Just curious if anyone knows why Room requires you to list out each entity. Why can't it automatically find all of your entities with the #Entity annotation?
Since you can have more than a single database in a project, Room needs to know which classes are used by which DB.
By declaring the Entities in the DB class you are actually building a hierarchy that informs the compiler which classes to use to produce the wanted result from the DAO.
In theory, your argument does have a point as in cases of a single DB or where there are multi DB but no overlaps there should not be a problem but to prevent overlaps and for clarity sake, they demand that you declare everything.
Related
I am using spring data JDBC.
I normally use the specific repository object as auto-wired and perform the necessary operation.
Let us consider, I have employees who belong to a specific continent.
We have a repository for each continent.
After retrieving data from employee table, based on his continent value, need to initialize the specific continent reporisotory.
Can you please guide me on how to create a repository object dynamically?
To at least hint to an answer for the verbatim question:
Take a look at JdbcRepositoryFactoryBean and JdbcRepositoryFactoryBeanUnitTest.
But I don't think this would solve your problem nor would anything in that direction.
What you might find helpful though is JdbcAggregateTemplate. It is hard to tell since you share very little about what you actually want to achieve.
In general Spring Data is not build for data models that are self referencing, i.e. where you obtain table or column names from the data model itself at runtime. In such cases it is probably better to create your own repository implementation, which takes your special use case into account but is limited to the exact features you need which very often is sufficiently limited to be maintainable.
In our project we're trying to apply the Bounded Context ideology and we've faced kind of obvious problem of performance. E.g., we have different classes (in different contexts) for representing a user in the system: Person in our core domain's context and User in security context. So, we have two different repositories for each of the aggregate, but they are using the same table in DB and sometimes accessing the same data.
Is there common solution to minimize db roundtrips in this case? Are there ORM's which deals with it, or should we code some caching system by ourselves?
upd: the db is from legacy app, and we'll have to use it "as is"
So, we have two different repositories for each of the aggregate, but
they are using the same table in DB and sometimes accessing the same
data.
The fact that you have two aggregates stored in the same table is an indication of a problem with the design. In this case, it seems you have two bounded contexts - a BC for the core domain (Person is here) and an identity/access BC (User is here). The BCs are related and the latter can be seen as upstream from the former. A Person in the core domain has a corresponding User in the identity BC, but they are not exactly the same thing.
Beyond this relationship between the BCs there are questions regarding ownership of behavior. For example, both a Person and a User may have a name and what is to be determined is who own's the behavior of changing a name. This can be implemented in several ways. Person may have its own name and changes should be propagated to the identity BC. Similarly, User may own changes to name, in which case they must be propagated to Person via a synchronization mechanism.
Overall, your problem could be addressed in two ways. First, you can store Person and User aggregates in different tables. Any given query should only use one of these tables and they can be synchronized in an eventually consistent matter. Another approach is to decouple the behavioral domain model from a model designed for queries (read-model). This way, you can create a read-model designed to serve a specific screen(s) and have a customized query, perhaps even outside of an ORM.
If all the Users are Person too (sometimes external services are modeled as special users too), the only data that User and Person should share on the database are their identifiers.
Indeed each entity in a domain model should hold references only to the data that they need to ensure their invariants.
Moreover I guess that Users are identified by Username and Persons are identified by something else (VAT code or so..).
Thus, the simplest optimization technique is to avoid to encapsulate in an entity those informations that are not required to ensure its invariants.
Furthermore you simply need an effective context mapping technique to easily pass from User to Person when needed. I use shared identifiers for this.
As an example you can expose the Person's identifier in the User class, so that a simple query to the Person's repository can provide you the data you need.
Finally I suggest you the Vaughn Vernon series on Aggregate Root Design.
I would like to find out how people out there manage the dbml file in a more scalable manner?
Do you have just one DataClasses1.dbml and drag every table into it?
Do you have separate files for separate logical groupings, eg Accounts, HR? If so, how do you visually see the foreign key relationships when one table has links to a table in another dbml file?
Thanks.
Better will be to use one single DBML file for all your tables, so that you can see all your relations i.e Foreign Key etc all together..But its depends upon your requirement totally..
Using Entity Framework (same for linq-to-sql) I like to use separate context classes for distinct parts of the database.
