The Ruby community values simplicity...what's your argument for simplifying a db schema in a new project? - ruby-on-rails

I'm working on a project with developers who have not worked with Ruby OR Rails before.
They have created a schema that is too complicated, in my opinion. The schema has 117 tables, and obtaining the simplest piece of information would require traversing/joining 7 tabels...and of course, there's no "main" table that serves as a sort of key between them. The schema renders many of the rails tools like 'find' method, and many of the has_many/belongs to relationships almost useless. And coding for all of these relationships will likely be more time-consuming than we have the money to code for.
THE QUESTION:
Assuming you are VERY convinced (IMHO...hehe) that the schema is not ideal, and there are multiple ways to represent the domain, how would you argue FOR simplifying the schema (aside from what I've already said)?

I'll stand up in 2 roles here
DBA: Database admin/designer.
Dev: Application developer.
I assume the DBA is a person who really know all the Database tricks. Reaallyy Knows.
DBA:
Database is the key of the application and should have predefined structure in order to serve its purpose well and with best performance.
If you cannot use random schema (which is reasonably normalised and good) then the tools are wrong.
Dev:
The database is just a data store, so we need to keep it simple and concentrate on the application.
DBA:
Database is not a store it is the core of the application. There is no application without database.
Dev:
No. The application is the core. There is no application without the front-end and the business logic applied to it.
And the war begins...
Both points are valid and it is always trade off.
If the database will ONLY be used by RoR, then you can use it more like a simple store.
If the DB can be used by other application OR it will be used with large amount of data and high traffic it must enforce some best practices.
Generally there is no way you can disagree with DBA.
But they can understand your situation and might allow you to loose the standards a bit so you could be more productive.
So you need to work closely, together.
And you need to talk to each other to explain and prove the point why database should be like this or that.
Otherwise, the team is broken and project can be failure with hight probability.
ActiveRecord is a very handy tool. But it cannot do everything for you. It does not provide Database structure by default that you expect exactly. So it should be tuned.
On the other side. If DBA can accept that all PKs are Auto incremented integers that would make Developer's life easier (ActiveRecord does it by default).
On the other side, if developers would accept some of DBA constraints it would make DBA's life easier.
Now to answer your question:
how would you argue FOR simplifying the schema
Do not argue. Meet the team and deliver the message and point on WHY it should be done.
Maybe it really shouldn't and you don't know all the things, maybe they are not aware of something.
You could agree on the general structure of the database AND try to describe it using RoR migrations as a meta language.
This way they would see the general picture, and you would use your great ActiveRecords.
And also everybody would be on the same page.

Your DB schema should reflect the domain and its relationships.
De-normalisation should only be done when you have measured that there is a performance problem.
7 joins is not excessive or bad, provided you have good indexes in place.

The general way to make this argument up the chain is based on cost. If you do things simply, there will be less code and fewer bugs. The system will be able to be built more quickly, or with more features, and thus will create more ROI. If you can get the money manager on board with that approach, he or she may let you dictate terms to the team. There is the counterargument that extreme over-normalization prevents bad data, but I have found that this is not the case, as the complexity it engenders tends to lead to more errors and more database code in general.
The architectural and technical argument here is simple. You have decided to use Ruby on Rails. Therefore you have decided to use the ActiveRecord pattern. The ActiveRecord pattern is driven by having the database tables match the object model. That's the pattern in use here, and in many other places, so the best practices they are trying to apply for extreme data normalization simply do not apply. Buy a copy of Patterns of Enterprise Application Architecture and put the little red bookmark at page 160 so they can understand how the pattern works from the architecture perspective.
What the DBA types tend to be unaware of is how much work ActiveRecord does for you, from query generation, cascading deletes, optimistic locking, auto populated columns, versioning (with acts_as_versioned), soft deletes (with acts_as_paranoid), etc. There is a strong argument to use well tested, community supported library functions to perform these operations versus custom code that must be maintained by a DBA.
The real issue with DBAs is then that they need some work to do. Let them focus on monitoring performance, finding slow queries in the code, creating indexes and doing backups.
If you end up losing the political battle for a sane schema, you may want to consider switching to DataMapper. It's the next pattern in PoEAA. The other thing you may be able to get them to do is to create views in the database that correspond to the object model. This way, you could use many of the finding capabilities in the ActiveRecord model based on the views, but have custom insert, update, and delete methods.

