- A
Consolidate all workloads into a single high-availability cluster
Why wrong: Mixing long-running services with transient jobs can lead to resource contention and higher costs. Separate clusters are better.
- B
Use local SSDs for all nodes to improve I/O performance
Why wrong: Local SSDs are ephemeral and not suitable for HDFS data. Standard persistent disks or SSD persistent disks are recommended.
- C
Use preemptible instances for worker nodes in the transient Spark cluster
Preemptible workers reduce costs significantly for fault-tolerant batch jobs. Spark can handle node preemption via checkpointing.
- D
Use Dataproc on GKE to run long-running services
Why wrong: Dataproc on GKE adds Kubernetes overhead and is not necessary for Hive/HBase; a standard Dataproc cluster works fine.
- E
Separate long-running services into a dedicated cluster with standard instances
Dedicated cluster ensures stability for services like Hive and HBase, while transient jobs can use cheaper preemptible workers elsewhere.
PDE Designing Data Processing Systems Practice Question
This PDE practice question tests your understanding of designing 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 team is migrating an on-premises Hadoop cluster to Dataproc. The cluster runs a mix of long-running services (Hive, HBase) and transient Spark jobs. They want to minimize cost while maintaining performance. Which TWO strategies should they implement?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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 in the transient Spark cluster
Preemptible workers are cost-effective for fault-tolerant Spark jobs. Separating long-running services into a separate cluster avoids interference and allows independent scaling. Using a single-node cluster for services is not practical. Dataproc on GKE adds complexity. Standard persistent disks are fine for HDFS.
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.
- ✗
Consolidate all workloads into a single high-availability cluster
Why it's wrong here
Mixing long-running services with transient jobs can lead to resource contention and higher costs. Separate clusters are better.
- ✗
Use local SSDs for all nodes to improve I/O performance
Why it's wrong here
Local SSDs are ephemeral and not suitable for HDFS data. Standard persistent disks or SSD persistent disks are recommended.
- ✓
Use preemptible instances for worker nodes in the transient Spark cluster
Why this is correct
Preemptible workers reduce costs significantly for fault-tolerant batch jobs. Spark can handle node preemption via checkpointing.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Dataproc on GKE to run long-running services
Why it's wrong here
Dataproc on GKE adds Kubernetes overhead and is not necessary for Hive/HBase; a standard Dataproc cluster works fine.
- ✓
Separate long-running services into a dedicated cluster with standard instances
Why this is correct
Dedicated cluster ensures stability for services like Hive and HBase, while transient jobs can use cheaper preemptible workers elsewhere.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 PDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Designing Data Processing Systems — study guide chapter
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FAQ
Questions learners often ask
What does this PDE question test?
Designing Data Processing Systems — This question tests Designing Data Processing Systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use preemptible instances for worker nodes in the transient Spark cluster — Preemptible workers are cost-effective for fault-tolerant Spark jobs. Separating long-running services into a separate cluster avoids interference and allows independent scaling. Using a single-node cluster for services is not practical. Dataproc on GKE adds complexity. Standard persistent disks are fine for HDFS.
What should I do if I get this PDE question wrong?
Identify which PDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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