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Spark Coding: Using explode() Function to flatten nested arrays

Python/Codingmedium0.4 min readPremium
Frequency
Low
Asked at 1 company
Category
179
questions in Python/Coding
Difficulty Split
127E|24M|28H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Lumiq
Key Concepts Tested
joinpartitionspark
Expert AnswerPremium
78 wordsInterview-ready
**Why Explode:** Nested JSON (items array per order) → one row per item for joins/aggregation. Normalization for star schema. **Functions:** explode()—one-to-many; null/empty arrays drop row. explode_outer()—keeps row, null for empty. posexplode()—adds position index. For multiple array cols: arrays_zip then explode. **Scalability Risk:** Large arrays cause row explosion—1 row with 10K items → 10K rows. Can cause skew. Use explode then repartition or broadcast the small side for joins....
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