Java for 循环性能问题

Question

考虑这个例子:

public static void main(final String[] args) {
    final List<String> myList = Arrays.asList("A", "B", "C", "D");
    final long start = System.currentTimeMillis();
    for (int i = 1000000; i > myList.size(); i--) {
        System.out.println("Hello");
    }
    final long stop = System.currentTimeMillis();
    System.out.println("Finish: " + (stop - start));
}

对比

public static void main(final String[] args) {
    final List<String> myList = Arrays.asList("A", "B", "C", "D");
    final long start = System.currentTimeMillis();
    final int size = myList.size();
    for (int i = 1000000; i > size; i--) {
        System.out.println("Hello");
    }
    final long stop = System.currentTimeMillis();
    System.out.println("Finish: " + (stop - start));
}

这会有什么不同吗？在我的机器上，第二个似乎执行得更快，但我不知道它是否真的准确。编译器会优化这段代码吗？如果循环条件是不可变对象(immutable对象)(例如字符串数组)，我可以认为他会这样做。

Answer 1

如果你想测试这样的东西，你真的必须优化你的微基准来衡量你关心的东西。

首先，使循环廉价但不可能跳过。计算总和通常可以解决问题。

其次，比较两个时序。

这里有一些代码可以做到这两点:

import java.util.*;

public class Test {

public static long run1() {
  final List<String> myList = Arrays.asList("A", "B", "C", "D");
  final long start = System.nanoTime();
  int sum = 0;
  for (int i = 1000000000; i > myList.size(); i--) sum += i;
  final long stop = System.nanoTime();
  System.out.println("Finish: " + (stop - start)*1e-9 + " ns/op; sum = " + sum);
  return stop-start;
}

public static long run2() {
  final List<String> myList = Arrays.asList("A", "B", "C", "D");
  final long start = System.nanoTime();
  int sum = 0;
  int limit = myList.size();
  for (int i = 1000000000; i > limit; i--) sum += i;
  final long stop = System.nanoTime();
  System.out.println("Finish: " + (stop - start)*1e-9 + " ns/op; sum = " + sum);
  return stop-start;
}

public static void main(String[] args) {
  for (int i=0 ; i<5 ; i++) {
    long t1 = run1();
    long t2 = run2();
    System.out.println("  Speedup = " + (t1-t2)*1e-9 + " ns/op\n");
  }
}

}

如果我们运行它，在我的系统上我们会得到:

Finish: 0.481741256 ns/op; sum = -243309322
Finish: 0.40228402 ns/op; sum = -243309322
  Speedup = 0.079457236 ns/op

Finish: 0.450627151 ns/op; sum = -243309322
Finish: 0.43534661700000005 ns/op; sum = -243309322
  Speedup = 0.015280534 ns/op

Finish: 0.47738474700000005 ns/op; sum = -243309322
Finish: 0.403698331 ns/op; sum = -243309322
  Speedup = 0.073686416 ns/op

Finish: 0.47729349600000004 ns/op; sum = -243309322
Finish: 0.405540508 ns/op; sum = -243309322
  Speedup = 0.071752988 ns/op

Finish: 0.478979617 ns/op; sum = -243309322
Finish: 0.36067492700000003 ns/op; sum = -243309322
  Speedup = 0.11830469 ns/op

这意味着方法调用的开销大约为 0.1 ns。如果您的循环执行的时间不超过 1-2 ns，那么您应该关心这一点。否则，不要。