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What is YARN?

Spark/Big Dataeasy0.4 min read

**YARN**: Hadoop's resource management layer. Replaced MapReduce 1's fixed slots. Allocates CPU and memory across cluster. Enables MapReduce, Spark, Hive, etc. on same infrastructure. **Key Idea**: Decouples resource management from processing. ResourceManager + NodeManagers +...

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Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Altimetrik
Key Concepts Tested
spark

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This easy-level Spark/Big Data question appears frequently in data engineering interviews at companies like Altimetrik. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (spark) will help you answer variations of this question confidently.

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Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
71 words

YARN: Hadoop's resource management layer. Replaced MapReduce 1's fixed slots. Allocates CPU and memory across cluster. Enables MapReduce, Spark, Hive, etc. on same infrastructure.

Key Idea: Decouples resource management from processing. ResourceManager + NodeManagers + ApplicationMaster per job.

Why It Exists: MapReduce 1 scaled poorly; one JobTracker. YARN scales to 10K+ nodes.

Scalability Trade-offs: HA for ResourceManager; odd-number NodeManagers for resilience.

Cost Implications: Shared cluster efficiency; one platform for many workloads.

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