- A
Increase the number of nodes in the Bigtable cluster to handle the load.
Why wrong: Adding nodes helps with overall throughput but does not fix the hot spot on a few row keys.
- B
Change the storage type from HDD to SSD to improve performance.
Why wrong: Storage type affects latency but not the distribution of load across row keys.
- C
Redesign the row key scheme to distribute the workload across more tablets.
Row key design is critical. Using a hash or adding a salt prefix spreads reads across nodes.
- D
Enable replication across multiple zones.
Why wrong: Replication provides high availability and read scaling but does not solve hot spotting on a single cluster.
Question 27 of 1,000
PCDOE Manage Database Solutions Practice Question
This PCDOE practice question tests your understanding of manage database solutions. 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.
A Cloud Bigtable instance is experiencing high read latency due to hot spots. The operations team uses the Key Visualizer tool and identifies that a small set of row keys are being read disproportionately. Which action should they take to mitigate the hot spotting?
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
✓
Redesign the row key scheme to distribute the workload across more tablets.
Option C is correct because hot spotting in Cloud Bigtable is typically caused by a suboptimal row key design that concentrates read/write traffic on a small number of tablets. Redesigning the row key scheme to distribute the workload—for example, by adding a hash prefix or using a more granular key—spreads requests across multiple tablets, alleviating the hotspot. Key Visualizer explicitly identifies the skewed row keys, guiding the redesign effort.
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.
- ✗
Increase the number of nodes in the Bigtable cluster to handle the load.
Why it's wrong here
Adding nodes helps with overall throughput but does not fix the hot spot on a few row keys.
- ✗
Change the storage type from HDD to SSD to improve performance.
Why it's wrong here
Storage type affects latency but not the distribution of load across row keys.
- ✓
Redesign the row key scheme to distribute the workload across more tablets.
Why this is correct
Row key design is critical. Using a hash or adding a salt prefix spreads reads across nodes.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Enable replication across multiple zones.
Why it's wrong here
Replication provides high availability and read scaling but does not solve hot spotting on a single cluster.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common mistake in Google Cloud exams is to think that adding nodes or changing storage type can fix design-level hotspots, when in fact the correct action is always to address the data distribution pattern at the row key level using the Key Visualizer results.
Detailed technical explanation
How to think about this question
Cloud Bigtable splits data into tablets based on row key ranges; a poorly designed key (e.g., monotonically increasing timestamps) causes all writes to land on the last tablet, creating a hotspot. Key Visualizer uses heatmaps to show access patterns, and a common mitigation is to prepend a hash of the key (e.g., MD5 or a field-specific hash) to ensure uniform distribution across the key space. In real-world scenarios, this is critical for time-series data where sequential keys like '2025-03-01#user123' would all hit the same tablet until a split occurs.
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.
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FAQ
Questions learners often ask
What does this PCDOE question test?
Manage Database Solutions — This question tests Manage Database Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Redesign the row key scheme to distribute the workload across more tablets. — Option C is correct because hot spotting in Cloud Bigtable is typically caused by a suboptimal row key design that concentrates read/write traffic on a small number of tablets. Redesigning the row key scheme to distribute the workload—for example, by adding a hash prefix or using a more granular key—spreads requests across multiple tablets, alleviating the hotspot. Key Visualizer explicitly identifies the skewed row keys, guiding the redesign effort.
What should I do if I get this PCDOE 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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