I have Meeting objects that form the basis of a scheduling system, of which gridviews are used to display the important information. This is for the purpose of scheduling employees to meetings, and for employees to view what has been scheduled.
I have been trying to follow DDD principles, but I'm having difficulty knowing what to pass from my service layer down to presentation area of system. This is because the schedule can be LARGE, and actually consists of many different elements of the system. Eg. Client Name, Address, Case Info, Group,etc, all of which are needed for the meeting scheduler to make a decision.
In addition to this, the scheduler needs to change values within this schedule and pass it back up to the service layer (eg. assign employees from dropdowns, maybe change group, etc). So, the information isn't really "readonly" - it needs to be interacted with. ie. It's not just a report.
Our current approach is to populate a flattened "Schedule Object" from SQL, which is constructed from small parts of different domain objects. It's quite a complex query. When changes have been made, this is then passed back up to the service layer, and the service will retrieve the domain objects in question, and fire business methods on the domain objects using information from the DTOs.
My question is, is this the correct approach? ie. Continue to generate large custom objects from SQL, and then pass down from Service Layer to Presentation Layer objects that feel a lot like View Models?
UPDATE due to an answer
To give a idea of the amount entities / aggregates relationships involved. (this is an obfuscated examples, so relationships are the important things here)
Client is in one default group
Client has one open case but many closed
Cases have many Meetings
Meeting have many assigned Employees
Meeting have many reasons
Meeting can get scheduled to different groups
Employees can be associated with many groups.
The schedule need to loads all meetings in open cases that belong to patients who are in the same groups as the employee.
Scheduler can see Client Name, Client Address, Case Info, MeetingTime, MeetingType, MeetingReasons, scheduledGroup(s) (showstrail), Assigned Employees (also has hidden employee ids).
Editable fields are assign employee dropdowns and scheduled group.
Schedule may be up to two hundred rows.
DTO is coming down from WCF, so domain model is accessed above this service layer, and not below.
Domain model business calls leveraged by service based on DTO values passed back, and repositories deal with inserts/updates.
So, I suppose to update, is using a query to populate an object which contains all of the above acceptable to pass down as one merged DTO? And if not, how would you approach it? ( giving some example calls to service layer, and explaining a little bit about how you conceive the ORM fetching the data keeping in mind performance)
In the service layer and below, I would treat each entity (see aggregate roots in DDD) separate with respect to it's transactional boundary. I.e. even if you could update a client and a case in the same UI view, it would be best to transactionally modify the client and then modify the case. The more you try to modify in one transaction, the more you can conflict with other users.
Although your schedule is large and can contain lots of objects, the service layer should again deal with each entity (aggregate root) separately and then bundle them together into a new view model. Sadly, on brown-field projects, a lot of logic might be in the SQL and the massive multi-table joins might make this harder to refactor into more atomic queries that do exactly what is needed. The old-school data-centric view of 'do everything you can in the database' goes against everything DDD.
Because DDD is a collection of design ideas and patterns and not particularly a methodology or an architecture, it sounds that it might be too late to try shoe-horn your current application into a DDD application-centric design. It sounds as though your current app is very entrenched in the data-centric view.
If everything is currently being passed up through the layers in one monolithic chunk, it might be best to keep with this style and just expose these monolithic chunks to the people in the other team who wish to consume them, for use in their new app. You might be able to put some sort of view model caching in place (a bit like the caching view model element in CQRS).
In my personal opinion, data-centric, normalised data apps have had their day (they made sense in the 1970s when hard disk space was expensive) and all apps should be moving toward more modern practices. In reality, only when legacy systems are crawling on their knees, will stakeholders usually put up the cash to look for alternatives (usually after stuffing every last server with RAM). It might be possible or best to convince them to refactor small sections at a time.
Related
I have a aggregate called Investor; investor is composed on various entities (say stocks, bonds), some value objects as well (address)
I would like to make a service that return an Investor for some investor ID (/get-investor/id/:id)
The data for stocks for an investor is stored in database 1; bonds in database 2, address in database 3.
Where should the actual fetching of data from other microservices live?
In the domain model? (does not seem right)
Coordinated by a service (gets the data from various repositories) which then composes the domain model with all that information?
The data for stocks for an investor is stored in database 1; bonds in database 2, address in database 3.
If that's the case (and it certainly makes sense that you might break things out that way), then investor probably isn't an AGGREGATE, in the Eric Evans sense.
