OSGi and the Modularity of Persistence: The Effect of Relationships - schema

Most questions revolving around the title of this post ask about making Hibernate, or some other access layer, run in an OSGi container. Or they ask about making the data source run in an OSGi container.
My questions concern the effect of OSGi modularity on the structure of the database itself. Specifically:
How do we make the structure of a database itself modular, so that
when we load a module--say, Contact Management--the schema is
updated to include tables specifically associated with that module?
What is the effect of the foregoing approach on relationships?
I think the second question is the more interesting. Let's say that Contact Management and Project Management are two distinct OSGi modules. Each would have its own set of tables in the schema. But what if, at the database level, we need to form cross-module relationships between two or more tables? Maybe we wish to see a list of projects that a certain contact is, or has been, working on.
Any solution seems to lead down the path of the various modules' having to know too much about each other. We could write into the Project Management specification that that module expects a source of contacts, and then abstract such an expectation through services, interfaces, pub-sub etc. Seems like a lot of work, though, to avoid a hard-wired relationship between the two modules' underlying tables.
What's the point of being modular up top and in the middle if we may necessarily need to break that modularity with relationships between tables down below? Are denormalization and a service bus really a healthy solution?
Any thoughts?
Thank you.

Regarding first question, LiquiBase can be used. You can update and rollback changesets on bundle activation and deactivation.
Regarding second question, I think it is something that should be considered while designing your architecture. There is no help from some tool.
If PM module depends on CM module, it is safe for PM module to assume CM tables currently exist and make foreign relations to them, but not in the opposite direction. You should make it clear in your architecture that what modules depends on what modules and prevent dependency cycles.

After 5 years of JPA, I decided to leave it and after months of investigation I found Querydsl+Liquibase combo the best.
I worked a lot on developing helper OSGi components and a maven-plugin. The functionality of maven-plugin (code generation) can be easily integrated into other build tools as the maven plugin is only a wrapper around a standalone library.
You can find a detailed article about the solution here: http://bzsoldos.wordpress.com/2014/06/18/modularized-persistence/

In this kind of situation it is important to evaluate how independent are these modules/contexts. In DDD terms these two seem to be independent bounded contexts, so a contact in the pm module is a distinct entity (and also another class) than contact in the cm module. If you keep this distinction you then have some denormalization wrt the contact entity (e.g. you copy the id and name of the contact when adding it to a project, later changes to the contact in the cm module will require some pubsub to keep consistency) but each module will be very independent. I would keep the ui as a separate module, depending on both and providing the necessary glue (i.e. passing the ids and required info between them).

Maybe I misread the question, but in my opinion OSGI modularity has absolutely no impact on database structure. It's a data storage level, it can be modular of course, but for it's very own reasons - performance, data volumes, load, etc and with it's very own solutions - clusters, olap, partitioning and replication.
If you need data integrity between cm and pm, it should be provided by means which were initially designed for such sort of task - RDBMS. If you need software modularity - you select OSGI solution and your modules are communicating on much more higher logical/business level. They can be absolutely unaware of how persistence is provided - plain text file or 100-node Oracle RAC cluster.

Related

Share common dependencies for two .NET Core apps

I have two ASP.NET Core apps running on the same server and they share many dependencies.
I want to put all these common dependencies in a directory in order to save disk space. But I don't know how the config the apps needs to be so they search this particular directory in order to load them.
Thanks in advance
As far as I can see, there is conceptual complexity and misunderstanding here. Before I explain this, I would like to inform you that go over some assumptions.
There are only 2 web applications(could be API projects or different). I assume you don't have any projects. I have already asked you.
Dependencies are a big problem throughout the development process. And we developers are responsible handle this. Evolve the Tightly-Coupled systems to Loosely-coupled system gives us many advantages. For this reason, we aim to reduce the dependencies of the applications by using many technics, design patterns throughout the development process. I recommend you looking for dependencies and coupling concepts. I share some information that will be a starting point for you.
After looking for it, you will become aware that you need to separate dependencies at the application level rather than at the disk level. You will find that have many technic and approach. I am sure that after looking it for you take action will be easy.
Here are points;
https://dev.to/franiglesias/dependencies-and-coupling-4365
https://stackify.com/dependency-inversion-principle/
What is the difference between loose coupling and tight coupling in the object oriented paradigm?

Domain services seem to require only a fraction of the total queries defined in repositories -- how to address that?