But what is "distinct"?
In most cases everything that is related to the core business of an application is too much interrelated for a separate context to be meaningful. But almost every application has lateral tasks like authorization, translation, auditing and so on. These are good candidates for separate contexts.
There will still be connections to the business logic though. As you probably know, you cannot join classes from separate contexts in a way that the join is translated to SQL. Only in memory. So it is useful to duplicate some entities in several contexts. So, for instance, both the business context and the authorization context will contain User entities. One context should be responsible for maintenance of the entity and the other one(s) should use it read-only.
Edit
By duplication of entities I mean that two (or more) contexts can have an entity that maps to the same table in the database. Like User. If you like, the business context could be for creating and updating users, the authorization context is (for instance) for adding roles to a specific user, without modifying the user itself.
I have an MVC3 NHibernate/ActiveRecord project. The project is going okay, and I'm getting a bit of use out of my model objects (mostly one giant hierarchy of three or four classes).
My application is analytics based; I store hierarchial data, and later slice it up, display it in graphs, etc. so the actual relationship is not that complicated.
So far, I haven't benefited much from ORM; it makes querying easy (ActiveRecord), but I frequently need less information than full objects, and I need to write "hard" queries through complex and multiple selects and iterations over collections -- raw SQL would be much faster and cleaner.
So I'm thinking about ditching ORM in this case, and going back to raw SQL. But I'm not sure how to rearchitect my solution. How should I handle the database tier?
Should I still have one class per model, with static methods to query for objects? Or should I have one class representing the DB?
Should I write my own layer under ActiveRecord (or my own ActiveRecord-like implementation) to keep the existing code more or less sound?
Should I combine ORM methods (like Save/Delete) into my model classes or not?
Should I change my table structure (one table per class with all of the fields)?
Any advice would be appreciated. I'm trying to figure out the best architecture and design to go with.
Many, including myself, think the ActiveRecord pattern is an anti-pattern mainly because it breaks the SRP and doesn't allow POCO objects (tightly coupling your domain to a particular ORM).
In saying that, you can't beat an ORM for simple CRUD stuff, so I would keep some kind of ORM around for that kind of work. Just re-architect your application to use POCO objects and some kind or repository pattern with your ORM implementation specifics in another project.
As for your "hard" queries, I would consider creating one class per view using a tiny ORM (like Dapper, PetaPoco, or Massive), to query the objects with your own raw sql.
I am working on an asp.net MVC 3 web application and I am using database first, but after I have mapped the DB tables into entity classes using entity framework, I am interacting with these tables as I will be interacting on the code first approach by dealing with Database tables as classes an objects.
So after mapping the tables into entity classes I find that the code first approach and DB first are very similar but except of start writing the entities classes from scratch (as in code first) I have created the entity classes from existing database tables - which is easier and more convenient in my case.
So are there specific cases on which i will not be able to do some functionalities unless i am using one approach over the other which till now i cannot find any?
Having dealt with many many headaches using db-1st EDMX pre EF 4.1, I am partial to code-first. But I'm not going to evangelize it.
In addition to the direct sproc mapping & function import features mentioned in Pawel's answer & comment, you won't be able to change the namespaces or any other code in the generated files when you use db-first. Afaik all of the files are nested under the .tt file. If there is a way to move them into logical folders & namespaces in your project, then I'm not aware of it.
Also if you ever want to separate your DbContext into a separate project from your entities, I recall this was possible pre-EF 4.1. But it was more cumbersome, because you had to run custom tool on both .tt files after each db change. With code-first this is pretty straightforward because you're dealing with pure OOP.
I think that the biggest limitation of CodeFirst (as compared to ModelFirst/DatabaseFirst approaches) is that you cannot map your CUD operations to stored procedures. If you are not planning to do that then you should be good to go.
To be more specific - You can invoke stored procedures using SqlQuery method on DbSet which will cause the returned entities to be tracked or more general SqlQuery and ExecuteSqlCommand on Database class (for Database.SqlQuery the returned objects do not have to be entities and there is no tracking for these objects). That's about it. You cannot map Create/Update/Delete operations to stored procedures. FunctionImports are not supported as well
EDIT
It's possible to map CUD operations to stored procedures in EF6 now