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Retranslate the complete English edition from Simplified Chinese (#2010)

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* Retranslate the complete English edition from Simplified Chinese

* Polish three English explanations after reader-focused review
This commit is contained in:
Yudong Jin
2026-10-31 03:35:51 +08:00
committed by GitHub
parent ef46e2ed95
commit 14c314c08c
1502 changed files with 29459 additions and 23517 deletions
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12
en/codes/java/chapter_heap/top_k.java
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@@ -10,17 +10,17 @@ import utils.*;
import java.util.*;
public class top_k {
/* Find the largest k elements in array based on heap */
/* Use a heap to find the k largest elements in an array */
static Queue<Integer> topKHeap(int[] nums, int k) {
// Python's heapq module implements min heap by default
// Initialize a min heap
Queue<Integer> heap = new PriorityQueue<Integer>();
// Enter the first k elements of array into heap
// Push the first k array elements onto the heap
for (int i = 0; i < k; i++) {
heap.offer(nums[i]);
}
// Starting from the (k+1)th element, maintain heap length as k
// Starting with element k+1, keep the heap size at k
for (int i = k; i < nums.length; i++) {
// If current element is greater than top element, top element exits heap, current element enters heap
// If the current element is larger than the heap top, pop the top element and push the current element
if (nums[i] > heap.peek()) {
heap.poll();
heap.offer(nums[i]);
@@ -34,7 +34,7 @@ public class top_k {
int k = 3;
Queue<Integer> res = topKHeap(nums, k);
System.out.println("The largest " + k + " elements are");
System.out.println("The largest " + k + " elements are:");
PrintUtil.printHeap(res);
}
}