- A
Create a Dataflow pipeline that reads from Spanner using JDBC
Why wrong: Using JDBC would require full table scans and is not efficient for real-time change capture; change streams are designed for this.
- B
Use Cloud Functions to poll the Spanner tables for changes every minute
Why wrong: Polling is inefficient, introduces latency, and does not capture deletes easily.
- C
Enable Cloud Spanner change streams on the tables and configure them to write to Pub/Sub
Change streams capture all DML changes and can be set up to stream to Pub/Sub for downstream use.
- D
Export the Spanner tables to Avro files in GCS and use BigQuery Change Data Capture
Why wrong: This batch approach is not real-time; BigQuery Change Data Capture is for BigQuery tables, not Spanner.
Question 204 of 980
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. 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 retail company uses Cloud Spanner as its global transactional database. They need to capture all data changes (inserts, updates, deletes) from specific tables and stream them to a Pub/Sub topic for real-time downstream processing. What Google Cloud feature should they use?
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 Cloud Spanner change streams on the tables and configure them to write to Pub/Sub
Option C is correct because Cloud Spanner change streams provide a native, fully managed, and low-latency mechanism to capture row-level changes (inserts, updates, deletes) from Spanner tables. These change streams can be directly configured to write to a Pub/Sub topic via a Dataflow template or a custom pipeline, enabling real-time streaming without polling or external tools.
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.
- ✗
Create a Dataflow pipeline that reads from Spanner using JDBC
Why it's wrong here
Using JDBC would require full table scans and is not efficient for real-time change capture; change streams are designed for this.
- ✗
Use Cloud Functions to poll the Spanner tables for changes every minute
Why it's wrong here
Polling is inefficient, introduces latency, and does not capture deletes easily.
- ✓
Enable Cloud Spanner change streams on the tables and configure them to write to Pub/Sub
Why this is correct
Change streams capture all DML changes and can be set up to stream to Pub/Sub for downstream use.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Export the Spanner tables to Avro files in GCS and use BigQuery Change Data Capture
Why it's wrong here
This batch approach is not real-time; BigQuery Change Data Capture is for BigQuery tables, not Spanner.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between batch export/import methods (like Avro exports or JDBC reads) and native streaming change data capture (like Spanner change streams), leading candidates to choose familiar but incorrect batch-oriented options.
Detailed technical explanation
How to think about this question
Cloud Spanner change streams use a transactional commit timestamp-based mechanism to capture mutations at the row level, and they support filtering by table and column. The change records are consumed via a Dataflow job that uses the Spanner change streams connector, which can then publish to Pub/Sub with exactly-once semantics and sub-second latency. In a real-world scenario, this is ideal for global retail systems needing to synchronize inventory or order updates across regions in near real-time.
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.
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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 Cloud Spanner change streams on the tables and configure them to write to Pub/Sub — Option C is correct because Cloud Spanner change streams provide a native, fully managed, and low-latency mechanism to capture row-level changes (inserts, updates, deletes) from Spanner tables. These change streams can be directly configured to write to a Pub/Sub topic via a Dataflow template or a custom pipeline, enabling real-time streaming without polling or external tools.
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
This PCD 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 PCD exam.
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