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Count records for INNER JOIN and LEFT JOIN

SQLmedium0.5 min readPremium

**Architectural Logic**: Join type determines output cardinality and null semantics. **INNER JOIN**: Only matching rows from both tables; count ≤ min(left, right) when 1:1 or N:1. **LEFT JOIN**: All left rows; right columns NULL where no match; count = left count (if left is...

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Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Pubmatic
Key Concepts Tested
join

Why This Question Matters

This medium-level SQL question appears frequently in data engineering interviews at companies like Pubmatic. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join) 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
98 words

Architectural Logic: Join type determines output cardinality and null semantics. INNER JOIN: Only matching rows from both tables; count ≤ min(left, right) when 1:1 or N:1. LEFT JOIN: All left rows; right columns NULL where no match; count = left count (if left is 'one' side). Cardinality Rules: INNER can reduce rows (excludes orphans); LEFT preserves left. Use COUNT() for total rows; COUNT(right.key) for non-null matches (LEFT JOIN gives matched count). Why It Matters: Data quality checks—LEFT JOIN with COUNT(right.key) < COUNT() reveals orphaned left rows. Scalability: Join strategy (broadcast, sort-merge) affects shuffle; understanding cardinality informs optimizer hints.

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 SQL 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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