5
我写了一些java类，来评估/演示不同的排序算法。不过，当我运行我的演示课时，我感到困惑。希望你们能给我一个解释。 （这个问题不是作业。）相同的代码，相同的输入，有时运行速度快，有时慢，为什么？
首先我会列出一些与此问题相关的代码。
AbstractDemo
public abstract class AbstractDemo {
protected final int BIG_ARRAY_SIZE = 20000;
protected final int SMALL_ARRAY_SIZE = 14;
protected Stopwatch stopwatch = new Stopwatch();
public final void doDemo() {
prepareDemo();
specificDemo();
}
protected abstract void prepareDemo();
protected abstract void specificDemo();
protected final void printInfo(final String text) {
System.out.println(text);
}
}
SortingDemo
public class SortingDemo extends AbstractDemo {
private static final String FMT = "%-10s| %-21s| %7s ms.";
private static final String SPL = AlgUtil.lineSeparator('-', 45);
private static final String SPLT = AlgUtil.lineSeparator('=', 45);
private int[] data;
private final List<Sorting> demoList = new LinkedList<Sorting>();
@Override
protected void specificDemo() {
int[] testData;
//*** this comment is interesting!!! for (int x = 1; x < 6; x++) {
printInfo(String.format("Sorting %7s elements", data.length));
printInfo(SPLT);
for (final Sorting sort : demoList) {
// here I made a copy of the original Array, avoid to sort an already sorted array.
testData = new int[data.length];
System.arraycopy(data, 0, testData, 0, data.length);
stopwatch.start();
// sort
sort.sort(testData);
stopwatch.stop();
printInfo(String.format(FMT, sort.getBigO(), sort.getClass().getSimpleName(), stopwatch.read()));
printInfo(SPL);
testData = null;
stopwatch.reset();
}
//}
}
@Override
protected void prepareDemo() {
data = AlgUtil.getRandomIntArray(BIG_ARRAY_SIZE, BIG_ARRAY_SIZE * 5, false);
demoList.add(new InsertionSort());
demoList.add(new SelectionSort());
demoList.add(new BubbleSort());
demoList.add(new MergeSort()); //here is interesting too
demoList.add(new OptimizedMergeSort());
}
public static void main(final String[] args) {
final AbstractDemo sortingDemo = new SortingDemo();
sortingDemo.doDemo();
}
}
秒表
public class Stopwatch {
private boolean running;
private long startTime;
private long elapsedMillisec;
public void start() {
if (!running) {
this.startTime = System.currentTimeMillis();
running = true;
} else {
throw new IllegalStateException("the stopwatch is already running");
}
}
public void stop() {
if (running) {
elapsedMillisec = System.currentTimeMillis() - startTime;
running = false;
} else {
throw new IllegalStateException("the stopwatch is not running");
}
}
public void reset() {
elapsedMillisec = 0;
}
public long read() {
if (running) {
elapsedMillisec = System.currentTimeMillis() - startTime;
}
return this.elapsedMillisec;
}
}
方法生成随机阵列
public static int[] getRandomIntArray(final int len, final int max, boolean allowNegative) {
final int[] intArray = new int[len];
final Random rand = new Random();
rand.setSeed(20100102);
if (!allowNegative) {
if (max <= 0) {
throw new IllegalArgumentException("max must be possitive if allowNegative false");
}
for (int i = 0; i < intArray.length; i++) {
intArray[i] = rand.nextInt(max);
}
} else {
int n;
int i = 0;
while (i < len) {
n = rand.nextInt();
if (n < max) {
intArray[i] = n;
i++;
}
}
}
return intArray;
}
你可以看到，我生成一个int数组，具有20000层的元件。由于我在getRandomIntArray方法中有一个固定的种子，每次我调用它时，我总是有相同的数组。类SortingDemo有主要方法，如果我运行这个类，我得到了输出：
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 101 ms.
---------------------------------------------
O(n^2) | SelectionSort | 667 ms.
---------------------------------------------
O(n^2) | BubbleSort | 1320 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 39 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 11 ms.
---------------------------------------------
看起来没问题。现在有些事情让我感到困惑。如果我更改了SortingDemo的demoList.add（）序列，说：
demoList.add(new InsertionSort());
demoList.add(new SelectionSort());
demoList.add(new BubbleSort());
// OptimizedMergeSort before Mergesort
demoList.add(new OptimizedMergeSort());
demoList.add(new MergeSort());
我：
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 103 ms.
---------------------------------------------
O(n^2) | SelectionSort | 676 ms.
---------------------------------------------
O(n^2) | BubbleSort | 1313 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 41 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 14 ms.
---------------------------------------------
为什么输出是从第一次运行有什么不同？ OptimizedMergeSort花的时间比正常归并...
如果我取消注释SortingDemo的for (int x=1; x<6; x++)线（与同一阵列运行测试5倍）我：
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 101 ms.
---------------------------------------------
O(n^2) | SelectionSort | 668 ms.
---------------------------------------------
O(n^2) | BubbleSort | 1311 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 37 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 10 ms.
---------------------------------------------
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 94 ms.
---------------------------------------------
O(n^2) | SelectionSort | 665 ms.
---------------------------------------------
O(n^2) | BubbleSort | 1308 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 5 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 7 ms.
---------------------------------------------
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 116 ms.
---------------------------------------------
O(n^2) | SelectionSort | 318 ms.
---------------------------------------------
O(n^2) | BubbleSort | 969 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 5 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 10 ms.
---------------------------------------------
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 116 ms.
---------------------------------------------
O(n^2) | SelectionSort | 319 ms.
---------------------------------------------
O(n^2) | BubbleSort | 964 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 5 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 5 ms.
---------------------------------------------
Sorting 20000 elements
=============================================
O(n^2) | InsertionSort | 116 ms.
---------------------------------------------
O(n^2) | SelectionSort | 320 ms.
---------------------------------------------
O(n^2) | BubbleSort | 963 ms.
---------------------------------------------
O(?) | OptimizedMergeSort | 4 ms.
---------------------------------------------
O(nlog(n))| MergeSort | 6 ms.
---------------------------------------------
对于其他的分类法，中，结果如下合理。但对于mergeSort，为什么第一次运行需要比以后更长的时间？ OptimizedMergeSort为37ms：4ms。
我认为即使Optimized/MergeSort的实现是错误的，输出也应该保持不变，为什么有时候同样的方法调用需要更长的时间，有时候更短的时间？
作为信息，所有那些* Sort类都扩展了超级抽象类Sorting。它有一个抽象方法void sort(int[] data)
MergeSort有mergeSorting方法和merge（）方法。 OptimizedMergeSort扩展MergeSort，并覆盖mergeSorting()方法，（因为当数组大小< = 7时，它将执行insertSort）并重用MergeSort类中的merge()方法。
感谢您阅读这篇长文和代码。我很感激你们是否可以给我一些解释。
所有的测试都是在Eclipse下在linux下完成的。
做归并和OptimizedMergeSort共享代码？如果是这样，那么很可能你会看到jit编译的影响。在java中编写准确的微基准测试是非常困难的（由于jit），并且有许多文章专门讨论这个主题。 – jtahlborn
@minitech thx评论。我认为随机不会影响结果。因为prepareDemo只被调用一次。无论它是什么样的随机数，它都是相同的数组。 – Kent
@jtahlborn是的，我在写的问题，OptimzedMS是MS的一个子类，它们共享合并方法（在MS类保护）。感谢您的JIT暗示，我将搜索和阅读它 – Kent