- A
Use a single Dataflow pipeline that reads from Spanner change streams and writes to both Pub/Sub and BigQuery
Why wrong: Spanner change streams can write directly to Pub/Sub; it is simpler to let change streams publish to Pub/Sub and then use Dataflow to consume from Pub/Sub to BigQuery.
- B
Enable Spanner change streams to publish to Pub/Sub, and then use a Dataflow pipeline to subscribe to the Pub/Sub topic and write to BigQuery
This uses change streams for real-time events and Dataflow for archiving to BigQuery, with minimal complexity.
- C
Use two separate Dataflow pipelines: one reading from change streams to Pub/Sub, another reading from Pub/Sub to BigQuery
Why wrong: This adds unnecessary duplication; change streams can directly publish to Pub/Sub without a Dataflow pipeline.
- D
Export Spanner tables to Avro in GCS nightly and load into BigQuery; use Cloud Functions to capture changes to Pub/Sub
Why wrong: Nightly export is not real-time; Cloud Functions are not needed if change streams are used.
PCD Practice Question: Manage a Solution that Can Span Multiple Database Systems
This PCD practice question tests your understanding of manage a solution that can span multiple database 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 company uses Cloud Spanner for its global ordering system and needs to stream order changes to a Pub/Sub topic for real-time inventory updates. They also need to archive old orders to BigQuery for historical analysis. What is the simplest architecture to achieve both goals?
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 Spanner change streams to publish to Pub/Sub, and then use a Dataflow pipeline to subscribe to the Pub/Sub topic and write to BigQuery
Option B is correct because it leverages Spanner change streams' native ability to publish directly to Pub/Sub, which is the simplest integration path. A single Dataflow pipeline then subscribes to that Pub/Sub topic to write to BigQuery, fulfilling both the real-time streaming and archival requirements with minimal moving parts. This avoids the complexity of reading change streams directly in Dataflow or managing multiple pipelines.
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.
- ✗
Use a single Dataflow pipeline that reads from Spanner change streams and writes to both Pub/Sub and BigQuery
Why it's wrong here
Spanner change streams can write directly to Pub/Sub; it is simpler to let change streams publish to Pub/Sub and then use Dataflow to consume from Pub/Sub to BigQuery.
- ✓
Enable Spanner change streams to publish to Pub/Sub, and then use a Dataflow pipeline to subscribe to the Pub/Sub topic and write to BigQuery
Why this is correct
This uses change streams for real-time events and Dataflow for archiving to BigQuery, with minimal complexity.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use two separate Dataflow pipelines: one reading from change streams to Pub/Sub, another reading from Pub/Sub to BigQuery
Why it's wrong here
This adds unnecessary duplication; change streams can directly publish to Pub/Sub without a Dataflow pipeline.
- ✗
Export Spanner tables to Avro in GCS nightly and load into BigQuery; use Cloud Functions to capture changes to Pub/Sub
Why it's wrong here
Nightly export is not real-time; Cloud Functions are not needed if change streams are used.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common mistake is to think that Dataflow must directly read from Spanner change streams (Option A) or that multiple pipelines are necessary (Option C), when the simplest approach is to leverage Spanner's native Pub/Sub integration.
Detailed technical explanation
How to think about this question
Spanner change streams capture row-level changes (inserts, updates, deletes) with a commit timestamp and can be configured to publish directly to a Pub/Sub topic via a built-in connector, eliminating the need for custom streaming code. The Dataflow pipeline uses a Pub/Sub subscription to read these changes, applies windowing or deduplication if needed, and writes to BigQuery using the BigQuery sink with exactly-once semantics. In a real-world scenario, this architecture handles high-throughput order changes (e.g., thousands per second) while maintaining low latency for inventory updates and reliable archival.
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
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FAQ
Questions learners often ask
What does this PCD question test?
Manage a Solution that Can Span Multiple Database Systems — This question tests Manage a Solution that Can Span Multiple Database Systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable Spanner change streams to publish to Pub/Sub, and then use a Dataflow pipeline to subscribe to the Pub/Sub topic and write to BigQuery — Option B is correct because it leverages Spanner change streams' native ability to publish directly to Pub/Sub, which is the simplest integration path. A single Dataflow pipeline then subscribes to that Pub/Sub topic to write to BigQuery, fulfilling both the real-time streaming and archival requirements with minimal moving parts. This avoids the complexity of reading change streams directly in Dataflow or managing multiple pipelines.
What should I do if I get this PCD 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.
About these practice questions
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Last reviewed: Jul 4, 2026
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