Related

How to handle database scalability with Ruby on Rails

I am creating a management system and I want to know how "Ruby on Rails" can support me in the mission of ensuring that each customer has their information, records and tables independent from other customers.
Is it better to put everything in a database and put a customer identifier to pull information through this parameter in queries or create a database for each customer automatically?
I admit that the second option attracts me more ... And I know that putting everything in one database will be detrimental to performance, because I assume that customers and their data will increase exponentially!
I want to know which option is more viable in the long run. And if the best option is to create separate databases, how can I do this with Ruby on Rails ??
There are pro and cons for both solutions which really depend on your use case.
Separating each customer in its own database has definitely advantages for scaling, running in different data centres or even onsite. However, this comes with higher complexity. For instance you can't query across customers anymore, you would need to run queries for each customers and aggregate the results. This approach is called multi tenancy (or shardening). There is a good gem called Apartment available (https://github.com/influitive/apartment).
Keeping everything in one database might be simpler to start of as it's less complex but it really depends on your use case.
Edit
Adding some more information based on the questions.
There are several reasons to use a one db per client architecture.
You have clearly separated tenants. In case it might make sense to go with the one db approach.
Scale. Having separated databases for each tenant makes scaling of course easier.
If 2) is the main reason you want to go for a one db per client approach I would strongly advise you against it. You add so much more complexity to your app which you might not need for years to come (if ever).
If scaling is your main concern I recommend reading Designing Data Intensive Applications by Martin Kleppmann. But basically, don't worry about scale for the first few years and focus on your product.

Does a serialized hash column make more sense than an associated model/table for flexibility?

I have been researching quite a bit and the general consensus is to avoid serialized hashes in a DB whenever possible, however the design I have lends itself to this structure, so I'm hoping to get some opinions and/or advice. Here is the scenario:
I have a model/table :products which houses financial products. Each product has_many investment strategies, which I had originally stored in a separate :strategies model/table. Since each product has completely different strategies, and each strategy has different attributes, its become extremely difficult (and hacky) to manipulate each strategy's attributes into normalized, consistent columns (to the point where I have products that I simply cannot add to the application). Additionally, a strategy's attributes can sometimes change based on the amount of money allocated to that strategy.
In order to solve this issue, I am looking into removing the :strategies model/table altogether and simply adding a strategies column to my :products model/table. The new column would house a multi-dimensional hash of each product's strategies. This option allows for tremendous flexibility from a data storage perspective.
My primary question is, do I lose any functionality by restructuring my database this way? There will be times when I need to search a product by it's strategy's attributes and I have read that searching within a multi-dimensional hash is difficult at best. Is this considered bad practice? Is there a third solution that I haven't considered?
The advantages of rolling with multiple tables for this design is you can leverage the database to protect your data with constraints, functions and triggers. The database is the only place you can protect your customers data with 100% confidence. These tried and true techniques have lost their luster in recent years and are viewed as cumbersome and/or unnecessary to those who do not understand them.
Hash based stores within relational databases are currently changing quickly due to popularity of nosql databases, however, traditionally it has been difficult to fully protect your customers data from the database with this implementation. Therefore, the application layer is where much of this protection lives. With that said, this is being innovated on and maybe someday they will solve it.
The big advantage of using the hash as a column in a table is you can get up and going more quickly while your figuring out your problem. In addition, you can pivot more easily because most modifications are made in the application layer on the fly.
Full text seaching and complex queries can also be a bit more difficult if your using an hash based store within a relational database.
General rule of thumb is if you need the data to safe and or have some complex reporting to do, go relational. Think a big financial services type app ;) Otherwise if your building a more social, data display style app, or just mocking things up there is nothing wrong with a serialized hash column. Most importantly remember to write tests so you can refactor more confidently if you choose wrong!
My $0.02
I would be curious to know which decision you choose and how it has worked out.

