Why You Should NOT Implement Layered Architectures

Abstraction layers in software are what architecture astronauts tell you to do. Instead, however, half of all applications out there would be so easy, fun, and most importantly: productive to implement if you just got rid of all those layers.

Frankly, what do you really need? You need these two:

  • Some data access
  • Some UI

Because that’s the two things that you inevitably have in most systems. Users, and data. Here’s Kyle Boon’s opinion on possible choices that you may have

Very nice choice, Kyle. Ratpack and jOOQ. You could choose any other APIs, of course. You could even choose to write JDBC directly in JSP. Why not. As long as you don’t go pile up 13 layers of abstraction:

Geek and Poke's Footprints - Licensed CC-BY 2.0
Geek and Poke’s Footprints – Licensed CC-BY 2.0

That’s all bollocks, you’re saying? We need layers to abstract away the underlying implementation so we can change it? OK, let’s give this some serious thought. How often do you really change the implementation? Some examples:

  • SQL. You hardly change the implementation from Oracle to DB2
  • DBMS. You hardly change the model from relational to flat or XML or JSON
  • JPA. You hardly switch from Hibernate to EclipseLink
  • UI. You simply don’t replace HTML with Swing
  • Transport. You just don’t switch from HTTP to SOAP
  • Transaction layer. You just don’t substitute JavaEE with Spring, or JDBC transactions

Nope. Your architecture is probably set in stone. And if – by the incredible influence of entropy and fate – you happen to have made the wrong decision in one aspect, about 3 years ago, well you’re in for a major refactoring anyway. If SQL was the wrong choice, well good luck to you migrating everything to MongoDB (which is per se the wrong choice again, so prepare for migrating back). If HTML was the wrong choice, well even more tough luck to you. Likelihood of your layers not really helping you when a concrete incident happens: 95% (because you missed an important detail)

Layers = Insurance

If you’re still thinking about implementing an extremely nice layered architecture, ready to deal with pretty much every situation where you simply switch a complete stack with another, then what you’re really doing is filing a dozen insurance policies. Think about it this way. You can get:

  • Legal insurance
  • Third party insurance
  • Reinsurance
  • Business interruption insurance
  • Business overhead expense disability insurance
  • Key person insurance
  • Shipping insurance
  • War risk insurance
  • Payment protection insurance
  • pick a random category

You can pay and pay and pay in advance for things that probably won’t ever happen to you. Will they? Yeah, they might. But if you buy all that insurance, you pay heavily up front. And let me tell you a secret. IF any incident ever happens, chances are that you:

  • Didn’t buy that particular insurance
  • Aren’t covered appropriately
  • Didn’t read the policy
  • Got screwed

And you’re doing exactly that in every application that would otherwise already be finished and would already be adding value to your customer, while you’re still debating if on layer 37 between the business rules and transformation layers, you actually need another abstraction because the rule engine could be switched any time.

Stop doing that

You get the point. If you have infinite amounts of time and money, implement an awesome, huge architecture up front.

Your competitor’s time to market (and fun, on the way) is better than yours. But for a short period of time, you were that close to the perfect, layered architecture!

The Code That Made me Cry

A friend of mine recently told me about the kind of problems he’s currently struggling with in the legacy application he’s maintaining. Here’s a sample piece of code to illustrate what I’m talking about:

String q = "select replace('" +
            accountNo +
           "%','- ','-') from dual";
rs = stmt.executeQuery(q);
if (rs.next()) {
    accountNoFormatted = rs.getString(1);
}

It instantly made me cry. As in Code That Made Me Cry, or #CTMMC. If this is just a sample, I can imagine what the rest of the application looks like. As a matter of fact, these problems were the very reason why he thought he needed to sort out a couple of things first, before he could even think about introducing jOOQ or any other new technology in that application. Yes, there’s some serious teaching to be done (or slapping?)

If you’ve read through this article thus far without knowing what I’m talking about, then let me give you some advice. Please follow this advice to keep my friend from jumping out the window:

NEVER send such trivial logic to the database for execution!

I’ve recently blogged about various reasons why you should calculate / execute some stuff in the database. A simple string replacement is not one of those things! Heck, why risk the database round trip / network latency, connection and/or data transfer timeouts, and all sorts of other stuff for something that could be written as such in Java?

accountNo.replace("- ", "-");

The method even has the same name as the SQL function. Heck, why even go through the hassle of using the horrible JDBC API for this? Please, dear developer. Take 1h and study the entire list of methods available to java.lang.String. It’s such an awesome and completely underestimated class!

NEVER reformat previously formatted data

This is the rule of thumb: Once data is formatted, it is eternally lost and unavailable to computing / data processing. There is only one simple reason why anyone would ever format any data. It is for displaying data to human beings. Humans are not good at deciphering or memorizing things like

a56225e0-45ef-11e3-8f96-0800200c9a66

Humans are good at reading and memorizing things like:

My wife's bank account

So repeat after me. Once data is formatted, it is eternally lost and unavailable to computing / data processing. If the formatting was wrong in any way, then fix the formatting where it is wrong. NEVER re-format the previously formatted data. NEVER.

NEVER format data in the data access layer

Just as humans are incredibly bad at operating on long technical IDs, machines are incredibly bad at operating on formatted data. In fact, there are so few reasons to ever format data in the data access layer that it should probably not even occur to you. One acceptable reason is when you have a very very sophisticated, highly tuned report which runs in the DB. But you don’t have that, because you considered using the SQL replace() function to remove a whitespace from a Java string. That isn’t exactly sophisticated reporting.

So read after me. NEVER format data in the data access layer, unless you have a compelling technical reason for it. Your accountNo should remain as untouched and technical and ID-style as long as possible throughout your application. There is absolutely no need to format it for human consumption before the accountNo hits the UI.

OK, to be fair, there’s another exception to this rule. When you choose to sort data in the UI, then you might want to sort the data by the formatted version of the accountNo, as the sorting result will be consumed by a human:

SELECT ..
FROM accounts a
ORDER BY a.account_no_formatted

Be lazy

There is one very simple way to become a better programmer: Be lazy. Be too lazy to write 10 lines of code for a simple replacement of "- " by "-". By being so incredibly lazy, you will always think:

There HAS to be a better way to write this

There’s nothing wrong with not knowing. But there’s everything wrong with using the path of least resistance and writing 10 lines of code for something as trivial as this. Believe me. Your life will be so much better, once trivial stuff can be written in one-liners. You can focus again on your business logic.