untrusted environment like public API, then your API gateway becomes a client, and it should have necessary read models to validate references.
If you want to accept a command fast and check it later, then log events like ClientAppliedForParkingLot, and have a Saga/Process manager handle further workflow by keeping its internal state, and issuing commands like AcceptApplication or RejectApplication.
I understand the need for validation but I don't think the example you gave calls for cross-Aggregate (or cross-microservice for that matter) compensating measures as stated in the Q title.
Verifications like checking that the ID the client gave along with the flat rental command matches a flat and not a parking lot, that the client has permission to do that, and so forth, are legitimate. But letting the client create such commands in the wild and waiting for an external actor to come around and enforce these rules seems subpar because the rules could be made intrinsic properties of the object originating the process.
So what I'd recommend is to change the entry point into the operation - to create the Candidature Aggregate Root as part of another Aggregate Root's behavior. If that other Aggregate (RentalProperty in our case) lives in another Bounded Context/microservice, you can maintain a list of RentalProperties in the Candidate Bounded Context with just the amount of info needed, and initiate the Candidature from there.
So you would have
FlatCandidatureHandler ==loads==> RentalProperty ==creates==> FlatCandidature
or
FlatCandidatureHandler ==checks existence==> local RentalProperty data
==creates==> FlatCandidature
As a side note, what could actually necessitate compensating actions are factors extrinsic to the root object of the process. For instance, if the property becomes unavailable in the mean time. Then whatever Aggregate holds that information should emit an event when that happens and the compensation should be initiated.
Imagine I have an application that request to the user a name, a category list. When user click on save button, application will save name and category to a database.
I have a layer that get name and category from UI. This layer check if there is a name (a string with length > 0). If this is correct, it will pass name a category to another layer. Note: category is a radiobutton list where one item is always selected.
On this second layer, application will select a suitable class to save name, depending on category.
On last layer, a class will save this name on a database. On this class I will check if name is empty or not.
My question is: where is the right place to check method's input parameters? on every layer? Maybe, I'm going to use these layers on others developments.
Is my example correct? Maybe, I can left validation on database layer and raise an exception to UI layer.
In general, in terms of the larger question about validating input that is ultimately persisted, it is best to:
Convert the input parameters to a
fully encapsulated business object as
soon as possible after you receive
it.
Validate early and fail fast then to
wait until you get to a lower layer
-- waste of resources, waste of time, possibly more complex (more things to
roll back).
Validate the business logic once and make that part of
your object instantiation process. (but note that validation of view logic and persistence logic may need to be done at the other layers and is separate from business logic)
Model how your object is persisted
using an ORM (e.g., Hibernate) so
that you could work purely at the
object level in memory and leave
persistence as an implementation
detail. Focus the business logic at
the object layer.
And in terms of method validation itself, I agree with Oded -- at every layer, and it should be done immediate upon method entry. Again, this is part of the fail fast methodology. But, as I noted above, this doesn't mean you validate business logic at every method (or every layer). I'm just referring to the basic practice of validating inputs (either by assertions or explicit checks and exceptions thrown).
where is the right place to check method's input parameters? on every layer?
Yes, on every layer. This is called defense in depth.
There are different reasons to do so on each layer:
UI/Client code: keep things responsive and avoid roundtrips when data is invalid
Business layer: Ensure business rules are kept
Data layer: Ensure that valid data is passed through
I disagree with the recommendation about every layer, all the time. It sounds too dogmatic to me.
All design represents a choice between functionality and cost. Your validation choices should reflect that as well.
I think your decisions should take into account the sharing and reuse of layers.
If the database is shared by more than one application, then the database cannot depend on every application validating properly. In that case, the database must validate to protect itself.
In this day and age of SQL injection attacks, I think binding and validating prior to reaching the persistence tier is a must. The schema should do what it must to ensure referential and business integrity (e.g. unique constraints on columns and required "not null"), but other validations should be done prior to hitting the database.
If the database is wholly owned by one and only one application, and there's a service that is the only gateway into the data, then validation can be done by the service. The cost of duplicating the validation on the database layer can be waived.
Likewise between the UI and the service layer.
Double validation on client and service tiers is common because the service is shared by many clients in a service oriented architecture. Today your service might be used by a browser based UI; suddenly there's a flock of mobile apps along side it that clamor for services, too. In that case the service absolutely must validate and bind each and every request.
