Answer-first summary for fast verification
Answer: CPU utilization is sustained at approximately 75%.
**CPU utilization** is the most direct indicator of compute efficiency in a Spark cluster. Maintaining a sustained utilization around **70–80%** (such as 75%) suggests that the executors are actively processing tasks without being idle, while still leaving enough headroom to handle transient spikes in demand without causing significant queuing or resource contention. ### Why other options are incorrect: * **Five-minute load average:** A steady load average simply tracks the number of processes in the queue; it does not indicate if the CPU cores are actually performing useful work or if they are balanced across the cluster. * **Network I/O:** Low network I/O might suggest the job is not bottlenecked by data movement, but it could also indicate that the cluster is under-utilized or not processing much data, which isn't a sign of resource efficiency. * **Disk space usage:** Disk usage is a storage metric and does not reflect the real-time processing efficiency of the CPU or Memory during execution.
Author: LeetQuiz Editorial Team
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When monitoring a Databricks cluster with 3 executor nodes using Ganglia, which of the following observations indicates that the cluster's virtual machine (VM) resources are being utilized efficiently?
A
CPU utilization is sustained at approximately 75%.
B
The five-minute load average remains perfectly steady and does not fluctuate.
C
Network I/O remains consistently low without any sudden increases.
D
Total disk space usage on the nodes remains unchanged throughout the job execution.
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