首先，我们可以从未排序的数组中构建一个BST，它需要O(n)时间，从BST中我们可以找到O(log(n))中第k个最小的元素，它的总计数为O(n)。

c++标准库几乎完全有这个函数调用nth_element，尽管它确实会修改数据。它有线性运行时间，O(N)，它也做部分排序。

const int N = ...;
double a[N];
// ... 
const int m = ...; // m < N
nth_element (a, a + m, a + N);
// a[m] contains the mth element in a

这是一个Javascript实现。

如果您释放了不能修改数组的约束，则可以使用两个索引来标识“当前分区”(经典快速排序样式- http://www.nczonline.net/blog/2012/11/27/computer-science-in-javascript-quicksort/)来防止使用额外的内存。

function kthMax(a, k){
    var size = a.length;

    var pivot = a[ parseInt(Math.random()*size) ]; //Another choice could have been (size / 2) 

    //Create an array with all element lower than the pivot and an array with all element higher than the pivot
    var i, lowerArray = [], upperArray = [];
    for (i = 0; i  < size; i++){
        var current = a[i];

        if (current < pivot) {
            lowerArray.push(current);
        } else if (current > pivot) {
            upperArray.push(current);
        }
    }

    //Which one should I continue with?
    if(k <= upperArray.length) {
        //Upper
        return kthMax(upperArray, k);
    } else {
        var newK = k - (size - lowerArray.length);

        if (newK > 0) {
            ///Lower
            return kthMax(lowerArray, newK);
        } else {
            //None ... it's the current pivot!
            return pivot;
        }   
    }
}  

如果你想测试它的表现，你可以使用这个变量:

    function kthMax (a, k, logging) {
         var comparisonCount = 0; //Number of comparison that the algorithm uses
         var memoryCount = 0;     //Number of integers in memory that the algorithm uses
         var _log = logging;

         if(k < 0 || k >= a.length) {
            if (_log) console.log ("k is out of range"); 
            return false;
         }      

         function _kthmax(a, k){
             var size = a.length;
             var pivot = a[parseInt(Math.random()*size)];
             if(_log) console.log("Inputs:", a,  "size="+size, "k="+k, "pivot="+pivot);

             // This should never happen. Just a nice check in this exercise
             // if you are playing with the code to avoid never ending recursion            
             if(typeof pivot === "undefined") {
                 if (_log) console.log ("Ops..."); 
                 return false;
             }

             var i, lowerArray = [], upperArray = [];
             for (i = 0; i  < size; i++){
                 var current = a[i];
                 if (current < pivot) {
                     comparisonCount += 1;
                     memoryCount++;
                     lowerArray.push(current);
                 } else if (current > pivot) {
                     comparisonCount += 2;
                     memoryCount++;
                     upperArray.push(current);
                 }
             }
             if(_log) console.log("Pivoting:",lowerArray, "*"+pivot+"*", upperArray);

             if(k <= upperArray.length) {
                 comparisonCount += 1;
                 return _kthmax(upperArray, k);
             } else if (k > size - lowerArray.length) {
                 comparisonCount += 2;
                 return _kthmax(lowerArray, k - (size - lowerArray.length));
             } else {
                 comparisonCount += 2;
                 return pivot;
             }
     /* 
      * BTW, this is the logic for kthMin if we want to implement that... ;-)
      * 

             if(k <= lowerArray.length) {
                 return kthMin(lowerArray, k);
             } else if (k > size - upperArray.length) {
                 return kthMin(upperArray, k - (size - upperArray.length));
             } else 
                 return pivot;
     */            
         }

         var result = _kthmax(a, k);
         return {result: result, iterations: comparisonCount, memory: memoryCount};
     }

剩下的代码只是创建一些游乐场:

    function getRandomArray (n){
        var ar = [];
        for (var i = 0, l = n; i < l; i++) {
            ar.push(Math.round(Math.random() * l))
        }

        return ar;
    }

    //Create a random array of 50 numbers
    var ar = getRandomArray (50);   

