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).
In OOD, design of an object is said to be characterized by its identity and behavior.
Having used ORM's in the past, the primary purpose, in my opinion, revolves around the ability to store/retrieve data. That is to say, ORM objects are not design by behavior, but rather data (i.e. database tables). Case and point: Many ORM tools come with a point-to-a-database-table-and-click-object-generator.
If objects are no longer characterized by behavior this will, in my opinion, muddy the identity and responsibility of the objects. Subsequently, if objects are not defined by a responsibility this could lend a hand to having tightly coupled classes and overall poor design.
Furthermore, I would think that in an application setting, you would be heading towards scalability issues.
So, my question is, do you think that ORM's are counterproductive to OO design? Perhaps the underlying question would be whether or not they are counterproductive to application development.
There's a well-known and oft-ignored impedance mismatch between the requirements of good database design and the requirements of good OO design. Most developers (in my experience) either do not understand this impedance mismatch or do not care. Since it's more common to start with the database and generate the objects from it (rather than the reverse), then yes, you'll end up with objects that are great as a persistence layer but sub-optimal from an OO perspective. (The reverse, generating the database from the object model, makes me want to stab my eyes out.)
Why are they sub-optimal from an OO perspective? Because the objects produced by an ORM are not business objects, even with partial classes and the like. Business objects model behavior. ORM objects model persistence. I'm not going to spend ten paragraphs arguing this distinction. It's something Rocky Lhotka has covered quite well in his books on Business Objects and his CSLA framework. Whether or not you like or use CSLA, I think his arguments are solid ones.
If objects are no longer characterized by behavior this will, in my opinion, muddy the
identity and responsibility of the objects.
The objects in question do have database reading and writing as defined behavior. They just don't have much other than that.
The reality of the situation is pretty simple: object orientation isn't an end in itself, it's a means to an end -- but in some cases it just doesn't do much to improve the end result. A lot of uses for ORM form a case in point -- they are thousands of variations of CRUD applications that don't need or want to attach any real behavior to most of the data they process.
The application as a whole gains flexibility by not encoding much (if any) of the data's "behavior" into the code of the application itself. Instead, they're often better off with that as "dumb" data, that they simply pass through from UI to database and back out to reports and such. With a bit of care, this can allow a substantial level of user customization that's almost impossible to match when you try to treat the data as real objects with real behavior encoded into the application proper.
Of course, there's another side to that: it can make it substantially more difficult to ensure the integrity of the data or that the data is only used appropriately -- I've seen code that accidentally used the wrong field in a calculation, so they were averaging the office numbers instead of office sizes in square feet. Both were user-defined fields that just said the contents should be numeric. The application had no way to know that one made perfect sense, and the other didn't at all.
Case and point: Many OR/M tools come with a point-to-a-database-table-and-click-object-generator.
Yes but there are equal, if not greater numbers or ORM solutions that base themselves off your objects and generate your database tables.
If you start with data and then tramp down forcing auto-generated objects to have object behaviours, yes, you might get confused... But if you start with the object and generate the database as a secondary layer, you end up with something a lot more usable, even if the database isn't perhaps as optimised as it could be.
If you're looking for an excuse not to use ORM, don't use it. I personally find it saves me thousands of lines of code doing trivial things that the ORM does just great.
I don't believe ORM are counterproductive to OO design, unless you want to insist that persistence is an integral part of behavior.
I'd separate persistence from business behavior. You're certainly free to add busines behavior to any object that an ORM generates for you.
I've also seen ORM systems which tend to go from the OO model and generate the database.
If anything, I would say ORMs are more biased towards producing good OO code than they are to producing good database code.
Ideally, a successful ORM bridges the two worlds and your application code would be great from a business domain problem-solving and implementation perspective and your database code and model would be great from a normalization, performance and ETL/reporting/replication whatever perspective.
On systems where it separates your data from behavior it's absolutely counterproductive.
Orm systems tend to analyze existing database tables to create stupid "Objects" in your language. These things are not true objects because they do not contain business behavior, but since people have these structures, they tend to want to use them.
Ruby on Rails (Active Record) actually binds your data to a "Live" class--this is much better.
I've never seen a system I really liked--ActiveRecord is close but it makes a few rubiesque assumptions that I'm not quite comfortable with--the biggest being supplying public setters & getters by default.
But to sum up--I've seen a lot of good OO programmers write screwed up code because of ORM.
As with most questions of this type, it depends on your usage.
The main ways to use ORM tools are:
Define object by data, use this object throughout application code (BAD BAD BAD)
Use ORM objects only for data access, define your own objects with an interpretive layer between (Much Better)
If starting from scratch a 3rd method is to design data from your object model. (Best if possible)
So yes, if you define the object by the data tables and use that throughout your code you will not be using OOD and introducing very poor design and maintenance issues.
But if you only use the ORM objects as a data access tool (replacing ADO) then you are free to use good OOD and ORM together. Sure, more code is required to build the interpretation layer, but enables much better practices, with not much more code required than old ADO code.
