Design innovative, scalable, and highly available cloud database solutions →mediumMultiple ChoiceObjective-mapped
PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A team is migrating a relational database to Cloud Bigtable. They need to design a row key that distributes write traffic evenly across nodes. The original table had a composite primary key of customer_id and order_date. Which row key design is BEST for high write throughput?
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
✓
hash(customer_id) # customer_id # order_date
Adding a hash prefix (salting) to the row key distributes writes across multiple tablet servers, avoiding hotspots. The customer_id alone may cause hotspots if some customers are more active.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
customer_id # order_date
Why it's wrong here
This could cause hotspots on popular customers.
- ✓
hash(customer_id) # customer_id # order_date
Why this is correct
The hash prefix distributes writes evenly while preserving query ability on customer_id.
- ✗
order_date # customer_id
Why it's wrong here
Date prefix can cause hotspots on current date.
- ✗
customer_id only
Why it's wrong here
Single customer_id as row key would cause hotspots for active customers.
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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.