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Core
Batch vs Streaming
Batch processes a bounded dataset on a schedule; streaming processes an unbounded flow of events continuously. The real decision is about the data and the latency the business needs, not the tool, and it forces you to reason about event time vs processing time, windowing, and watermarks for late data. Applied-AI interviews probe it because most candidates jump to Kafka or Flink before they can say whether the problem even needs sub-minute latency, and micro-batch is often the pragmatic answer.
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RELATED CONCEPTS
PRACTICE THIS IN REAL QUESTIONS
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