The answer is that all 10 workers being preemptible VMs is the most likely reason for the executor lost errors. Preemptible VMs in Compute Engine can be terminated by Google with only 30 seconds notice due to resource contention, and when every worker node is preemptible, Spark executors running on them are constantly reclaimed, leading to frequent job failures. On the Google Professional Data Engineer exam, this scenario tests your understanding of how preemptible instances behave in Dataproc clusters and the critical distinction between master and worker node types. A common trap is assuming the error stems from code or configuration issues, but the direct cause is the inherent instability of an all-preemptible worker pool. Remember the memory tip: "If all workers are preemptible, your executors are always interruptible."
PDE Practice Question: Building and operationalizing data processing systems
This PDE practice question tests your understanding of building and operationalizing data processing systems. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data engineer notices that Spark jobs on the Dataproc cluster shown often fail with executor lost errors. What is the most likely reason?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
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.
Trap categories for this question
Command / output trap
The config shows no secondary workers and preemptibility is set; autoscaling is not evident.
Detailed technical explanation
How to think about this question
Preemptible VMs have a maximum lifetime of 24 hours and can be terminated earlier if Google needs the capacity. Spark's executor heartbeat mechanism detects lost executors after a timeout (default 60 seconds), leading to task recomputation and job delays. In a cluster with all preemptible workers, the probability of losing at least one executor during a long job is very high, causing repeated failures.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Building and operationalizing data processing systems — This question tests Building and operationalizing data processing systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this PDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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