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What is Predicate Pushdown and AQE with Example

Spark/Big Datahard0.6 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Nagarro
Key Concepts Tested
joinoptimizationpartition
Expert AnswerPremium
124 wordsInterview-ready
**Predicate Pushdown**: Filter pushed to data source; only matching rows/row-groups read. Example: `df.filter("date = '2024-01-01'")` — Parquet reader skips row groups that don't contain that date. Partition pruning = filter on partition columns; entire directories skipped. **AQE (Adaptive Query Execution)**: Runtime optimizations. (1) **Coalesce**—after shuffle, merge small partitions (e.g., 200 → 10). (2) **Skew Join**—split hot partitions....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Nagarro. The answer also includes follow-up discussion points that interviewers commonly explore.

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