jdk自帶排序學習，比如我們寫一個排序代碼
List score = new ArrayList();
score.add(1);
score.add(12);
score.add(45);
score.add(67);
Collections.sort(score);來看一下sort的實現(xiàn)
/**
* 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);
}繼續(xù)跟進
/**
* 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 >
* 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 >
* 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);
}
}
如果沒有自定義排序就執(zhí)行默認排序
/**
* 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 >
* 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 歸并排序默認關閉的，重點關注?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;大小就進行折半插入排序，如果大于32進行
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是一個自適應的、混合的、穩(wěn)定的排序算法，是由Tim Peter于2002年發(fā)明的，最早應用在Python中，現(xiàn)在廣泛應用于Python、Java、Android 等語言與平臺中，作為基礎的排序算法使用。其中Java語言的Collection.sort在JDK1.6使用的是普通的歸并排序，歸并排序雖然時間復雜度低，但是空間復雜度要求較高，所以從JDK1.7開始就更改為了TimSort算法。
Timsort 的時間復雜度是 O(n log n)，與歸并排序的時間復雜度相同，那它的優(yōu)勢是啥呢，實際上可以認為TimSort排序算法是歸并排序算法的優(yōu)化版，從它的三個特征就可以看出，第二個特征“混合的”，沒錯，它不單純是一種算法，而是融合了歸并算法和二分插入排序算法的精髓，因此能夠在排序性能上表現(xiàn)優(yōu)異。
總結：排序->自定義接口實現(xiàn)排序->歸并排序->折半插入排序->TImSort文章來源：http://www.zghlxwxcb.cn/news/detail-818171.html
歡迎指正交流文章來源地址http://www.zghlxwxcb.cn/news/detail-818171.html
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