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Answer: Use Azure Data Factory to copy and aggregate small files into larger ones.
Using Azure Data Factory to copy and aggregate small files into larger ones is a strategic approach to optimizing the storage and processing of small files in Azure Data Lake Storage. This method involves creating pipelines that efficiently merge small files into larger, more manageable files, which reduces the overhead associated with file management and improves the performance of subsequent data processing tasks. This approach leverages the scalability and automation capabilities of Azure Data Factory to handle large volumes of small files effectively.
Author: LeetQuiz Editorial Team
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In the context of Azure Data Lake Storage, describe how you would manage and optimize the storage of small files to enhance the performance of data processing jobs. Provide specific techniques or tools that can be used to aggregate or manage these small files effectively.
A
Leave the small files as they are without any optimization.
B
Use Azure Data Factory to copy and aggregate small files into larger ones.
C
Manually compress and archive small files periodically.
D
Delete small files to free up storage space.
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