I'm currently facing some doubts about layering and repositories.
I was thinking of creating my repositories in a persistence module. Those repositories would inherit (or implement/extend) from repositories created in the domain layer module, being kept "persistence agnostic".
The issue is that from all I can see, the necessities of the domain layer regarding its repositories are quite humble. In general, they tend to be rather CRUDish.
It's in general at the application layer level, when solving particular business use-cases that the queries tend to be more complex and contrived (and thus, the number of repository's methods to explode).
So this raises the question of how to deal with this:
1) Should I just leave the domain repository interfaces simple and then just add the extra methods in the repository implementations (such that the application layer, that does know about the repository implementations, can use them)?
2) Should I just add those methods at the domain level repository implementations? I think not.
3) Should I create another set of repositories to be used just at the application layer level? This would probably mean moving to a more CQRSesque application.
Thanks
I think you should react to the realities of your business / requirements.
That is, if your use-cases are clearly not "persistence agnostic" then don't hold on to that particular restriction. Not everything can be reduced to CRUD. In fact I think most things worth implementing can't be reduced to CRUD persistence. Most database systems relational or otherwise have a lot of features nowadays, and it seems quaint to just ignore those. Use them.
If you don't want to mix SQL with other code, there are still a lot of other "patterns" that let you do that without requiring you to abstract access to something you actually don't need abstraction to.
On the flipside, you build a dependency to a particular persistence system. Is that a problem? Most of the time it actually isn't, but you have to decide for yourself.
All in all I would choose option 4: Model the problem. If I need a complicated SQL to build a use-case, and I don't need database independence (I rarely if ever do), then just write it where it is used, end of story.
You can use other tools like refactoring later to correct design issues.
The Application layer doesn't have to know about the Infrastructure.
Normally it should be fine working with just what Repository interfaces declared in the Domain provide. The concrete implementations are injected at runtime.
Declaring repository interfaces in the Domain layer is not only about using them in domain services but also elsewhere.
Should I create another set of repositories to be used just at the
application layer level? This would probably mean moving to a more
CQRSesque application.
You could do that, but you would lose some reusability.
It is also not related to CQRS - CQRS is a vertical division of the whole application between queries and commands, not giving horizontal layers different ways of fetching data.
Given that a repository is not about querying but about working with full aggregates most of the time perhaps you could elaborate on why you may need to create a separate set of repositories that are used only in your application/integration layer?
Perhaps you need to have a read-specific implementation that is optimised for data retrieval:
This would probably mean moving to a more CQRSesque application
Well, you'd probably want to implement read-specific bits that make sense. I usually have my data access separated either by namespace and, at times, even in a separate assembly. I then use I{Aggregate}Query implementations that return the relevant bits of data in as simple a type as possible. However, it is quite possible to even map to a more complex read model that even has relations but it is still only a read model and is not concerned with any command processing. To this end the domain is never even aware of these classes.
I would not go with extending the repositories.

ASP.NET MVC4 n-Tier Architecture: best approach

I developing a 3 tier architecture for an MVC4 webapp + EntityFramwork5.
I want to keep separete the layer, so only DAL knows that I'm using EF, for example.
Actually I have a lot of classes to manage that:
DAL
Entity POCO
Entity DataContext : DbContext
Entity Repository
BL
Entity ViewModel
Entity Service(instantiate Entity Repository)
WEB
Entity Controllers (instantiate Entity Service)
This is working but is quite hard to mantain. I was thinking to remove the Entity Repository in DAL and use directly the DataContext (if I'm not wrong, after all DbContext has been desingned to be a Repository and a Unit of Work), but that will force me to add a reference to EntityFramework.dll in my BL. Is not a big issue, but I0m not sure it is the best choice.
Any advice?
(I hope I gave enough informations, if you need more, just ask)
You can use this this and this article.
An experienced Architect does not need to go through every single step in the book to get a reasonable design done for a small web
application. Such Architects can use their experience to speed up the
process. Since I have done similar web applications before and have
understood my deliverable, I am going to take the faster approach to
get the initial part of our DMS design done. That will hopefully
assist me to shorten the length of this article.
For those who do not have experience, let me briefly mention the general steps that involved in architecturing a software below...
Understand the initial customer requirement - Ask questions and do research to further elaborate the requirement
Define the process flow of the system preferably in visual (diagram) form. I usually draw a process-flow diagram here. In my
effort, I would try to define the manual version of the system first
and then would try to convert that into the automated version while
identifying the processes and their relations. This process-flow
diagram that we draw here can be used as the medium to validate the
captured requirements with the customer too.
Identify the software development model that suite your requirements
When the requirements are fully captured and defined before the design start, you can use the 'Water-Fall' model. But when the
requirements are undefined, a variant of 'Spiral' can be used to deal
with that.
When requirements are not defined, the system gets defined while it is being designed. In such cases, you need to keep adequate spaces
in respective modules, which later expansions are expected.
Decide what architecture to be used. In my case, to design our Document Management System (DMS), I will be using a combination of
ASP.NET MVC and Multitier Architecture (Three Tier Variant).
Analyze the system and identify its modules or sub systems.
Pick one sub system at a time and further analyze it and identify all granular level requirements belonging to that part of the systems.
Recognize the data entities and define the relationships among entities (Entity Relationship Diagram or ER Diagram). That can
followed by identifying the business entities (Some business entities
directly map with the classes of your system) and define the business
process flow.
Organized your entities. This is where you normalize your database, and decide what OOP concepts and design pattern to be used
etc.
Make your design consistent. Follow the same standards across all modules and layers. This includes streamlining the concepts (as an
example, if you have used two different design patterns in two
different modules to achieve the same goal, then pick the better
approach and use that in both the places), and conventions used in the
project.
Tuning the design is the last part of the process. In order to do this, you need to have a meeting with the project team. In that
meeting you need to present your design to your team and make them ask
questions about it. Take this as an opportunity to honestly evaluate/
adjust your design.