How do you keep your business rules DRY?

In the perfect application every business rule would exist only once.
I work for a shop that enforces business rules in as much as possible in the database. In many cases to achieve a better user experience we're performing identical validations on the client side. Not very DRY. Being a SPOT purist, I hate this.
On the other end of the spectrum, some shops create dumb databases (the Rails community leans in this direction) and relegate the business logic to a separate tier. But even with this tack, some validation logic ends up repeated client side.
To further complicate the matter, I understand why the database should be treated as a fortress and so I agree that validations be enforced/repeated at the database.
Trying to enforce validations in one spot isn't easy in light of conflicting concerns -- stay DRY, keep the database a fortress, and provide a good user experience. I have some idea for overcoming this issue, but I imagine there are better.
Can we balance these conflicting concerns in a DRY manner?
Anyone who doesn't enforce the required business rules in the database where they belong is going to have bad data, simple as that. Data integrity is the job of the database. Databases are affected by many more sources than the application and to put required rules in the application only is short-sighted. If you do this you will get bad data from imports, from other applications when they connect, from ad hoc queries to fix large amounts of data (think increasing all the prices by 10%), etc. It is foolish in the extreme to enforce rules only through an application. But then again, I'm the person who has to fix the bad data that gets into poorly designed databases where application developers think they should do stuff only in the application.
The data will live on long past the application in many cases. You lose the rules when this happens as well.
In way, a clean separation of concerns where all business logic exists in a single core location is a Utopian fantasy that’s hard to uphold
Can't see why.
handle all of the business logic in a separate tier (in Rails the models would house “most” of this)
Correct. Django does this also.
some business logic does end up spilling into other places (in Rails it might spill over into the controllers
Not really. The business logic can -- and should -- be in the model tier. Some of it will be encoded as methods of classes, libraries, and other bundles of logic that can be used elsewhere. Django does this with Form objects that validate input. These come from the model, but are used as part of the front-end HTML as well as any bulk loads.
There's no reason for business logic to be defined elsewhere. It can be used in other tiers, but it should be defined in the model.
Use an ORM layer to generate the SQL from the model. Everything in one place.
[database] built on constraints that cause it to reject bad data
I think that's a misreading the Database As A Fortress post. It says "A solid data model", "reject data that does not belong, and to prevent relationships that do not make sense". These are simple declarative referential integrity.
An ORM layer can generate this from the model.
The concerns of database-as-a-fortress and single-point-of-truth are one and the same thing. They are not mutually exclusive. And so there is no need what so ever to "balance them".
What you call "database-as-a-fortress" really is the only possible way to implement single-point-of-truth.
"database-as-a-fortress" is a good thing. It means that the database forces anyone to stay away who does not want to comply (to the truth that the database is supposed to adhere to). That so many people find that a problem (rather than the solution that it really is), says everything about how the majority of database users thinks about the importance of "truth" (as opposed to "I have this shit load of objects I need to persist, and I just want the database to do that despite any business rule what so ever.").
The Model-View-Controller framework is one way to solve this issue. The rails community uses a similar concept...
The basic idea is that all business logic is handled in the controller, and where rules need to be applied in the view or model they are passed into it by the controller.
Well, in general, business rules are much more than sets of constraints, so it's obvious not all business rules can be placed in the database. On the other hand, HLGEM pointed out that it's naive to expect the application to handle all data validation: I can confirm this from experience.
I don't think there's a nice way to put all of the business rules in one place and have them applied on the client, the server side and the database. I live with business rules at the entity level (as hibernate recreates them at the database level) and the remaining rules at the service level.
Database-as-a-fortress is nonsense for relational databases. You need an OODB for that.

server side db programming: why?

