这是一个关于自动拳击的实验。主要想法是分别使用pop()
和push()
执行Stack
和Stack<Integer>
的挂载。下面的核心课程:
public class FixedCapcityStack<Item> {
private final int cap;
private Item[] arr;
private int N;
public FixedCapcityStack(int cap){
this.cap = cap;
arr = (Item[]) new Object[cap];
}
public void push(Item i){
arr[N++] = i;
}
public Item pop(){// 不考虑其他其他情况,方便测试
return arr[--N];
}
public boolean isEmpty() {
return N==0;
}
public boolean isFull() {
return N == cap;
}
}
public class FixedCapcityStackOfInts {
private final int cap;
private int[] arr;
private int N;
public FixedCapcityStackOfInts(int cap){
this.cap = cap;
arr = new int[cap];
}
public void push(int i){
arr[N++] = i;
}
public int pop(){// 不考虑其他其他情况,方便测试
return arr[--N];
}
public boolean isEmpty() {
return N==0;
}
public boolean isFull() {
return N == cap;
}
}
我使用以下代码进行测试:
public static void main(String args[]) {
Random random = new Random();
int SIZE = 10;
FixedCapcityStackOfInts intStack = new FixedCapcityStackOfInts(SIZE);
//FixedCapcityStack<Integer> intStack = new FixedCapcityStack(SIZE);
int N = 200;
while (true) {
Stopwatch stopwatch = new Stopwatch();
for (int j = 0; j < N; j++) {
for (int i = 0; i < SIZE; i++) {
intStack.push(random.nextInt());
}
for (int i = 0; i < SIZE; i++) {
int k = intStack.pop();
}
}
System.out.printf("N: %d, elapseTime: %f \n", N, stopwatch.elapsedTime());
N*=2;
}
}
没有通用的堆栈结果是
N: 100, elapseTime: 0.033000s
N: 200, elapseTime: 0.026000s
N: 400, elapseTime: 0.025000s
N: 800, elapseTime: 0.047000s
N: 1600, elapseTime: 0.124000s
N: 3200, elapseTime: 0.238000s
N: 6400, elapseTime: 0.490000s
N: 12800, elapseTime: 0.731000s
N: 25600, elapseTime: 1.437000s
N: 51200, elapseTime: 2.951000s
N: 102400, elapseTime: 5.891000s
N: 204800, elapseTime: 11.810000s
N: 409600, elapseTime: 23.699000s
N: 819200, elapseTime: 46.441000s
Stack<Integer>
的结果是:
N: 100, elapseTime: 0.034000s
N: 200, elapseTime: 0.018000s
N: 400, elapseTime: 0.049000s
N: 800, elapseTime: 0.053000s
N: 1600, elapseTime: 0.150000s
N: 3200, elapseTime: 0.251000s
N: 6400, elapseTime: 0.536000s
N: 12800, elapseTime: 0.885000s
N: 25600, elapseTime: 1.570000s
N: 51200, elapseTime: 3.181000s
N: 102400, elapseTime: 6.321000s
N: 204800, elapseTime: 12.923000s
N: 409600, elapseTime: 25.643000s
N: 819200, elapseTime: 51.373000s
表现并不差。 但是当您使用以下代码进行测试时:
long start = System.currentTimeMillis();
Long sum = 0L;
for (long i = 0; i < Integer.MAX_VALUE; i++) {
sum += i;
}
long end = System.currentTimeMillis();
System.out.println("Long sum took: " + (end - start) + " milliseconds");
start = System.currentTimeMillis();
long sum2 = 0L;
for (long i = 0; i <Integer.MAX_VALUE; i++) {
sum2 += i;
}
end = System.currentTimeMillis();
System.out.println("long sum took: " + (end - start) + " milliseconds");
结果是:
Long sum took: 8043 milliseconds
long sum took: 793 milliseconds
哦,天啊!为什么这两个结果彼此不同。当然,关于自动拳击的结论也来自两个结果。这让我很困惑。
答案 0 :(得分:0)
在第一个例子中,堆栈对象本身导致很多开销。盒装基元使得课程变慢,但还有其他需要考虑的瓶颈。
在第二个例子中,开销非常小,使得盒装与非盒装基元之间的性能差异更加显着。