How to design a business logic layer

To be perfectly clear, I do not expect a solution to this problem. A big part of figuring this out is obviously solving the problem. However, I don't have a lot of experience with well architected n-tier applications and I don't want to end up with an unruly BLL.
At the moment of writing this, our business logic is largely a intermingled ball of twine. An intergalactic mess of dependencies with the same identical business logic being replicated more than once. My focus right now is to pull the business logic out of the thing we refer to as a data access layer, so that I can define well known events that can be subscribed to. I think I want to support an event driven/reactive programming model.
My hope is that there's certain attainable goals that tell me how to design these collection of classes in a manner well suited for business logic. If there are things that differentiate a good BLL from a bad BLL I'd like to hear more about them.
As a seasoned programmer but fairly modest architect I ask my fellow community members for advice.
Edit 1:
So the validation logic goes into the business objects, but that means that the business objects need to communicate validation error/logic back to the GUI. That get's me thinking of implementing business operations as objects rather than objects to provide a lot more metadata about the necessities of an operation. I'm not a big fan of code cloning.
Kind of a broad question. Separate your DB from your business logic (horrible term) with ORM tech (NHibernate perhaps?). That let's you stay in OO land mostly (obviously) and you can mostly ignore the DB side of things from an architectural point of view.
Moving on, I find Domain Driven Design (DDD) to be the most successful method for breaking a complex system into manageable chunks, and although it gets no respect I genuinely find UML - especially action and class diagrams - to be critically useful in understanding and communicating system design.
General advice: Interface everything, build your unit tests from the start, and learn to recognise and separate the reusable service components that can exist as subsystems. FWIW if there's a bunch of you working on this I'd also agree on and aggressively use stylecop from the get go :)
I have found some o fthe practices of Domain Driven Design to be excellent when it comes to splitting up complex business logic into more managable/testable chunks.
Have a look through the sample code from the following link:
http://dddpds.codeplex.com/
DDD focuses on your Domain layer or BLL if you like, I hope it helps.
We're just talking about this from an architecture standpoint, and what remains as the gist of it is "abstraction, abstraction, abstraction".
You could use EBC to design top-down and pass the interface definitions to the programmer teams. Using a methology like this (or any other visualisation technique) visualizing the dependencies prevents you from duplicating business logic anywhere in your project.
Hmm, I can tell you the technique we used for a rather large database-centered application. We had one class which managed the datalayer as you suggested which had suffix DL. We had a program which automatically generated this source file (which was quite convenient), though it also meant if we wanted to extend functionality, you needed to derive the class since upon regeneration of the source you'd overwrite it.
We had another file end with OBJ which simply defined the actual database row handled by the datalayer.
And last but not least, with a well-formed base class there was a file ending in BS (standing for business logic) as the only file not generated automatically defining event methods such as "New" and "Save" such that by calling the base, the default action was done. Therefore, any deviation from the norm could be handled in this file (including complete rewrites of default functionality if necessary).
You should create a single group of such files for each table and its children (or grandchildren) tables which derive from that master table. You'll also need a factory which contains the full names of all objects so that any object can be created via reflection. So to patch the program, you'd merely have to derive from the base functionality and update a line in the database so that the factory creates that object rather than the default.
Hope that helps, though I'll leave this a community wiki response so perhaps you can get some more feedback on this suggestion.
Have a look in this thread. May give you some thoughts.
How should my business logic interact with my data layer?
This guide from Microsoft could also be helpful.
Regarding "Edit 1" - I've encountered exactly that problem many times. I agree with you completely: there are multiple places where the same validation must occur.
The way I've resolved it in the past is to encapsulate the validation rules somehow. Metadata/XML, separate objects, whatever. Just make sure it's something that can be requested from the business objects, taken somewhere else and executed there. That way, you're writing the validation code once, and it can be executed by your business objects or UI objects, or possibly even by third-party consumers of your code.
There is one caveat: some validation rules are easy to encapsulate/transport; "last name is a required field" for example. However, some of your validation rules may be too complex and involve far too many objects to be easily encapsulated or described in metadata: "user can include that coupon only if they aren't an employee, and the order is placed on labor day weekend, and they have between 2 and 5 items of this particular type in their cart, unless they also have these other items in their cart, but only if the color is one of our 'premiere sale' colors, except blah blah blah...." - you know how business 'logic' is! ;)
In those cases, I usually just accept the fact that there will be some additional validation done only at the business layer, and ensure there's a way for those errors to be propagated back to the UI layer when they occur (you're going to need that communication channel anyway, to report back persistence-layer errors anyway).

