Java Collections类排序学习

jdk自带排序学习，比如我们写一个排序代码

       List score = new ArrayList();
        score.add(1);
        score.add(12);
        score.add(45);
        score.add(67);
       Collections.sort(score);

来看一下sort的实现

    /**
     * Sorts the specified list into ascending order, according to the
     * {@linkplain Comparable natural ordering} of its elements.
     * All elements in the list must implement the {@link Comparable}
     * interface.  Furthermore, all elements in the list must be
     * <i>mutually comparable</i> (that is, {@code e1.compareTo(e2)}
     * must not throw a {@code ClassCastException} for any elements
     * {@code e1} and {@code e2} in the list).
     *
     * <p>This sort is guaranteed to be <i>stable</i>:  equal elements will
     * not be reordered as a result of the sort.
     *
     * <p>The specified list must be modifiable, but need not be resizable.
     *
     * @implNote
     * This implementation defers to the {@link List#sort(Comparator)}
     * method using the specified list and a {@code null} comparator.
     *
     * @param  <T> the class of the objects in the list
     * @param  list the list to be sorted.
     * @throws ClassCastException if the list contains elements that are not
     *         <i>mutually comparable</i> (for example, strings and integers).
     * @throws UnsupportedOperationException if the specified list's
     *         list-iterator does not support the {@code set} operation.
     * @throws IllegalArgumentException (optional) if the implementation
     *         detects that the natural ordering of the list elements is
     *         found to violate the {@link Comparable} contract
     * @see List#sort(Comparator)
     */
    @SuppressWarnings("unchecked")
    public static <T extends Comparable<? super T>> void sort(List<T> list) {
        list.sort(null);
    }

继续跟进

    /**
     * Sorts this list according to the order induced by the specified
     * {@link Comparator}.
     *
     * <p>All elements in this list must be <i>mutually comparable</i> using the
     * specified comparator (that is, {@code c.compare(e1, e2)} must not throw
     * a {@code ClassCastException} for any elements {@code e1} and {@code e2}
     * in the list).
     *
     * <p>If the specified comparator is {@code null} then all elements in this
     * list must implement the {@link Comparable} interface and the elements'
     * {@linkplain Comparable natural ordering} should be used.
     *
     * <p>This list must be modifiable, but need not be resizable.
     *
     * @implSpec
     * The default implementation obtains an array containing all elements in
     * this list, sorts the array, and iterates over this list resetting each
     * element from the corresponding position in the array. (This avoids the
     * n<sup>2</sup> log(n) performance that would result from attempting
     * to sort a linked list in place.)
     *
     * @implNote
     * This implementation is a stable, adaptive, iterative mergesort that
     * requires far fewer than n lg(n) comparisons when the input array is
     * partially sorted, while offering the performance of a traditional
     * mergesort when the input array is randomly ordered.  If the input array
     * is nearly sorted, the implementation requires approximately n
     * comparisons.  Temporary storage requirements vary from a small constant
     * for nearly sorted input arrays to n/2 object references for randomly
     * ordered input arrays.
     *
     * <p>The implementation takes equal advantage of ascending and
     * descending order in its input array, and can take advantage of
     * ascending and descending order in different parts of the same
     * input array.  It is well-suited to merging two or more sorted arrays:
     * simply concatenate the arrays and sort the resulting array.
     *
     * <p>The implementation was adapted from Tim Peters's list sort for Python
     * (<a href="http://svn.python.org/projects/python/trunk/Objects/listsort.txt">
     * TimSort</a>).  It uses techniques from Peter McIlroy's "Optimistic
     * Sorting and Information Theoretic Complexity", in Proceedings of the
     * Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pp 467-474,
     * January 1993.
     *
     * @param c the {@code Comparator} used to compare list elements.
     *          A {@code null} value indicates that the elements'
     *          {@linkplain Comparable natural ordering} should be used
     * @throws ClassCastException if the list contains elements that are not
     *         <i>mutually comparable</i> using the specified comparator
     * @throws UnsupportedOperationException if the list's list-iterator does
     *         not support the {@code set} operation
     * @throws IllegalArgumentException
     *         (<a href="Collection.html#optional-restrictions">optional</a>)
     *         if the comparator is found to violate the {@link Comparator}
     *         contract
     * @since 1.8
     */
    @SuppressWarnings({"unchecked", "rawtypes"})
    default void sort(Comparator<? super E> c) {
        Object[] a = this.toArray();
        Arrays.sort(a, (Comparator) c);
        ListIterator<E> i = this.listIterator();
        for (Object e : a) {
            i.next();
            i.set((E) e);
        }
    }

