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35. 3Sum

mediumAsked at Datadog

Find all unique triplets that sum to zero. Datadog uses this as the cornerstone two-pointer + dedup question — the same pattern needed for finding triple-correlations in cross-metric anomaly detection.

By Sam K., Founder, InterviewChamp.AI · Last verified

Source citations

Public interview reports confirming this problem appears in Datadog loops.

  • Glassdoor (2026-Q1)Datadog onsite — focal point of mid-tier rounds.
  • Blind (2025-12)Recurring at Datadog NYC.

Problem

Given an integer array nums, return all the triplets [nums[i], nums[j], nums[k]] such that i != j, i != k, and j != k, and nums[i] + nums[j] + nums[k] == 0. Notice that the solution set must not contain duplicate triplets.

Constraints

  • 3 <= nums.length <= 3000
  • -10^5 <= nums[i] <= 10^5

Examples

Example 1

Input
nums = [-1,0,1,2,-1,-4]
Output
[[-1,-1,2],[-1,0,1]]

Example 2

Input
nums = [0,1,1]
Output
[]

Example 3

Input
nums = [0,0,0]
Output
[[0,0,0]]

Approaches

1. Brute force three loops + dedup

Check every (i, j, k); dedup via sorted-tuple Set.

Time
O(n^3)
Space
O(n^3)
// Three nested loops with set-based dedup of sorted tuples.
// Always too slow at Datadog scale.

Tradeoff: Cubic — fails on 3000-element inputs and signals you missed the sort+two-pointer pattern.

2. Sort + two-pointer with dedup (optimal)

Sort. For each i, use two pointers j, k to find pairs summing to -nums[i]. Skip duplicates at all three levels.

Time
O(n^2)
Space
O(1) extra (output O(k))
function threeSum(nums) {
  nums.sort((a, b) => a - b);
  const out = [];
  for (let i = 0; i < nums.length - 2; i++) {
    if (nums[i] > 0) break;
    if (i > 0 && nums[i] === nums[i - 1]) continue;
    let j = i + 1, k = nums.length - 1;
    while (j < k) {
      const sum = nums[i] + nums[j] + nums[k];
      if (sum === 0) {
        out.push([nums[i], nums[j], nums[k]]);
        while (j < k && nums[j] === nums[j + 1]) j++;
        while (j < k && nums[k] === nums[k - 1]) k--;
        j++; k--;
      } else if (sum < 0) {
        j++;
      } else {
        k--;
      }
    }
  }
  return out;
}

Tradeoff: O(n^2) time, O(1) extra space. The dedup logic at three levels (outer i, inner j, inner k) is what Datadog grades on.

Datadog-specific tips

Datadog interviewers grade on the three dedup checks: skip i when nums[i] === nums[i-1]; after finding a triplet, advance j past duplicates AND k past duplicates. Forgetting any one produces duplicates. Articulate all three before coding.

Common mistakes

  • Using a Set of sorted tuples as a hack for dedup — works but signals you didn't think through the sort+skip logic.
  • Only skipping duplicates at i, not j or k — produces [a, b, c] and [a, b, c] when there are repeats of b or c.
  • Forgetting the nums[i] > 0 early-exit — wastes work in the all-positive tail.

Follow-up questions

An interviewer at Datadog may pivot to one of these next:

  • 3Sum Closest (LC 16) — find triplet closest to target.
  • 4Sum (LC 18) — two outer loops + two pointers.
  • k-Sum — generalized recursive structure.

Solve it now

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Output

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FAQ

Why sort first?

Sorting enables two-pointer (monotonic sweep) and makes adjacent-duplicate skip trivial. Without sort, dedup requires a hashset, blowing memory.

Why skip duplicates AFTER finding a match (j and k)?

Otherwise the same triplet can be found multiple times when there are repeats in the array.

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