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Home/Questions/Spark/Big Data/What is YARN, and how does it manage resources in a Hadoop ecosystem?

What is YARN, and how does it manage resources in a Hadoop ecosystem?

Spark/Big Dataeasy0.3 min readPremium

**YARN**: Yet Another Resource Negotiator. Cluster resource manager. Allocates containers (CPU, memory) to applications (MapReduce, Spark, Hive). **Components**: ResourceManager (scheduler, allocates), NodeManager (per-node, runs containers), ApplicationMaster (per-app,...

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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
Infosys
Key Concepts Tested
spark

Why This Question Matters

This easy-level Spark/Big Data question appears frequently in data engineering interviews at companies like Infosys. 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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Expert Answer
69 words

YARN: Yet Another Resource Negotiator. Cluster resource manager. Allocates containers (CPU, memory) to applications (MapReduce, Spark, Hive).

Components: ResourceManager (scheduler, allocates), NodeManager (per-node, runs containers), ApplicationMaster (per-app, negotiates resources).

Why It Matters: Multi-tenancy; multiple frameworks share cluster. Fair/Capacity schedulers for fairness.

Scalability Trade-offs: Single ResourceManager (or HA pair); scale NodeManagers. Tune container size for Spark (yarn.nodemanager.resource.memory-mb).

Cost Implications: Shared cluster = higher utilization than dedicated. Tune to avoid under/over-allocation.

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According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data 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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