{ "data": { "question": { "questionId": "3495", "questionFrontendId": "3275", "categoryTitle": "Algorithms", "boundTopicId": 2857597, "title": "K-th Nearest Obstacle Queries", "titleSlug": "k-th-nearest-obstacle-queries", "content": "
There is an infinite 2D plane.
\n\nYou are given a positive integer k
. You are also given a 2D array queries
, which contains the following queries:
queries[i] = [x, y]
: Build an obstacle at coordinate (x, y)
in the plane. It is guaranteed that there is no obstacle at this coordinate when this query is made.After each query, you need to find the distance of the kth
nearest obstacle from the origin.
Return an integer array results
where results[i]
denotes the kth
nearest obstacle after query i
, or results[i] == -1
if there are less than k
obstacles.
Note that initially there are no obstacles anywhere.
\n\nThe distance of an obstacle at coordinate (x, y)
from the origin is given by |x| + |y|
.
\n
Example 1:
\n\nInput: queries = [[1,2],[3,4],[2,3],[-3,0]], k = 2
\n\nOutput: [-1,7,5,3]
\n\nExplanation:
\n\nqueries[0]
, there are less than 2 obstacles.queries[1]
, there are obstacles at distances 3 and 7.queries[2]
, there are obstacles at distances 3, 5, and 7.queries[3]
, there are obstacles at distances 3, 3, 5, and 7.Example 2:
\n\nInput: queries = [[5,5],[4,4],[3,3]], k = 1
\n\nOutput: [10,8,6]
\n\nExplanation:
\n\nqueries[0]
, there is an obstacle at distance 10.queries[1]
, there are obstacles at distances 8 and 10.queries[2]
, there are obstacles at distances 6, 8, and 10.\n
Constraints:
\n\n1 <= queries.length <= 2 * 105
queries[i]
are unique.-109 <= queries[i][0], queries[i][1] <= 109
1 <= k <= 105
有一个无限大的二维平面。
\n\n给你一个正整数 k
,同时给你一个二维数组 queries
,包含一系列查询:
queries[i] = [x, y]
:在平面上坐标 (x, y)
处建一个障碍物,数据保证之前的查询 不会 在这个坐标处建立任何障碍物。每次查询后,你需要找到离原点第 k
近 障碍物到原点的 距离 。
请你返回一个整数数组 results
,其中 results[i]
表示建立第 i
个障碍物以后,离原地第 k
近障碍物距离原点的距离。如果少于 k
个障碍物,results[i] == -1
。
注意,一开始 没有 任何障碍物。
\n\n坐标在 (x, y)
处的点距离原点的距离定义为 |x| + |y|
。
\n\n
示例 1:
\n\n输入:queries = [[1,2],[3,4],[2,3],[-3,0]], k = 2
\n\n输出:[-1,7,5,3]
\n\n解释:
\n\n最初,不存在障碍物。
\n\nqueries[0]
之后,少于 2 个障碍物。queries[1]
之后, 两个障碍物距离原点的距离分别为 3 和 7 。queries[2]
之后,障碍物距离原点的距离分别为 3 ,5 和 7 。queries[3]
之后,障碍物距离原点的距离分别为 3,3,5 和 7 。示例 2:
\n\n输入:queries = [[5,5],[4,4],[3,3]], k = 1
\n\n输出:[10,8,6]
\n\n解释:
\n\nqueries[0]
之后,只有一个障碍物,距离原点距离为 10 。queries[1]
之后,障碍物距离原点距离分别为 8 和 10 。queries[2]
之后,障碍物距离原点的距离分别为 6, 8 和10 。\n\n
提示:
\n\n1 <= queries.length <= 2 * 105
queries[i]
互不相同。-109 <= queries[i][0], queries[i][1] <= 109
1 <= k <= 105
k
obstacles. Can the k + 1th
obstacle ever be the answer to any query?",
"Maintain a max heap of size k
, thus heap will contain minimum element at the top in that queue.",
"Remove top element and insert new element from input array if current max is larger than this."
],
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