现在给你做几次测试。 因为Math.random()每次都会产生不同的结果:

    kthMax(ar, 2, true);
    kthMax(ar, 2);
    kthMax(ar, 2);
    kthMax(ar, 2);
    kthMax(ar, 2);
    kthMax(ar, 2);
    kthMax(ar, 34, true);
    kthMax(ar, 34);
    kthMax(ar, 34);
    kthMax(ar, 34);
    kthMax(ar, 34);
    kthMax(ar, 34);

如果你测试它几次，你甚至可以看到经验的迭代次数，平均来说，O(n) ~=常数* n, k的值不会影响算法。

创建优先级队列。 将所有元素插入堆中。 调用poll() k次。 getKthLargestElements(int[] arr) ｛ PriorityQueue<Integer> pq = new PriorityQueue<>((x, y) -> (y-x)); //将所有元素插入堆中 For (int ele: arr) pq.offer(避署); //调用poll() k次 int i = 0; 而(i&lt; k) ｛ Int result = pq.poll(); ｝ 返回结果; ｝

Haskell的解决方案:

kthElem index list = sort list !! index

withShape ~[]     []     = []
withShape ~(x:xs) (y:ys) = x : withShape xs ys

sort []     = []
sort (x:xs) = (sort ls `withShape` ls) ++ [x] ++ (sort rs `withShape` rs)
  where
   ls = filter (<  x)
   rs = filter (>= x)

这通过使用withShape方法来实现中值解的中值，从而发现分区的大小，而无需实际计算分区大小。

下面是eladv建议的算法的实现(我也把随机pivot的实现放在这里):

public class Median {

    public static void main(String[] s) {

        int[] test = {4,18,20,3,7,13,5,8,2,1,15,17,25,30,16};
        System.out.println(selectK(test,8));

        /*
        int n = 100000000;
        int[] test = new int[n];
        for(int i=0; i<test.length; i++)
            test[i] = (int)(Math.random()*test.length);

        long start = System.currentTimeMillis();
        random_selectK(test, test.length/2);
        long end = System.currentTimeMillis();
        System.out.println(end - start);
        */
    }

    public static int random_selectK(int[] a, int k) {
        if(a.length <= 1)
            return a[0];

        int r = (int)(Math.random() * a.length);
        int p = a[r];

        int small = 0, equal = 0, big = 0;
        for(int i=0; i<a.length; i++) {
            if(a[i] < p) small++;
            else if(a[i] == p) equal++;
            else if(a[i] > p) big++;
        }

        if(k <= small) {
            int[] temp = new int[small];
            for(int i=0, j=0; i<a.length; i++)
                if(a[i] < p)
                    temp[j++] = a[i];
            return random_selectK(temp, k);
        }

        else if (k <= small+equal)
            return p;

        else {
            int[] temp = new int[big];
            for(int i=0, j=0; i<a.length; i++)
                if(a[i] > p)
                    temp[j++] = a[i];
            return random_selectK(temp,k-small-equal);
        }
    }

    public static int selectK(int[] a, int k) {
        if(a.length <= 5) {
            Arrays.sort(a);
            return a[k-1];
        }

        int p = median_of_medians(a);

        int small = 0, equal = 0, big = 0;
        for(int i=0; i<a.length; i++) {
            if(a[i] < p) small++;
            else if(a[i] == p) equal++;
            else if(a[i] > p) big++;
        }

        if(k <= small) {
            int[] temp = new int[small];
            for(int i=0, j=0; i<a.length; i++)
                if(a[i] < p)
                    temp[j++] = a[i];
            return selectK(temp, k);
        }

        else if (k <= small+equal)
            return p;

        else {
            int[] temp = new int[big];
            for(int i=0, j=0; i<a.length; i++)
                if(a[i] > p)
                    temp[j++] = a[i];
            return selectK(temp,k-small-equal);
        }
    }

    private static int median_of_medians(int[] a) {
        int[] b = new int[a.length/5];
        int[] temp = new int[5];
        for(int i=0; i<b.length; i++) {
            for(int j=0; j<5; j++)
                temp[j] = a[5*i + j];
            Arrays.sort(temp);
            b[i] = temp[2];
        }

        return selectK(b, b.length/2 + 1);
    }
}