Why do we need entity objects? [closed]

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I really need to see some honest, thoughtful debate on the merits of the currently accepted enterprise application design paradigm.
I am not convinced that entity objects should exist.
By entity objects I mean the typical things we tend to build for our applications, like "Person", "Account", "Order", etc.
My current design philosophy is this:
All database access must be accomplished via stored procedures.
Whenever you need data, call a stored procedure and iterate over a SqlDataReader or the rows in a DataTable
(Note: I have also built enterprise applications with Java EE, java folks please substitute the equvalent for my .NET examples)
I am not anti-OO. I write lots of classes for different purposes, just not entities. I will admit that a large portion of the classes I write are static helper classes.
I am not building toys. I'm talking about large, high volume transactional applications deployed across multiple machines. Web applications, windows services, web services, b2b interaction, you name it.
I have used OR Mappers. I have written a few. I have used the Java EE stack, CSLA, and a few other equivalents. I have not only used them but actively developed and maintained these applications in production environments.
I have come to the battle-tested conclusion that entity objects are getting in our way, and our lives would be so much easier without them.
Consider this simple example: you get a support call about a certain page in your application that is not working correctly, maybe one of the fields is not being persisted like it should be. With my model, the developer assigned to find the problem opens exactly 3 files. An ASPX, an ASPX.CS and a SQL file with the stored procedure. The problem, which might be a missing parameter to the stored procedure call, takes minutes to solve. But with any entity model, you will invariably fire up the debugger, start stepping through code, and you may end up with 15-20 files open in Visual Studio. By the time you step down to the bottom of the stack, you forgot where you started. We can only keep so many things in our heads at one time. Software is incredibly complex without adding any unnecessary layers.
Development complexity and troubleshooting are just one side of my gripe.
Now let's talk about scalability.
Do developers realize that each and every time they write or modify any code that interacts with the database, they need to do a throrough analysis of the exact impact on the database? And not just the development copy, I mean a mimic of production, so you can see that the additional column you now require for your object just invalidated the current query plan and a report that was running in 1 second will now take 2 minutes, just because you added a single column to the select list? And it turns out that the index you now require is so big that the DBA is going to have to modify the physical layout of your files?
If you let people get too far away from the physical data store with an abstraction, they will create havoc with an application that needs to scale.
I am not a zealot. I can be convinced if I am wrong, and maybe I am, since there is such a strong push towards Linq to Sql, ADO.NET EF, Hibernate, Java EE, etc. Please think through your responses, if I am missing something I really want to know what it is, and why I should change my thinking.
[Edit]
It looks like this question is suddenly active again, so now that we have the new comment feature I have commented directly on several answers. Thanks for the replies, I think this is a healthy discussion.
I probably should have been more clear that I am talking about enterprise applications. I really can't comment on, say, a game that's running on someone's desktop, or a mobile app.
One thing I have to put up here at the top in response to several similar answers: orthogonality and separation of concerns often get cited as reasons to go entity/ORM. Stored procedures, to me, are the best example of separation of concerns that I can think of. If you disallow all other access to the database, other than via stored procedures, you could in theory redesign your entire data model and not break any code, so long as you maintained the inputs and outputs of the stored procedures. They are a perfect example of programming by contract (just so long as you avoid "select *" and document the result sets).
Ask someone who's been in the industry for a long time and has worked with long-lived applications: how many application and UI layers have come and gone while a database has lived on? How hard is it to tune and refactor a database when there are 4 or 5 different persistence layers generating SQL to get at the data? You can't change anything! ORMs or any code that generates SQL lock your database in stone.
I think it comes down to how complicated the "logic" of the application is, and where you have implemented it. If all your logic is in stored procedures, and all your application does is call those procedures and display the results, then developing entity objects is indeed a waste of time. But for an application where the objects have rich interactions with one another, and the database is just a persistence mechanism, there can be value to having those objects.
So, I'd say there is no one-size-fits-all answer. Developers do need to be aware that, sometimes, trying to be too OO can cause more problems than it solves.
Theory says that highly cohesive, loosely coupled implementations are the way forward.
So I suppose you are questioning that approach, namely separating concerns.
Should my aspx.cs file be interacting with the database, calling a sproc, and understanding IDataReader?
In a team environment, especially where you have less technical people dealing with the aspx portion of the application, I don't need these people being able to "touch" this stuff.
Separating my domain from my database protects me from structural changes in the database, surely a good thing? Sure database efficacy is absolutely important, so let someone who is most excellent at that stuff deal with that stuff, in one place, with as little impact on the rest of the system as possible.
Unless I am misunderstanding your approach, one structural change in the database could have a large impact area with the surface of your application. I see that this separation of concerns enables me and my team to minimise this. Also any new member of the team should understand this approach better.
