easyMultiple ChoiceObjective-mapped
PDE Practice Question: A data engineer notices that Spark jobs on the…
Exhibit
Refer to the exhibit.
```
# gcloud dataproc clusters describe output
clusterName: my-cluster
config:
softwareConfig:
imageVersion: '2.0-debian10'
gceClusterConfig:
zoneUri: projects/my-project/zones/us-central1-a
internalIpOnly: false
masterConfig:
machineTypeUri: n1-standard-4
numInstances: 1
workerConfig:
machineTypeUri: n1-standard-4
numInstances: 10
preemptibility: ON
secondaryWorkerConfig:
numInstances: 0
status:
state: RUNNING
```A data engineer notices that Spark jobs on the Dataproc cluster shown often fail with executor lost errors. What is the most likely reason?
⚠ Common exam trap
The trap here is that candidates may overlook the 'all 10 workers are preemptible' detail and instead focus on common misconfigurations like single-zone risk or autoscaling, but the explicit mention of preemptible VMs is the key indicator of frequent, unpredictable executor loss.
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
✓
All 10 workers are preemptible and can be reclaimed by Compute Engine at any time.
Preemptible VMs in Google Compute Engine can be terminated at any time due to resource contention or other factors, with only 30 seconds notice. If all 10 worker nodes are preemptible, Spark executors running on them will be frequently lost, causing job failures. This is the most direct cause of 'executor lost' errors in a Dataproc cluster.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
All 10 workers are preemptible and can be reclaimed by Compute Engine at any time.
Why this is correct
Preemptible VMs can be terminated within 24 hours; Spark executors fail when workers are preempted.
- ✗
The master node has only 4 vCPUs, which may be insufficient for job coordination.
Why it's wrong here
Master node specs are adequate for coordination; executor loss is more likely from worker preemption.
- ✗
The cluster is in a single zone, so a zone failure could cause all workers to shut down.
Why it's wrong here
Zone failures are rare; preemption is more common.
- ✗
Autoscaling is enabled and scaling down is causing workers to be removed during job execution.
Why it's wrong here
The config shows no secondary workers and preemptibility is set; autoscaling is not evident.
Go deeper
Related to this question
About these practice questions
Courseiva writes every PDE question from scratch — 890 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.