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PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
You are designing a Cloud Bigtable schema for a time-series application where the most common write pattern is high-throughput writes (10,000 writes per second) and the row key starts with a timestamp. Write throughput is lower than expected. What is the most likely cause?
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 row key uses a timestamp as the leading component, causing a hotspot
Using a timestamp as the first part of the row key causes all writes to hit a single tablet (hotspot), leading to poor write throughput. The recommendation is to salt the timestamp with a hash prefix.
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 column family has too many columns
Why it's wrong here
Column family design affects storage but not write throughput.
- ✗
The row key is too long
Why it's wrong here
Row key length affects performance but not as drastically as a hotspot.
- ✗
The cluster has insufficient nodes
Why it's wrong here
Even with more nodes, the hotspot would limit throughput.
- ✓
The row key uses a timestamp as the leading component, causing a hotspot
Why this is correct
Monotonically increasing row keys create hotspots.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.