Also, your approach seems to advocate the business logic of your application to reside in your database? This feels wrong to me, SQL is really good at querying data, and not, imho, expressing business logic.
Interesting thought though, although it feels one step away from SQL in the aspx, which from my bad old unstructured asp days, fills me with dread.
One reason - separating your domain model from your database model.
What I do is use Test Driven Development so I write my UI and Model layers first and the Data layer is mocked, so the UI and model is build around domain specific objects, then later I map these objects to what ever technology I'm using the the Data Layer. Its a bad idea to let the database structure determine the design of your application. Where possible write the app first and let that influence the structure of your database, not the other way around.
For me it boils down to I don't want my application to be concerned with how the data is stored. I'll probably get slapped for saying this...but your application is not your data, data is an artifact of the application. I want my application to be thinking in terms of Customers, Orders and Items, not a technology like DataSets, DataTables and DataRows...cuz who knows how long those will be around.
I agree that there is always a certain amount of coupling, but I prefer that coupling to reach upwards rather than downwards. I can tweak the limbs and leaves of a tree easier than I can alter it's trunk.
I tend to reserve sprocs for reporting as the queries do tend to get a little nastier than the applications general data access.
I also tend to think with proper unit testing early on that scenario's like that one column not being persisted is likely not to be a problem.
Eric,
You are dead on. For any really scalable / easily maintained / robust application the only real answer is to dispense with all the garbage and stick to the basics.
I've followed a similiar trajectory with my career and have come to the same conclusions. Of course, we're considered heretics and looked at funny. But my stuff works and works well.
Every line of code should be looked at with suspicion.
I would like to answer with an example similar to the one you proposed.
On my company I had to build a simple CRUD section for products, I build all my entities and a separate DAL. Later another developer had to change a related table and he even renamed several fields. The only file I had to change to update my form was the DAL for that table.
What (in my opinion) entities brings to a project is:
Ortogonality: Changes in one layer might not affect other layers (off course if you make a huge change on the database it would ripple through all the layers but most small changes won't).
Testability: You can test your logic with out touching your database. This increases performance on your tests (allowing you to run them more frequently).
Separation of concerns: In a big product you can assign the database to a DBA and he can optimize the hell out of it. Assign the Model to a business expert that has the knowledge necessary to design it. Assign individual forms to developers more experienced on webforms etc..
Finally I would like to add that most ORM mappers support stored procedures since that's what you are using.
Cheers.
I think you may be "biting off more than you can chew" on this topic. Ted Neward was not being flippant when he called it the "Vietnam of Computer Science".
One thing I can absolutely guarantee you is that it will change nobody's point of view on the matter, as has been proven so often on innumerable other blogs, forums, podcasts etc.
It's certainly ok to have open disucssion and debate about a controversial topic, it's just this one has been done so many times that both "sides" have agreed to disagree and just got on with writing software.
If you want to do some further reading on both sides, see articles on Ted's blog, Ayende Rahein, Jimmy Nilson, Scott Bellware, Alt.Net, Stephen Forte, Eric Evans etc.
#Dan, sorry, that's not the kind of thing I'm looking for. I know the theory. Your statement "is a very bad idea" is not backed up by a real example. We are trying to develop software in less time, with less people, with less mistakes, and we want the ability to easily make changes. Your multi-layer model, in my experience, is a negative in all of the above categories. Especially with regards to making the data model the last thing you do. The physical data model must be an important consideration from day 1.
I found your question really interesting.
Usually I need entities objects to encapsulate the business logic of an application. It would be really complicated and inadequate to push this logic into the data layer.
What would you do to avoid these entities objects? What solution do you have in mind?
Entity Objects can facilitate cacheing on the application layer. Good luck caching a datareader.
We should also talk about the notion what entities really are.
When I read through this discussion, I get the impression that most people here are looking at entities in the sense of an Anemic Domain Model.
A lot of people are considering the Anemic Domain Model as an antipattern!
There is value in rich domain models. That is what Domain Driven Design is all about.
I personally believe that OO is a way to conquer complexity. This means not only technical complexity (like data-access, ui-binding, security ...) but also complexity in the business domain!
If we can apply OO techniques to analyze, model, design and implement our business problems, this is a tremendous advantage for maintainability and extensibility of non-trivial applications!
There are differences between your entities and your tables. Entities should represent your model, tables just represent the data-aspect of your model!
It is true that data lives longer than apps, but consider this quote from David Laribee: Models are forever ... data is a happy side effect.
Some more links on this topic:
Why Setters and Getters are evil
Return of pure OO
POJO vs. NOJO
Super Models Part 2
TDD, Mocks and Design
Really interesting question. Honestly I can not prove why entities are good. But I can share my opinion why I like them. Code like
void exportOrder(Order order, String fileName){...};
