- A
Session windows with a 10-minute gap and allowed lateness of 2 minutes.
Why wrong: Session windows with a 10-minute gap would merge sessions separated by up to 10 minutes, producing one window per session rather than regular 5-minute aggregates. Additionally, the allowed lateness of 2 minutes cannot compensate for the mismatch in aggregation frequency.
- B
Fixed windows of 5 minutes with allowed lateness of 2 minutes.
Fixed windows of 5 minutes directly match the required aggregation interval. Allowed lateness of 2 minutes accommodates events arriving up to 2 minutes late, ensuring they are included in the correct window.
- C
Sliding windows of 5 minutes with a 1-minute period and allowed lateness of 2 minutes.
Why wrong: Sliding windows of 5 minutes with a 1-minute period would produce overlapping windows and emit results every minute, which is not the required every-5-minutes aggregation.
- D
Dataflow pipeline with exactly-once processing mode.
Configuring exactly-once processing mode in Dataflow is essential to meet the requirement of exactly-once processing semantics. It ensures that each event is processed only once, even in the case of failures or retries.
- E
Pub/Sub subscription with exactly-once delivery.
Why wrong: While Pub/Sub exactly-once delivery can reduce duplicates at the source, it is not a Dataflow pipeline configuration. The pipeline itself must still be set to exactly-once processing mode (option D) to guarantee end-to-end exactly-once semantics.
PDE Fixed windows Practice Question
This PDE practice question tests your understanding of designing data processing systems. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. A key principle to apply: fixed windows. 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 engineering team is designing a streaming pipeline using Dataflow to process real-time clickstream data from a website. They need to aggregate user session metrics (e.g., number of sessions, average duration) every 5 minutes. The pipeline must handle late-arriving events (up to 2 minutes late) and ensure exactly-once processing semantics. Which TWO of the following should they configure? (Choose two.)
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
Fixed windows of 5 minutes with allowed lateness of 2 minutes.
The correct answers are B and D. For aggregating session metrics every 5 minutes, Fixed windows of 5 minutes with allowed lateness of 2 minutes (option B) align with the desired interval and handle late data. To guarantee exactly-once processing semantics, the Dataflow pipeline must be configured with exactly-once processing mode (option D). Option E (Pub/Sub exactly-once delivery) is a source-level feature that can help prevent duplicates, but the question asks which two configurations to set for the pipeline itself. Option A (Session windows with a 10-minute gap) would merge sessions up to 10 minutes apart, not producing fixed 5-minute aggregates. Option C (Sliding windows with 5-minute size and 1-minute period) would emit results every minute, which is not required.
Key principle: Fixed windows
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Session windows with a 10-minute gap and allowed lateness of 2 minutes.
Why it's wrong here
Session windows with a 10-minute gap would merge sessions separated by up to 10 minutes, producing one window per session rather than regular 5-minute aggregates. Additionally, the allowed lateness of 2 minutes cannot compensate for the mismatch in aggregation frequency.
- ✓
Fixed windows of 5 minutes with allowed lateness of 2 minutes.
Why this is correct
Fixed windows of 5 minutes directly match the required aggregation interval. Allowed lateness of 2 minutes accommodates events arriving up to 2 minutes late, ensuring they are included in the correct window.
Related concept
Fixed windows
- ✗
Sliding windows of 5 minutes with a 1-minute period and allowed lateness of 2 minutes.
Why it's wrong here
Sliding windows of 5 minutes with a 1-minute period would produce overlapping windows and emit results every minute, which is not the required every-5-minutes aggregation.
- ✓
Dataflow pipeline with exactly-once processing mode.
Why this is correct
Configuring exactly-once processing mode in Dataflow is essential to meet the requirement of exactly-once processing semantics. It ensures that each event is processed only once, even in the case of failures or retries.
Related concept
Fixed windows
- ✗
Pub/Sub subscription with exactly-once delivery.
Why it's wrong here
While Pub/Sub exactly-once delivery can reduce duplicates at the source, it is not a Dataflow pipeline configuration. The pipeline itself must still be set to exactly-once processing mode (option D) to guarantee end-to-end exactly-once semantics.
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
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Fixed windows
- Exactly-once processing
- Allowed lateness
- Pub/Sub exactly-once delivery
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
Fixed windows
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Fixed windows Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review fixed windows, then practise related PDE questions on the same topic to reinforce the concept.
- →
Designing Data Processing Systems — study guide chapter
Learn the concepts, then practise the questions
- →
Designing Data Processing Systems practice questions
Targeted practice on this topic area only
- →
All PDE questions
1,000 questions across all exam domains
- →
Google Professional Data Engineer study guide
Full concept coverage aligned to exam objectives
- →
PDE practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related PDE practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Designing Data Processing Systems practice questions
Practise PDE questions linked to Designing Data Processing Systems.
Ingesting and Processing the Data practice questions
Practise PDE questions linked to Ingesting and Processing the Data.
Storing the Data practice questions
Practise PDE questions linked to Storing the Data.
Preparing and Using Data for Analysis practice questions
Practise PDE questions linked to Preparing and Using Data for Analysis.
Maintaining and Automating Data Workloads practice questions
Practise PDE questions linked to Maintaining and Automating Data Workloads.
Building and operationalizing data processing systems practice questions
Practise PDE questions linked to Building and operationalizing data processing systems.
Operationalizing machine learning models practice questions
Practise PDE questions linked to Operationalizing machine learning models.
Ensuring solution quality practice questions
Practise PDE questions linked to Ensuring solution quality.
PDE fundamentals practice questions
Practise PDE questions linked to PDE fundamentals.
PDE scenario practice questions
Practise PDE questions linked to PDE scenario.
PDE troubleshooting practice questions
Practise PDE questions linked to PDE troubleshooting.
Practice this exam
Start a free PDE practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this PDE question test?
Designing Data Processing Systems — This question tests Designing Data Processing Systems — Fixed windows.
What is the correct answer to this question?
The correct answer is: Fixed windows of 5 minutes with allowed lateness of 2 minutes. — The correct answers are B and D. For aggregating session metrics every 5 minutes, Fixed windows of 5 minutes with allowed lateness of 2 minutes (option B) align with the desired interval and handle late data. To guarantee exactly-once processing semantics, the Dataflow pipeline must be configured with exactly-once processing mode (option D). Option E (Pub/Sub exactly-once delivery) is a source-level feature that can help prevent duplicates, but the question asks which two configurations to set for the pipeline itself. Option A (Session windows with a 10-minute gap) would merge sessions up to 10 minutes apart, not producing fixed 5-minute aggregates. Option C (Sliding windows with 5-minute size and 1-minute period) would emit results every minute, which is not required.
What should I do if I get this PDE question wrong?
Review fixed windows, then practise related PDE questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Fixed windows
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 →
Keep practising
More PDE practice questions
- A company wants to process large CSV files stored in Cloud Storage and load them into BigQuery. The files are generated…
- A company runs a Dataflow streaming pipeline that reads from Cloud Pub/Sub and writes to BigQuery. The pipeline uses a s…
- A company uses Cloud Dataproc for ephemeral clusters to run batch jobs. They want to ensure job reliability and data qua…
- Your company uses Vertex AI Pipelines to automate model retraining. The pipeline has three steps: data extraction from B…
- A company wants to use BigQuery to query data stored in Parquet files in Cloud Storage without loading the data into Big…
- A company has deployed a machine learning model to AI Platform Prediction. The model uses a custom container with a Tens…
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.