Given that database is generally the least scalable component (of a web application), are there any situations where one would put logic in procedures/triggers over keeping it in his favorite programming language (ruby...) or her favorite web framework (...rails!).
Server-side logic is often much faster, even with procedural approach.
You can fine-tune your grant options and hide the data you don't want to show
All queries in one places are more convenient than if they were scattered all around the code.
And here's a (very subjective) article in my blog on the reason I prefer stored procedures:
Schema Junk
BTW, triggers (as opposed to functions / stored procedures / packages) I generally dislike.
They are completely other story.
You're keeping the processing in the database, along with the data.
If you process on the server side, then you have to transfer the data out to a server process across the network, process it, and (optionally) send it back. You have the network bandwidth/latency issues, plus memory overheads.
To clarify - if I have 10m rows of data, my two extreme scenarios are to a) pull those 10m rows across the network and process on the server side, or b) process in place in the database using the server and language (SQL) optimised for this purpose. Note that this is a generalisation and not a hard-and-fast rule, but it's the one I follow for most scenarios.
When many heterogeneous applications and various other systems need to access your single database and be sure through their operations data stays consistent without integrity conflicts. So you put your logic into triggers and stored procedures that will offer an interface to external clients.
Maybe not for most web-based systems, but certainly for enterprise databases. Stored procedures and the like allow you much greater control over security and performance, as well as offering a bit of encapsulation for the database itself. You can change the schema all you want as long as the stored procedure interface remains the same.
In (almost) every situation you would keep the processing that is part of the database in the database. Application code cannot substitute for triggers, you won't get very far before you have updated the database and failed to fire the application's equivalent of the triggers (the first time you use the DBMS's management console, for instance).
Let the database do the database work and let the application to the application's work. If you have a specific performance problem with the database, and that performance problem can be addressed by moving processing from the database, in that case you might want to consider doing so.
But worrying about database performance without a database performance problem existing (which is what you seem to be doing here) is both silly and, sadly, apparently a pre-occupation of many Stackoverlow posters.
Least scalable? SQL???
Look up, "federating."
If the database is shared, having logic in the database is better in order to control everything that happens. If it's not it might just make the system overly complicated.
If you have multiple applications that talk to your database, stored procedures and triggers can enforce correctness more pervasively. Accordingly, if correctness is more important than convenience, putting logic in the database is sensible.
Scalability may be a red herring, though. Sometimes it's easier to express the behavior you want in the domain layer of an OO language, but it can be actually more expensive than doing the idiomatic SQL way.
The security mechanism at a previous company was first built in the service layer, then pushed to the db side. The motivation was actually due to some limitations in a data access framework we were using. The solution turned out to be a bit buggy because our security model was complicated, but the upside was that bugs only had to be fixed in the database; we didn't have to worry about different clients following different rules.
Triggers mean 3rd-party apps can modify the database without creating logical inconsistencies.
If you do that, you are tying your business logic to your model. If you code all your business logic in T-SQL, you aren't going to have a lot of fun if later you need to use Oracle or what have you as your database server. Actually, I'm not sure I understand this question exactly. How do you think this would improve scalability? It really shouldn't.
