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Extract insights from given JSON data using your preferred framework.

General/Othermedium0.2 min readPremium
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
Flipkart
Key Concepts Tested
partitionspark
Expert AnswerPremium
45 wordsInterview-ready
**Approach**: PySpark—spark.read.json() or from_json() for nested. Define StructType for type safety. Flatten, explode arrays. Example: df.select(explode('items')).groupBy('item.category').count(). from_json(col, schema) for nested. **Scale**: mode PERMISSIVE with columnOfCorruptRecord for malformed; partitioning for large....
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