- A
Enable message ordering in Pub/Sub with a session ID as the ordering key, and in Dataflow use a global window with a custom trigger that fires on watermark and uses a BigQuery sink with 'exactly-once' mode enabled.
D is correct because Pub/Sub ordering keys maintain order per session, and Dataflow's exactly-once sink to BigQuery prevents duplicates when combined with deterministic triggers.
- B
Use a Pub/Sub pull subscription with a subscriber that acknowledges messages immediately after processing, and a Dataflow pipeline with a sliding window.
Why wrong: A is wrong because strict ordering per session is not maintained with pull subscriptions without ordering keys.
- C
Assign a unique session ID as the message ordering key in Pub/Sub, use a Dataflow pipeline with session windows and .withAllowedLateness(0), and write to BigQuery using a batch load.
Why wrong: C is wrong because session windows in Dataflow may still produce late data, and batch loads are not real-time.
- D
Use a Pub/Sub push subscription with an acknowledgment deadline of 600 seconds and enable exactly-once delivery on the subscription.
Why wrong: B is wrong because Pub/Sub exactly-once delivery only applies to the subscription side, but Dataflow sink to BigQuery may still produce duplicates.
Quick Answer
The answer is to enable message ordering in Pub/Sub with a session ID as the ordering key, and in Dataflow use a global window with a watermark-based trigger and a BigQuery sink in exactly-once mode. This configuration is correct because Pub/Sub’s ordering key ensures events for the same session are delivered sequentially, while Dataflow’s global window with a watermark trigger guarantees all events for that session are processed before the window fires, preventing partial writes. The BigQuery exactly-once sink then eliminates duplicate rows even if the pipeline retries, satisfying both strict per-session ordering and exactly-once semantics. On the Google Professional Data Engineer exam, this scenario tests your understanding of how Pub/Sub ordering keys interact with Dataflow’s streaming engine and sink modes—a common trap is assuming Dataflow’s default at-least-once mode suffices, which would allow duplicates. Remember the mnemonic: “Order key in, watermark fire, exactly-once sink to retire.”
PDE Practice Question: Building and operationalizing data processing systems
This PDE practice question tests your understanding of building and operationalizing 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 data engineering team uses Cloud Pub/Sub to ingest clickstream events and Cloud Dataflow to process them. They need to maintain strict event ordering per user session, and the processing output must be written to a BigQuery table with exactly-once semantics. Which configuration should the team implement?
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
Enable message ordering in Pub/Sub with a session ID as the ordering key, and in Dataflow use a global window with a custom trigger that fires on watermark and uses a BigQuery sink with 'exactly-once' mode enabled.
Option A is correct because it combines Pub/Sub message ordering (using a session ID as the ordering key) with Dataflow's exactly-once sink to BigQuery. The global window with a watermark-based trigger ensures all events for a session are processed in order before writing, while the BigQuery 'exactly-once' mode prevents duplicate rows even if the pipeline retries. This satisfies both strict per-session ordering and exactly-once semantics.
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.
- ✓
Enable message ordering in Pub/Sub with a session ID as the ordering key, and in Dataflow use a global window with a custom trigger that fires on watermark and uses a BigQuery sink with 'exactly-once' mode enabled.
Why this is correct
D is correct because Pub/Sub ordering keys maintain order per session, and Dataflow's exactly-once sink to BigQuery prevents duplicates when combined with deterministic triggers.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a Pub/Sub pull subscription with a subscriber that acknowledges messages immediately after processing, and a Dataflow pipeline with a sliding window.
Why it's wrong here
A is wrong because strict ordering per session is not maintained with pull subscriptions without ordering keys.
- ✗
Assign a unique session ID as the message ordering key in Pub/Sub, use a Dataflow pipeline with session windows and .withAllowedLateness(0), and write to BigQuery using a batch load.
Why it's wrong here
C is wrong because session windows in Dataflow may still produce late data, and batch loads are not real-time.
- ✗
Use a Pub/Sub push subscription with an acknowledgment deadline of 600 seconds and enable exactly-once delivery on the subscription.
Why it's wrong here
B is wrong because Pub/Sub exactly-once delivery only applies to the subscription side, but Dataflow sink to BigQuery may still produce duplicates.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that Pub/Sub's exactly-once delivery subscription alone guarantees end-to-end exactly-once processing, ignoring that Dataflow's sink configuration and windowing strategy are required for ordering and deduplication in the output.
Detailed technical explanation
How to think about this question
Under the hood, Pub/Sub message ordering uses a sequence number per ordering key, and Dataflow's BigQuery sink with exactly-once mode leverages the Streaming Buffer's deduplication by row hash and insert ID. A subtle behavior: if a Dataflow worker fails after writing to BigQuery but before committing the checkpoint, the sink retries the write, and BigQuery deduplicates based on the insert ID, ensuring no duplicate rows. In real-world scenarios, this is critical for financial clickstream analytics where duplicate events would inflate conversion metrics.
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
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FAQ
Questions learners often ask
What does this PDE question test?
Building and operationalizing data processing systems — This question tests Building and operationalizing data processing systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable message ordering in Pub/Sub with a session ID as the ordering key, and in Dataflow use a global window with a custom trigger that fires on watermark and uses a BigQuery sink with 'exactly-once' mode enabled. — Option A is correct because it combines Pub/Sub message ordering (using a session ID as the ordering key) with Dataflow's exactly-once sink to BigQuery. The global window with a watermark-based trigger ensures all events for a session are processed in order before writing, while the BigQuery 'exactly-once' mode prevents duplicate rows even if the pipeline retries. This satisfies both strict per-session ordering and exactly-once semantics.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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