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Answer: Use Committed Use Discounts for the BI Tool VMs and manage Cloud Dataproc clusters dynamically, creating them for data loading and deleting when idle.
This approach minimizes costs by leveraging Committed Use Discounts for the continuously running BI Tool VMs and reducing Cloud Dataproc expenses by dynamically managing clusters based on actual usage.
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To optimize costs for a data processing pipeline using Cloud Dataproc and BigQuery, with a BI tool on Compute Engine VMs running continuously, what is the best strategy?
A
Apply Committed Use Discounts to both the BI Tool VMs and the Cloud Dataproc nodes.
B
Use Committed Use Discounts for the BI Tool VMs and manage Cloud Dataproc clusters dynamically, creating them for data loading and deleting when idle.
C
Apply Committed Use Discounts to the BI Tool VMs only.
D
Apply Committed Use Discounts to both the BI Tool VMs and the Cloud Dataproc nodes, and manage Cloud Dataproc clusters dynamically.
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