Personally, I'm really not a fan of triggers, particularly in a database dedicated to a single application. I hate trying to track down why some data is inconsistent, to find it's down to a poorly written trigger (and they can be tricky to get exactly correct).
Security is another advantage of using stored procs. You do not have to set the security at the table level if you don't use dynamic code (Including ithe stored proc). This means your users cannot do anything unless they have a proc to to it. This is one way of reducing the possibility of fraud.
Further procs are easier to performance tune than most application code and even better, when one needs to change, that is all you have to put on production, not recomplie the whole application.
Data integrity must be maintained at the database level. That means constraints, defaults values, foreign keys, possibly triggers (if you have very complex rules or ones involving multiple tables). If you do not do this at the database level, you will eventually have integrity issues. Peolpe will write a quick fix for a problem and run the code in the query window and the required rules are missed creating a larger problem. A millino new records will have to be imported through an ETL program that doesn't access the application because going through the application code would take too long running one record at a time.
If you think you are building an application where scalibility will be an issue, you need to hire a database professional and follow his or her suggestions for design based on performance. Databases can scale to terrabytes of data but only if they are originally designed by someone is a specialist in this kind of thing. When you wait until the while application is runnning slower than dirt and you havea new large client coming on board, it is too late. Database design must consider performance from the beginning as it is very hard to redesign when you already have millions of records.
A good way to reduce scalability of your data tier is to interact with it on a procedural basis. (Fetch row..process... update a row, repeat)
This can be done within a stored procedure by use of cursors or within an application (fetch a row, process, update a row) .. The result (poor performance) is the same.
When people say they want to do processing in their application it sometimes implies a procedural interaction.
Sometimes its necessary to treat data procedurally however from my experience developers with limited database experience will tend to design systems in a way that do not leverage the strenght of the platform because they are not comfortable thinking in terms of set based solutions. This can lead to severe performance issues.
For example to add 1 to a count field of all rows in a table the following is all thats needed:
UPDATE table SET cnt = cnt + 1
The procedural treatment of the same is likely to be orders of magnitude slower in execution and developers can easily overlook concurrency issues that make their process inconsistant. For example this kind of code is inconsistant given the avaliable read isolation levels of many RDMBS platforms.
SELECT id,cnt FROM table
...
foreach row
...
UPDATE table SET cnt = row.cnt+1 WHERE id=row.id
...
I think just in terms of abstraction and ease of servicing a running environment utilizing stored procedures can be a useful tool.
Procedure plan cache and reduced number of network round trips in high latency environments can also have significant performance advantages.
It is also true that trying to be too clever or work very complex problems in the RDBMS's half-baked procedural language can easily become a recipe for disaster.
"Given that database is generally the least scalable component (of a web application), are there any situations where one would put logic in procedures/triggers over keeping it in his favorite programming language (ruby...) or her favorite web framework (...rails!)."
What makes you think that "scalability" is the only relevant concern in a system design ? I agree with rexem where he commented that it is very obvious that you are "not" biased ...
Databases are sets of assertions of fact. Those sets become more valuable if they can also be guaranteed to conform to certain integrity rules. Those guarantees are not worth a dime if it is the applications that are expected to enforce such integrity. Triggers and sprocs are the only way SQL systems have to allow such guarantees to be offered by the DBMS itself.
That aspect outweighs "scalability" anytime, anywhere, anyhow.

