I'm giving up traditional DDD, which is often a massive timewaster, and forces me to do endless mapping: data layer <--> domain layer <--> presentation layer.
For even a small change I must change data models, domain models, presentation models / viewmodels, then the repositories, manager/service classes, and of course the AutoMapper maps, and then test the whole thing! Each call requires calling a layer which calls a layer which calls the underlying code. And I don't get anything in return other than "you might need it in the future". Meh.
My current approach is more pragmatic:
I don't worry about the difference between the "data layer" and "domain layer" any longer, as there's no point - the terms are interchangeable. I let EF do it's thing, and add interfaces and repositories on top when needed.
I've merged my "data" and "domain" projects (into "core", boring name, I know), and I could almost swear that Visual Studio is actually running faster.
I allow EF entities to go up and down the stack, but, I still map them to presentation models / viewmodels as usual.
For simple operations I call repositories directly from controllers, for complex operations I use domain managers/services as usual; the repositories never expose IQueryable.
I define entities/POCOs as partial classes, so I can add domain behavior separately in corresponding partial classes.
The problem: I now use the entities all over the place, so client code can see their navigation properties. And the models are always materialized after they leave a repository, so those navigation properties are often null.
Possible solutions:
1. Live with it. It's ugly but preferable to the problems explained above.
2. For each entity, define an interface which hides the navigation properties; and make client code use the interfaces. But ironically, this means another layer (albeit thin and manageable).
3. What else?
I'm not used to this sort of fast-and-loose programming style, so maybe I'm missing some obvious tricks. Is there anything else I should take into account? I'm sure there are other problems I will encounter soon.
EDIT:
This question is not about DDD. And note that many struggle with a traditional DDD approach -- Seemann appears to arrive at the same conclusion, Rahien speaks about the "Useless Abstraction For The Sake Of Abstraction Anti Pattern", and Evans himself said DDD is only truly useful in 5% of cases. Also see this thread. Some of the comments/answers are predictably about how I'm doing DDD wrong, or how I can tweak my system to do it right. However, I'm not asking about DDD or bashing it for the cases where it is suitable, rather I'd like to know what others are doing in line with the thinking I've described above. It's not as if DDD is a panacea to all design ills, every decade a new process comes out (RUP anyone? XP, Agile, Booch, blah...). DDD is just the shiniest new one, and the most well known and used. But pragmatism should come first as I'm trying to build salable products that ship on time and are easy to maintain. The most useful programming axiom I've learned, by far, is YAGNI. What I want is to change my system to a sort of "DDD-lite", where I get it's strong design/OOP/pattern philosophy, but without the fat.
A typical persistence approach with DDD is to map the domain model directly to corresponding tables. Technically, the mappings are still there (and are usually declared in code), but there is no explicit data model, as pointed out by lazyberezovsky.
The problem with navigation properties can be resolved in a few different ways, regardless of whether you are employing DDD or not. I dislike approach 1 because it makes it more difficult to reason about your code - you never know which properties will be set and which won't. Approach 2 is much better in theory, because it makes it very explicit what that a given query requires and making things explicit is a good practice in general. A similar, but simpler and less brittle approach is to use read-models, which are just objects designed to fulfill requirements of a given query of set of queries. Within the context of DDD, they allow you to decouple behavior rich entities from queries, which are quite often at odds. Now proponents of DRY may scream heresy and come at you with torches and pitchforks, but in practice it is often much easier to maintain a read-model and an entity then to try to coerce entities to fulfill query requirements by way of interfaces or complex mapping strategies. Additionally, the responsibilities of a read-model and a behavior model are quite different, therefore DRY isn't applicable.
This is not to say that DDD is applicable in your scenario. It is often a wise decision to avoid full fledged DDD, especially in scenarios that are mostly CRUD. You are correct to be cautious, a good example of KISS and YAGNI. DDD reaps benefits when your domain consists of complex behavior, not just data. At any rate, the read-model pattern applies.
