Subarray Counting
Reported by candidates from DataBricks's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
DataBricks hit you with a subarray counting problem in September, and it's exactly the kind of thing that lands candidates in a blank stare during the OA. You need to count subarrays that meet some condition, and the naive approach will time out. The trick is usually a combination of prefix sums and a hash table to track what you've seen. If you blank mid-OA, StealthCoder reads the exact condition and feeds you the pattern in real time. You won't waste mental cycles second-guessing the approach.
Pattern and pitfall
Subarray counting almost always boils down to prefix sums plus a hash map. You compute a running value (sum, XOR, whatever) and ask: how many times have I seen this value before. That count tells you how many valid subarrays end at the current position. The brute force is O(n^2), which breaks. The optimized path is O(n) with a map to cache prefix states. Edge case: off-by-one on the initial map entry (usually you seed it with 0 -> 1). The hash table is your real weapon here. StealthCoder catches the exact condition in the problem statement and hands you the formula.
If you see this problem in your OA tomorrow, the play is to recognize the pattern in 30 seconds. StealthCoder buys you that recognition.
You can drill Subarray Counting 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 passed his OA cold and still thinks the filter is broken.
Get StealthCoderRelated leaked OAs
This OA pattern shows up on LeetCode as subarray sum equals k. If you have time before the OA, drill that.
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DataBricks reuses patterns across OAs. Built by an Amazon engineer who passed his OA cold and still thinks the filter is broken. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Subarray Counting FAQ
Is this about counting subarrays with a specific sum?+
Usually, yes. Or XOR equal to a target, or some other aggregate property. The mechanism is the same: prefix technique plus hash map. Figure out what property you're tracking, then cache it. The condition is always in the problem statement.
Will the brute force pass?+
No. O(n^2) enumeration of all subarrays fails on large inputs. You need O(n) with a hash map. The optimization is not optional. That's the whole point of the question.
What's the most common mistake?+
Forgetting to initialize the map with the base case (often 0 -> 1 or similar). You're asking 'how many prefixes before this one match a target', and you need the zero-prefix to count. Miss that and your counts are off by one or more.
Do I need to handle negative numbers or constraints differently?+
Depends on the exact condition. If it's sum-based, negatives are fine, the prefix sum method handles them. If it's something else (XOR, modulo, etc.), the logic shifts slightly, but the pattern remains: cache and count. The problem text tells you.
Can I solve this in one pass?+
Yes, that's the point. Single pass, hash map to store prefix states, counter to accumulate results. You don't revisit the array. That's how you get from O(n^2) to O(n) in one clean move.