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Answer: The maximum number of workers
The correct answer is D. By increasing the maximum number of workers, you ensure that Cloud Dataflow can scale its compute power to handle the increased data processing load efficiently. This enables Cloud Dataflow to add up to the specified number of workers as needed, ensuring optimal performance and scalability. This approach aligns with the autoscaling capability of Cloud Dataflow, which helps manage varying workloads dynamically.
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MJTelco has completed the setup of their Google Cloud Dataflow pipeline for processing data from 50,000 installations. To ensure that Cloud Dataflow can automatically adjust its compute resources to handle varying loads, which specific configuration setting in the Cloud Dataflow pipeline needs to be updated?
A
The zone
B
The number of workers
C
The disk size per worker
D
The maximum number of workers
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