Question 1

Explain how Spark handles fault tolerance. How does it recover from node failures?

Accepted Answer

**Section 1 — The Context (The 'Why')**
This system design addresses "Explain how Spark handles fault tolerance. How does it recover from node failure..." at production scale. The primary challenges are throughput under variable load, fault tolerance across distributed components, and maintaining consistency guarantees that match business requirements....

Question 2

How do you ensure data quality in a big data pipeline, and what strategies do you use for data validation?

Accepted Answer

**Section 1 — The Context (The 'Why')**
This system design addresses "How do you ensure data quality in a big data pipeline, and what strategies do yo..." at production scale. The primary challenges are throughput under variable load, fault tolerance across distributed components, and maintaining consistency guarantees that match business requirements....

Question 3

How does Spark handle distributed computing, and what challenges have you faced while working on distributed systems?

Accepted Answer

**Section 1 — The Context (The 'Why')**
The primary challenge in 'How does Spark handle distributed computing, and what challenges have you faced while working on distributed systems?' 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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Coforge System Design Interview Questions

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