    /**
     * Sorts the specified array of objects according to the order induced by
     * the specified comparator.  All elements in the array must be
     * <i>mutually comparable</i> by the specified comparator (that is,
     * {@code c.compare(e1, e2)} must not throw a {@code ClassCastException}
     * for any elements {@code e1} and {@code e2} in the array).
     *
     * <p>This sort is guaranteed to be <i>stable</i>:  equal elements will
     * not be reordered as a result of the sort.
     *
     * <p>Implementation note: This implementation is a stable, adaptive,
     * iterative mergesort that requires far fewer than n lg(n) comparisons
     * when the input array is partially sorted, while offering the
     * performance of a traditional mergesort when the input array is
     * randomly ordered.  If the input array is nearly sorted, the
     * implementation requires approximately n comparisons.  Temporary
     * storage requirements vary from a small constant for nearly sorted
     * input arrays to n/2 object references for randomly ordered input
     * arrays.
     *
     * <p>The implementation takes equal advantage of ascending and
     * descending order in its input array, and can take advantage of
     * ascending and descending order in different parts of the the same
     * input array.  It is well-suited to merging two or more sorted arrays:
     * simply concatenate the arrays and sort the resulting array.
     *
     * <p>The implementation was adapted from Tim Peters's list sort for Python
     * (<a href="http://svn.python.org/projects/python/trunk/Objects/listsort.txt">
     * TimSort</a>).  It uses techniques from Peter McIlroy's "Optimistic
     * Sorting and Information Theoretic Complexity", in Proceedings of the
     * Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pp 467-474,
     * January 1993.
     *
     * @param <T> the class of the objects to be sorted
     * @param a the array to be sorted
     * @param c the comparator to determine the order of the array.  A
     *        {@code null} value indicates that the elements'
     *        {@linkplain Comparable natural ordering} should be used.
     * @throws ClassCastException if the array contains elements that are
     *         not <i>mutually comparable</i> using the specified comparator
     * @throws IllegalArgumentException (optional) if the comparator is
     *         found to violate the {@link Comparator} contract
     */
    public static <T> void sort(T[] a, Comparator<? super T> c) {
        if (c == null) {
            sort(a);
        } else {
            if (LegacyMergeSort.userRequested)
                legacyMergeSort(a, c);
            else
                TimSort.sort(a, 0, a.length, c, null, 0, 0);
        }
    }

如果没有自定义排序就执行默认排序

    /**
     * Sorts the specified array of objects into ascending order, according
     * to the {@linkplain Comparable natural ordering} of its elements.
     * All elements in the array must implement the {@link Comparable}
     * interface.  Furthermore, all elements in the array must be
     * <i>mutually comparable</i> (that is, {@code e1.compareTo(e2)} must
     * not throw a {@code ClassCastException} for any elements {@code e1}
     * and {@code e2} in the array).
     *
     * <p>This sort is guaranteed to be <i>stable</i>:  equal elements will
     * not be reordered as a result of the sort.
     *
     * <p>Implementation note: This implementation is a stable, adaptive,
     * iterative mergesort that requires far fewer than n lg(n) comparisons
     * when the input array is partially sorted, while offering the
     * performance of a traditional mergesort when the input array is
     * randomly ordered.  If the input array is nearly sorted, the
     * implementation requires approximately n comparisons.  Temporary
     * storage requirements vary from a small constant for nearly sorted
     * input arrays to n/2 object references for randomly ordered input
     * arrays.
     *
     * <p>The implementation takes equal advantage of ascending and
     * descending order in its input array, and can take advantage of
     * ascending and descending order in different parts of the the same
     * input array.  It is well-suited to merging two or more sorted arrays:
     * simply concatenate the arrays and sort the resulting array.
     *
     * <p>The implementation was adapted from Tim Peters's list sort for Python
     * (<a href="http://svn.python.org/projects/python/trunk/Objects/listsort.txt">
     * TimSort</a>).  It uses techniques from Peter McIlroy's "Optimistic
     * Sorting and Information Theoretic Complexity", in Proceedings of the
     * Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pp 467-474,
     * January 1993.
     *
     * @param a the array to be sorted
     * @throws ClassCastException if the array contains elements that are not
     *         <i>mutually comparable</i> (for example, strings and integers)
     * @throws IllegalArgumentException (optional) if the natural
     *         ordering of the array elements is found to violate the
     *         {@link Comparable} contract
     */
    public static void sort(Object[] a) {
        if (LegacyMergeSort.userRequested)
            legacyMergeSort(a);
        else
            ComparableTimSort.sort(a, 0, a.length, null, 0, 0);
    }

    /** To be removed in a future release. */
    private static void legacyMergeSort(Object[] a) {
        Object[] aux = a.clone();
        mergeSort(aux, a, 0, a.length, 0);
    }

legacyMergeSort 归并排序默认关闭的，重点关注?ComparableTimSort.sort

    /**
     * Sorts the given range, using the given workspace array slice
     * for temp storage when possible. This method is designed to be
     * invoked from public methods (in class Arrays) after performing
     * any necessary array bounds checks and expanding parameters into
     * the required forms.
     *
     * @param a the array to be sorted
     * @param lo the index of the first element, inclusive, to be sorted
     * @param hi the index of the last element, exclusive, to be sorted
     * @param work a workspace array (slice)
     * @param workBase origin of usable space in work array
     * @param workLen usable size of work array
     * @since 1.8
     */
    static void sort(Object[] a, int lo, int hi, Object[] work, int workBase, int workLen) {
        assert a != null && lo >= 0 && lo <= hi && hi <= a.length;

        int nRemaining  = hi - lo;
        if (nRemaining < 2)
            return;  // Arrays of size 0 and 1 are always sorted