is not concerned where order came from - from DB, from web request, from unit test, etc. It makes this method more explicitly declare what exactly it requires, instead of taking DataRow and documenting which columns it expects to have and which types they should be. Same applies if you implement it somehow as stored procedure - you still need to push record id to it, while it not necessary should be present in DB.
Implementation of this method would be done based on Order abstraction, not based on how exactly it is presented in DB. Most of such operations which I implemented really do not depend on how this data is stored. I do understand that some operations require coupling with DB structure for perfomance and scalability purposes, just in my experience there are not too much of them. In my experience very often it is enough to know that Person has .getFirstName() returning String, and .getAddress() returning Address, and address has .getZipCode(), etc - and do not care which tables are involed to store that data.
If you have to deal with such problems as you described, like when additional column breaks report perfomance, then for your tasks DB is a critical part, and you indeed should be as close as possible to it. While entities can provide some convenient abstractions they can hide some important details as well.
Scalability is interesting point here - most of websites which require enormous scalability (like facebook, livejournal, flickr) tend to use DB-ascetic approach, when DB is used as rare as possible and scalability issues are solved by caching, especially by RAM usage. http://highscalability.com/ has some interesting articles on it.
There are other good reasons for entity objects besides abstraction and loose coupling. One of the things I like most is the strong typing that you can't get with a DataReader or a DataTable. Another reason is that when done well, proper entity classes can make the code more maintanable by using first-class constructs for domain-specific terms that anyone looking at the code is likely to understand rather than a bunch of strings with field names in them used for indexing a DataRow. Stored procedures are really orthogonal to the use of an ORM since a lot of mapping frameworks give you the ability to map to sprocs.
I wouldn't consider sprocs + datareaders a substitute for a good ORM. With stored procedures, you're still constrained by, and tightly-coupled to, the procedure's type signature, which uses a different type system than the calling code. Stored procedures can be subject to modification to acommodate additional options and schema changes. An alternative to stored procedures in the case where the schema is subject to change is to use views--you can map objects to views and then re-map views to the underlying tables when you change them.
I can understand your aversion to ORMs if your experience mainly consists of Java EE and CSLA. You might want to have a look at LINQ to SQL, which is a very lightweight framework and is primarily a one-to-one mapping with the database tables but usually only needs minor extension for them to be full-blown business objects. LINQ to SQL can also map input and output objects to stored procedures' paramaters and results.
The ADO.NET Entity framework has the added advantage that your database tables can be viewed as entity classes inheriting from each other, or as columns from multiple tables aggregated into a single entity. If you need to change the schema, you can change the mapping from the conceptual model to the storage schema without changing the actual application code. And again, stored procedures can be used here.
I think that more IT projects in enterprises fail because of unmaintainability of the code or poor developer productivity (which can happen from, e.g., context switching between sproc-writing and app-writing) than scalability problems of an application.
I would also like to add to Dan's answer that separating both models could enable your application to be run on different database servers or even database models.
What if you need to scale your app by load balancing more than one web server? You could install the full app on all web servers, but a better solution is to have the web servers talk to an application server.
But if there aren't any entity objects, they won't have very much to talk about.
I'm not saying that you shouldn't write monoliths if its a simple, internal, short life application. But as soon as it gets moderately complex, or it should last a significant amount of time, you really need to think about a good design.
This saves time when it comes to maintaining it.
By splitting application logic from presentation logic and data access, and by passing DTOs between them, you decouple them. Allowing them to change independently.
You might find this post on comp.object interesting.
I'm not claiming to agree or disagree but it's interesting and (I think) relevant to this topic.
A question: How do you handle disconnected applications if all your business logic is trapped in the database?
In the type of Enterprise application I'm interested in, we have to deal with multiple sites, some of them must be able to function in a disconnected state.
If your business logic is encapsulated in a Domain layer that is simple to incorporate into various application types -say, as a dll- then I can build applications that are aware of the business rules and are able, when necessary, to apply them locally.
In keeping the Domain layer in stored procedures on the database you have to stick with a single type of application that needs a permanent line-of-sight to the database.
It's ok for a certain class of environments, but it certainly doesn't cover the whole spectrum of Enterprise applications.
#jdecuyper, one maxim I repeat to myself often is "if your business logic is not in your database, it is only a recommendation". I think Paul Nielson said that in one of his books. Application layers and UI come and go, but data usually lives for a very long time.
How do I avoid entity objects? Stored procedures mostly. I also freely admit that business logic tends to reach through all layers in an application whether you intend it to or not. A certain amount of coupling is inherent and unavoidable.
I have been thinking about this same thing a lot lately; I was a heavy user of CSLA for a while, and I love the purity of saying that "all of your business logic (or at least as much as is reasonably possible) is encapsulated in business entities".