I'm answering this from a C# perspective, since that is where I do the majority of my development....
I see your point, but I think with the ability to create partial classes you can still create objects with any behavior you like and still get the power that an OR/M brings to the table for data retrieval.
From what I've seen of ORMs they do not go against OO principles - fairly orthogonal to them in fact. (for info - pretty new to ORM technology, Java perspective)
My reasoning is that ORMs help you store the data members of a class to a persistent store without having to couple to that store and write that code yourself. You still decide on the data members and write the behaviours of a class.
I guess you could abuse ORMs to break OO principles, but then you can do that with anything. You might use tooling to create skeletal data classes from a pre-existing table, but you would still create methods etc.
I read a debate in the comments here (current live site, without comments).
Why the debate? A Dataset for me is like a relational database, an Object is a hierarchical-like model. Why do people absolutely want a "pure" Object model, whereas we still deal with relational databases, so why not combine the two?
And if we should, is there any lightweight, comprehensive framework that allows us to do that (not a heavy mammoth, like NHibernate, which has a huge learning curve)?
"Pure objects" are a lot easier to work with, the typed object gives you intellisense and compile-time type checking.
Bare datasets are very cumbersome and annoying to work with - you need to know the column names, there's no type checking possible, so if you mistype a column name, you're out of luck and won't discover the error until runtime (the worst possible scenario).
Typed datasets are a step in the right direction, but the "things" you work with in your .NET code are still tied very closely and tightly to your database implementation - not typically a good thing, since any change in the underlying database might affect your app all the way up to your UI and cause a lot of changes being necessary.
Using an ORM like NHibernate allows you to better abstract and decouple the database (physical storage) layer from your logical business model - only in the simplest of scenarios will those two be an exact 1:1 match, so you'll need some kind of "translation" or mapping between the two anyway.
So all in all - using typed datasets might be okay for small, simple apps, but for a challenging, larger-scale, enterprise-level business app, I would never recommend coupling your business object model so closely and tightly to the database.
Marc
why do people absolutly want "pure" Object model
Because you don't want your application to depend on the database schema
Well, all the reasons you give were the same as the academical reasons that were given for EJB in Java which was a mess in the past. So arent't people falling into another fashionable hype ?
As I read here:
http://blogs.tedneward.com/2006/06/26/The+Vietnam+Of+Computer+Science.aspx
the promise is one thing, the reality is other thing.
Where is the proof upon the claims ?
Scientifically, Complexity is tight to the Concept of Entropy, you cannot reduce the inherent complexity of things, you can just move it somewhere else, so for me there is something fundamentally irational.
Ted Newards is highly controversial because it seems to me that everybody is herding like in the old EJB days: nobody dared to say EJB suck until Rod Johnson gets out with Hibernate.
Now it seems nobody cares to say ORM frameworks like Hibernate, Entity Framework, etc. are too complex, because there isn't yet another Rod Johnson II maybe :)
You pretend that adding a new layer solves the problem, it's not always the case even theorcially, like adding more team members when a project becomes a mess because adding more programmers also mean add to coordination and communication problem.
And in practice, what it seems, is that the layers that should be independant at least from the GUI viewpoint, aren't really. I see many people struggle to do simple stuff in the GUI when they use an ORM.
I am really torn right now between using O/R mappers or just sticking to traditional data access. For some reason, every time I bring up O/R mappers, fellow developers cringe and speak about performance issues or how they're just bad in general. What am I missing here? I'm looking at LINQ to SQL and Microsoft Entity Framework. Is there any basis to any of these claims? What kind of things do I have to compromise if I want to use an O/R mapper. Thanks.
This will seem like an unrelated answer at first, but: one of my side interests is WWII-era fighter planes. All of the combatant nations (US, Great Britain, Germany, USSR, Japan etc.) built a bunch of different fighters during the war. Some of them used radial engines (P47, Corsair, FW-190, Zero); some used inline liquid-cooled engines (Bf-109, Mustang, Yak-7, Spitfire); and some used two engines instead of one (P38, Do-335). Some used machine guns, some used cannons, and some used both. Some were even made out of plywood, if you can imagine.
In the end, they all went really really fast, and in the hands of a competent, experienced pilot, they would shoot your rookie ass down in a heartbeat. I don't imagine many pilots flew around thinking "oh, that idiot is flying something with a radial engine - I don't have to worry about him at all". Everyone understood that there were many different ways of achieving the ultimate goal, and each approach had its particular advantages and disadvantages, depending on the circumstances.
The debate between ORM and traditional data access is just like this, and it behooves any programmer to become competent with both approaches, and choose the option that is right for the job at hand.
