很高效的用于调度的最小堆

来源：互联网发布：能打开db数据库的软件编辑：程序博客网时间：2024/06/06 21:42
摘自于Hadoop大量文件调度合并
public abstract class PriorityQueue<T> {    private T[] heap;    private int size;    private int maxSize;    protected abstract boolean lessThan(Object a, Object b);    @SuppressWarnings("unchecked")    protected final void initialize(int maxSize) {        size = 0;        int heapSize = maxSize + 1;        heap = (T[]) new Object[heapSize];        this.maxSize = maxSize;    }    public final void put(T element) {        size++;        heap[size] = element;        upHeap();    }    /**     * @param element     * @return     */    public boolean insert(T element) {        if (size < maxSize) {            put(element);            return true;        } else if (size > 0 && !lessThan(element, top())) {            heap[1] = element;            adjustTop();            return true;        } else            return false;    }    /**     * @return     */    public final T top() {        if (size > 0)            return heap[1];        else            return null;    }    public final T pop() {        if (size > 0) {            T result = heap[1];            heap[1] = heap[size];            heap[size] = null;            size--;            downHeap();            return result;        } else            return null;    }    public final void adjustTop() {        downHeap();    }    public final int size() {        return size;    }    public final void clear() {        for (int i = 0; i <= size; i++)            heap[i] = null;        size = 0;    }    private final void upHeap() {        int i = size;        T node = heap[i];        int j = i >>> 1;        while (j > 0 && lessThan(node, heap[j])) {            heap[i] = heap[j];            i = j;            j = j >>> 1;        }        heap[i] = node;    }    private final void downHeap() {        int i = 1;        T node = heap[i];        int j = i << 1;        int k = j + 1;        if (k <= size && lessThan(heap[k], heap[j])) {            j = k;        }        while (j <= size && lessThan(heap[j], node)) {            heap[i] = heap[j];            i = j;            j = i << 1;            k = j + 1;            if (k <= size && lessThan(heap[k], heap[j])) {                j = k;            }        }        heap[i] = node;    }    /**     * Test     *     * @param args     */    public static void main(String[] args) {        int max = 10000000;        long s = System.currentTimeMillis();        Random r = new Random();        System.out.println("---------- 有序数据结构比较 ----------");        //最小堆        PriorityQueue<Integer> queue = new PriorityQueue<Integer>() {            @Override            protected synchronized boolean lessThan(Object a, Object b) {                Integer a1 = (Integer) a;                Integer a2 = (Integer) b;                return a1 > a2;            }        };        queue.initialize(max);        for (int i = 0; i < max; i++) {            queue.insert(r.nextInt());        }        while (queue.size() > 0) {            queue.pop();        }        System.out.println("最小堆性能:" + (System.currentTimeMillis() - s) + "ms");        s = System.currentTimeMillis();        List<Integer> list = new ArrayList<Integer>(max);        for (int i = 0; i < max; i++) {            list.add(r.nextInt());        }        Collections.sort(list);        System.out.println("归并性能:" + (System.currentTimeMillis() - s) + "ms");        s = System.currentTimeMillis();        ConcurrentSkipListSet<Integer> skiptable = new ConcurrentSkipListSet<Integer>();        for (int i = 0; i < max; i++) {            skiptable.add(r.nextInt());        }        System.out.println("跳跃表性能:" + (System.currentTimeMillis() - s) + "ms");        s = System.currentTimeMillis();        TreeSet<Integer> rbt = new TreeSet<Integer>() {            @Override            public synchronized boolean add(Integer integer) {                return super.add(integer);            }        };        for (int i = 0; i < max; i++) {            rbt.add(r.nextInt());        }        System.out.println("红黑树性能:" + (System.currentTimeMillis() - s) + "ms");    }}
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