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What techniques ensure deduplication in large datasets?

Spark/Big Datamedium0.4 min readPremium
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Asked at 1 company
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questions in Spark/Big Data
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1,863
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Asked at these companies
Virtusa
Key Concepts Tested
partitionwindow
Expert AnswerPremium
77 wordsInterview-ready
**Techniques**: (1) **dropDuplicates** on keys. (2) **Window**: row_number() over (partition by key order by ts desc) — keep latest. (3) **Delta MERGE** with dedup in merge key. (4) **Hash** (e.g., md5 of cols) for idempotency. (5) **Bloom filter** for approximate. **When**: Event streams (at-least-once), CDC, replays. **Why**: Duplicates corrupt analytics, billing, inventory. **Scalability Trade-offs**: Window on 1B rows = shuffle. Partition by key....
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