- A
Change the worker machine type to a higher CPU/memory configuration
More CPU/memory per worker can speed up processing if the transform is compute-intensive.
- B
Decrease the window duration to reduce data per window
Why wrong: Decreasing window size may increase overhead and not necessarily improve overall latency.
- C
Enable Dataflow Streaming Engine
Streaming Engine offloads state management to backend services, improving throughput.
- D
Increase the number of workers in the pipeline
More workers increase parallelism, reducing backlog.
- E
Add additional Pub/Sub subscriptions to the same topic
Why wrong: Multiple subscriptions would not increase the throughput to a single pipeline; the pipeline reads from one subscription.
Question 625 of 1,000
PDE Designing Data Processing Systems Practice Question
This PDE practice question tests your understanding of designing data processing systems. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Your company runs a Dataflow streaming pipeline that processes user activity from Pub/Sub and writes aggregated results to BigQuery. Lately, the pipeline is experiencing high latency and backlog growth during peak hours. You need to troubleshoot and improve performance. Which THREE actions should you take? (Choose 3.)
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
✓
Change the worker machine type to a higher CPU/memory configuration
Increasing the number of workers allows the pipeline to process more data in parallel. Using streaming engine can improve throughput and reduce latency by offloading state management. Adjusting the worker machine type to use more CPU/memory can help if the processing is compute-intensive. Adding more subscriptions would not help because the pipeline reads from a single subscription. Changing the window size affects business logic but not necessarily performance. Combining these three optimizations addresses common bottlenecks.
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.
- ✓
Change the worker machine type to a higher CPU/memory configuration
Why this is correct
More CPU/memory per worker can speed up processing if the transform is compute-intensive.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the window duration to reduce data per window
Why it's wrong here
Decreasing window size may increase overhead and not necessarily improve overall latency.
- ✓
Enable Dataflow Streaming Engine
Why this is correct
Streaming Engine offloads state management to backend services, improving throughput.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Increase the number of workers in the pipeline
Why this is correct
More workers increase parallelism, reducing backlog.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Add additional Pub/Sub subscriptions to the same topic
Why it's wrong here
Multiple subscriptions would not increase the throughput to a single pipeline; the pipeline reads from one subscription.
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
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 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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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: Change the worker machine type to a higher CPU/memory configuration — Increasing the number of workers allows the pipeline to process more data in parallel. Using streaming engine can improve throughput and reduce latency by offloading state management. Adjusting the worker machine type to use more CPU/memory can help if the processing is compute-intensive. Adding more subscriptions would not help because the pipeline reads from a single subscription. Changing the window size affects business logic but not necessarily performance. Combining these three optimizations addresses common bottlenecks.
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.
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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