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Handling node failures

General/Othermedium0.2 min readPremium

**Strategies**: (1) Replication—data on multiple nodes; (2) Health checks—heartbeats, liveness; (3) Failover—auto promotion (Kafka ISR, Spark); (4) Idempotency—reprocessing = same result; (5) Checkpointing—resume from last. **Spark**: Driver failover; executor retry. Kafka:...

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Frequency
Low
Asked at 1 company
Category
243
questions in General/Other
Difficulty Split
151E|43M|49H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
media.net
Key Concepts Tested
partitionspark

Why This Question Matters

This medium-level General/Other question appears frequently in data engineering interviews at companies like media.net. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (partition, spark) will help you answer variations of this question confidently.

How to Approach This

Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.

Expert Answer
41 words

Strategies: (1) Replication—data on multiple nodes; (2) Health checks—heartbeats, liveness; (3) Failover—auto promotion (Kafka ISR, Spark); (4) Idempotency—reprocessing = same result; (5) Checkpointing—resume from last.

Spark: Driver failover; executor retry. Kafka: partition replication. Design for failure; chaos test; monitor failure rates.

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According to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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