Can you/How do you save CPU and memory by choosing wisely

I understand the JVM optimizes some things for you (not clear on which things yet), but lets say I were to do this:

while(true) {
     int var = 0;

would doing:

int var;
while(true) {
     var = 0;

take less space? Since you aren't declaring a new reference every time, you don't have to specify the type every time.

I understand you really would only need to put var outside of while if I wanted to use it outside of that loop (instead of only being able to use it locally like in the first example). Also, what about objects, would it be different that primitive types in that situation? I understand it's a small situation, but build-up of this kind of stuff can cause my application to take a lot of memory/cpu. I'm trying to use the least amount of operations possible, but I don't completely understand whats going on behind the scenes.

If someone could help me out, even maybe link me to somewhere I can learn about saving cpu by decreasing amount of operations, it would be highly appreciated. Please no books (unless they're free! :D), no way of getting one right now /:


Don't. Premature optimization is the root of all evil.

Instead, write your code as it makes most sense conceptually. Write it thoughtfully, yes. But don't think you can be a 'human compiler' and optimize and still write good code.

Once you have written your code (more or less naively, depending on your level of experience) you write performance tests for it. Try to think of different ways in which the code may be used (many times in a row, from front to back or reversed, many concurrent invocations etc) and try to cover these in test cases. Then benchmark your code.

If you find that some test cases are not performing well, investigate why. Measure parts of the test case to see where the time is going. Zoom into the parts where most time is spent.

Mostly, you will find weird loops where, upon reading the code again, you will think 'that was silly to write it that way. Of course this is slow' and easily fix it. In my experience most performance problems can be solved this way and 'hardcore optimization' is hardly ever needed.

In the end you will find that 99* percent of all performance problems can be solved by touching only 1 percent of the code. The other code never comes into play. This is why you should not 'prematurely' optimize. You will be spending valuable time optimizing code that had no performance issues in the first place. And making it less readable in the process.

Numbers made up of course but you know what I mean :)

Hot Licks points out the fact that this isn't much of an answer, so let me expand on this with some good ol' perfomance tips:

  1. Keep an eye out for I/O

    Most performance problems are not in pure Java. Instead they are in interfacing with other systems. In particular disk access is notoriously slow. So is the network. So minimize it's use.

  2. Optimize SQL queries

    SQL queries will add seconds, even minutes, to your program's execution time if you don't watch out. So think about those very carefully. Again, benchmark them. You can write very optimized Java code, but if it first spends ten seconds waiting for the database to run some monster SQL query than it will never be fast.

  3. Use the right kind of collections

    Most performance problems are related to doing things lots of times. Usually when working with big sets of data. Putting your data in a Map instead of in a List can make a huge difference. Also there are specialized collection types for all sorts of performance requirements. Study them and pick wisely.

  4. Don't write code

    When performance really matters, squeezing the last 'drops' out of some piece of code becomes a science all in itself. Unless you are writing some very exotic code, chances are great there will be some library or toolkit to solve your kind of problems. It will be used by many in the real world. Tried and tested. Don't try to beat that code. Use it.

We humble Java developers are end-users of code. We take the building blocks that the language and it's ecosystem provides and tie it together to form an application. For the most part, performance problems are caused by us not using the provided tools correctly, or not using any tools at all for that matter. But we really need specifics to be able to discuss those. Benchmarking gives you that specifity. And when the slow code is identified it is usually just a matter of changing a collection from list to map, or sorting it beforehand, or dropping a join from some query etc.

Attempting to optimise code which doesn't need to be optimised increases complexity and decreases readability.

However, there are cases were improving readability also comes with improved performance.

For example,

  • if a numeric value cannot be null, use a primitive instead of a wrapper. This makes it clearer that the value cannot be null but also uses less memory and reduces pressure on the GC.
  • use a Set when you have a collection which cannot have duplicates. Often a List is used when in fact a Set would be more appropriate, depending on the operations you perform, this can also be faster by reducing time complexity.
  • consider using an enum with one instance for a singleton (if you have to use singletons at all) This is much simpler as well as faster than double check locking. Hint: try to only have stateless singletons.
  • writing simpler, well structured code is also easier for the JIT to optimise. This is where trying to out smart the JIT with more complex solutions will back fire because you end up confusing the JIT and what you think should be faster is actually slower. (And it's more complicated as well)
  • try to reduce how much you write to the console (and IO in general) in critical sections. Writing to the console is so expensive, both for the program and the poor human having to read it that is it worth spending more time producing concise console output.
  • try to use a StringBuilder when you have a loop of elements to add. Note: Avoid using StringBuilder for one liners, just series of append() as this can actually be slower and harder to read.

Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away. -- Antoine de Saint-Exupery, French writer (1900 - 1944)

Developers like to solve hard problems and there is a very strong temptation to solve problems which don't need to be solved. This is a very common behaviour for developers of up to 10 years experience (it was for me anyway ;), after about this point you have already solved most common problem before and you start selecting the best/minimum set of solutions which will solve a problem. This is the point you want to get to in your career and you will be able to develop quality software in far less time than you could before.

If you dream up an interesting problem to solve, go ahead and solve it in your own time, see what difference it makes, but don't include it in your working code unless you know (because you measured) that it really makes a difference.

However, if you find a simpler, elegant solution to a problem, this is worth including not because it might be faster (thought it might be), but because it should make the code easier to understand and maintain and this is usually far more valuable use of your time. Successfully used software usually costs three times as much to maintain as it cost to develop. Do what will make the life of the poor person who has to understand why you did something easier (which is harder if you didn't do it for any good reason in the first place) as this might be you one day ;)

A good example on when you might make an application slower to improve reasoning, is in the use of immutable values and concurrency. Immutable values are usually slower than mutable ones, sometimes much slower, however when used with concurrency, mutable state is very hard to get provably right, and you need this because testing it is good but not reliable. Using concurrency you have much more CPU to burn so a bit more cost in using immutable objects is a very sensible trade off. In some cases using immutable objects can allow you to avoid using locks and actually improve throughput. e.g. CopyOnWriteArrayList, if you have a high read to write ration.

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