Question

So I was searching the web looking for best practices when implementing the repository pattern with multiple data stores when I found my entire way of looking at the problem turned upside down. Here’s what I have…

My application is a BI tool pulling data from (as of now) four different databases. Due to internal constraints, I am currently using LINQ-to-SQL for data access but require a design that will allow me to change to Entity Framework or NHibernate or the next data access du jour. I also hold steadfast to decoupled layers in my apps using an IoC framework (Castle Windsor in this case).

As such, I’ve used the Repository pattern to abstract the actual data access code from my business layer. As a result, my business object is coded against some I<Entity>Repository interface and the IoC Container is used to manage the actual implementation. In this case, I would expect to have a concrete Linq<Entity>Repository that implements the interface using LINQ-to-SQL to do the work. Later I could replace this with an EF<Entity>Repository with no changes required to my business layer.

Also, because I’m coding against the interface, I can easily mock the repository for unit testing purposes.

So the first question that I have as I begin coding the application is whether I should have one repository per DataContext or per entity (as I’ve typically done)? Let’s say one database contains Customers and Sales with the expected relationship. Should I have a single OrderTrackingRepository with methods that work with both entities or have a separate CustomerRepository and a different SalesRepository?

Next, as a BI tool, the primary interface is for reporting, charting, etc and often will require a “mashup” of data across multiple sources. For instance, the reality is that one database contains customer information while another handles sales information and a third holds other financial information but one of my requirements is to display aggregated information that spans all three. Plus, I have to support dynamic filtering in the UI. Obviously working directly against the LINQ-to-SQL or EF DataContext objects (Table<Entity>, for instance) will allow me to pretty much do anything. What’s the best approach to expose that same functionality to my business logic when abstracting the DAL with a repository interface?

This article: link text indicates that EF4 has turned this approach around and that the repository is nothing more than an IQueryable returned from the EF DataContext which brings up a whole other set of questions.

But, I think I’ve rambled on enough…

UPDATE (Thanks, Steven!)

Okay, let me put a more tangible (for me, at least) example on the table and clarify a few points that will hopefully lead to an approach I can better wrap my head around.

While I understand what Steven has proposed, I have a team of developers I have to consider when implementing such things and I’m afraid they will get lost in the complexity (yes, a real problem here!).

So, let’s remove any direct tie-in with Linq-to-Sql because I don’t want a solution that is dependant upon the way L2S works – or even EF, for that matter. My intent has been to abstract away the data access technology being used so that I can change it as needed without requiring collateral changes to the consuming code in my business layer. I’ve accomplished this in the past by presenting the business layer with IRepository interfaces to work against. Perhaps these should have been named IUnitOfWork or, more to my liking, IDataService, but the goal is the same. These interfaces typically exposed methods such as Add, Remove, Contains and GetByKey, for example.

Here’s my situation. I have three databases to work with. One is DB2 and contains all of the business information for a customer (franchise) such as their info and their Products, Orders, etc. Another, SQL Server database contains their financial history while a third SQL Server database contains application-specific information. The first two databases are shared by multiple applications.

Through my application, the customer may enter/upload their financial information for a given time period. When entered, I have to perform the following steps:

1.Validate the entered data against a set of static rules. For example, the data must contain a legitimate customer ID value (in the case of an upload). This requires a lookup in the DB2 database to verify that the supplied customer ID exists and is current.
2.Next I have to validate the data against a set of dynamic rules which are contained in the third (SQL Server) database. An example may be that a given value cannot exceed a certain percentage of another value.
3.Once validated, I persist the data to the second SQL Server database containing the financial data.
All the while, my code must have loosely-coupled dependencies so I may mock them in my unit tests.

As part of the analysis, I know that I have three distinct data stores to work with and about a half-dozen or so entities (at this time) that I am working with. In generic terms, I presume that I would have three DataContexts in my application, one per data store, with the entities exposed by the appropriate data context.

I could then create a separate I{repository|unit of work|service} for each entity that would be consumed by my business logic with a concrete implementation that knows which data context to use. But this seems to be a risky proposition as the number of entities increases, so does the number of individual repository|UoW|service types.

Then, take the case of my validation logic which works with multiple entities and, thereby, multiple data contexts. I’m not sure this is the most efficient way to do this.

The other requirement that I have yet to mention is on the reporting side where I will need to execute some complex queries on the data stores. As of right now, these queries will be limited to a single data store at a time, but the possibility is there that I might need to have the ability to mash data together from multiple sources.

Finally, I am considering the idea of pulling out all of the data access stuff for the first two (shared) databases into their own project and have been looking at WCF Data Services as a possible approach. This would give me the basis for a consistent approach for any application making use of this data.

How does this change your thinking?

Answer 1

Look at this SO answer. I think it shows a simplified model of what you want. IQueryable<T> is indeed our new Repository :-). DataContext and ObjectContext are our Unit of Work.

UPDATE 2:

Here is a blog post that describes the model you might be looking for.

UPDATE 3

It would be wise to hide the shared databases behind a service. This will solve several problems:

1. This will make the database private to the service, which makes it much easier to change the implementation when needed.
2. You can put the needed validation logic (for database 1) in that service and can create tests for that validation logic in that project.
3. Clients accessing that service can assume correctness of the service, and its validation logic.

The result of this is that your application will send data to the service to validate it. Call the service to fetch data. Query its own private database (database 3) and join the data of the three data source locally together. I’ve never been a fan of using cross-database or even cross-server (in your situation) database calls and letting the database join everything together. Transactions will be promoted to distributed-transactions and it’s hard to predict how many data the servers will exchange.

When you abstract the shared databases behind the service, things get easier (at least from your application’s point of view). Your application calls services it trusts which limits the amount of code in that application and the amount of tests. You still want to mock the calls to such a service, but that would be pretty easy. It should also solve the problem of validating over multiple data sources.

Validation is always a hard part. I’m very familiar with Validation Application block, and love it for it’s flexibility. It isn’t however an easy framework, but you might take a peek at what you can do with it. For instance, I’ve written several articles about integration with O/RM tools and how to ’embed’ a context (context as in DataContext/Unit of Work) in Validation Application Block.