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Improve this questionI had a debate with my co-worker on whether certain logic belongs in the data access or business logic layer.
The scenario is, the BLL needs some data to work with. That data primarily lives in the database. We want to cache that data (using System.Runtime.Caching) so it's quickly available on subsequent requests. The architecture is such that the DAL and the BLL live on the same box and in different assemblies (projects in the same solution). So there is no concern of hitting a DAL over the wire or anything like that.
My argument is that the decision to hi开发者_StackOverflow社区t the cache vs the database is a concern of the DAL. The business logic layer should not care where the data comes from, only that it gets the data it needs.
His argument is that the data access layer should be "pure" and "dumb" and any logic to make that decision to hit the cache vs the database should be in the business logic layer.
In my opinion what he's saying is undermining separation of concerns and causing the layers to be more tightly coupled when the goal is to keep things loosely coupled. I can see where the BLL might want to control this if it was a specific program/ui function to decide where to go for data, but that simply isn't the case here. It's just a very simple caching scenario where the database is the primary data store.
Thoughts?
I agree with you 100%.
Caching is part of the DAL and does not belong in the BLL.
Let's take hibernate as an example, it use a caching system to store your entity's. Hibernate is responsible and know how to control his cache, (dirty read, flushing data etc)
You don't want to cluttered your BLL with all this low-level data logic.
Regards
I believe that the caching should be done in the business layer. The moment you try to get the data from DAL, you can check if the data is available in cache system.runtime.caching, then use cache data otherwise fetch data from the database. Moreover if you want to invalidate cache due to some reason, you can do it by calling a function in the business later.
The whole purpose in separating business logic from data is so that you can swap them out as business requirements or technology changes. By intermixing them, you are defeating this logic, and therefore, on a theoretical level you are correct. In the real world however, I think you need to be a bit more pragmatic. What's the real life expectancy of the application , what is the likelihood that the technology is going to change, and how much extra work is involved in keeping the two cleanly separated?
My initial reaction would be the same as yours, to let the data layer cache the information. This can even be integrated in with a strategy to subscribe to changes in the database, or implement polling to ensure the data is kept up-to-date.
However, if you intend to re-use the data layer in other projects, or even if not, it might not be a bad idea to implement a new business layer between the existing one and the data layer to handle caching decisions. Because ultimately, caching is a not just a performance issue, it does involve business decisions about concurrency and other matters.
An n-tier system is just that, you're not limited on how many levels you want to seperate things into.
I know I'm over two years late to the game but I wanted to add something:
If you have an interface defined for your DAL, you can write a caching mechanism that follows that interface and manages 'cache vs. hit the data source' concerns without the technology or source-specific DAL code having to worry about it and without the BLL having to worry about it. Example:
internal interface IThingsGateway
{
public Thing GetThing(int thingId);
public void UpdateThing(ThingUpdateInfo info);
}
internal class MsSqlThingsGateway : IThingsGateway
{
// implementation specific to MsSql here
}
internal class CachingThingsGateway : IThingsGateway
{
private IThingsGateway underlyingImplementation;
public CachingThingsGateway(IThingsGateway implementation)
{
this.underlyingGateway = implementation;
}
public Thing GetThing(int thingId)
{
if (this.HasCachedThing(thingId))
{
return this.GetCachedThing(thingId);
}
var thing = this.underlyingGateway.GetThing(thingId);
this.SetCachedThing(thingId);
return thing;
}
public void UpdateThing(ThingUpdateInfo info)
{
this.underlyingGateway.UpdateThing(info);
this.ClearCachedThing(info.ThingId);
}
}
And I would use this same approach if I needed to check multiple data sources for a thing: write an implementation of IThingsGateway
that handles the logic of juggling the various data sources, delegating to the appropriate one... then wrap that in the CachingThingsGateway
. Client code will ultimately obtain an IThingsGateway
reference from some factory or container, which is where the wrapping and instantiating would occur.
And all of this really doesn't take that much extra effort. If you use caching you will have to write that code anyways, and the overhead generated by putting it in another class with the same interface is minimal at worst.
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