**SQL**: SELECT trans_date, SUM(amount) AS daily, AVG(SUM(amount)) OVER (ORDER BY trans_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma_7d FROM transactions GROUP BY trans_date. **Logic**: Inner SUM for daily total; outer AVG over 7 rows. **Spark**: Group by date, then...
This medium-level General/Other question appears frequently in data engineering interviews at companies like Goldman Sachs. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (spark, sql, window) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
SQL: SELECT trans_date, SUM(amount) AS daily, AVG(SUM(amount)) OVER (ORDER BY trans_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma_7d FROM transactions GROUP BY trans_date. Logic: Inner SUM for daily total; outer AVG over 7 rows. Spark: Group by date, then window. Best practice: Handle sparse dates; use ROWS for dense.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.