Why all the Active Record hate? [closed]

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Closed 11 years ago.
As I learn more and more about OOP, and start to implement various design patterns, I keep coming back to cases where people are hating on Active Record.
Often, people say that it doesn't scale well (citing Twitter as their prime example) -- but nobody actually explains why it doesn't scale well; and / or how to achieve the pros of AR without the cons (via a similar but different pattern?)
Hopefully this won't turn into a holy war about design patterns -- all I want to know is ****specifically**** what's wrong with Active Record.
If it doesn't scale well, why not?
What other problems does it have?
There's ActiveRecord the Design Pattern and ActiveRecord the Rails ORM Library, and there's also a ton of knock-offs for .NET, and other languages.
These are all different things. They mostly follow that design pattern, but extend and modify it in many different ways, so before anyone says "ActiveRecord Sucks" it needs to be qualified by saying "which ActiveRecord, there's heaps?"
I'm only familiar with Rails' ActiveRecord, I'll try address all the complaints which have been raised in context of using it.
#BlaM
The problem that I see with Active Records is, that it's always just about one table
Code:
class Person
belongs_to :company
end
people = Person.find(:all, :include => :company )
This generates SQL with LEFT JOIN companies on companies.id = person.company_id, and automatically generates associated Company objects so you can do people.first.company and it doesn't need to hit the database because the data is already present.
#pix0r
The inherent problem with Active Record is that database queries are automatically generated and executed to populate objects and modify database records
Code:
person = Person.find_by_sql("giant complicated sql query")
This is discouraged as it's ugly, but for the cases where you just plain and simply need to write raw SQL, it's easily done.
#Tim Sullivan
...and you select several instances of the model, you're basically doing a "select * from ..."
Code:
people = Person.find(:all, :select=>'name, id')
This will only select the name and ID columns from the database, all the other 'attributes' in the mapped objects will just be nil, unless you manually reload that object, and so on.
I have always found that ActiveRecord is good for quick CRUD-based applications where the Model is relatively flat (as in, not a lot of class hierarchies). However, for applications with complex OO hierarchies, a DataMapper is probably a better solution. While ActiveRecord assumes a 1:1 ratio between your tables and your data objects, that kind of relationship gets unwieldy with more complex domains. In his book on patterns, Martin Fowler points out that ActiveRecord tends to break down under conditions where your Model is fairly complex, and suggests a DataMapper as the alternative.
I have found this to be true in practice. In cases, where you have a lot inheritance in your domain, it is harder to map inheritance to your RDBMS than it is to map associations or composition.
The way I do it is to have "domain" objects that are accessed by your controllers via these DataMapper (or "service layer") classes. These do not directly mirror the database, but act as your OO representation for some real-world object. Say you have a User class in your domain, and need to have references to, or collections of other objects, already loaded when you retrieve that User object. The data may be coming from many different tables, and an ActiveRecord pattern can make it really hard.
Instead of loading the User object directly and accessing data using an ActiveRecord style API, your controller code retrieves a User object by calling the API of the UserMapper.getUser() method, for instance. It is that mapper that is responsible for loading any associated objects from their respective tables and returning the completed User "domain" object to the caller.
Essentially, you are just adding another layer of abstraction to make the code more managable. Whether your DataMapper classes contain raw custom SQL, or calls to a data abstraction layer API, or even access an ActiveRecord pattern themselves, doesn't really matter to the controller code that is receiving a nice, populated User object.
Anyway, that's how I do it.
I think there is a likely a very different set of reasons between why people are "hating" on ActiveRecord and what is "wrong" with it.
On the hating issue, there is a lot of venom towards anything Rails related. As far as what is wrong with it, it is likely that it is like all technology and there are situations where it is a good choice and situations where there are better choices. The situation where you don't get to take advantage of most of the features of Rails ActiveRecord, in my experience, is where the database is badly structured. If you are accessing data without primary keys, with things that violate first normal form, where there are lots of stored procedures required to access the data, you are better off using something that is more of just a SQL wrapper. If your database is relatively well structured, ActiveRecord lets you take advantage of that.
To add to the theme of replying to commenters who say things are hard in ActiveRecord with a code snippet rejoinder
#Sam McAfee Say you have a User class in your domain, and need to have references to, or collections of other objects, already loaded when you retrieve that User object. The data may be coming from many different tables, and an ActiveRecord pattern can make it really hard.
user = User.find(id, :include => ["posts", "comments"])
first_post = user.posts.first
first_comment = user.comments.first
By using the include option, ActiveRecord lets you override the default lazy-loading behavior.
My long and late answer, not even complete, but a good explanation WHY I hate this pattern, opinions and even some emotions:
