Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Window + GROUP BY: use window for per-row rank/aggregate; GROUP BY for reduction. Example: with windowed as (select dept, salary, rank() over (partition by dept order by salary desc) rn from emp) select dept, max(case when rn=1 then salary end) top_sal from windowed group by...
Window + GROUP BY: use window for per-row rank/aggregate; GROUP BY for reduction. Example: with windowed as (select dept, salary, rank() over (partition by dept order by salary desc) rn from emp) select dept, max(case when rn=1 then salary end) top_sal from windowed group by dept. Or: window for rank, then filter rn=1, no GROUP BY needed. Why it matters: Design choices compound at scale—wrong approach can cause 100× overhead. Scalability trade-offs: Profile before optimizing; validate on sample then full. Cost implications: Suboptimal choices multiply at billion-row scale.
Red Flag: Generic textbook answers. Pro-Move: 'At scale we measured X, implemented Y, achieved Z%—validated and iterated.'
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