Question

I just realized that I need to synchronize a significant amount of data collection code in an aspect but performance is a real concern. If performance degrades too much my tool will be thrown out. I will be writing ints and longs individually and to various arrays, ArrayLists and Maps. There will be multiple threads of an application that will make function calls that will be picked up by my aspect. What kind of things should I look out for that will negatively affect performance? What code patterns are more efficient?

In particular I have a method that calls many other data recording methods:

void foo() {
    bar();
    woz();
    ...
}

The methods mostly do adding an incrementing of aspect fields

void bar() {
    f++; // f is a field of the aspect
    for (int i = 0; i < ary.length; i++) {
        // get some values from aspect point cut
        if (some condiction) {
            ary[i] += someValue; // ary a field of the aspect
        }
     }
 }

Should I synchronize foo, or bar, woz and others individually, or should I move all the code in bar, woz, etc into foo and just synchronize it? Should I synchronize on this, on a specifically created synchronization object:

private final Object syncObject = new Object();

(see this post), or on individual data elements within the methods:

ArrayList<Integer> a = new ArrayList<Integer>();

void bar() {    
    synchronize(a) {
        // synchronized code
    }
}

Answer 1

Concurrency is extremely tricky. It’s very easy to get it wrong, and very hard to get right. I wouldn’t be too terribly worried about performance at this point. My first and foremost concern would be to get the concurrent code to work safely (no deadlocks or race conditions).

But on the issue of performance: when in doubt, profile. It’s hard to say just how different synchronization schemes will affect performance. It’s even harder for us to give you suggestions. We’d need to see a lot more of your code and gain a much deeper understanding of what the application does to give you a truly useful answer. In contrast, profiling gives you hard evidence as to if one approach is slower than another. It can even help you identify where the slowdown is.

There are a lot of great profiling tools for Java these days. The Netbeans and Eclipse profilers are good.

Also, I’d recommend staying away from raw synchronization altogether. Try using some of the classes in the java.util.concurrency package. They make writing concurrent code much easier, and much less error prone.

Also, I recommend you read Java Concurrency in Practice by Brian Goetz, et al. It’s very well written and covers a lot of ground.