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How would you handle duplicate or corrupted data in a batch ETL job?

SQLmedium0.7 min readPremium
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
Adidas
Key Concepts Tested
etlpartitionspark
Expert AnswerPremium
143 wordsInterview-ready
Handling duplicate or corrupted data in batch ETL involves multiple layers. First, implement idempotency—use MERGE/UPSERT or truncate-and-reload with deterministic keys. For duplicates, apply business rules: keep most recent (MAX(updated_at)), first occurrence, or aggregate. Use ROW_NUMBER() OVER (PARTITION BY composite_key ORDER BY timestamp DESC) and filter rn=1. For corrupted data, validate schemas at ingestion, reject bad records to a quarantine table, and alert....
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 Adidas. The answer also includes follow-up discussion points that interviewers commonly explore.

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