1) short version: Active Record creates a "thin layer" of "strong binding" between the database and the application code. Which solves no logical, no whatever-problems, no problems at all. IMHO it does not provide ANY VALUE, except some syntactic sugar for the programmer (which may then use an "object syntax" to access some data, that exists in a relational database). The effort to create some comfort for the programmers should (IMHO...) better be invested in low level database access tools, e.g. some variations of simple, easy, plain hash_map get_record( string id_value, string table_name, string id_column_name="id" ) and similar methods (of course, the concepts and elegance greatly varies with the language used).
2) long version: In any database-driven projects where I had the "conceptual control" of things, I avoided AR, and it was good. I usually build a layered architecture (you sooner or later do divide your software in layers, at least in medium- to large-sized projects):
A1) the database itself, tables, relations, even some logic if the DBMS allows it (MySQL is also grown-up now)
A2) very often, there is more than a data store: file system (blobs in database are not always a good decision...), legacy systems (imagine yourself "how" they will be accessed, many varieties possible.. but thats not the point...)
B) database access layer (at this level, tool methods, helpers to easily access the data in the database are very welcome, but AR does not provide any value here, except some syntactic sugar)
C) application objects layer: "application objects" sometimes are simple rows of a table in the database, but most times they are compound objects anyway, and have some higher logic attached, so investing time in AR objects at this level is just plainly useless, a waste of precious coders time, because the "real value", the "higher logic" of those objects needs to be implemented on top of the AR objects, anyway - with and without AR! And, for example, why would you want to have an abstraction of "Log entry objects"? App logic code writes them, but should that have the ability to update or delete them? sounds silly, and App::Log("I am a log message") is some magnitudes easier to use than le=new LogEntry(); le.time=now(); le.text="I am a log message"; le.Insert();. And for example: using a "Log entry object" in the log view in your application will work for 100, 1000 or even 10000 log lines, but sooner or later you will have to optimize - and I bet in most cases, you will just use that small beautiful SQL SELECT statement in your app logic (which totally breaks the AR idea..), instead of wrapping that small statement in rigid fixed AR idea frames with lots of code wrapping and hiding it. The time you wasted with writing and/or building AR code could have been invested in a much more clever interface for reading lists of log-entries (many, many ways, the sky is the limit). Coders should dare to invent new abstractions to realize their application logic that fit the intended application, and not stupidly re-implement silly patterns, that sound good on first sight!
D) the application logic - implements the logic of interacting objects and creating, deleting and listing(!) of application logic objects (NO, those tasks should rarely be anchored in the application logic objects itself: does the sheet of paper on your desk tell you the names and locations of all other sheets in your office? forget "static" methods for listing objects, thats silly, a bad compromise created to make the human way of thinking fit into [some-not-all-AR-framework-like-]AR thinking)
E) the user interface - well, what I will write in the following lines is very, very, very subjective, but in my experience, projects that built on AR often neglected the UI part of an application - time was wasted on creation obscure abstractions. In the end such applications wasted a lot of coders time and feel like applications from coders for coders, tech-inclined inside and outside. The coders feel good (hard work finally done, everything finished and correct, according to the concept on paper...), and the customers "just have to learn that it needs to be like that", because thats "professional".. ok, sorry, I digress ;-)
Well, admittedly, this all is subjective, but its my experience (Ruby on Rails excluded, it may be different, and I have zero practical experience with that approach).
In paid projects, I often heard the demand to start with creating some "active record" objects as a building block for the higher level application logic. In my experience, this conspicuously often was some kind of excuse for that the customer (a software dev company in most cases) did not have a good concept, a big view, an overview of what the product should finally be. Those customers think in rigid frames ("in the project ten years ago it worked well.."), they may flesh out entities, they may define entities relations, they may break down data relations and define basic application logic, but then they stop and hand it over to you, and think thats all you need... they often lack a complete concept of application logic, user interface, usability and so on and so on... they lack the big view and they lack love for the details, and they want you to follow that AR way of things, because.. well, why, it worked in that project years ago, it keeps people busy and silent? I don't know. But the "details" separate the men from the boys, or .. how was the original advertisement slogan ? ;-)
After many years (ten years of active development experience), whenever a customer mentions an "active record pattern", my alarm bell rings. I learned to try to get them back to that essential conceptional phase, let them think twice, try them to show their conceptional weaknesses or just avoid them at all if they are undiscerning (in the end, you know, a customer that does not yet know what it wants, maybe even thinks it knows but doesn't, or tries to externalize concept work to ME for free, costs me many precious hours, days, weeks and months of my time, live is too short ... ).
So, finally: THIS ALL is why I hate that silly "active record pattern", and I do and will avoid it whenever possible.
