- A
Enable Dataflow Streaming Engine for exactly-once processing.
Why wrong: Streaming Engine improves scalability but does not guarantee exactly-once; committed mode does.
- B
Use side inputs to enrich streaming data with static data.
Why wrong: Side inputs are not related to windowing or late data handling.
Question 845 of 1,000
PDE Ingesting and Processing the Data Practice Question
This PDE practice question tests your understanding of ingesting and processing the data. 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.
You are building a Dataflow pipeline that reads from Pub/Sub, applies transformations, and writes to BigQuery. The pipeline must handle late-arriving data and ensure that the windowing and triggering are correct. Which THREE configurations should you consider? (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
✓
Use the BigQuery Storage Write API with committed mode to ensure exactly-once writes.
Option C is correct because the BigQuery Storage Write API with committed mode provides exactly-once write semantics, which is essential for ensuring that late-arriving data processed by the pipeline does not result in duplicate rows in BigQuery. This mode uses stream offsets to track writes, guaranteeing that each record is written exactly once even if the pipeline retries.
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 Dataflow Streaming Engine for exactly-once processing.
Why it's wrong here
Streaming Engine improves scalability but does not guarantee exactly-once; committed mode does.
- ✗
Use side inputs to enrich streaming data with static data.
Why it's wrong here
Side inputs are not related to windowing or late data handling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common misconception is that Dataflow Streaming Engine alone provides exactly-once processing. In reality, it is the combination of source/sink semantics (like the BigQuery Storage Write API) that ensures exactly-once, not the engine itself.
Detailed technical explanation
How to think about this question
The BigQuery Storage Write API uses a stream-based protocol where each write request includes an offset; in committed mode, the API commits the data only when the offset is finalized, preventing duplicates. Allowed lateness (Option D) works with event-time timestamps and watermark tracking to determine how long the pipeline waits for late data before closing windows, while triggering frequency (Option E) controls when speculative or final pane results are emitted, both critical for correct windowing in streaming pipelines.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PDE question test?
Ingesting and Processing the Data — This question tests Ingesting and Processing the Data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the BigQuery Storage Write API with committed mode to ensure exactly-once writes. — Option C is correct because the BigQuery Storage Write API with committed mode provides exactly-once write semantics, which is essential for ensuring that late-arriving data processed by the pipeline does not result in duplicate rows in BigQuery. This mode uses stream offsets to track writes, guaranteeing that each record is written exactly once even if the pipeline retries.
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: Jul 4, 2026
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