How should I practice K Closest Points to a Target?

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Problem · Array

K Closest Points to a Target

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Problem statement

Given distinct two-dimensional integer points, a two-dimensional integer target, and an integer k, return the k points closest to target.

For a point [x, y], use squared Euclidean distance (x - target[0])^2 + (y - target[1])^2. Smaller distance is closer. Break equal-distance ties by smaller x, then smaller y.

Return the selected points ordered from closest to farthest using that same distance-and-coordinate order.

Function

kClosestPoints(points: int[][], target: int[], k: int) → int[][]

Examples

Example 1

points = [[1,3],[-2,2],[2,-2],[4,0]]target = [0,0]k = 2return = [[-2,2],[2,-2]]

The two selected points both have squared distance 8. The tie is resolved by the smaller x-coordinate.

Example 2

points = [[5,5],[3,4],[4,3],[2,2]]target = [3,3]k = 3return = [[3,4],[4,3],[2,2]]

The first two returned points have squared distance 1. [2,2] follows with squared distance 2.

Example 3

points = [[0,0]]target = [7,-4]k = 1return = [[0,0]]

The only point must be returned.

Constraints

1 <= points.length <= 10^5.
points[i].length == 2 and target.length == 2.
All points are distinct.
1 <= k <= points.length.
-10^9 <= points[i][j], target[j] <= 10^9.
Use 64-bit arithmetic for squared distances.