The answer is a misconfigured watermark. In Cloud Dataflow, the watermark is the mechanism that governs event-time progress and determines when windows are closed and results are emitted; if it is set too aggressively or based on incorrect timestamps, late-arriving data—which is common when the source uses at-least-once delivery—can be processed in multiple window firings, causing duplicate rows even with idempotent writes to BigQuery. On the Google Professional Data Engineer exam, this question tests your understanding of how Dataflow’s exactly-once semantics depend on correct watermark configuration, not just on sink idempotency. A common trap is to blame autoscaling or window type, but the core issue is that a faulty watermark fails to account for late data, leading to re-processing. Memory tip: think of the watermark as a gate—if it closes too early, late data sneaks in twice.
PDE Designing data processing systems 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. 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 uses Cloud Dataflow to process financial transactions from Pub/Sub to BigQuery. The pipeline must ensure exactly-once semantics. Recently, they noticed duplicate rows in BigQuery. The source publishes with at-least-once. The Dataflow pipeline uses idempotent writes. What is the most likely cause? Options: A. The pipeline uses GlobalWindows. B. The pipeline has autoscaling enabled. C. The pipeline uses file loads as a sink. D. The pipeline's watermark is misconfigured.
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Clue: "least"
Why it matters: You want the option with minimum overhead, fewest steps, or lowest impact — not the most feature-rich or comprehensive answer.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The pipeline's watermark is misconfigured
The most likely cause is a misconfigured watermark. In Dataflow, the watermark tracks event time progress and determines when to trigger window results. If the watermark is misconfigured (e.g., too aggressive or based on incorrect timestamps), late-arriving data may be processed in multiple windows, leading to duplicate rows even with idempotent writes. Since the source uses at-least-once delivery, late data can be re-published, and a faulty watermark can cause it to be written again.
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.
✗
The pipeline uses file loads as a sink
Why it's wrong here
File loads are batch; if idempotent, they should not duplicate.
✓
The pipeline's watermark is misconfigured
Why this is correct
A misconfigured watermark can cause late data to be processed again, producing duplicates.
Clue confirmation
The clue words "most likely", "least" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The pipeline uses GlobalWindows
Why it's wrong here
GlobalWindows accumulate data, they do not cause duplicates.
✗
The pipeline has autoscaling enabled
Why it's wrong here
Autoscaling does not cause duplicates; it adjusts workers.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume idempotent writes alone guarantee exactly-once, but they overlook that watermark misconfiguration can cause the same event to be processed in multiple windows, leading to duplicates despite idempotent sinks.
Detailed technical explanation
How to think about this question
Watermarks in Dataflow are derived from the source's timestamp and the pipeline's allowed lateness. If the watermark advances too quickly (e.g., due to a misconfigured timestamp policy), late-arriving data may be considered 'dropped' and then re-processed in a new window when it arrives again from Pub/Sub's at-least-once delivery. This can cause duplicate writes even with idempotent BigQuery inserts because the same event may be written in two different window panes. In practice, setting allowed lateness too low or using a watermark that doesn't account for Pub/Sub's potential re-delivery is a common source of duplicates.
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 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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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: The pipeline's watermark is misconfigured — The most likely cause is a misconfigured watermark. In Dataflow, the watermark tracks event time progress and determines when to trigger window results. If the watermark is misconfigured (e.g., too aggressive or based on incorrect timestamps), late-arriving data may be processed in multiple windows, leading to duplicate rows even with idempotent writes. Since the source uses at-least-once delivery, late data can be re-published, and a faulty watermark can cause it to be written again.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely", "least". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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