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Answer: CDF can optimize data processing by tracking changes and applying them efficiently, reducing the overhead of frequent updates and deletions.
CDF can optimize data processing workflows by tracking and efficiently handling frequent updates and deletions. This involves enabling CDF on the Delta Lake tables and modifying the data processing jobs to leverage the change data for efficient handling of updates and deletions. This approach reduces the overhead associated with frequent changes and ensures efficient data processing.
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Explain how CDF can be used to optimize data processing workflows in a scenario where frequent updates and deletions occur. Describe the steps you would take to leverage CDF for efficient handling of these operations, including any necessary code modifications to implement this optimization.
A
CDF is not suitable for handling frequent updates and deletions; manual tracking is required.
B
CDF can optimize data processing by tracking changes and applying them efficiently, reducing the overhead of frequent updates and deletions.
C
Frequent updates and deletions require a complete reprocessing of the dataset, regardless of CDF.
D
CDF only handles insert operations; updates and deletions must be managed separately.