UPDATE
For implementations that don't employ a read-model, take a look at Fetching Strategy Design where the notion of a fetching strategy allows the specification of exactly what is needed from the database which mitigates issues with navigational properties. The material referenced in the linked post is also of interest. Overall, this attempts to avoid the a layer of indirection present in other approaches. However, in my opinion, using the proposed fetching strategy is more complex than using a read-model while the net result is the same.
Some thoughts about this point:
... the repositories never expose IQueryable ... the models are always
materialized after they leave a repository ...
Your question is tagged with "asp.net-mvc", so you have a web application in mind. 90% or more of all requests will be GET requests that are supposed to fetch some data from the database and show those data in a web view. How often are those needed data really entities rather than only bags of properties (a selection of properties of an entity type or perhaps composed of properties from multiple entities)?
Say, your application has 100 views. Only a minority of these will show complete entities:
50 of them are list views that show selected data (a customer with ID and address, but without the customer's contact person, phone number and sales volume)
20 of them contain autocomplete text boxes to select a reference (the customer for an order, but only the customer's name and city is shown in the autocomplete list, not the rest of the address nor contact person, phone number and sales volume and only the first 5 hits are displayed)
1 is an edit view for a customer that shows everything, but not the sales volume
1 is a details view for a customer with his last five orders
1 is a details view for an order including order items including product of each item but without the product's supplier name
1 is the same view but specialized for the purchasing department that wants to see the supplier for each item and item's product with average supplier's lead time for the last three months.
1 is a view for the service department that shows the order with only the order items of product category "repair service"
1 view for the Human Resources department shows employees including a photo stored as a big blob
1 view for personnel planning department shows a short version of the employee without photo
etc., etc.
As a UI programmer I would have all kinds of data requirements to render a view with the examples above:
I need only a selection of properties
I need even different selections of the same entity's properties for different views
I need an order including all items but without a reference to a product
I need an order including all items (but not all properties of the items) and including a reference to a product and to a supplier (but not all supplier's properties)
I need an order including only a filtered list of order items
I need a customer including the last five orders, not all 3000 orders he ever had
I need an employee but please without the big blob image
etc., etc.
How to fulfill these requirements as a data access/repository/service developer?
I only provide a handful of methods and materialize entities: load order header, load order header with items, load order header with items and product, load order header with items and product and supplier, load customer header (throw 15 of the 20 properties away, dear UI developer, if you only need five properties), load customer header with all 3000 orders (throw 2995 away, dear UI developer, if you only need five), etc., etc. I return interfaces from the repositories that hide not loaded navigation properties.
I care about every detail that the UI needs: I create repository/service methods like GetFiveCustomerPropertiesForAutoComplete, GetCustomerWithLastFiveOrders, etc. etc. I return interfaces from the repositories that hide the properties (also scalar) I haven't loaded. Or I return "DTOs" that contain the requested properties. I change the repository/services and create new DTOs every day when a UI developer calls with a data requirement for the next view.
I return IQueryable<TEntity> from the repositories and tell the UI developer "create the LINQ query yourself to fetch the data you need for your views". (Next morning the DBA is complaining about hundreds of terrible performing database queries.)
I return "prepared" IQueryable<TEntity>s from the repositories/services that cover - for example - security concerns like applying Where clauses for the user's access rights or append a Where clause for a search term or apply a NoTracking option to the query. I tell the UI developer: "You are allowed to extend the query with a) projections (Select), b) paging (Take and Skip) and perhaps c) sorting (OrderBy) because I consider those three query parts as UI concerns. All other query requirements (filtering, joining, grouping, etc.) have to be implemented in the repository/service layer and are forbidden in the UI layer." The most important piece here are projections that materialize ViewModels directly through the LINQ/SQL query without intermediate mapping layer and without the overhead to load more than the needed columns/properties.
These are only some thoughts. Every approach has its benefits and downsides. Working in small teams where at least one or a few developers have an overview what is happening in both the repository/service and the UI/"projection" layer the last option works fine for me in my experience although it doesn't always work with the strict rules decribed (for example, the filter by product category for included order items of an order requires to apply a Where clause inside of the projection, i.e. in the UI layer). For POST requests and data modifications I would use DTOs that send to data collected from a view back to a service to be processed there.
