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PCD Practice Question: Designing a Cloud Bigtable schema for a…
You are designing a Cloud Bigtable schema for a time-series application. To optimize performance and avoid hot spots, which THREE row key design practices should you follow? (Choose 3)
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
✓
Place the highest cardinality field (e.g., device ID) first in the row key
Reversing timestamps, salting keys, and promoting high-cardinality fields to the start of the row key are recommended to distribute writes evenly.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Place the highest cardinality field (e.g., device ID) first in the row key
Why this is correct
High cardinality field first distributes rows across tablets.
- ✗
Use a single table for all data
Why it's wrong here
Single table vs multiple tables is a design choice, but not directly related to hot spotting.
- ✗
Use sequential integers as row keys
Why it's wrong here
Sequential integers cause hot spots on the last tablet.
- ✓
Reverse the timestamp so that recent data does not create hot spots
Why this is correct
Reversing the timestamp randomizes the order and prevents hot spots on the newest data.
- ✓
Salt the key with a random prefix to distribute writes
Why this is correct
Salting spreads writes across tablets.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCD 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 PCD exam.