Question 1

Briefly explain the architecture of Kafka.

Accepted Answer

**Section 1 — The Context (The 'Why')**
Kafka must handle millions of events per second while guaranteeing durability, ordering within partitions, and consumer group coordination. Failures include broker loss, consumer rebalance storms, and retention vs. storage cost trade-offs....

Question 2

How would you handle a schema change when new files arrive?

Accepted Answer

**Approach**: (1) Evolution—additive; new columns default; (2) Validation—quarantine unknowns; (3) Versioning—tag files; (4) mergeSchema=True for Parquet; (5) Migration—support old+new; update consumers. Schema registry for contracts; coordinate with producers....

Question 3

How would you design a cost-effective, scalable, and efficient data pipeline for an e-commerce website?

Accepted Answer

**Section 1 — The Context (The 'Why')**
The primary challenge in 'How would you design a cost-effective, scalable, and efficient data pipeline for an e-commerce website?' centers on designing for production scale, correctness guarantees, and operational resilience. A naive or underspecified design fails under load: single points of failure cascade, non-idempotent operations cause duplicates on retry, and lack of observability blocks root-cause analysis....

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