24. Median of Two Sorted Arrays
hardAsked at UdemyFind the median of two sorted arrays in O(log(m+n)) — Udemy uses this to test binary search mastery applied to statistical ranking and recommendation scoring.
By Alex Chen, Founder, InterviewChamp.AI · Last verified
Problem
Given two sorted arrays nums1 and nums2 of size m and n, return the median of the two sorted arrays. The overall run time complexity must be O(log(m+n)).
Constraints
0 <= m, n <= 10000 <= m + nnums1 and nums2 are sorted in non-decreasing order
Examples
Example 1
nums1 = [1,3], nums2 = [2]2.00000Example 2
nums1 = [1,2], nums2 = [3,4]2.50000Approaches
1. Merge and select
Merge both arrays then return the middle element — O(m+n) time, does not meet the log constraint.
- Time
- O(m+n)
- Space
- O(m+n)
function findMedianSortedArrays(nums1, nums2) {
const merged = [...nums1, ...nums2].sort((a,b) => a-b);
const mid = Math.floor(merged.length / 2);
return merged.length % 2 === 0 ? (merged[mid-1] + merged[mid]) / 2 : merged[mid];
}Tradeoff:
2. Binary search partition
Binary search on the smaller array to find a partition such that all elements on the left side of both partitions are <= all elements on the right side; the median is then computed from the four boundary elements.
- Time
- O(log(min(m,n)))
- Space
- O(1)
function findMedianSortedArrays(nums1, nums2) {
if (nums1.length > nums2.length) return findMedianSortedArrays(nums2, nums1);
const m = nums1.length, n = nums2.length;
let lo = 0, hi = m;
while (lo <= hi) {
const i = (lo + hi) >> 1;
const j = ((m + n + 1) >> 1) - i;
const maxL1 = i === 0 ? -Infinity : nums1[i-1];
const minR1 = i === m ? Infinity : nums1[i];
const maxL2 = j === 0 ? -Infinity : nums2[j-1];
const minR2 = j === n ? Infinity : nums2[j];
if (maxL1 <= minR2 && maxL2 <= minR1) {
const left = Math.max(maxL1, maxL2);
if ((m + n) % 2 === 1) return left;
return (left + Math.min(minR1, minR2)) / 2;
} else if (maxL1 > minR2) hi = i - 1;
else lo = i + 1;
}
}Tradeoff:
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