DEA-C01 Data Operations and Support Practice Question
A company uses Amazon EMR to run Spark jobs on a transient cluster. The jobs are submitted via a step in the cluster. The cluster is configured to auto-terminate after the last step completes. However, the cluster is not terminating even though the step shows as 'COMPLETED'. What could be the cause?
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
✓
The step's 'ActionOnFailure' parameter is set to 'CONTINUE' and 'KeepClusterAliveOnFailure' is true.
In Amazon EMR, the step-level parameter `KeepClusterAliveOnFailure` (or `KeepJobFlowAliveWhenNoSteps` for the cluster) can prevent auto-termination. When `ActionOnFailure` is set to `CONTINUE` and `KeepClusterAliveOnFailure` is `true`, the cluster remains running even after the last step completes, overriding the transient cluster's auto-terminate setting. Option A is incorrect because root device size does not affect termination. Option B is incorrect because the step status 'COMPLETED' indicates success, not a bug. Option C is incorrect because the cluster is explicitly configured as transient and auto-terminating, not long-running.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The cluster's root device size is too large.
Why it's wrong here
Root device size does not affect termination.
- ✗
The step failed with an error, but the status shows 'COMPLETED' due to a reporting bug.
Why it's wrong here
Status is reliable.
- ✗
The cluster is configured as a long-running cluster.
Why it's wrong here
It is described as transient.
- ✓
The step's 'ActionOnFailure' parameter is set to 'CONTINUE' and 'KeepClusterAliveOnFailure' is true.
Why this is correct
These settings prevent auto-termination.
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