        // If array is small, do a "mini-TimSort" with no merges
        if (nRemaining < MIN_MERGE) {
            int initRunLen = countRunAndMakeAscending(a, lo, hi);
            binarySort(a, lo, hi, lo + initRunLen);
            return;
        }

        /**
         * March over the array once, left to right, finding natural runs,
         * extending short natural runs to minRun elements, and merging runs
         * to maintain stack invariant.
         */
        ComparableTimSort ts = new ComparableTimSort(a, work, workBase, workLen);
        int minRun = minRunLength(nRemaining);
        do {
            // Identify next run
            int runLen = countRunAndMakeAscending(a, lo, hi);

            // If run is short, extend to min(minRun, nRemaining)
            if (runLen < minRun) {
                int force = nRemaining <= minRun ? nRemaining : minRun;
                binarySort(a, lo, lo + force, lo + runLen);
                runLen = force;
            }

            // Push run onto pending-run stack, and maybe merge
            ts.pushRun(lo, runLen);
            ts.mergeCollapse();

            // Advance to find next run
            lo += runLen;
            nRemaining -= runLen;
        } while (nRemaining != 0);

        // Merge all remaining runs to complete sort
        assert lo == hi;
        ts.mergeForceCollapse();
        assert ts.stackSize == 1;
    }

如果小于 private static final int MIN_MERGE = 32;大小就进行折半插入排序，如果大于32进行

TimSort排序

    /**
     * Sorts the given range, using the given workspace array slice
     * for temp storage when possible. This method is designed to be
     * invoked from public methods (in class Arrays) after performing
     * any necessary array bounds checks and expanding parameters into
     * the required forms.
     *
     * @param a the array to be sorted
     * @param lo the index of the first element, inclusive, to be sorted
     * @param hi the index of the last element, exclusive, to be sorted
     * @param work a workspace array (slice)
     * @param workBase origin of usable space in work array
     * @param workLen usable size of work array
     * @since 1.8
     */
    static void sort(Object[] a, int lo, int hi, Object[] work, int workBase, int workLen) {
        assert a != null && lo >= 0 && lo <= hi && hi <= a.length;

        int nRemaining  = hi - lo;
        if (nRemaining < 2)
            return;  // Arrays of size 0 and 1 are always sorted

        // If array is small, do a "mini-TimSort" with no merges
        if (nRemaining < MIN_MERGE) {
            int initRunLen = countRunAndMakeAscending(a, lo, hi);
            binarySort(a, lo, hi, lo + initRunLen);
            return;
        }

        /**
         * March over the array once, left to right, finding natural runs,
         * extending short natural runs to minRun elements, and merging runs
         * to maintain stack invariant.
         */
        ComparableTimSort ts = new ComparableTimSort(a, work, workBase, workLen);
        int minRun = minRunLength(nRemaining);
        do {
            // Identify next run
            int runLen = countRunAndMakeAscending(a, lo, hi);

            // If run is short, extend to min(minRun, nRemaining)
            if (runLen < minRun) {
                int force = nRemaining <= minRun ? nRemaining : minRun;
                binarySort(a, lo, lo + force, lo + runLen);
                runLen = force;
            }

            // Push run onto pending-run stack, and maybe merge
            ts.pushRun(lo, runLen);
            ts.mergeCollapse();

            // Advance to find next run
            lo += runLen;
            nRemaining -= runLen;
        } while (nRemaining != 0);

        // Merge all remaining runs to complete sort
        assert lo == hi;
        ts.mergeForceCollapse();
        assert ts.stackSize == 1;
    }

Timsort是一个自适应的、混合的、稳定的排序算法，是由Tim Peter于2002年发明的，最早应用在Python中，现在广泛应用于Python、Java、Android 等语言与平台中，作为基础的排序算法使用。其中Java语言的Collection.sort在JDK1.6使用的是普通的归并排序，归并排序虽然时间复杂度低，但是空间复杂度要求较高，所以从JDK1.7开始就更改为了TimSort算法。

Timsort 的时间复杂度是 O(n log n)，与归并排序的时间复杂度相同，那它的优势是啥呢，实际上可以认为TimSort排序算法是归并排序算法的优化版，从它的三个特征就可以看出，第二个特征“混合的”，没错，它不单纯是一种算法，而是融合了归并算法和二分插入排序算法的精髓，因此能够在排序性能上表现优异。

总结：排序->自定义接口实现排序->归并排序->折半插入排序->TImSort

欢迎指正交流