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Home/Questions/Cloud/Tools/Why specific cloud services (AWS Glue, EMR) were chosen for scalability and cost-effectiveness

Why specific cloud services (AWS Glue, EMR) were chosen for scalability and cost-effectiveness

Cloud/Toolseasy0.4 min readPremium

**Glue**: Serverless Spark; no cluster management; Data Catalog integration; job bookmarks. Suits standard batch ETL, moderate Spark. Cost-effective for variable/infrequent jobs. 15-min DPU minimum—inefficient for very short jobs. **EMR**: Full Spark control; custom configs;...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
179
questions in Cloud/Tools
Difficulty Split
104E|27M|48H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
PayPal
Key Concepts Tested
etlspark

Why This Question Matters

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

How to Approach This

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
73 words

Glue: Serverless Spark; no cluster management; Data Catalog integration; job bookmarks. Suits standard batch ETL, moderate Spark. Cost-effective for variable/infrequent jobs. 15-min DPU minimum—inefficient for very short jobs. EMR: Full Spark control; custom configs; MLlib, graph. Use when Glue doesn't fit—long-running, custom libs. Scalability: Both auto-scale; Glue per-job; EMR per-cluster. Cost: Glue for sporadic; EMR for steady or custom. Decision: Glue for most pipelines; EMR for ML, graph, or when 15-min minimum hurts.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked Cloud/Tools 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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