EDIT: I would even call this a No-Pattern. It does not solve any problem (patterns are not meant to create syntactic sugar). It creates many problems: the root of all its problems (mentioned in many answers here..) is, that it just hides the good old well-developed and powerful SQL behind an interface that is by the patterns definition extremely limited.
This pattern replaces flexibility with syntactic sugar!
Think about it, which problem does AR solve for you?
Some messages are getting me confused.
Some answers are going to "ORM" vs "SQL" or something like that.
The fact is that AR is just a simplification programming pattern where you take advantage of your domain objects to write there database access code.
These objects usually have business attributes (properties of the bean) and some behaviour (methods that usually work on these properties).
The AR just says "add some methods to these domain objects" to database related tasks.
And I have to say, from my opinion and experience, that I do not like the pattern.
At first sight it can sound pretty good. Some modern Java tools like Spring Roo uses this pattern.
For me, the real problem is just with OOP concern. AR pattern forces you in some way to add a dependency from your object to infraestructure objects. These infraestructure objects let the domain object to query the database through the methods suggested by AR.
I have always said that two layers are key to the success of a project. The service layer (where the bussiness logic resides or can be exported through some kind of remoting technology, as Web Services, for example) and the domain layer. In my opinion, if we add some dependencies (not really needed) to the domain layer objects for resolving the AR pattern, our domain objects will be harder to share with other layers or (rare) external applications.
Spring Roo implementation of AR is interesting, because it does not rely on the object itself, but in some AspectJ files. But if later you do not want to work with Roo and have to refactor the project, the AR methods will be implemented directly in your domain objects.
Another point of view. Imagine we do not use a Relational Database to store our objects. Imagine the application stores our domain objects in a NoSQL Database or just in XML files, for example. Would we implement the methods that do these tasks in our domain objects? I do not think so (for example, in the case of XM, we would add XML related dependencies to our domain objects...Truly sad I think). Why then do we have to implement the relational DB methods in the domain objects, as the Ar pattern says?
To sum up, the AR pattern can sound simpler and good for small and simple applications. But, when we have complex and large apps, I think the classical layered architecture is a better approach.
The question is about the Active
Record design pattern. Not an orm
Tool.
The original question is tagged with rails and refers to Twitter which is built in Ruby on Rails. The ActiveRecord framework within Rails is an implementation of Fowler's Active Record design pattern.
The main thing that I've seen with regards to complaints about Active Record is that when you create a model around a table, and you select several instances of the model, you're basically doing a "select * from ...". This is fine for editing a record or displaying a record, but if you want to, say, display a list of the cities for all the contacts in your database, you could do "select City from ..." and only get the cities. Doing this with Active Record would require that you're selecting all the columns, but only using City.
Of course, varying implementations will handle this differently. Nevertheless, it's one issue.
Now, you can get around this by creating a new model for the specific thing you're trying to do, but some people would argue that it's more effort than the benefit.
Me, I dig Active Record. :-)
HTH
Although all the other comments regarding SQL optimization are certainly valid, my main complaint with the active record pattern is that it usually leads to impedance mismatch. I like keeping my domain clean and properly encapsulated, which the active record pattern usually destroys all hope of doing.
I love the way SubSonic does the one column only thing.
Either
DataBaseTable.GetList(DataBaseTable.Columns.ColumnYouWant)
, or:
Query q = DataBaseTable.CreateQuery()
.WHERE(DataBaseTable.Columns.ColumnToFilterOn,value);
q.SelectList = DataBaseTable.Columns.ColumnYouWant;
q.Load();
But Linq is still king when it comes to lazy loading.
#BlaM:
Sometimes I justed implemented an active record for a result of a join. Doesn't always have to be the relation Table <--> Active Record. Why not "Result of a Join statement" <--> Active Record ?
I'm going to talk about Active Record as a design pattern, I haven't seen ROR.
Some developers hate Active Record, because they read smart books about writing clean and neat code, and these books states that active record violates single resposobility principle, violates DDD rule that domain object should be persistant ignorant, and many other rules from these kind of books.
The second thing domain objects in Active Record tend to be 1-to-1 with database, that may be considered a limitation in some kind of systems (n-tier mostly).
Thats just abstract things, i haven't seen ruby on rails actual implementation of this pattern.
The problem that I see with Active Records is, that it's always just about one table. That's okay, as long as you really work with just that one table, but when you work with data in most cases you'll have some kind of join somewhere.
Yes, join usually is worse than no join at all when it comes to performance, but join usually is better than "fake" join by first reading the whole table A and then using the gained information to read and filter table B.
The problem with ActiveRecord is that the queries it automatically generates for you can cause performance problems.
You end up doing some unintuitive tricks to optimize the queries that leave you wondering if it would have been more time effective to write the query by hand in the first place.
Try doing a many to many polymorphic relationship. Not so easy. Especially when you aren't using STI.

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