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|  | 1 | +package com.leetcode.heaps; | 
|  | 2 | + | 
|  | 3 | +import com.rampatra.base.MaxHeap; | 
|  | 4 | + | 
|  | 5 | +import java.util.PriorityQueue; | 
|  | 6 | + | 
|  | 7 | +import static org.junit.jupiter.api.Assertions.assertEquals; | 
|  | 8 | + | 
|  | 9 | +/** | 
|  | 10 | + * Level: Medium | 
|  | 11 | + * Link: https://leetcode.com/problems/kth-largest-element-in-an-array/ | 
|  | 12 | + * Description: | 
|  | 13 | + * Find the kth largest element in an unsorted array. Note that it is the kth largest element in the sorted order, not | 
|  | 14 | + * the kth distinct element. | 
|  | 15 | + * <p> | 
|  | 16 | + * Example 1: | 
|  | 17 | + * Input: [3,2,1,5,6,4] and k = 2 | 
|  | 18 | + * Output: 5 | 
|  | 19 | + * <p> | 
|  | 20 | + * Example 2: | 
|  | 21 | + * Input: [3,2,3,1,2,4,5,5,6] and k = 4 | 
|  | 22 | + * Output: 4 | 
|  | 23 | + * <p> | 
|  | 24 | + * Note: | 
|  | 25 | + * You may assume k is always valid, 1 ≤ k ≤ array's length. | 
|  | 26 | + * | 
|  | 27 | + * @author rampatra | 
|  | 28 | + * @since 2019-08-19 | 
|  | 29 | + */ | 
|  | 30 | +public class KthLargestElementInArray { | 
|  | 31 | + | 
|  | 32 | +    /** | 
|  | 33 | +     * Runtime: <a href="https://leetcode.com/submissions/detail/252999497/">1 ms</a>. | 
|  | 34 | +     * | 
|  | 35 | +     * @param nums | 
|  | 36 | +     * @param k | 
|  | 37 | +     * @return | 
|  | 38 | +     */ | 
|  | 39 | +    public static int findKthLargest(int[] nums, int k) { | 
|  | 40 | +        return heapSortUntilK(nums, k); | 
|  | 41 | +    } | 
|  | 42 | + | 
|  | 43 | +    /** | 
|  | 44 | +     * In heapsort, after each iteration we have the max element at the end of the array. Ergo, if we run the algorithm | 
|  | 45 | +     * k times then we would have our kth largest element. | 
|  | 46 | +     * | 
|  | 47 | +     * @param a | 
|  | 48 | +     * @param k | 
|  | 49 | +     * @return | 
|  | 50 | +     */ | 
|  | 51 | +    public static int heapSortUntilK(int[] a, int k) { | 
|  | 52 | +        buildMaxHeap(a); | 
|  | 53 | +        int count = 0; | 
|  | 54 | + | 
|  | 55 | +        for (int i = a.length - 1; i > 0; i--) { | 
|  | 56 | +            if (count++ == k) { | 
|  | 57 | +                break; | 
|  | 58 | +            } | 
|  | 59 | +            swap(a, 0, i); | 
|  | 60 | +            maxHeapify(a, 0, i); | 
|  | 61 | +        } | 
|  | 62 | + | 
|  | 63 | +        return a[a.length - k]; | 
|  | 64 | +    } | 
|  | 65 | + | 
|  | 66 | +    /** | 
|  | 67 | +     * Makes the array {@param a} satisfy the max heap property starting from | 
|  | 68 | +     * {@param index} till {@param end} position in array. | 
|  | 69 | +     * <p/> | 
|  | 70 | +     * See this {@link MaxHeap#maxHeapify} for a basic version of maxHeapify. | 
|  | 71 | +     * <p/> | 
|  | 72 | +     * Time complexity: O(log n). | 
|  | 73 | +     * | 
|  | 74 | +     * @param a | 
|  | 75 | +     * @param index | 
|  | 76 | +     * @param end | 
|  | 77 | +     */ | 
|  | 78 | +    public static void maxHeapify(int[] a, int index, int end) { | 
