Trapping Rain Water II
A hard-tier problem at 59% community acceptance, tagged with Array, Breadth-First Search, Heap (Priority Queue). Reported in interviews at Otter.ai and 5 others.
Trapping Rain Water II is a hard problem that shows up at Google, ByteDance, Palantir, and other top-tier companies. You get a 2D elevation map and need to calculate how much water gets trapped after it rains. The naive approach (simulate water level, iterate cells) will time out. The trick is a priority queue and boundary-inward traversal. This is the kind of problem where if you haven't drilled the specific pattern, you'll blank on the assessment. If that happens and you need a working solution fast, StealthCoder surfaces it invisibly during your live OA.
Companies that ask "Trapping Rain Water II"
Trapping Rain Water II is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core insight is that water height at any cell is determined by the minimum of the maximum heights on all paths to the boundary. Use a min-heap of boundary cells, process them inward in order of ascending height, and track the water level as you go. Cells you haven't visited yet are trapped at the current water level minus their elevation. Most candidates try to simulate water directly or use dynamic programming on a 2D grid, which either explodes in time complexity or misses the boundary constraint. Breadth-First Search with a priority queue is the intended approach. If you hit this live and don't know the heap-based boundary strategy, StealthCoder gives you the working code in seconds.
Pattern tags
You know the problem.
Make sure you actually pass it.
Trapping Rain Water II recycles across companies for a reason. It's hard-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Trapping Rain Water II interview FAQ
Is this just Trapping Rain Water (1D) scaled up?+
No. The 1D version uses two-pointer greedy. Here, water can come from any direction, so you need a priority queue and BFS. You're processing boundaries inward, not left-to-right. The 2D constraint forces a completely different algorithm.
Why does the min-heap approach work?+
Water level at a cell is capped by the lowest wall it must cross to escape. By processing boundary cells in ascending height order, you ensure the water level is correct when you visit each interior cell. Cells visited later are trapped at the current level.
How often do top companies ask this?+
It appears in reports from Google, ByteDance, Palantir, and others. Acceptance rate is around 59 percent, so it's a real filter. Most hard problems sit lower, so expect it in later-round technical screens at FAANG.
What's the main pitfall candidates hit?+
Trying to track water per cell or simulate water filling from the top down. Both fail on 2D. The correct move is to think of the boundary as a container wall and process inward. If you're iterating rows and columns, you're on the wrong path.
Do I need to memorize this or can I derive it?+
Deriving it under interview pressure is hard. The heap-and-BFS pattern isn't obvious without exposure. It's worth drilling once so the insight clicks. If you blank, that's when StealthCoder is your hedge during the live assessment.
Want the actual problem statement? View "Trapping Rain Water II" on LeetCode →