Find Hash
Reported by candidates from Amazon's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Amazon's "Find Hash" problem hit the OA circuit in June 2025, and candidates report it's a straightforward hash-table play that trips people up only when they overthink it. You're likely looking at a problem that asks you to find or validate a hash value, match keys to values, or detect duplicates across a dataset. The core mechanic is recognizing when a hash map or set solves the problem in linear time. If you blank on the exact approach during the live OA, StealthCoder will read the problem and surface the pattern instantly, so you stay on pace.
Pattern and pitfall
Hash-table problems at Amazon usually hinge on one of three moves: store elements in a map to count frequency, use a set to track what you've seen, or match values across two collections. The trick here is avoiding nested loops and remembering that hash operations (insert, lookup, delete) are O(1) on average. A common pitfall is forgetting to handle edge cases like empty inputs, collisions in your mental model, or misunderstanding what "find" means in context. During the OA, if the wording is vague or you second-guess the approach, StealthCoder becomes your safety net, reading the exact problem and confirming whether you need a frequency map, a set for membership, or a lookup table. That clarity buys you confidence and speed.
If this hits your live OA and you blank, StealthCoder solves it in seconds, invisible to the proctor.
You can drill Find Hash cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it.
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This OA pattern shows up on LeetCode as contains duplicate. If you have time before the OA, drill that.
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Amazon reuses patterns across OAs. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Find Hash FAQ
Is this a frequency-count problem or a membership/lookup problem?+
Without the full problem text, both are common at Amazon. Frequency (how many times does X appear) usually calls for a dictionary/map. Membership (have I seen this before) calls for a set. Read the first two sentences carefully. The verb matters: 'count' means frequency; 'check', 'find', or 'detect' often means set or lookup.
Do I need to sort the result or the input?+
Hash-table problems rarely require sorting as the core logic. If the output is 'return the hash value', no sort needed. If it's 'return all matches in order', you may need to sort the keys after building the map. Ask yourself: does order matter to the problem statement?
What if there are multiple test cases or large inputs?+
Hash tables scale well. O(n) time, O(n) space is your baseline. If the input is 10^6 elements, a hash-based solution will pass. Avoid nested loops. If you're tempted to loop through the map for every input element, you're heading toward O(n^2), which will time out.
Should I use a dictionary, a set, or a Counter?+
Python Counter is a dict subclass, great for frequency. Use dict if you need key-value pairs. Use set if you only care about presence/absence. At Amazon, they rarely care which you pick, as long as your logic is sound. Pick the clearest one for you in 30 seconds.
How do I prepare for this in 24-48 hours if I haven't seen the problem?+
Drill two LeetCode-style problems: one on frequency counting (Two Sum, Valid Anagram), one on membership/deduplication (Contains Duplicate). That covers 80% of hash-table OA asks. Memorize the three patterns and you're solid. The rest is reading the problem carefully on the day.