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Design a data pipeline for streaming analytics.

System Design/Architecturehard3 min readPremium
Frequency
Low
Asked at 1 company
Category
179
questions in System Design/Architecture
Difficulty Split
15E|6M|158H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Uber
Key Concepts Tested
joinoptimizationpartitionsparkwindow
Expert AnswerPremium
601 wordsIncludes code examplesInterview-ready
**Section 1 — The Context (The 'Why')** Streaming analytics pipelines face the fundamental tension between low-latency ingestion and consistent aggregation at scale. The primary challenge is maintaining exactly-once or at-least-once semantics while supporting late-arriving events, handling backpressure when downstream processors cannot keep pace, and avoiding data skew when hot partitions (e.g., popular products) overwhelm single workers....
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 Uber. The answer also includes follow-up discussion points that interviewers commonly explore.

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