I reluctantly adopted a data mapper approach for my current project but I've been left a little confused.
Business Model
A worker has a name, a set of working hours, and a cost.
Data Model
A worker is made up of a labour type and a working pattern (three different tables). The cost of the worker is calculated based on a combination of the labour type and the working pattern.
My problem...
I seem to have two different models, one that represents business logic and one that represents data structure. I was of the understanding that my model should represent the business logic, but what happens when I want to insert a new worker? This is done using a form with two drop downs, the working pattern & the cost, the id's of which are not needed by the business model.
Confused? I am.
There is no real support for data models with the zend framework. But weierophinney does a realy good job to show how they could be implemented. Another very good description is this one.
Usually a model represents the data and includes the logic. The data model is a backend independed way to write/get data. For the model and the application it doesn't matter from where the data comes. Thus the datastorage can be exchanged without having to touch anything else.
Default data modelling in Zend Framework (Zend_Db_Table) isn't probably the best choice for object oriented data modelling.
Try using ORM like Doctrine (http://www.doctrine-project.org/) it allows you to create domain object model and almost transparently store it in database. This way you can have business model and data model combined in single classes.
Related
I am implementing a database search algorithm which searches over many collections in a MongoDB and returns optimized results based on the state of the entire database. I have no problems with the implementation, but the nomenclature and how I should structure the file system is bugging me. Where in the model-view-controller pattern should I place read only operations? Is it a service? It has a controller but I hardly think it satisfies the criteria to be a model.
This question is extremely language dependant and the features that exist within that language. I will speak from a PHP point of view.
Search functions should go into the model, the model backs up as a data provider in the MVC pattern. A single central point from which to dish out instances of it self.
Some MVCs implement what is known as factory classes. They are specifically designed to sit outside of the MVCs normal pattern to be able to provide data: http://en.wikipedia.org/wiki/Factory_method_pattern . As someone who has used this pattern I can say it gets complicated and unmanageable very quickly. That is why I prefer to backup the model as a data provider itself, it merely requires class organisation.
Model View Controller architecture is pretty much the equivalent of a three or four tier solution in a client server setup and the same rules apply.
Complex and intensive database functionality lives with the tool that is best suited to the task and is most re-usable and in this case I would argue that the RDBMS would be the best option in the vast majority of RDBMS's as it is the RDBMS that best knows how to manipulate it's data, work out query plans etc...
It could also be argued that the model layer would be the most natural place from a purist coding point of view where you have all your data access in one layer.
It is highly unlikely that it would ever be advantageous to place this sort of functionality in the least re-usable layer i.e. the controller/view
This is of course only my opinion and I suspect you will get many alternative opinions but ( can not for the life of me think that from a performance point of view that yopur logic belongs anywhere other than at the database level
UPDATE
A model is the guardian of all data. if a view or controller wants data, it asks the model for that data. The view or controller shouldn't care about how the data is obtained or where it comes from. It's about separation of concerns. So that leaves the question. Do I place the code to query the database in the model or in the RDBMS?
Well of course you have to have a method in a model for the view or controller to call in the first place so of course you need a model but what goes inside that method and where the actual query SQL lives is up to the designer. The point is, that so long as the query lives at model or database level you are hiding the implementation from the view or controller and are free to change the implementation whenever you wish without having to worry about the potentially many places it is called from.
So model or RDBMS is the answer. The solution chosen depends on the MVC tools you are using and the RDBMS you are using. Also remember that a model does not have to consist of a single method which is what you are implying you may be thinnking from your comment.
I've been reading a lot about Entity Frameworks and now I want to implement it on my game. An Entity Framework is based on making the game entities simple containers of Components, where a Component contains a certain characteristic of an Entity (and all the variables/accessors which describe this characteristic).
The game logic is then modularized by creating Systems. Each System implements and runs a certain aspect of the game logic (eg. Collisions, Rendering, Animation). Each System has to be able to access every Entity which has some certain combination of Components (eg. RenderSystem has to get only Entities which have PositionComponent and AnimationComponent).
My question regards the best data structure for achieving such functionality.
