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Home/Questions/Cloud/Tools/Explain steps to optimize data read performance from cloud storage (S3 or Azure Blob).

Explain steps to optimize data read performance from cloud storage (S3 or Azure Blob).

Cloud/Toolshard0.3 min readPremium
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
Fragma Data Systems
Key Concepts Tested
optimizationpartitionspark
Expert AnswerPremium
56 wordsInterview-ready
Architectural optimizations: (1) Partitioning—query only needed partitions. (2) Columnar (Parquet/ORC)—read only columns. (3) File size 128–512MB—avoid small files; compact. (4) Parallelism—partitions, parallelism in Spark/Glue. (5) S3 Select/Blob query—push predicates. (6) Caching—Spark cache, Athena result cache. Trade-off: Over-partitioning = many small files. Cost: Fewer bytes scanned = lower Athena/Glue cost....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Fragma Data Systems. The answer also includes follow-up discussion points that interviewers commonly explore.

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