I have seen the business entity model provide a lot of value in cases where the design of the database is different than the way you work with the data, which is the case in a lot of business software.
For example, the idea of a "customer" may consist of a main record in a Customer table, combined with all of the orders the customer has placed, as well as all the customer's employees and their contact information, and some of the properties of a customer and its children may be determined from lookup tables. It's really nice from a development standpoint to be able to work with the Customer as a single entity, since from a business perspective, the concept of Customer contains all of these things, and the relationships may or may not be enforced in the database.
While I appreciate the quote that "if your business rule is not in your database, it's only a suggestion", I also believe that you shouldn't design the database to enforce business rules, you should design it to be efficient, fast and normalized.
That said, as others have noted above, there is no "perfect design", the tool has to fit the job. But using business entities can really help with maintenance and productivity, since you know where to go to modify business logic, and objects can model real-world concepts in an intuitive way.
Eric,
No one is stopping you from choosing the framework/approach that you would wish. If you are going to go the "data driven/stored procedure-powered" path, then by all means, go for it! Especially if it really, really helps you deliver your applications on-spec and on-time.
The caveat being (a flipside to your question that is), ALL of your business rules should be on stored procedures, and your application is nothing more than a thin client.
That being said, same rules apply if you do your application in OOP : be consistent. Follow OOP's tenets, and that includes creating entity objects to represent your domain models.
The only real rule here is the word consistency. Nobody is stopping you from going DB-centric. No one is stopping you from doing old-school structured (aka, functional/procedural) programs. Hell, no one is stopping anybody from doing COBOL-style code. BUT an application has to be very, very consistent once going down this path, if it wishes to attain any degree of success.
I'm really not sure what you consider "Enterprise Applications". But I'm getting the impression you are defining it as an Internal Application where the RDBMS would be set in stone and the system wouldn't have to be interoperable with any other systems whether internal or external.
But what if you had a database with 100 tables which equate to 4 Stored Procedures for each table just for basic CRUD operations that's 400 stored procedures which need to be maintained and aren't strongly-typed so are susceptible to typos nor can be Unit Tested. What happens when you get a new CTO who is an Open Source Evangelist and wants to change the RDBMS from SQL Server to MySql?
A lot of software today whether Enterprise Applications or Products are using SOA and have some requirements for exposing Web Services, at least the software I am and have been involved with do.
Using your approach you would end up exposing a Serialized DataTable or DataRows. Now this may be deemed acceptable if the Client is guaranteed to be .NET and on an internal network. But when the Client is not known then you should be striving to Design an API which is intuitive and in most cases you would not want to be exposing the Full Database schema.
I certainly wouldn't want to explain to a Java developer what a DataTable is and how to use it. There's also the consideration of Bandwith and payload size and serialized DataTables, DataSets are very heavy.
There is no silver bullet with software design and it really depends on where the priorities lie, for me it's in Unit Testable code and loosely coupled components that can be easily consumed be any client.
just my 2 cents
I'd like to offer another angle to the problem of distance between OO and RDB: history.
Any software has a model of reality that is to some degree an abstraction of reality. No computer program can capture all the complexities of reality, and programs are written just to solve a set of problems from reality. Therefore any software model is a reduction of reality. Sometimes the software model forces reality to reduce itself. Like when you want the car rental company to reserve any car for you as long as it is blue and has alloys, but the operator can't comply because your request won't fit in the computer.
RDB comes from a very old tradition of putting information into tables, called accounting. Accounting was done on paper, then on punch cards, then in computers. But accounting is already a reduction of reality. Accounting has forced people to follow its system so long that it has become accepted reality. That's why it is relatively easy to make computer software for accounting, accounting has had its information model, long before the computer came along.
Given the importance of good accounting systems, and the acceptance you get from any business managers, these systems have become very advanced. The database foundations are now very solid and noone hesitates about keeping vital data in something so trustworthy.
I guess that OO must have come along when people have found that other aspects of reality are harder to model than accounting (which is already a model). OO has become a very successful idea, but persistance of OO data is relatively underdeveloped. RDB/Accounting has had easy wins, but OO is a much larger field (basically everything that isn't accounting).
So many of us have wanted to use OO but we still want safe storage of our data. What can be safer than to store our data the same way as the esteemed accounting system does? It is an enticing prospects, but we all run into the same pitfalls. Very few have taken the trouble to think of OO persistence compared to the massive efforts by the RDB industry, who has had the benefit of accounting's tradition and position.
Prevayler and db4o are some suggestions, I'm sure there are others I haven't heard of, but none have seemed to get half the press as, say, hibernation.
Storing your objects in good old files doesn't even seem to be taken seriously for multiuser applications, and especially web applications.
