20. Subarray Sum Equals K
mediumAsked at RedisCount the number of contiguous subarrays that sum to k; Redis uses it to test prefix-sum + hashmap intuition, the same trick that powers GETSET cumulative counters.
By Alex Chen, Founder, InterviewChamp.AI · Last verified
Problem
Given an integer array nums and integer k, return the total number of contiguous subarrays whose sum equals k.
Constraints
1 <= nums.length <= 2 * 10^4-1000 <= nums[i] <= 1000-10^7 <= k <= 10^7
Examples
Example 1
nums=[1,1,1], k=22Example 2
nums=[1,2,3], k=32Approaches
1. Nested sum
Enumerate every (i, j) subarray; add nums[j] to running sum and compare.
- Time
- O(n^2)
- Space
- O(1)
let count = 0;
for (let i = 0; i < nums.length; i++) {
let s = 0;
for (let j = i; j < nums.length; j++) {
s += nums[j];
if (s === k) count++;
}
}
return count;Tradeoff:
2. Prefix sum + hash map
Walk once with running sum S; for each S add seen[S - k] to count, then bump seen[S]. Maps onto how Redis HINCRBY-based counters answer range-sum queries via cumulative deltas.
- Time
- O(n)
- Space
- O(n)
function subarraySum(nums, k) {
const seen = new Map();
seen.set(0, 1);
let sum = 0, count = 0;
for (const n of nums) {
sum += n;
count += seen.get(sum - k) || 0;
seen.set(sum, (seen.get(sum) || 0) + 1);
}
return count;
}Tradeoff:
Redis-specific tips
Redis interviewers like to hear how you'd persist the running prefix-sum hash to a Redis HASH so multiple stream consumers can answer the same range-count without re-scanning.
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