This PDE practice question tests your understanding of ensuring solution quality. 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 company runs a batch processing job on Dataproc that uses Apache Spark to process 500 GB of data daily. The job completes successfully but takes 4 hours. The team wants to reduce the runtime to under 2 hours without increasing cost. What should they do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use preemptible VMs for worker nodes and increase the number of workers.
Preemptible VMs cost significantly less than standard VMs (about 60-80% discount). By using preemptible VMs for worker nodes, you can increase the number of workers (and thus parallelism) without increasing cost. This directly reduces runtime by distributing the 500 GB workload across more executors, while the cost savings from preemptible VMs offset the additional nodes.
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.
✓
Use preemptible VMs for worker nodes and increase the number of workers.
Why this is correct
Preemptible VMs are cheaper, allowing more workers for the same cost, reducing runtime.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the master node's machine type to n2-standard-8.
Why it's wrong here
Master node size has minimal impact on processing speed.
✗
Increase the machine type of worker nodes to n2-highmem-8.
Why it's wrong here
Higher CPU machines cost more, potentially increasing cost.
✗
Migrate the job to Dataflow with autoscaling enabled.
Why it's wrong here
Migration may require code changes and Dataflow costs may not be lower.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the trade-off between cost and performance by making candidates think that upgrading machine types (more CPU/memory) is the only way to speed up a job, ignoring that preemptible VMs allow scaling out (more nodes) without increasing cost.
Detailed technical explanation
How to think about this question
Preemptible VMs in Dataproc are Compute Engine instances that can be terminated at any time (up to 24 hours). Spark jobs on Dataproc handle preemption gracefully via checkpointing and speculative execution, but you must ensure the job is resilient to node loss (e.g., use HDFS or Cloud Storage for intermediate data). Increasing the number of workers reduces runtime linearly up to the point of diminishing returns due to task scheduling overhead and data shuffle bottlenecks.
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
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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.
Ensuring solution quality — This question tests Ensuring solution quality — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use preemptible VMs for worker nodes and increase the number of workers. — Preemptible VMs cost significantly less than standard VMs (about 60-80% discount). By using preemptible VMs for worker nodes, you can increase the number of workers (and thus parallelism) without increasing cost. This directly reduces runtime by distributing the 500 GB workload across more executors, while the cost savings from preemptible VMs offset the additional nodes.
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.
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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