DEA-C01 Data Operations and Support Practice Question
A company is running an Amazon EMR cluster with Spark for data processing. The data engineer wants to automatically scale the core and task nodes based on the YARN memory and CPU utilization. Which scaling metric should the engineer use for the EMR managed scaling policy?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
YARNMemoryAvailablePercentage
EMR managed scaling uses YARNMemoryAvailablePercentage and YARNContainersPending as the default metrics for scaling. Option B is incorrect because CPUUtilization is not a default metric for EMR managed scaling. Option C is incorrect because HDFSUtilization is for HDFS, not YARN. Option D is incorrect because IOPS is not a metric for EMR managed scaling.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
YARNMemoryAvailablePercentage
Why this is correct
EMR managed scaling uses YARN memory metrics.
- ✗
CPUUtilization
Why it's wrong here
CPUUtilization is not a default EMR scaling metric.
- ✗
DiskIOPS
Why it's wrong here
DiskIOPS is not used by EMR managed scaling.
- ✗
HDFSUtilization
Why it's wrong here
HDFSUtilization is for storage, not compute scaling.
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