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