PCDE Design and implement database schemas Practice Question
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
Refer to the exhibit.
gcloud spanner instances describe test-instance
-- output:
config: nam3
nodeCount: 2
processingUnits: 2000
state: READY
-- Schema:
CREATE TABLE Events (
EventId INT64 NOT NULL,
EventType STRING(50) NOT NULL,
EventData BYTES(MAX) NOT NULL,
CreatedAt TIMESTAMP NOT NULL OPTIONS (allow_commit_timestamp=true)
) PRIMARY KEY (EventId);
Refer to the exhibit. The team notices high write latency on the Events table. They are inserting 1,000 events per second. The EventId is generated by a sequence. What is the most likely issue?
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.
Exhibit
Refer to the exhibit.
gcloud spanner instances describe test-instance
-- output:
config: nam3
nodeCount: 2
processingUnits: 2000
state: READY
-- Schema:
CREATE TABLE Events (
EventId INT64 NOT NULL,
EventType STRING(50) NOT NULL,
EventData BYTES(MAX) NOT NULL,
CreatedAt TIMESTAMP NOT NULL OPTIONS (allow_commit_timestamp=true)
) PRIMARY KEY (EventId);
A
The sequential primary key creates a hotspot on a single split.
Sequential keys cause all writes to hit the same split, leading to contention and latency.
B
The allow_commit_timestamp option on CreatedAt column adds overhead.
Why wrong: Commit timestamp option is efficient and not a cause of hotspotting.
C
The BYTES(MAX) data type causes excessive writing.
Why wrong: Data size affects throughput but not specifically the hotspot issue.
D
The node count is insufficient for the write throughput.
Why wrong: 2 nodes can handle 1k writes/s if writes are distributed; the issue is distribution.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The sequential primary key creates a hotspot on a single split.
The sequential primary key (EventId generated by a sequence) causes all new writes to be directed to the last tablet or split in the table, creating a hotspot. In Cloud Spanner, this leads to contention on a single split, increasing write latency despite adequate overall throughput capacity.
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 sequential primary key creates a hotspot on a single split.
Why this is correct
Sequential keys cause all writes to hit the same split, leading to contention and latency.
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 allow_commit_timestamp option on CreatedAt column adds overhead.
Why it's wrong here
Commit timestamp option is efficient and not a cause of hotspotting.
✗
The BYTES(MAX) data type causes excessive writing.
Why it's wrong here
Data size affects throughput but not specifically the hotspot issue.
✗
The node count is insufficient for the write throughput.
Why it's wrong here
2 nodes can handle 1k writes/s if writes are distributed; the issue is distribution.
Common exam traps
Common exam trap: answer the scenario, not the keyword
In the Google Professional Cloud Developer Engineer exam, a common pitfall is confusing high write latency with insufficient node count or data type choices, when the real issue is often key design causing a hotspot on a single split in Cloud Spanner.
Detailed technical explanation
How to think about this question
Cloud Spanner splits data by key range, and sequential keys (e.g., monotonically increasing integers) cause all new rows to land in the same split, creating a hot spot. This can be mitigated by using a UUID or a hash-prefixed key to distribute writes evenly across splits. Under the hood, Spanner's split management and load balancing rely on key distribution; a sequential key defeats this mechanism.
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 sequential primary key creates a hotspot on a single split. — The sequential primary key (EventId generated by a sequence) causes all new writes to be directed to the last tablet or split in the table, creating a hotspot. In Cloud Spanner, this leads to contention on a single split, increasing write latency despite adequate overall throughput capacity.
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.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This PCDE 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 PCDE exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.