How to Avoid Hot Spots in Cloud Spanner by Designing Primary Keys Correctly
This PCDE practice question tests your understanding of plan and manage database infrastructure. 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 Users (
UserId INT64 NOT NULL,
Name STRING(MAX),
) PRIMARY KEY (UserId);
Refer to the exhibit. This DDL is used to create a table in Cloud Spanner. The table will be used for storing user data with high write throughput. What is one performance issue with this table design?
Exhibit
CREATE TABLE Users (
UserId INT64 NOT NULL,
Name STRING(MAX),
) PRIMARY KEY (UserId);
A
The primary key is a monotonically increasing integer
Sequential keys cause write hotspots in Spanner, leading to uneven load.
B
The Name column is of type STRING(MAX)
Why wrong: STRING(MAX) is valid and does not inherently cause performance issues.
C
There are no secondary indexes
Why wrong: Lack of indexes affects reads but not write throughput directly.
D
The table is not interleaved with another table
Why wrong: Interleaving is optional and not related to this performance issue.
The answer is a monotonically increasing integer primary key, which creates hot spots in Cloud Spanner. This occurs because Cloud Spanner distributes data across splits based on key ranges, and sequential keys like UserId cause all new writes to target the last split, overwhelming that node while others remain idle. On the Google Professional Cloud Database Engineer exam, this tests your understanding of distributed database design and the importance of key distribution for write throughput—a common trap is assuming any integer key is fine, but the monotonic pattern is the culprit. To avoid Cloud Spanner hot spots from monotonically increasing primary keys, you should use a key with high cardinality and uniform distribution, such as a hash prefix or a universally unique identifier. Remember the memory tip: "Don't let your keys climb in a line, or your writes will all bottleneck in time."
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 primary key is a monotonically increasing integer
Option A is correct because using a monotonically increasing integer as the primary key in Cloud Spanner causes all writes to be directed to a single split (tablet), creating a hotspot that severely limits write throughput. Cloud Spanner distributes splits across nodes based on key ranges, and sequential keys prevent this distribution, leading to performance degradation under high write load.
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 is a monotonically increasing integer
Why this is correct
Sequential keys cause write hotspots in Spanner, leading to uneven load.
Related concept
Read the scenario before looking for a memorised answer.
✗
The Name column is of type STRING(MAX)
Why it's wrong here
STRING(MAX) is valid and does not inherently cause performance issues.
✗
There are no secondary indexes
Why it's wrong here
Lack of indexes affects reads but not write throughput directly.
✗
The table is not interleaved with another table
Why it's wrong here
Interleaving is optional and not related to this performance issue.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common misconception is that any integer primary key is acceptable, but in Cloud Spanner, monotonically increasing keys create hotspots because all writes are directed to a single split, limiting write throughput.
Detailed technical explanation
How to think about this question
Cloud Spanner uses a distributed storage architecture where data is partitioned into splits based on the primary key range. A monotonically increasing key, such as a sequential integer or timestamp, causes all new writes to land on the last split, creating a single-point bottleneck. To avoid this, use a key that distributes writes uniformly, such as a UUID or a hash prefix of the key, ensuring splits are evenly utilized across nodes.
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.
Plan and manage database infrastructure — This question tests Plan and manage database infrastructure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The primary key is a monotonically increasing integer — Option A is correct because using a monotonically increasing integer as the primary key in Cloud Spanner causes all writes to be directed to a single split (tablet), creating a hotspot that severely limits write throughput. Cloud Spanner distributes splits across nodes based on key ranges, and sequential keys prevent this distribution, leading to performance degradation under high write load.
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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