In my everyday struggle to close the chasm between OO and RDB I use OO as much as possible but try to keep inheritance to a minimum. I don't often use SPs. I'll use the advanced query stuff only in aspects that look like accounting.
I'll be happily supprised when the chasm is closed for good. I think the solution will come when Oracle launches something like "Oracle Object Instance Base". To really catch on, it will have to have a reassuring name.
Not a lot of time at the moment, but just off the top of my head...
The entity model lets you give a consistent interface to the database (and other possible systems) even beyond what a stored procedure interface can do. By using enterprise-wide business models you can make sure that all applications affect the data consistently which is a VERY important thing. Otherwise you end up with bad data, which is just plain evil.
If you only have one application then you don't really have an "enterprise" system, regardless of how big that application or your data are. In that case you can use an approach similar to what you talk about. Just be aware of the work that will be needed if you decide to grow your systems in the future.
Here are a few things that you should keep in mind (IMO) though:
Generated SQL code is bad
(exceptions to follow). Sorry, I
know that a lot of people think that
it's a huge time saver, but I've
never found a system that could
generate more efficient code than
what I could write and often the
code is just plain horrible. You
also often end up generating a ton
of SQL code that never gets used.
The exception here is very simple
patterns, like maybe lookup tables.
A lot of people get carried away on
it though.
Entities <> Tables (or even logical data model entities necessarily). A data model often has data rules that should be enforced as closely to the database as possible which can include rules around how table rows relate to each other or other similar rules that are too complex for declarative RI. These should be handled in stored procedures. If all of your stored procedures are simple CRUD procs, you can't do that. On top of that, the CRUD model usually creates performance issues because it doesn't minimize round trips across the network to the database. That's often the biggest bottleneck in an enterprise application.
Sometimes, your application and data layer are not that tightly coupled. For example, you may have a telephone billing application. You later create a separate application which monitors phone usage to a) better advertise to you b) optimise your phone plan.
These applications have different concerns and data requirements (even the data is coming out of the same database), they would drive different designs. Your code base can end up an absolute mess (in either application) and a nightmare to maintain if you let the database drive the code.
Applications that have domain logic separated from the data storage logic are adaptable to any kind of data source (database or otherwise) or UI (web or windows(or linux etc.)) application.
Your pretty much stuck in your database, which isn't bad if your with a company who is satisfied with the current database system your using. However, because databases evolve overtime there might be a new database system that is really neat and new that your company wants to use. What if they wanted to switch to a web services method of data access (like Service Orientated architecture sometime does). You might have to port your stored procedures all over the place.
Also the domain logic abstracts away the UI, which can be more important in large complex systems that have ever evolving UIs (especially when they are constantly searching for more customers).
Also, while I agree that there is no definitive answer to the question of stored procedures versus domain logic. I'm in the domain logic camp (and I think they are winning over time), because I believe that elaborate stored procedures are harder to maintain than elaborate domain logic. But that's a whole other debate
I think that you are just used to writing a specific kind of application, and solving a certain kind of problem. You seem to be attacking this from a "database first" perspective. There are lots of developers out there where data is persisted to a DB but performance is not a top priority. In lots of cases putting an abstraction over the persistence layer simplifies code greatly and the performance cost is a non-issue.
Whatever you are doing, it's not OOP. It's not wrong, it's just not OOP, and it doesn't make sense to apply your solutions to every othe problem out there.
Interesting question. A couple thoughts:
How would you unit test if all of your business logic was in your database?
Wouldn't changes to your database structure, specifically ones that affect several pages in your app, be a major hassle to change throughout the app?
Good Question!
One approach I rather like is to create an iterator/generator object that emits instances of objects that are relevant to a specific context. Usually this object wraps some underlying database access stuff, but I don't need to know that when using it.
For example,
An AnswerIterator object generates AnswerIterator.Answer objects. Under the hood it's iterating over a SQL Statement to fetch all the answers, and another SQL statement to fetch all related comments. But when using the iterator I just use the Answer object that has the minimum properties for this context. With a little bit of skeleton code this becomes almost trivial to do.
I've found that this works well when I have a huge dataset to work on, and when done right, it gives me small, transient objects that are relatively easy to test.
It's basically a thin veneer over the Database Access stuff, but it still gives me the flexibility of abstracting it when I need to.
The objects in my apps tend to relate one-to-one to the database, but I'm finding using Linq To Sql rather than sprocs makes it much easier writing complicated queries, especially being able to build them up using the deferred execution. e.g. from r in Images.User.Ratings where etc. This saves me trying to work out several join statements in sql, and having Skip & Take for paging also simplifies the code rather than having to embed the row_number & 'over' code.
Why stop at entity objects? If you don't see the value with entity objects in an enterprise level app, then just do your data access in a purely functional/procedural language and wire it up to a UI. Why not just cut out all the OO "fluff"?