(Rolling back transactions across multiple databases is not usually a good time.)
I would like to make a service that return an Investor for some investor ID (/get-investor/id/:id)
You seem to be describing a report that combines information copied from multiple databases. In that case, a domain model isn't really necessary because we're not interested in trying to change the official copy of the data, and therefore we don't really need the rules that describe how you constrain changes.
Depending on the liveness requirements you have, you might reasonably query the different databases from the application layer when you get a request for a page. Alternatively, you might perform those queries in the background, copying the information you need into a local cache (which in turn is queried by the application layer).
The same ideas can work when you are trying to change the official copy of some information, and need reference data from somewhere else to compute the right changes to make. That's the ideal case - when the logic of deciding what data you need from somewhere else is trivially determined.
When you need to do work in the domain model to determine what reference data you need, there are at least two candidate approaches.
By far the most common is to use a "domain service" that acts as a facade in front of the query implementation - you pass the service to the model with your other arguments, and it invokes the service when it needs to.
Rare, but viable is to instead design a protocol between the domain model and the application code, such that the domain model can ask for the information it needs and the application code can run the query and pass that information back to the domain model. It has the advantage of getting some of the (possibly implicit) error handling out of the domain model, and putting it into the application code with the other I/O concerns. But it certainly isn't as "easy" as just calling the query when you want it.
(Remember: the machine doesn't care very much how you do it - any correct implementation is fine. But some designs are easier for the human beings that need to maintain them, and different human beings in different contexts have different priorities.)
I was asked to implement CQRS/Event sourcing patterns into a legacy web application, in order to prepare to migrate it from a monolithic/state oriented model to a distributed, service oriented app.
I have some questions on how I can design a Domain oriented code bundle that would connect the legacy entities strongly coupled to database, with a new Event sourced model.
The first things I did were:
writing a small "framework" for CQRS/ES, with classes like AggregateRoot, DomainEvent, Command, Handlers, Messaging, Eventstore, AggregateIds, etc.
trying to group and "migrate" the legacy Entities into some Aggregates to reconstruct all the history and states of the app into EventSoourced Aggregates
plug some Commands dispatching in the old controllers in order to let the app work as is, but also to feed the new CQRS/ES system on the side.
The context:
The legacy app contains several entities, mapped to database, that hold the model layer. (Our domain is Human resources (manpower).
Let's say we have those existing entities:
Worker, with various fields and related entities (OneToOne, OneToMany), like
name
address 1-1
competences 1-N
Society, in which worker works, with various fields and related entities (OneToOne, OneToMany), like
name
address 1-1
hours
Contract, with various fields and related entities (OneToOne, OneToMany), like
address 1-1
Worker 1-1
Society 1-1
documents 1-N
days 1-N
hours
etc.
From this legacy model, I designed a MissionAggregate that holds:
A db independent ID, like UUID
some Value objects: address, days (they were an entity in the legacy model, they became VOs here)
I also designed a WorkerAggregate and a SocietyAggregate, with fields and UUIDS, and in the MissionAggregate I added:
a reference to WorkerAggregate's UUID
a reference to SocietyAggregate's UUID
As I said earlier, my aim is to leave the legacy app as is, but just introduce in the CRUD controller's methods some calls to dispatch Commands to the new CQRS system.
For example:
After flushing newly created Contract in bdd, I want to dispatch a "CreateMissionCommand" to the new command bus.
It targets the appropriate Command Handler, that handles all the command's data, passes it to a newly created Aggregate with a new UUID and stores "MissionCreatedDomainEvent" in the EventStore.
The DomainEvent is indexed with an AggregateId, a playhead, and has a payload which contains the fields necessary to be applied to and build the MissionAggregate.
The newly Contract created in the app has now its former lifecycle, as usual, with all the updates that the legacy app does on it. But I also need to reflects all those changes to the corresponding EventSourcedAggregate, so every time there is a flush in database in the app, I dispatch a Command that translates the "crud like operations" of the legacy app into a Domain oriented /Command oriented pattern.
To sum up the workflow is:
A Crud legacy operation occurs and flushes some changes on the Contract Entity
In just a row of code in the controller, I dispatch a command built with necessary fields (AggregateId of the MissionAggregate... that I need to have stored somewhere... see next problems) to the Domain command bus, so that the impact on the existing code base is very low.
