Game Play Analysis IV
A medium-tier problem at 39% community acceptance, tagged with Database. Reported in interviews at GSN Games and 0 others.
Game Play Analysis IV is a database problem that hits harder than it looks. With a 39% acceptance rate, most candidates fail because they treat it as a straightforward SQL query when it's really asking you to build cumulative logic across sessions. GSN Games asks this one, and if you're interviewing there or at similar gaming platforms, you need to know the exact pattern: how to partition data by player, order by date, and compute running aggregates without tripping up on null handling or window function syntax. If this problem lands in your assessment and you blank on the window function approach, StealthCoder solves it in seconds, invisible to the proctor.
Companies that ask "Game Play Analysis IV"
Game Play Analysis IV 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 because the OA filter rejects engineers who'd pass the on-site. That's a broken filter. This is the workaround.
Get StealthCoderThe trap is the multi-step aggregation. Most candidates write a basic SELECT with GROUP BY and miss that the problem wants cumulative or session-level stats across time. You need to order events by date, often using ROW_NUMBER or RANK to identify session boundaries, then aggregate upward. Common failures: forgetting to partition by player_id first, mixing up the window frame (ROWS BETWEEN vs RANGE), or returning duplicate rows because the join logic compounds. The real trick is recognizing when you need a CTE or subquery to stage the data before the final aggregation. Database problems like this reward precision; one syntax error or logic flub and the whole result set breaks. StealthCoder reads the schema and problem statement, then surfaces the exact window function pattern you need, saving you the debugging cycle during the live OA.
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Game Play Analysis IV recycles across companies for a reason. It's medium-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 because the OA filter rejects engineers who'd pass the on-site. That's a broken filter. This is the workaround. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Game Play Analysis IV interview FAQ
Why is the acceptance rate so low on this one?+
Candidates approach it as a simple GROUP BY problem, then realize mid-query they need cumulative or session logic. Window functions are the solution, but they're easy to mess up: wrong PARTITION BY clause, incorrect ROWS frame, or forgetting to order by date. The schema is also sometimes ambiguous, so misreading the table structure costs time.
What's the actual trick to solving this?+
Build the query in stages: first, identify player sessions or events using ROW_NUMBER() PARTITION BY player_id ORDER BY date. Then, aggregate upward using SUM() OVER or similar window functions to compute cumulative stats. Finally, join or filter to match the required output format. Avoid doing it all in one query.
Is this still asked at gaming or gaming-adjacent companies?+
Yes. GSN Games reports it, and similar companies running player analytics pipelines ask database problems like it. If you're interviewing at a platform with user sessions, events, or time-series data, expect this pattern to appear in some form.
How does this relate to typical database interview problems?+
It's a step up from basic joins and GROUP BY. It tests whether you understand window functions and can think in terms of ordered, partitioned data. Many medium-level database problems follow this same structure: partition, order, compute, aggregate.
What's the most common mistake candidates make?+
Forgetting to order by date within the window function, or using GROUP BY when they should use a window aggregate. Also, misunderstanding what 'cumulative' or 'session-level' means from the problem statement. Re-read the output spec carefully before writing a single line of SQL.
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