For stricter separation of "query layer" and UI layer I would probably prefer something close to the second option, maybe not with an interface/DTO for every UI requirement, but somehow reduced to a set of DTOs for the most common requirements (with the price of a little overhead of sometimes unnecessarily loaded properties). However, I expect that to be more work than the last option due to the larger amount of necessary repository/service methods, the additional maintenance of (perhaps many) DTOs and the intermediate mapping between DTOs and ViewModels.
Personally I am concerned about materializing full entities, especially complex object graphs, when I don't need them 90% of the time. But my concern is not verified by extensive performance measurements proving that this approach is really a problem for a "normal" application that doesn't have special high performance needs.
How can anyone give you sound advice when we have no clue as to what it is you are building? In the grand scheme of things, you might be building the wrong solution (not saying you are). So do realize all we can relate to is technical design issues and similar past experiences.
Many people face your problem, indeed. The mapping is loose coupling tax in the land of static typing. Maybe a more dynamic language could solve some of your pain. Or maybe you might find virtue in automating more (DSL, MDA). You could also switch to client server instead.
Interfaces are not layers, rather abstractions. Use them wisely.
Personally, I'd never take these shortcuts. Been bitten too many times trying to skip steps. Logic starts popping up in odd places. If I have a data driven app to develop simple datasets come to mind, EF as well. But I don't call the objects aggregate or entity in the DDD sense, just entity in the ERD sense. Transactionscript might be a better fit than doing the partial method sprinkeling. As for read model objects, these are not layers of indirection.
Overall, I get the feeling, and it is just that, you're making a mess of things because you fight the mapping friction by taking on a dependency on objects that don't reveal the required shape (navigation properties that are null) thereby causing problems in a different area.
I'll just try to be short - we went for the method 2 - ie, add layer of interfaces that you use on the client. You can have EF generate them for you, just a little tweak of the .tt templates.
Yes, it creates (yet) another layer, but it's logic-free and adds no complexity. Of course, if your client needs to deserialize entities, you have to add (yet) another layer that will handle deserialization and reference both the entities definitions and the interfaces that he'll return to the client. But it's also thin, so we learned to live with it, because it turned out to work just fine, and the client really stays clean...
The problem: I now use the entities all over the place, so client code
can see their navigation properties.
I don't quite get why this is a problem and how it's related to EF entities in particular. By client code do you mean presentation layer code or any code consuming your entities ?
For UI code a simple solution is to define ViewModels that just don't expose these navigation properties (or only expose a few of them depending on the object graph depth your GUIs need).
For other code it's only normal to be able to see the navigation properties of entities. They are public for a reason. You can end up breaking the Law of Demeter if you abuse them, but it's a matter of developer discipline not to fall into that trap.
An entity contains its own contract - all code that has access to the entity is supposed to be able to use any part of this contract. If you feel like your entities are exposing too much and that you need to put interfaces on top of them to restrain access to certain parts, maybe it's just a different entity.
I don't worry about the difference between the "data layer" and "domain layer" any longer, as there's no point - the terms are
interchangeable. I let EF do it's thing, and add interfaces and
repositories on top when needed.
I've merged my "data" and "domain" projects (into "core", boring name, I know), and I could almost swear that Visual Studio is
actually running faster.
I allow EF entities to go up and down the stack, but, I still map them to presentation models / viewmodels as usual.
For simple operations I call repositories directly from controllers, for complex operations I use domain managers/services as
usual; the repositories never expose IQueryable.
I define entities/POCOs as partial classes, so I can add domain behavior separately in corresponding partial classes.
None of these things seems to be fundamentally anti-DDD to me, except data/domain separation.
Especially if you do database-first EF -DDD is clearly a domain-centric approach and you shouldn't define your tables before defining your entities. It's also not clear whether some of your domain entities talk to the database or EF directly (not DDD - and more generally, layered-architecture - compliant) or you systematically have data access objects in between (DDD compliant).
I was wondering how people who follow DDD get around potential performance issues with using EF and the repository pattern with returning an aggregate root with children.
e.g. Parent
----- Child A
Or even e.g. Parent
----- Child A
------- Child A2
If I bring back the aggregate root's data from the repository and use a navigational property EF then fires off another query because it is utlising lazy loading. This is a problem because we are experiencing 100+ queries when we are in a loop.