The bus passes the command to the corresponding command handler
The handler loads the aggregate and applies the changes it by calling the appropriate Aggregate method
then after some validation, the aggregate raises and stores the appropriate event
My problems and questions (some of them at least) are:
I feel like I am rewriting all big portions of the legacy app, with the same kind of relations between the Aggregates that I have between the Entities, and with the same type of validations, checks etc.
Having references, to both WorkerAggregate and SocietyAggregate UUID in MissionAggregate implies that I have to build those aggregate also (hence to dispatch commands from legacy app when the Worker and Society entities are flushed). Can't I have only references to Worker's entity id and Society's entity id?
How can I avoid having a eternally growing MissionAggregate? The Contract Entity is quite huge, it has a lot of fields that are constantly updated (hours, days, documents, etc.) If I want to store all those events, I need to have a large MissionAggregate to reflect all those changes; and so I need to have a tons of CommandHandlers that react to all the Commands of add, update, etc. that I am going to dispatch from the legacy app.
How "free" is an Aggregate from the Root entity it is supposed to refer to ? For example, a Contract Entity needs to relate somewhere to it's related Mission Aggregate, like for example when I want to dispatch a Command from the app, just after the legacy code having flushed something on the Entity. Where to store this relation? In the Entity itself, in a AggregateId field? in the Aggregate, should I have a ContractId field? Or should I have some kind of Mapping Table somewhere that holds the relationship between Contract ID and MissionAggregate ID?
What to do with the past? Should I migrate all the existing data through a script that generates Aggregates and events on all the historical data?
Thanks in advance for your time.
You have a huge task ahead of you, let's try to break it down.
It's best to build this new part of the system in isolation from the legacy codebase, otherwise you're going to have your hands tied in every turn of the way.
Create a separate layer in your project for these new requirements. We're going to call it "bubble" from now on. This bubble will be like a greenfield project, with its own structure, dependencies, etc. There will be no direct communication between the bubble and the legacy; communication will happen through another dedicated translation layer, which we'll call "Anti-Corruption Layer" (ACL).
ACL
It is like an API between two systems.
It translates calls from the bubble to the legacy and vice-versa. Its purpose is to prevent one system from corrupting or influencing the other. This way you can keep building/maintaining each system independently from each other.
At the same time, the ACL allows one system to consume the other, and reuse logic, validations, rules, etc.
To answer your questions directly:
I feel like i am rewriting all big portions of the legacy app, with the same kind of relations between the Aggregates that i have between the Entities, and with the same type of validations, checks etc.
With the ACL, you can resort to calling validations and reuse implementations from the legacy code. This will allow you time to rewrite things as needed or as possible.
You may not need to rewrite the entire system, though. If your goal is to implement CQRS and Event Sourcing and you can achieve this goal by keeping most or part of the legacy system, I would say you do it. Unless, of course, one of the goals is to completely replace the old system. Otherwise, keep it; write as less code as possible.
Suggested workflow:
Keep the CQRS and Event Sourcing system in the bubble
Do not bring these new frameworks into legacy
Make the lagacy Controller issue method calls to the ACL
The ACL will convert these calls into Commands and dispatch them
Any events will be caught by your Event Sourcing framework
Results will be persisted to the bubble's database
The bubble's database can be a different schema in the same database or can be a different database altogether. But you'll have to think about synchronization, and that's a topic of its own. To reduce complexity, I recommend a different schema in the same database.
Having references, to both WorkerAggregate and SocietyAggregate UUID in MissionAggregate implies that i have to build those aggregate also (hence to dispatch commands from legacy app when the Worker and Society entities are flushed). Can't i have only references to Worker's entity id and Society's entity id?
How can i avoid having a eternally growing MissionAggregate ? The Contract Entity is quite huge, it has a looot of fields that are constantly updated (hours, days, documents, etc.) If i want to store all those events, i need to have a large MissionAggregate to reflect all those changes; and so i need to have a tons of CommandHandlers that react to all the Commands of add, update, etc that i am going to dispatch from the legacy app.
You should aim for small aggregates. Huge aggregates are likely to degrade performance and cause concurrency problems.
If you anticipate having a huge aggregate, it is best to rethink it and try to break it down. Ask what fields/properties change together - these are possibly a different aggregate.
Also, when you speak about CQRS, you generally lean towards a task-based way of doing things in your system.
Think of a traditional web application, where you have a huge page with lots of fields that are all sent to the server in one batch when the user saves.
