Answer: continuous and unbounded

## Explanation In stream processing, datasets are **continuous and unbounded**. ### Key Concepts: - **Continuous**: Data arrives continuously in real-time, without predefined start or end points - **Unbounded**: There is no fixed size or limit to the data stream - it can theoretically continue indefinitely ### Why Other Options Are Incorrect: - **A. continuous and bounded**: While stream data is continuous, it's not bounded (limited in size) - **C. micro-batch and unbounded**: Micro-batch processing is a specific implementation approach, not a characteristic of the dataset itself - **D. micro-batch and bounded**: This describes batch processing characteristics, not stream processing ### Stream Processing Characteristics: - Real-time data ingestion - No predefined dataset boundaries - Processing occurs as data arrives - Suitable for scenarios requiring immediate insights and actions This distinguishes stream processing from batch processing, where datasets are discrete and bounded.

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