No manufacturer polishes every surface to mirror quality. Sometimes a rough cast surface is permissible, because the benefit of grinding and polishing is negligible and the cost is too great.
Same with software.
I don't like dogmatic statements. It's better to understand the implications of your choices. Know the rules and when it's appropriate to break them.
If you're going for very loose coupling where other applications will also make use of these same layers, then I would recommend doing input checking at every step. Since each class/method should have no knowledge of expectation of the other classes/methods which ran before them in the stack, each one should enforce its requirements individually.
If the UI requires that a value be in the text box when the button is clicked, it should validate accordingly.
If the business logic requires that a name never be null/empty, it shouldn't allow a null/empty value to be placed in that property.
If the data layer has a constraint on that field requiring that a value be present, it should check that a value is present before trying to persist the data.
Hopefully you'll see the problem I'm describing in the scenario below. If it's not clear, please let me know.
You've got an application that's broken into three layers,
front end UI layer, could be asp.net webform, or window (used for editing Person data)
middle tier business service layer, compiled into a dll (PersonServices)
data access layer, compiled into a dll (PersonRepository)
In my front end, I want to create a new Person object, set some properties, such as FirstName, LastName according to what has been entered in the UI by a user, and call PersonServices.AddPerson, passing the newly created Person. (AddPerson doesn't have to be static, this is just for simplicity, in any case the AddPerson will eventually call the Repository's AddPerson, which will then persist the data.)
Now the part I'd like to hear your opinion on is validation. Somewhere along the line, that newly created Person needs to be validated. You can do it on the client side, which would be simple, but what if I wanted to validate the Person in my PersonServices.AddPerson method. This would ensure any person I want to save would be validated and removes any dependancy on the UI layer doing the work. Or maybe, validate both in UI and in by business server layer. Sounds good so far right?
So, for simplicity, I'll update the PersonService.AddPerson method to perform the following validation checks
- Check if FirstName and LastName are not empty
- Ensure this new Person doesn't already exist in my repository
And this method will return True if all validation passes and the Person is persisted, False if Validation fails or if the Person is not persisted.
But this Boolean value that AddPerson returns isn't enough for me at the UI layer to give the user a clear reason why the save process failed. So what's a lonely developer to do? Ultimately, I'd like the AddPerson method to be able to ensure what its about to save is valid, and if not, be able to communicate the reasons why it's not invalid to my UI layer.
Just to get your juices flowing, some ways of solving this could be: (Some of these solutions, in my opinion, suck, but I'm just putting them there so you get an understanding of what I'm trying to solve)
Instead of AddPerson returning a boolean, it can return an int (i.e. 0 = Success, Non Zero equals failure and the number indicates the reason why it failed.
In AddPerson, throw custom exceptions when validation fails. Each type of custom exception would have its own error message. In addition, each custom exception would be unique enough to catch in the UI layer
Have AddPerson return some sort of custom class that would have properties indicating whether validation passed or failed, and if it did fail, what were the reasons
Not sure if this can be done in VB or C#, but attach some sort of property to the Person and its underlying properties. This "attached" property could contain things like validation info
Insert your idea or pattern here
And maybe another here
Apologies for the long winded question, but I definately like to hear your opinion on this.
Thanks!
Multiple layers of validation go well with multi-layer apps.
The UI itself can do the simplest and quickest checks (are all mandatory fields present, are they using the appropriate character sets, etc) to give immediate feedback when the user makes a typo.
However the business logic should have the lion's share of validation responsibilities... and for once it's not a problem if this is "repetitious", i.e., if the business layer re-checks something that should already have been checked in the UI -- the BL should check all the business rules (this double checks on UI's correctness, enables multiple different UI clients that may not all be perfect in their checks -- e.g. a special client on a smart phone which may not have good javascript, and so on -- and, a bit, wards against maliciously hacked clients).
When the business logic saves the "validated" data to the DB, that layer should perform its own checks -- DBs are good at that, and, again, don't worry about some repetition -- it's the DB's job to enforce data integrity (you might want different ways to feed data to it one day, e.g. a "bulk loader" to import a number of Persons from another source, and it's key to ensure that all those ways to load data always respect data integrity rules); some rules such as uniqueness and referential integrity are really best enforced in the DB, in particular, for performance reasons too.