Now, contrast it with a modern web app where the user changes small portions of data at each step. If you think about your system this way you'll find those smaller aggregates.
PS. you don't need to rebuild your interfaces for this. If your legacy system has those huge pages, you could have logic in the controllers to detect which fields were changed and issue the appropriate commands.
How "free" is an Aggregate from the Root entity it is supposed to refer to ? For example, a Contract Entity needs to relate somewhere to it's related Mission Aggregate, like for example when i want to dispatch a Command from the app, just after the legacy code having flushed something on the Entity. Where to store this relation ? In the Entity itself, in a AggregateId field ? in the Aggregate, should i have a ContratId field ? Or should i have some kind of Mapping Table somewhere that holds the relationship between Contract ID and MissionAggregate ID?
Aggregates represent a conceptual whole. They are like atoms, indivisible things. You should always refer to an aggregate by its Root Entity Id, and never to a Child Entity Id: looking from the outside, there are no children.
An aggregate should be loaded as a whole and persisted as a whole. One more reason to have small aggregates.
An aggregate can be comprised of a single entity. Or it can have more entities and value objects, forming a graph, but one entity will be elected as the Root and will hold references to its children. Child entities and value objects should not hold references to their parents. The dependency is not bi-directional.
If Contract is an entity inside the Mission aggregate, the Contract should not have a reference to its parent.
But, if your Contract and Mission are different aggregates, then they can reference each other by their Ids.
What to do with the past? Should i migrate all the existing datas through a script that generates Aggregates and events on all the historical data?
That's a question for the business experts. Do they need it? If they don't, then don't implement it just for the sake of doing so. Every decision you make should be geared towards satisfying a business need and generating real value for it, considering the costs and tradeoffs.
Some people say that code is a liability, not an asset, and I aggre to some extent: every line of code you write needs to be tested and supported. Don't write any code that is not really necessary.
Also, have a look at this article about the Strangler Pattern, which shows how to migrate a legacy system by gradually replacing specific pieces of functionality with new applications and services.
If you have a chance, watch this course at Pluralsight (paid): Domain-Driven Design: Working with Legacy Projects. The author presents practical approaches for dealing with this kind of task.
I hope this has given you some insight.
I don't want to spoil your game. Everybody knows how cool it is to rewrite something from scratch. It's a challenge, it's fun, it's exciting. However...
migrate it from a monolithic/state oriented model to a distributed, service oriented app
CQRS/Event Sourcing won't solve any of your problems and it won't help you distribute the app in any reasonable way. If you just generate events on the CRUD operations you'll have a large tangled mess of dependencies between each part. Every part that needs data will have to call a couple of "services" (i.e. tables) to get it, than push data elsewhere, generate events1 that some other parts will react to. It will be a mess. Usually this is called a distributed monolith.
This is also the reason you already see problems with it. These problems won't go away, because you are essentially building the same system in the same way, but this time it'll be more complex.
Where to go from here
The very first thing is always: have a clear goal. You want a service oriented architecture you said. Why? Are there parts that need different scaling, different resources? Are they managed by different teams with different life-cycles? Etc.? Maybe you already have all this, I don't know, but if not, that's your first task.
Then. The parts you do want to pull out can't be just CRUD things. Those will not be independent, so whether your goal (see point above!) is scaling or different team, you won't reach your goal! To be independent you'll have to pull out the behavior with the data, and in a way that the service can operate on its own.
You can't just throw buzzwords at it and hope for the best. I'd suggest to just ignore all the hype and buzzwords and think about the goal you want to reach.
For example: I need a million workers to log their time in under 10 minutes total. So that means I need a "service" to enable worker to log their time with a web interface. So let's create that as a complete independent piece with its own database so it can be scaled to a 100 nodes when it needs to be. Export data to billing automatically every hour or so.
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.
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)
Background
Udi Dahan suggests a fetching strategy as a useful pattern to use for data access. I agree.
The concept is to make roles explicit. For example I have an Aggregate Root - Customer. I want customer in several parts of my application - a list of customers to select from, a view of the customer's details, and I want a button to deactivate a customer.
It seems Udi would suggest an interface for each of these roles. So I have ICustomerInList with very basic details, ICustomerDetail which includes the latest 10 products purchased, and IDeactivateCustomer which has a method to deactivate the customer. Each interface exposes just enough of my Customer Aggregate Root to get the job done in each situation. My Customer Aggregate Root implements all these interfaces.
