Avoid Write Hotspots in Cloud Spanner with Primary Key Design
This PCDE practice question tests your understanding of design and implement database schemas. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Exhibit
CREATE TABLE Orders (
OrderId INT64 NOT NULL,
CustomerId INT64 NOT NULL,
OrderDate DATE NOT NULL,
TotalAmount FLOAT64 NOT NULL
) PRIMARY KEY (OrderId, CustomerId);
Refer to the exhibit. You are reviewing the following Cloud Spanner DDL statement for a table storing customer orders. What potential performance issue will arise with this schema?
Exhibit
CREATE TABLE Orders (
OrderId INT64 NOT NULL,
CustomerId INT64 NOT NULL,
OrderDate DATE NOT NULL,
TotalAmount FLOAT64 NOT NULL
) PRIMARY KEY (OrderId, CustomerId);
A
The primary key includes two columns which reduces insert performance
Why wrong: Composite primary keys are normal in Spanner and do not inherently reduce performance.
B
The TotalAmount column should be INTEGER for performance
Why wrong: FLOAT64 is fine; data type choice is not a major performance factor here.
C
The table lacks a foreign key constraint
Why wrong: Foreign keys are not required and do not cause performance issues.
D
The OrderId is likely to be sequentially generated, causing write hotspots
Sequential keys lead to hotspotting; consider using a hash prefix or UUID.
The correct answer is that the OrderId being sequentially generated will cause write hotspots. This happens because Cloud Spanner distributes data across splits based on the primary key’s leading column, and monotonically increasing values like auto-increment IDs funnel all new inserts into a single split, overwhelming that node while others remain idle. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of how to avoid write hotspots in Cloud Spanner primary key design, often appearing as a trap where a composite key seems safe but the leading column’s sequential nature creates the bottleneck. A common memory tip is to think of a “hot key” as a single busy register at a store—if every new customer goes to register one, the line backs up. To distribute writes, always lead your primary key with a high-cardinality, non-sequential column, such as a customer ID or a hash of the timestamp. Remember: monotonic leads to monotony in performance.
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 OrderId is likely to be sequentially generated, causing write hotspots
Option D is correct because Cloud Spanner uses a distributed architecture that splits data across splits based on the primary key range. If OrderId is sequentially generated (e.g., auto-increment), all new inserts will target the same split, creating a write hotspot that degrades throughput and latency. This is a well-known anti-pattern in Spanner; the recommended approach is to use a UUID or a monotonically increasing key with a hash prefix to distribute writes evenly.
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 primary key includes two columns which reduces insert performance
Why it's wrong here
Composite primary keys are normal in Spanner and do not inherently reduce performance.
✗
The TotalAmount column should be INTEGER for performance
Why it's wrong here
FLOAT64 is fine; data type choice is not a major performance factor here.
✗
The table lacks a foreign key constraint
Why it's wrong here
Foreign keys are not required and do not cause performance issues.
✓
The OrderId is likely to be sequentially generated, causing write hotspots
Why this is correct
Sequential keys lead to hotspotting; consider using a hash prefix or UUID.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common misconception tested in this exam is that composite primary keys or missing foreign keys are the main performance culprits, when in fact the critical issue is write hotspotting caused by monotonically increasing primary keys in a distributed database like Cloud Spanner.
Detailed technical explanation
How to think about this question
Under the hood, Cloud Spanner splits data into tablets based on the primary key range, and each split is served by a separate node. When a primary key is monotonically increasing (e.g., sequential OrderId), all new rows are written to the last split, causing that split to become a bottleneck while other splits remain idle. This can be mitigated by using a key with a hash prefix (e.g., Hash(OrderId) + OrderId) or a UUID to ensure uniform distribution across splits. In real-world scenarios, this hotspot issue can cause Spanner to throttle writes and increase latency, especially under high-throughput workloads.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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.
Design and implement database schemas — This question tests Design and implement database schemas — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The OrderId is likely to be sequentially generated, causing write hotspots — Option D is correct because Cloud Spanner uses a distributed architecture that splits data across splits based on the primary key range. If OrderId is sequentially generated (e.g., auto-increment), all new inserts will target the same split, creating a write hotspot that degrades throughput and latency. This is a well-known anti-pattern in Spanner; the recommended approach is to use a UUID or a monotonically increasing key with a hash prefix to distribute writes evenly.
What should I do if I get this PCDE 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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