Source: http://blog.teamleadnet.com/2012/07/quick-select-algorithm-find-kth-element.html
Arr = [5 1 4 3 2] Pivot = [4] Steps: swap [5] and [2] as 5>=4 and 2< [2 1 4 3 5] swap [4] and [3] as 4>=4 and 3<4 [2 1 3 4 5]
Arr = [2 1 3 …] Pivot = [1] Steps: swap [2] and [1] as 2>=2 and 1<2 [1 2 3 …]
Arr = […2 3…] Pivot= [2]// Quick Select O(n) instead of O(nlogn) for large dataset
// Source :http://blog.teamleadnet.com/2012/07/quick-select-algorithm-find-kth-element.html public static int selectKth(int[] arr, int k) { if (arr == null || arr.length <= k) throw new Error(); int from = 0, to = arr.length - 1; // if from == to we reached the kth element while (from < to) { int r = from, w = to; int mid = arr[(r + w) / 2]; // stop if the reader and writer meets while (r < w) { if (arr[r] >= mid) { // put the large values at the end int tmp = arr[w]; arr[w] = arr[r]; arr[r] = tmp; w--; } else { // the value is smaller than the pivot, skip r++; } } // if we stepped up (r++) we need to step one down if (arr[r] > mid) r--; // the r pointer is on the end of the first k elements if (k <= r) { to = r; } else { from = r + 1; } } return arr[k]; }
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