My current idea is to create a Vector (with N cells, where N is the number of possible components) of List of Entity. So whenever I create (instantiate and add certain Components) an Entity, I would also reference this Entity from each List for each Component it contains. "Killing" an Entity would require removing each reference from each List. The problem would be querying which entities have to be processed by a certain System, because the search-key would be a combination of Components, and not a single Component, adding overhead to the operation (many searches and comparisons would have to be done).
Is my idea good? Is there any better data structure I can use? Note that everything in the game is supposed to be an Entity, summing up to thousands of Entites on a single Level (I could possibly use some space partitioning).
They are two ways of doing it,
The purely data oriented system would lead you not to have an Entity class but just components sharing an ID. In this case, a vector or a hashmap for every system wouldn't be a problem as the search in these data structure is fast. If you want several components per system per entity you can aggregate your components in one data structure adapted for each system.
The problem is that a pure data oriented system can be less usable than a more pragmatic approach where you keep all the features of the previously described system but you keep an entity class that holds reference to his components (or aggregated components structures) of every system. Processing an entity (deleting or inspecting it) becomes much easier as you still have a place where all the information about what the entity is, i.e. what it is made of and not what state it is in, can be found in one place instead of querying every system.
In your case, the best thing is to try... It's quite easy and fast to implement a rough engine in the two ways, and once you've played with the two you'll be able to decide which one suites you better.
This article is valuable as far as it suggests 4 iterations for the data structure, but no one is a good solution in my opinion. But I recommend to read it, because there is a detailed analysis of the problem, nice estimations in terms of memory and such other good material.
I stumbled upon the following two articles First and Second in which the author states in summary that ORM Entities and Domain Entities shouldn't be mixed up.
I face exactly this problem at the moment as I code with EF 6.0 using the Code First approach. I use the POCO classes as entities in the EF as well as my domain/business objects. But I find myself frequently in the situation where I define a property as public or a navigation property as virtual only because the EF Framework forces me to do so.
I don't know what to take as the bottom line of the two articles? Should I really create for example a CustomerEF class for the entity framework and a CustomerD for my domain. Then create a repository which consumes CustomerD maps it to CustomerEF do some queries and than maps back the received CustomerEF to CustomerD. I thought EF is all about mapping my domain entities to the data.
So please give me some advice. Do I overlook an important thing the EF is able to provide me with? Or is this a problem which can not completely solved by the EF? In the latter case what is a good way to manage this problem?
I agree with the general idea of these posts. An ORM class model is part of a data access layer first and foremost (even if it consists of so-called POCOs). If any conflict of interests arises between persistence and business logic (or any other concern), decisions should always be made in favor of persistence.
However, as software developers we always have to balance between purism and pragmatism. Whether or not to use the persistence model as a domain model depends on a number of factors:
The size/coherence of the development team. When the whole team knows that properties can be public just because of ORM requirements, but should not be set all over the place, it may not be a big deal. If everybody knows (and obeys) that an ID property is not to be used in business logic, having IDs may not be a big deal. A scattered, unexperienced or undisciplined team may need more stringent segregation of code.
The overlap between business logic concerns and persistence concerns. Object oriented design thrives when a class model sticks to SOLID principles. But these principles are not necessarily at odds with persistence concerns. I mean that although the concerns are different, in the end their resultant requirements may be quite similar. For instance, both concerns may require valid object state and correct associations.
There can be use cases, however, in which objects temporarily need to be in a state that absolutely shouldn't be stored. This may be a reason to work with dedicated domain classes. Another reason may be that the entity model just can't fulfill the best segmentation of responsibilities. For instance, a business process "blacklisting customer" may require data that is scattered over so many entity objects that new domain classes must be designed that can encapsulate the data and the methods working on them. In other words: doing this by entities would violate the Tell Don't Ask principle.
The need for layering. For instance, if the data access layer targets different database vendors it may have to consist of interchangeable parts that are vendor-specific (e.g. to account for subtle differences in data types between Oracle and Sql Server or to exploit vendor-specific features). Using the persistence model as domain model would probably bleed vendor-specific implementations into the business logic. That would be really bad. There the data access layer should be precisely that, a layer.
