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Home/Questions/General/Other/Calculate the total sales amount for customers born between 1998-01-15 and 2000-01-15.

Calculate the total sales amount for customers born between 1998-01-15 and 2000-01-15.

General/Othermedium0.2 min readPremium

**SQL**: SELECT SUM(s.amount) AS total_sales FROM sales s JOIN customers c ON s.customer_id = c.id WHERE c.birth_date BETWEEN '1998-01-15' AND '2000-01-15'. **Note**: BETWEEN inclusive. **Spark**: sales.join(customers, 'customer_id').filter((col('birth_date') >= '1998-01-15') &...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
243
questions in General/Other
Difficulty Split
151E|43M|49H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Aarete
Interview Pro Tip

Pro-Move: 'We have a birth_date index—this cohort query runs 10x faster; we materialize cohort tables for common segments.' Red Flag: Not knowing BETWEEN is inclusive—off-by-one on boundaries.

Key Concepts Tested
joinsparksql

Why This Question Matters

This medium-level General/Other question appears frequently in data engineering interviews at companies like Aarete. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join, spark, sql) will help you answer variations of this question confidently.

How to Approach This

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.

Expert Answer
41 words

SQL: SELECT SUM(s.amount) AS total_sales FROM sales s JOIN customers c ON s.customer_id = c.id WHERE c.birth_date BETWEEN '1998-01-15' AND '2000-01-15'. Note: BETWEEN inclusive. Spark: sales.join(customers, 'customer_id').filter((col('birth_date') >= '1998-01-15') & (col('birth_date') <= '2000-01-15')).agg(F.sum('amount')). Best practice: Index birth_date if frequent; consider timezone.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According 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.

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