Now I want to implement a fetching strategy for each of these roles. Each strategy can load a different amount of data into my Aggregate Root because it will be behind an interface exposing only the bits of information needed.
The general method to implement this part is to ask a Service Locator or some other style of dependency injection. This code will take the interface you are wanting, for example ICustomerInList, and find a fetching strategy to load it (IStrategyForFetching<ICustomerInList>). This strategy is implemented by a class that knows to only load a Customer with the bits of information needed for the ICustomerInList interface.
So far so good.
Question
What you pass to the Service Locator, or the IStrategyForFetching<ICustomerInList>. All of the examples I see are only selecting one object by a known id. This case is easy, the calling code passes this id through and will get back the specific interface.
What if I want to search? Or I want page 2 of the list of customers? Now I want to pass in more terms that the Fetching Strategy needs.
Possible solutions
Some of the examples I've seen use a predicate - an expression that returns true or false if a particular Aggregate Root should be part of the result set. This works fine for conditions but what about getting back the first n customers and no more? Or getting page 2 of the search results? Or how the results are sorted?
My first reaction is to start adding generic parameters to my IStrategyForFetching<ICustomerInList> It now becomes IStrategyForFetching<TAggregateRoot, TStrategyForSelecting, TStrategyForOrdering>. This quickly becomes complex and ugly. It's further complicated by different repositories. Some repositories only supply data when using a particular strategy for selecting, some only certain types of ordering. I would like to have the flexibility to implement general repositories that can take sorting functions along with specialised repositories that only return Aggregate Roots sorted in a particular fashion.
It sounds like I should apply the same pattern used at the start - How do I make roles explicit? Should I implement a strategy for fetching X (Aggregate Root) using the payload Y (search / ordering parameters)?
Edit (2012-03-05)
This is all still valid if I'm not returning the Aggregate Root each time. If each interface is implemented by a different DTO I can still use IStrategyForFetching. This is why this pattern is powerful - what does the fetching and what is returned doesn't have to map in any way to the aggregate root.
I've ended up using IStrategyForFetching<TEntity, TSpecification>. TEntity is the thing I want to get, TSpecification is how I want to get it.
Have you come across CQRS? Udi is a big proponent of it, and its purpose is to solve this exact issue.
The concept in its most basic form is to separate the domain model from querying. This means that the domain model only comes into play when you want to execute a command / commit a transaction. You don't use data from your aggregates & entities to display information on the screen. Instead, you create a separate data access service (or bunch of them) that contain methods that provide the exact data required for each screen. These methods can accept criteria objects as parameters and therefore do searching with whatever criteria you desire.
A quick sequence of how this works:
A screen shows a list of customers that have made orders in the last week.
The UI calls the CustomerQueryService passing a date as criteria.
The CustomerQueryService executes a query that returns only the fields required for this screen, including the aggregate id of each customer.
The user chooses a customer in the list, and chooses perform the 'Make Important Customer' action /command.
The UI sends a MakeImportantCommand to the Command Service (or Application Service in DDD terms) containing the ID of the customer.
The command service fetches the Customer aggregate from the repository using the ID passed in the command, calls the necessary methods and updates the database.
Building your app using the CQRS architecture opens you up to lot of possibilities regarding performance and scalability. You can take this simple example further by creating separate query databases that contain denormalised tables for every view, eventual consistency & event sourcing. There is a lot of videos/examples/blogs about CQRS that I think would really interest you.
I know your question was regarding 'fetching strategy' but I notice that he wrote this article in 2007, and it's likely that he considers CQRS its sucessor.
To summarise my answer:
Don't try and project cut down DTO's from your domain aggregates. Instead, just create separate query services that give you a tailored query for your needs.
Read up on CQRS (if you haven't already).
To add to the response by David Masters, I think all the fetching strategy interfaces are adding needless complexity. Having the Customer AR implement the various interfaces which are modeled after a UI is a needless constraint on the AR class and you will spend far to much effort trying to enforce it. Moreover, it is a brittle solution. What if a view requires data that while related to Customer, does not belong on the customer class? Does one then coerce the customer class and the corresponding ORM mappings to contain that data? Why not just have a separate set of classes for query purposes and be done with it? This allows you to deal with fetching strategies at the place where they belong - in the repository. Furthermore, what value does the fetching strategy interface abstraction really add? It may be an appropriate model of what is happening in the application, it doesn't help in implementing it.