I struggled with this decision for a long time. I think I was hesitant for two primary reasons. First, O/R mappers represented a lack of control over what was happening in a critical part of the app and, second, because so many times I've been disappointed by solutions that are awesome for the 90% case but miserable for the last 10%. Everything works for select * from authors, of course, but when you crank up the complexity and have a high-volume, critical system and your career is on the line, you feel you need to have complete control to tune every query pattern and byte over the wire. Most developers, including me, get frustrated the first time the tool fails us, and we cannot do what we need to do, or our need deviates from the established pattern supported by the tool. I'll probably get flamed for mentioning specific flaws in tools, so I'll leave it at that.
Fortunately, Anderson Imes finally convinced me to try CodeSmith with the netTiers template. (No, I don't work for them.) After more than a year using this, I can't believe we didn't do it sooner. My team uses Visual Studio DB Pro, and on every check-in our continuous integration build drops out a new set of data access layer assemblies. This handles all the common, low risk stuff automatically, yet we can still write custom sprocs for the tricky bits and have them included as methods on the generated classes, and we can customize the templates for the generated code as well. I highly recommend this approach. There may be other tools that allow this level of control as well, and there is a newer CodeSmith template called PLINQO that uses LINQ to SQL under the hood. We haven't that yet examined (haven't needed to), but this overall approach has a lot of merit.
Jerry
O/RM tools designed to perform very well in most situations. It will cache entities for you, it will execute queries in bulks, it has a very low level optimised access to objects which is way faster than manually assigning values to properties, they give you a very easy way to incorporate variations of aspect oriented programming using modern technics like interceptors, it will manage entity state for you and help resolve conflicts and many more.
Now cons of this approach usually lies in lack of understanding of how things work on a very low level. Most classic problem is "SELECT N+1" (link).
I've been working with NHibernate for 2.5 years now, and I'm still discovering something new about it almost on a daily basis...
Good. In most cases.
The productivity benefit of using an ORM, will in most case outweigh the loss of control over how the data is accessed.
There are not that many who would avoid C#, in order to program is MSIL or Assembly, although that would give them more control.
The problem that i see with a lot of OR mappers is that you get bloated domain objects, which are usually highly coupled with the rest of your data access framework. Our developers cringe at that as well :) It's just harder to port these object to another data access technology. If you use L2S, you can take a look at the generated code. It looks like a complete mess. NHibernate is probably one of the best at this. Your entities are completely unaware of your data access layer, if you design them right.
It really depends on the situation.
I went from a company that used a tweaked out ORM to a company that did not use a ORM and wrote SQL queries all the time. When I asked about using an ORM to simplify the code, I got that blank look in the face followed by all the negatives of it:
Its High Bloat
you don't have fine control over your queries and execute unnecessary ones
there is a heavy object to table mapping
its not dry code because you have to repeat your self
on an on
Well, after working there for a few weeks, I had noticed that:
we had several queries that were almost identical, and alot of times if there was a bug, only a handful would get fixed
instead of caching common tables queries, we would end up reading a table multiple times.
We were repeating our selves all over the place
We had several levels of skill level, so some queries were not written the most efficiently.
After I pointed most of this out, they wrote a "DBO" because the didn't want to call it an ORM. They decided to write one from scratch instead of tweaking out one.
Also, alot of the arguments come from ignorance against ORM's I feel. Every ORM that I have seen allows for custom queries, and even following the ORM's conventions, you can write very complex and detailed queries and normally are more human readable. Also, they tend to be very DRY, You give them your schema, and they figure the rest out, down to relationship mapping.
Modern ORM's have a lot of tools to help you out, like migration scripts, multiple DB types accessed to the same objects so you can leverage advantages of both NOSQL and SQL DB's. But you have to pick the right ORM for your project if your going to use one.
I first got into ORM mapping and Data Access Layers from reading Rockford Lhotka's book, C# business objects. He's spent years working on a framework for DAL's. While his framework out of the box is quite bloated and in some cases, overkill, he has some excellent ideas. I highly recommend the book for anyone looking at ORM mappers. I was influenced by his book enough to take away a lot of his ideas and build them into my own framework and code generation.
There is no simple answer to this since each ORM provider will have it's own particular pluses and minuses. Some ORM solutions are more flexible than others. The onus is on the developer to understand these before using one.
However, take LinqToSql - if you are sure you are not going to need to switch away from SQL Server then this solves a lot of the common problems seen in ORM mappers. It allows you to easily add stored procedures (as static methods), so you aren't just limited to generated SQL. It uses deferred execution, so that you can chain queries together efficiently. It uses partial classes to allow you to easily add custom logic to generated classes without needing to worry about what happens when you re-generate them. There is also nothing stopping you using LINQ to create your own, abstracted DAL - it just speeds up the process. The main, thing, though is that it alleviates the tedium and time required to create basic CRUD layer.
But there are downsides, too. There will be a tight coupling between your tables and classes, there will be a slight performance drop, you may occasionally generate queries that are not as efficient as you expected. And you are tied in to SQL Server (though some other ORM technlogies are database agnostic).
As I said, the main thing is to be aware of the pros and cons before pinning your colours to a particular methodology.
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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"?