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Home/Questions/SQL/Explain types of joins in Spark with examples.

Explain types of joins in Spark with examples.

SQLmedium0.4 min readPremium

**Inner**: Matches only. **Left/Right**: Preserve one side; null for no match. **Full outer**: All from both. **Cross**: Cartesian product. **Left semi**: Rows in left with match in right (EXISTS). **Left anti**: Rows in left with no match (NOT EXISTS). **Why each**: Inner for...

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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
Freecharge
Key Concepts Tested
joinspark

Why This Question Matters

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

Inner: Matches only. Left/Right: Preserve one side; null for no match. Full outer: All from both. Cross: Cartesian product. Left semi: Rows in left with match in right (EXISTS). Left anti: Rows in left with no match (NOT EXISTS). Why each: Inner for fact-dim; left for optional dimension; semi/anti for filtering without bringing right columns. Scalability: Broadcast for small side (<10MB); sort-merge for large-large; shuffle hash default. Cost: Cross join on large tables = disaster; broadcast avoids shuffle.

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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