PDE Designing Data Processing Systems Practice Question
A company is migrating their on-premises Hadoop workloads to Google Cloud. They want to use Dataproc for data processing and need to minimize costs for non-critical batch jobs that can tolerate interruptions. Which TWO configurations should they use?
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
✓
Use preemptible instances for worker nodes
Preemptible instances are cheaper and can be preempted, suitable for fault-tolerant batch jobs. Single-node clusters are cost-effective for small jobs.
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 instances for worker nodes
Why this is correct
Preemptible VMs are cheaper and suitable for fault-tolerant batch jobs.
- ✗
Enable high-availability mode
Why it's wrong here
HA mode adds cost for multiple masters.
- ✗
Use standard (non-preemptible) instances for all nodes
Why it's wrong here
Standard instances are more expensive, not cost-minimizing.
- ✓
Use single-node clusters for small jobs
Why this is correct
Single-node clusters are cost-effective for small, non-critical jobs.
- ✗
Use Dataproc on GKE
Why it's wrong here
While could be cost-effective, the question asks for TWO best configurations; preemptible + single-node are more direct.
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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.