|  | 79 | +        int largest = index; | 
|  | 80 | +        int leftIndex = 2 * index + 1; | 
|  | 81 | +        int rightIndex = 2 * index + 2; | 
|  | 82 | + | 
|  | 83 | +        if (leftIndex < end && a[index] < a[leftIndex]) { | 
|  | 84 | +            largest = leftIndex; | 
|  | 85 | +        } | 
|  | 86 | +        if (rightIndex < end && a[largest] < a[rightIndex]) { | 
|  | 87 | +            largest = rightIndex; | 
|  | 88 | +        } | 
|  | 89 | + | 
|  | 90 | +        if (largest != index) { | 
|  | 91 | +            swap(a, index, largest); | 
|  | 92 | +            maxHeapify(a, largest, end); | 
|  | 93 | +        } | 
|  | 94 | +    } | 
|  | 95 | + | 
|  | 96 | +    /** | 
|  | 97 | +     * Converts array {@param a} in to a max heap. | 
|  | 98 | +     * <p/> | 
|  | 99 | +     * Time complexity: O(n) and is not O(n log n). | 
|  | 100 | +     */ | 
|  | 101 | +    private static void buildMaxHeap(int[] a) { | 
|  | 102 | +        for (int i = a.length / 2 - 1; i >= 0; i--) { | 
|  | 103 | +            maxHeapify(a, i, a.length); | 
|  | 104 | +        } | 
|  | 105 | +    } | 
|  | 106 | + | 
|  | 107 | + | 
|  | 108 | +    /** | 
|  | 109 | +     * When you poll() on a PriorityQueue the smallest number in the queue is removed. Based on this property, we can | 
|  | 110 | +     * iterate over the entire array and in the end we would be left with the k largest element in the queue. | 
|  | 111 | +     * | 
|  | 112 | +     * @param nums | 
|  | 113 | +     * @param k | 
|  | 114 | +     * @return | 
|  | 115 | +     */ | 
|  | 116 | +    public static int findKthLargestUsingPriorityQueue(int[] nums, int k) { | 
|  | 117 | +        PriorityQueue<Integer> priorityQueue = new PriorityQueue<>(); | 
|  | 118 | + | 
|  | 119 | +        for (int num : nums) { | 
|  | 120 | +            priorityQueue.add(num); | 
|  | 121 | + | 
|  | 122 | +            if (priorityQueue.size() > k) { | 
|  | 123 | +                priorityQueue.poll(); | 
|  | 124 | +            } | 
|  | 125 | +        } | 
|  | 126 | + | 
|  | 127 | +        return priorityQueue.isEmpty() ? -1 : priorityQueue.peek(); | 
|  | 128 | +    } | 
|  | 129 | + | 
|  | 130 | +    private static void swap(int[] a, int firstIndex, int secondIndex) { | 
|  | 131 | +        a[firstIndex] = a[firstIndex] + a[secondIndex]; | 
|  | 132 | +        a[secondIndex] = a[firstIndex] - a[secondIndex]; | 
|  | 133 | +        a[firstIndex] = a[firstIndex] - a[secondIndex]; | 
|  | 134 | +    } | 
|  | 135 | + | 
|  | 136 | +    public static void main(String[] args) { | 
|  | 137 | +        assertEquals(5, findKthLargest(new int[]{3, 2, 1, 5, 6, 4}, 2)); | 
|  | 138 | +        assertEquals(3, findKthLargest(new int[]{3, 2, 1, 5, 6, 4}, 4)); | 
|  | 139 | + | 
|  | 140 | +        assertEquals(5, findKthLargestUsingPriorityQueue(new int[]{3, 2, 1, 5, 6, 4}, 2)); | 
|  | 141 | +        assertEquals(3, findKthLargestUsingPriorityQueue(new int[]{3, 2, 1, 5, 6, 4}, 4)); | 
|  | 142 | +    } | 
|  | 143 | +} | 
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