- A
The query is using time travel to a snapshot before the streaming buffer was committed
Time travel queries return data from a snapshot; if the snapshot is before the buffer is flushed, recent data is missing.
- B
The query is using cached results that exclude recent data
Why wrong: Cached results are only used if the query is identical and within cache lifetime, but can be disabled.
- C
The schema of the table was modified after the initial query
Why wrong: Schema changes do not cause data loss.
- D
The table has a partition expiration of 30 days
Why wrong: 30 days is longer than 90 minutes, so not relevant.
Quick Answer
The answer is that the query is using time travel to a snapshot taken before the streaming buffer was committed. This is the most likely cause because BigQuery’s streaming buffer provides low-latency access to recently ingested data, but that data is not immediately written to managed storage; it typically flushes within 90 minutes. When a user queries with `FOR SYSTEM_TIME AS OF` to a point before the flush, the query only sees data already in managed storage, so rows still buffered at that snapshot time are missing. On the Google Professional Data Engineer exam, this tests your understanding of the interplay between streaming ingestion and time travel, a common trap where candidates forget that time travel snapshots exclude uncommitted buffer data. Remember the 90-minute window: if rows vanish after that, suspect a time-travel query, not data loss. Memory tip: “Buffer before commit, time travel will omit.”
PDE Designing data processing systems Practice Question
This PDE practice question tests your understanding of designing data processing systems. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 BigQuery table contains streaming data from Cloud Pub/Sub. The table is partitioned by ingestion time. A user runs a query that accesses data from the last 5 minutes and gets correct results. After 90 minutes, the user runs the same query again but notices that some rows are missing. What is the most likely cause?
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.
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
The query is using time travel to a snapshot before the streaming buffer was committed
Option A is correct because BigQuery's streaming buffer provides low-latency access to recently ingested data, but this data is not immediately committed to managed storage. After the streaming buffer is flushed (typically within 90 minutes), the data becomes available in the table's base storage. If the user runs a query using time travel (e.g., `FOR SYSTEM_TIME AS OF`) to a snapshot taken before the buffer was committed, the query will only see data that was in managed storage at that snapshot time, missing rows that were still in the streaming buffer at that point.
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 query is using time travel to a snapshot before the streaming buffer was committed
Why this is correct
Time travel queries return data from a snapshot; if the snapshot is before the buffer is flushed, recent data is missing.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
The query is using cached results that exclude recent data
Why it's wrong here
Cached results are only used if the query is identical and within cache lifetime, but can be disabled.
- ✗
The schema of the table was modified after the initial query
Why it's wrong here
Schema changes do not cause data loss.
- ✗
The table has a partition expiration of 30 days
Why it's wrong here
30 days is longer than 90 minutes, so not relevant.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that cached results or schema changes are responsible for data inconsistencies, when the real issue is the separation between BigQuery's streaming buffer and managed storage, and how time travel queries only see committed data.
Detailed technical explanation
How to think about this question
BigQuery's streaming buffer uses a separate, temporary storage layer optimized for low-latency writes. Data in this buffer is not subject to time travel queries because time travel snapshots are based on the table's managed storage (the base table and its change history). The buffer is typically flushed to managed storage within 90 minutes, but the exact duration can vary based on system load and data volume. This behavior is critical for applications requiring consistent query results across time travel snapshots, such as incremental data processing or auditing.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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: The query is using time travel to a snapshot before the streaming buffer was committed — Option A is correct because BigQuery's streaming buffer provides low-latency access to recently ingested data, but this data is not immediately committed to managed storage. After the streaming buffer is flushed (typically within 90 minutes), the data becomes available in the table's base storage. If the user runs a query using time travel (e.g., `FOR SYSTEM_TIME AS OF`) to a snapshot taken before the buffer was committed, the query will only see data that was in managed storage at that snapshot time, missing rows that were still in the streaming buffer at that point.
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". 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.
About these practice questions
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Last reviewed: Jun 30, 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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