- A
Use a hash prefix in the primary key to distribute writes across splits.
Hashing prevents sequential writes from hitting the same split.
- B
Use a timestamp prefix in the primary key to sort by time.
Why wrong: Timestamp prefix causes all recent writes to go to the same split, creating a hotspot.
- C
Use interleaved tables to keep related rows together.
Why wrong: Interleaving helps with reads but can concentrate writes on a single split.
- D
Design the schema so that hot rows are split into multiple rows with different keys.
Spreading a hot logical row across multiple physical rows reduces write pressure.
- E
Decrease the number of splits by using a less granular primary key.
Why wrong: Fewer splits increase contention because all writes go to fewer nodes.
Question 660 of 1,000
Cloud Spanner Write Contention — How to Reduce with Schema Design
This PCDE practice question tests your understanding of design and implement database schemas. 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.
Which TWO schema design practices help reduce write contention in Cloud Spanner?
Quick Answer
The answer is to design the schema so that hot rows are split into multiple rows with different keys. This approach directly reduces write contention by distributing incoming writes across many distinct rows, preventing a single row from becoming a bottleneck under high traffic. In Cloud Spanner, contention occurs when multiple transactions try to modify the same row simultaneously, causing retries and latency; splitting the hot row into separate keys spreads the write load across different splits, improving throughput. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of schema design for distributed databases, often appearing as a trap where monotonically increasing keys or timestamp prefixes are mistakenly chosen because they seem logical but actually cause hotspotting. A common memory tip is to think of a busy checkout line: splitting one long line into multiple shorter lines reduces congestion, just as splitting a hot row into multiple keys reduces write contention.
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
✓
Use a hash prefix in the primary key to distribute writes across splits.
Option A is correct because using a hash prefix in the primary key distributes write operations uniformly across multiple splits (tablets). Cloud Spanner splits data based on key ranges; without a hash prefix, sequential writes (e.g., monotonically increasing keys) concentrate on a single split, causing hot spots and write contention. A hash prefix ensures that each new row lands on a different split, balancing the 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.
- ✓
Use a hash prefix in the primary key to distribute writes across splits.
Why this is correct
Hashing prevents sequential writes from hitting the same split.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a timestamp prefix in the primary key to sort by time.
Why it's wrong here
Timestamp prefix causes all recent writes to go to the same split, creating a hotspot.
- ✗
Use interleaved tables to keep related rows together.
Why it's wrong here
Interleaving helps with reads but can concentrate writes on a single split.
- ✓
Design the schema so that hot rows are split into multiple rows with different keys.
Why this is correct
Spreading a hot logical row across multiple physical rows reduces write pressure.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the number of splits by using a less granular primary key.
Why it's wrong here
Fewer splits increase contention because all writes go to fewer nodes.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often assume that using a timestamp prefix (Option B) is beneficial for time-series queries, but in Cloud Spanner, monotonically increasing keys cause all writes to hit a single split, creating a hot spot. Instead, hash prefixes (Option A) distribute writes evenly. Another misconception is that interleaved tables (Option C) reduce write contention; they actually improve read performance but do not address write hot spots. Also, decreasing splits (Option E) reduces parallelism, worsening contention.
Detailed technical explanation
How to think about this question
Under the hood, Cloud Spanner uses a distributed storage system where each split is a Paxos group responsible for a contiguous key range. A hash prefix (e.g., using SHA-256 or a simple modulo hash) spreads keys uniformly across the key space, ensuring that each split receives roughly the same number of writes. In real-world scenarios, this is critical for high-throughput applications like IoT sensor ingestion or event logging, where timestamps are natural keys but cause hot spots on the last split.
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
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FAQ
Questions learners often ask
What does this PCDE question test?
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: Use a hash prefix in the primary key to distribute writes across splits. — Option A is correct because using a hash prefix in the primary key distributes write operations uniformly across multiple splits (tablets). Cloud Spanner splits data based on key ranges; without a hash prefix, sequential writes (e.g., monotonically increasing keys) concentrate on a single split, causing hot spots and write contention. A hash prefix ensures that each new row lands on a different split, balancing the 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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Last reviewed: Jul 4, 2026
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