When the DB returns an error message (data not inserted as constraint X would be violated) to the business layer, the latter's job is to reinterpret that error in business terms and feed the results to the UI to inform the user; and of course the BL must similarly provide clear and complete info on business rules violation to the UI, again for display to the user.
A "custom object" is thus clearly "the only way to go" (in some scenarios I'd just make that a JSON object, for example). Keeping the Person object around (to maintain its "validation problems" property) when the DB refused to persist it does not look like a sharp and simple technique, so I don't think much of that option; but if you need it (e.g. to enable "tell me again what was wrong" functionality, maybe if the client went away before the response was ready and needs to smoothly restart later; or, a list of such objects for later auditing, &c), then the "custom validation-failure object" could also be appended to that list... but that's a "secondary issue", the main thing is for the BL to respond to the UI with such an object (which could also be used to provide useful non-error info if the insertion did in fact succeed).
Just a quick (and hopefully helpful) comment: when you're wondering where to place validation, try pretending that, soon, you're going to completely recreate your UI layer using a technology you're not yet so familiar with**. Try to keep out of that layer any validation-like business logic that you know for certain you'd have to rewrite in the new technology.
You'll find exceptions - business logic that ends up in your UI layer regardless, but it's a useful consideration nonetheless.
** Mobile dev, Silverlight, Voice XML, whatever - pretending you don't know the technology of your "new" UI layer helps you abstract your concerns and get less mired in implementation details.
The only important points are:
From the perspective of the front-end(s), the Middle Tier must perform all validation, you never know whether someone is going to try circumventing your front-end validation by talking directly to your Middle Tier (for whatever reason)
The Middle Tier may elect to delegate some of that validation to the DB layer (e.g. data integrity constraints)
You may optionally duplicate some validation in the UI, but that should only be for the sake of performance (to avoid round-trips to the Middle Tier for common scenarios, such as missing mandatory fields, incorrectly formatted data, etc.) These checks should never take the place of doing them in the Middle Tier
Validation should be done at all three levels.
When I am in a project I assume I am making a framework, which most of the time is not the case. Each layer is separate and must check all layers input before doing an operation
Each level can have a different way of doing it, it is not necessary they all use the same, but ideally they should all use the same validation with the ability to customize it.
You never want to let bad data into the database. So you can never trust the data you are getting from the business layer. It needs to be checked.
In the business layer you can never trust the UI layer, and you must check it to prevent un-needed calls to the database layer. The UI layer works the same way.
I disagree with David Basarab's comment that the same validations should be present in all layers. This defies the paradigm of responsibility of layers for one reason. Secondly, though the main intention is to make the layers (or components) loosely coupled, it is also important that a level of responsibility (and hence trust) is endowed on the layers. Though it might be necessary to duplicated some validations in UI and Business Layer (since UI layer can be bypassed by hacking attempts), however, it is not advisable to repeat the validations in each layer. Each layer should perform only those validations which they are responsible for. The biggest flaw in repeting validations in all layers is code redundancy, which can cause maintenance nightmare.
A lot of this is more style than substance. I personally favor returning status objects as a flexible and extensible solution. I would say that I think there are a couple classes of validation in play, the first being "does this person data conform to the contract of what a person is?" and the second being "does this person data violate constraints in the database?" I think the first validation can, and should be done at the client. The second should be done at the middle tier. With this division, you may find that the only reasons the save could fail are 1)violates a uniqueness constrains, or 2)something catastrophic. You could then return false for the first case, and throw an exception for the other.
If tier R is closer to the user (or any input stream you don't control) than tier S then tier S should validate all data received from tier R. This does not mean that tier R shouldn't validate data. It's better for the user if the GUI warns him he's making a mistake before he attempts a new transaction. But no matter how bulletproof the validation in your GUI is, the next tier up should not trust that any validation has taken place.
This assumes your database in completely under your control. If not, you have bigger problems.
Also, you could have the UI pass the data needed to build a Person object through some sort of PersonBuilder object, so that object creation is consolidated in the domain/business layer, and you can keep the Person object in a state that is always consistent. This makes more sense for more complex entities, however even for simple ones, it is good to centralize object creation, just like you centralize persistence, etc.