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Answer: Implement a partition strategy based on the data source, allowing for efficient data ingestion and processing from multiple sources.
Option B is the correct answer because implementing a partition strategy based on the data source allows for efficient data ingestion and processing from multiple sources. This approach enables better organization of the data and can improve query performance by reducing the amount of data scanned. Option A is incorrect because using a single partition for all streaming data can lead to performance bottlenecks as the volume of data grows. Option C is incorrect because partitioning based on data size alone may not be sufficient for optimizing performance in streaming workloads. Option D is incorrect because implementing a partition strategy is essential for handling streaming workloads effectively.
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You are working on a real-time data processing system using Azure Data Lake Storage Gen2 and need to implement a partition strategy for streaming workloads. What considerations should you take into account when designing the partitioning scheme, and how would this impact the system's performance?
A
Use a single partition for all streaming data to simplify the system architecture.
B
Implement a partition strategy based on the data source, allowing for efficient data ingestion and processing from multiple sources.
C
Partition the data based on the data's size, which will have no impact on the system's performance.
D
Do not implement any partition strategy, as it is not necessary for streaming workloads.
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