If I bring back the aggregate root's data from the repository with the children's data as well by using the 'Include' statements, this will bring back the childrens data from the repository with its parent. Then when I use the navigational properties no queries fire off because that data is already in memory.
The problem with the second approach is that some of our data for the child object can be quite big e.g. 100,000+ records.
Obviously I don't want to store 100,000+ records in memory for the child. We decided to use paging to select 10 at a time to get around this, but another issue is when we are trying to use calculations on the children like sum, total count etc but we can only do that in memory on the 10 records we have pulled back.
I know the DDD way is to pull back the object graph with all of its data in memory and then you traverse through the objects for the data you need to display.
There is a split in our team with some believing we should pull back the aggregate root and it's children together and some feel we should have a method on the aggregate root's repository that queries the childrens data directly and pulls back the child object.
I Just wondered how other people have solved the performance issues with large amounts of data being stored in memory with the parent/child.
If you have to deal with performance you must use the second approach with special method exposed on repository - that is the point of repository to provide you such methods otherwise you can use EF context / set directly.
Theory is nice if you work with theoretical data - once you have real data you must tweak theory to work in real world scenarios.
You can also check this article (there are three following articles on the blog). It does the second way but it pretends to be the first way. It works for Count but maybe you can use the idea for some other scenarios as well.
The DDD way isn't always to pull back all the data that is required. One technique we use a pattern called double dispatching. This is where you make your call to your aggregate roots' method (or domain service) with all the parameters it requires but also with it you pass in a 'query only' repository type interface parameter too. This enables the root or its children decide what extra data is required and when it's it should be returned by simply calling methods on this injected interface.
This approach adhere's to the DDD principals that states that aggregate roots should not be aware of repository implementation whilst providing an testable and highly performant domain code.
I am in the middle of trying to complete a design for a project and have basically come to a fork in the road. I have made up my mind that I want to use EF4 as my data persistence layer, but my existing database is causing me some pains. Changing or augmenting the database is not an option. I have a single table that really serves multiple purposes and contains 120 columns (I didn't design this table!!! - it is a DB2 carryover after a SQL Server conversion long ago). I have designed a class diagram that creates five entities from this table, at varying levels of aggregation. In my research of what to do in these situations, I have narrowed it down to either using a “QueryView” in my MSL layer or a “DefiningQuery” in my SSDL layer to create the entities I need from this monolith table. The resultant data will only need to be read-only. I’d prefer getting back a proper entity, but anonymous types or dbdatarecord would be okay.
I have attempted to use a QueryView in MSL with my entity defined in my CSDL but the MSL keeps getting regenerated and my changes lost when I compile. Why?
Can anyone provide input as to what I should do here? Is using a DefiningQuery or QueryView preferable in this situation? Any input as to keeping these changes after updating my model from the database or compiling would be also very appreciated.
QueryView should not be regenerated. I'm not sure how QueryView behaves when you do update from database. I'm sure that DefiningQuery will be deleted when doing Update from database because DefiningQuery is defined in SSDL which is completely deleted during Update from database. I have some workaround for custom DefiningQueries by using two different EDMXs - one just for queries and second for entities updated from database. General concept is described here.
Difference between QueryView and DefiningQuery is the level where these constructs are included. QueryView is MSL element built as custom ESQL query on top of existing entity so your 120 columns entity must exists in EDMX. From unknown reason QueryView has no support for aggregations. DefiningQuery is SSDL element build as custom SQL query. It is by default used for database views (btw. probably best choice for you).
I'm working on a RoR app, but this is a general question of strategy for OOP. Consider the case where there are multiple types of references that you are storing data for: Books, Articles, Presentations, Book Chapters, etc. Each type of reference is part of a hierarchy where common behaviors sit at the most general point of inheritance, and at the DB level I am using single-table inheritance. The type is set by use of a select option, so lets say that I was entering the data as if it were a Book, but then realize that it is only a chapter. So I change the type of reference by selecting "Book Chapter", which then posts an update to the existing model/form. The question is what is the correct strategy for handling this?