(Very trivial) The amount of data. Creating objects takes time and resources. When "many" objects are involved in a business case it may just be too expensive to build both entity objects and domain objects.
And more, undoubtedly.
So I would always try to be a pragmatist. If entity classes do a decent job, go for it. If the mismatch is too large, create a business domain for appropriate parts of the business logic. I would not slavishly follow a (any) design pattern just because it is a good pattern. Contrary to what is said in the post, it requires a lot of maintenance to map an entity model onto a business model. When you find yourself creating myriads of business classes that are almost identical to entity classes it's time to rethink what you're doing.
We develop the back office application with quite large Db.
It's not reasonable to load everything from DB to memory so when model's proprties are requested we read from DB (via EF)
But many of our UIs are just simple lists of entities with some (!) properties presented to the user.
For example, we just want to show Id, Title and Name.
And later when user select the item and want to perform some actions the whole object is needed. Now we have list of items stored in memory.
Some properties contain large textst, images or other data.
EF works with entities and reading a bunch of large objects degrades performance notably.
As far as I understand, the problem can be solved by creating lightweight entities and using them in appropriate context.
First.
I'm afraid that each view will make us create new LightweightEntity and we eventually will end with bloated object context.
Second. As the Model wraps EF we need to provide methods for various entities.
Third. ViewModels communicate and pass entities to each other.
So I'm stuck with all these considerations and need good architectural design advice.
Any ideas?
For images an large textst you may consider table splitting, which is commonly used to split a table in a lightweight entity and a "heavy" entity.
But I think what you call lightweight "entities" are data transfer objects (DTO's). These are not supplied by the context (so it won't get bloated) but by projection from entities, which is done in a repository or service.
For projection you can use AutoMapper, especially its newer feature that I describe here. This allows you to reduce the number of methods you need to provide "for various entities" (DTO's), because the type to project to can be given in a generic type parameter.
I know that core data should not be considered as ORM but it still offers the functionality that is similar to ORM. Just curious, is it implementing data mapper pattern? I know "The Data Mapper is a layer of software that separates the in-memory objects from the database. Its responsibility is to transfer data between the two and also to isolate them from each other." (Martin Fowler). IMHO context manager handles all SQL stuff into one transaction, so it's very performance wise design and IMHO core data might be considered implementing data mapper pattern.
One year latter, I will contribute with my two cents
I am not an ORM expert and just recently started something using a Data Mapper, but as a long time Core Data user I can say that no. The main objective of this pattern is having a clear cut of a domain object from all database related operations.
Once I start writing unit tests, the first thing I notice is that I must load a database, even if it is just some in memory store, but I do must load one. Also there are no mappers for each class, I have no control about how each relation is stored.
Core Data loads lots of meta information about your object graph and forces some structure to them. Although you can change the persistent store and bake something of your own, you will have lots of restrictions about how to do it, with a clear "relational" feeling to it.
The idea is good, we might say it is some variation of it. Something that I do love is that the save operation is done by the context, not the object itself. So there is some type of separation.
However look at those functions like "awakeFromFetch" or "didSave", both operations are related with the data store, not a plain domain object. A proper Data Mapper pattern would allow you to define those operations for each persistent store, not unified in a single object.
UPDATE:
Funny enough one day after my answer I had to deal with an old CoreData based project and must come back to improve this answer. To make things clear, I do consider that "seems like a pattern" is not enough. For example, implementation of the facade and adapter patterns is quite similar, but you name them differently depending on how you use them.
Is Core Data implementing data mapper?
I must say that my "not quite" should have been "definitely not!"
I have just been very angry because I needed to rename some fields and later add new ones. Although I do know quite well how auto-migrations work with Core Data I forgot how annoying these are.
How many times do you need some new field, rename something, experiment until you get it right.... and every single tiny change requires a full blown database migration? With Data Mappers this never happens because domain objects are perfectly decoupled. You only touch the database to catch up with the domain objects after you finish some new feature. Core Data forces you to bind at every single moment every single detail of your domain objects.
Boy, how sweet life was until I forgot that "tiny" annoyance of Core Data being the exact opposite of what you can achieve with data mappers.