Databricks Certified Data Engineer - Professional
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Ultimate access to all questions.
As a Databricks Certified Data Engineer, you are tasked with optimizing a Databricks cluster for memory-intensive workloads in a cost-sensitive environment. The workload involves processing large datasets that require significant memory resources but do not benefit significantly from additional CPU cores. Given these constraints, which of the following configurations would you choose to best meet the workload's requirements while also considering cost efficiency? (Choose one option)
A
Select a node type with a higher number of CPU cores and enable autoscaling to dynamically adjust resources, ensuring both memory and CPU are optimized for varying workloads.
B
Choose a node type with a larger amount of memory per node, as this directly addresses the memory requirements of the workload without unnecessarily increasing costs with additional CPU cores.
C
Configure the cluster to use a custom disk type with higher I/O performance, under the assumption that disk speed will compensate for memory limitations.
D
Implement a combination of node types, using some with high memory for memory-intensive tasks and others with high CPU for processing tasks, to balance cost and performance.