On one hand it seems preferable to transform the existing record in the DB to avoid id exhaustion, and potentially save on operations for creating/deleting records. This however tends to make the update strategy complex.
On the other hand, it seems more in keeping with general object orientation to create a new object (and record) using the old object to initialize values that you want to persist, then delete the old object. This I think makes more sense in terms of an Object Space (heap), and I think is more aligned to ideas like those of general systems.
However, I haven't nailed this down, and after sitting on it for a while, I'm pitching it to this community to see what "right" way to do this is.
Prefer immutable objects, in other words: the second strategy. Your objects may not be immutable by themselves, but reducing mutability is often a step in the right direction.
Besides that, this is the more natural way. In general OOP terms there's no way to change the type of an object. In your situation you can, but it's still an awkward and unusual thing to do.
On the other hand, if your objects are represented by the same (identical) class and changing the type is done by setting a high-level property, one could argue that re-creating the object is overkill.
Still, reducing mutability is a good think, but if your class is already designed to be mutable, it might not be worth it. (In that special case where there's actually only one actual class from the language point of view)
The transformation you're talking about doesn't seem to warrant a new record or even a new object.
Each of the entries you cited have the same form. They are block of text with siblings, parents and children. A chapter may have a block of text, with a parent book and a child endnote, for example. They are differentiated on a DB level only by their type, which itself could be a field.
All you need is a model to handle these 'elements' differently depending on whether or not it is flagged as a book, or a chapter, etc. If an element is flagged as a chapter, yet has no parent, for example, then you might flag it as a 'book' when it is saved to the DB.
Changing the way an element is flagged doesn't change the element, it only changes the way it is viewed. So long as the element knows how to find it's children the data will compute in the same way. As far as the model is concerned it's just an element you're worrying about. The rest is done in the UI.
#father = Hierarchy.find(:first, :conditions => ['label = ?', 'father'])
#father.children.each do |child|
puts #father.object_id == child.parent.object_id
end
I would have thought the results here would be all true.
Instead they are all false.
Why does ActiveRecord work this way instead of recognizing that these are the same Ruby objects?
To return existing objects when possible instead of creating new ones ActiveRecord would have to keep track of which objects were created and which entry in the database they respond to, which would be some overhead. Even then it would still have to lookup child.parent in the database to know that it's the same entry that #father represents, so there wouldn't be any considerable gain performance wise from this caching (well on the ruby side it safes allocating multiple objects but at the cost of the bookkeeping overhead, but on the database side it should be basically the same).
So given that the AR people probably decided that preventing different objects corresponding to the same database entry would either be detrimental or at least not worth the effort, so they chose not to do it.
For anyone who stumbles across this years after it was asked (like me!), check out https://stackoverflow.com/a/4116397/1000655.
It suggests using :inverse_of to set up Bi-directional associations. I wish I hadn't skimmed that bit of the documentation so many times in the past!
Object ID is the pointer (sort of) to the object. The loading of rails objects doesn't "share" memory space, so you're getting a copy of the parent object when you do child.parent. To understand this -- you can do parent.something = foo, and subsequently compare child.parent.something and you'll see they are different. You'd have to re-load the child from the database before it will reflect the changes to the parent object.
However, odds are you're using the wrong ID value. If you want the ActiveRecord ID (e.g. the value of the ID column in your SQL DBMS), use #father.id == child.parent.id
Reusing objects is problematic. What if you make changes to a model instance, but before you save it, you do another find that brings back that same object? The new one should reflect the database, but the old one should still have the changed data.
So yes, it would be a lot of overhead to keep track of each instance and the dirty fields in each one. The memory savings would not be worth the effort.
As far as I'm concerned AR should at least support an Identity Map plugin. This is the biggest issue I deal with when working with AR. I realize it adds some overhead, but short-lived memory overhead is better than the undue tax on the database by having it pull the same records again and again. It's like GC. You can do it yourself or you can use a high-level language to abstract it away so that you can concentrate on business logic. You can really fuss to optimize your AR or you can have take advantage of Identity Map.