Lets take an example of a product classification. All the products needs to be classified as vegetable or not. The business logic is, the product can be classified as vegetable if that product is from company A, B & C. If the product is not from those companies they are not vegetables. There are millions of products. This can be done in a stored proc with few lines of code. The operation may take only few seconds if it is done synchronizely.
As I understand, the DDD goes against the idea of putting the logic in the stored procedure. The logic can be put as a behavior on product which can self classify based on who is the source. To do this, all the million products need to be read into memory, process and then save it back to the database.
The problem here is the large amount of memory this operation needs. If the operation is done in chucks like 50,000 the repository has to first figure out how may products needs to be classified and should tell the domain the long running operation has to go in chunk. Surely, this approach is going to take more time and a bad user experience for the user who has to wait more time than a process than a stored procedure takes.
What is the reasonable approach to DDD when it comes to long running processes? Is the delay expected, so the app has to inform the user that the classification is going to take time and will let the user know when that is complete? And should not use stored procedure, but have the logic part of the domain.
UPDATE
Just to add some clarity, this classification process is done quite often. The application has to support the classification process, not an ETL or can't wait longer. That's why I'm trying to find the trade offs between using a stored procedure versus DDD.
Also note that it is not a Query, but a Command. The command can be called ClassifyAllProductsCommand(). When this command is run, there was no classification before. After the classification, other users of the system should see the new classification. For example, the product A is classified as Unavailable, and after the classification it can be Vegetable or Meat.
I think you're confusing DDD. If you were looking for
Vegetable
typeProducts
, you would call a service that would retrieveProducts
for a particularCompany
. There would be no need to load all the products into memory.Application or domain-centric design, just means designing your application around the business domain and not from a collection of database tables upwards (like a data-centric approach).
In contrast you end up with more data associations (joins) being done in your application and less in monolithic stored procedures. Which moves all your business logic into the application and not in the persistence device (the database), which kinda makes a lot of sense.
Also, if you deny yourself huge table joins then you also think carefully about things that traditionally cause massive overhead on your database and end up moving towards better design, like creating a separate reporting database, message buses, asynchronous tasks, etc.
EDIT
It seems like a common phrase in DDD but "it depends on your specific domain".
Without knowing the detail, I would want to know how often these classifications occur. Can they be done as the
Products
are created? Are they done often or rarely, planned or unpredictably?If the classifications are common and must be done across all one million products, it might be best to create a smaller model for the
Product
, maybe something with justSmallProduct.Id
andSmallProduct.CompanyId
(probably naming it something better). Then data cache this smaller collection in memory and perform operations against it.If the check to see if the product is a
Vegetable
is common and only one of a few possible classifications, it might be best to haveClassifications
in their own table and a linking table to link them toProducts
. Then the problem becomes more of a one time data setup issue.On the rare chance that you're using a Document Database, you could just store these classifications in a collection on the
Product
object itself.