- A
Separate frequently accessed columns (price, volume) from metadata (trade ID) into different column families
Different column families allow optimising compression and caching for different access patterns.
- B
Use the trade ID as the entire row key
Why wrong: Trade ID alone does not support efficient symbol+time range scans.
- C
Store all fields in a single column family
Why wrong: It's better to separate frequently accessed columns from infrequently accessed ones.
- D
Include a reversed timestamp in the row key for efficient recent-data scans
Reversed timestamp (max - timestamp) allows scanning most recent data first.
- E
Use a row key prefix of a hash of the symbol to distribute writes
Hashing the symbol as a prefix avoids hotspots on popular symbols.
Question 856 of 980
PCD Practice Question: Design Scalable and Highly Available Cloud Database Solutions
This PCD practice question tests your understanding of design scalable and highly available cloud 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.
You are designing a Bigtable schema for a financial data application that stores trade records. Each trade has a trade ID, symbol, timestamp, price, and volume. Queries include fetching all trades for a symbol in a time range. Which three row key design practices should you apply? (Choose THREE.)
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
✓
Separate frequently accessed columns (price, volume) from metadata (trade ID) into different column families
Option A is correct because separating frequently accessed columns like price and volume from metadata like trade ID into different column families optimizes read performance. In Bigtable, column families are stored separately on disk, so queries that only need price and volume can avoid reading the trade ID column family, reducing I/O and improving latency.
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.
- ✓
Separate frequently accessed columns (price, volume) from metadata (trade ID) into different column families
Why this is correct
Different column families allow optimising compression and caching for different access patterns.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use the trade ID as the entire row key
Why it's wrong here
Trade ID alone does not support efficient symbol+time range scans.
- ✗
Store all fields in a single column family
Why it's wrong here
It's better to separate frequently accessed columns from infrequently accessed ones.
- ✓
Include a reversed timestamp in the row key for efficient recent-data scans
Why this is correct
Reversed timestamp (max - timestamp) allows scanning most recent data first.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Use a row key prefix of a hash of the symbol to distribute writes
Why this is correct
Hashing the symbol as a prefix avoids hotspots on popular symbols.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that a unique identifier like trade ID should be the row key, but the trap here is that candidates overlook the need for write distribution and efficient range scans, leading them to choose Option B instead of the hash prefix and reversed timestamp.
Detailed technical explanation
How to think about this question
Bigtable row keys are sorted lexicographically, so including a reversed timestamp (e.g., Long.MAX_VALUE - timestamp) in the row key ensures that the most recent trades appear first in scans, enabling efficient time-range queries without full table scans. Hashing the symbol as a row key prefix distributes writes across tablets by randomizing the key space, preventing hotspotting on a single node for high-volume symbols.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Design Scalable and Highly Available Cloud Database Solutions — study guide chapter
Learn the concepts, then practise the questions
- →
Design Scalable and Highly Available Cloud Database Solutions practice questions
Targeted practice on this topic area only
- →
All PCD questions
980 questions across all exam domains
- →
Google Professional Cloud Developer study guide
Full concept coverage aligned to exam objectives
- →
PCD practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related PCD practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Manage a Solution that Can Span Multiple Database Systems practice questions
Practise PCD questions linked to Manage a Solution that Can Span Multiple Database Systems.
Deploy Scalable and Highly Available Databases in Google Cloud practice questions
Practise PCD questions linked to Deploy Scalable and Highly Available Databases in Google Cloud.
Design Scalable and Highly Available Cloud Database Solutions practice questions
Practise PCD questions linked to Design Scalable and Highly Available Cloud Database Solutions.
Migrate Data Solutions practice questions
Practise PCD questions linked to Migrate Data Solutions.
Designing highly scalable, available, and reliable cloud-native applications practice questions
Practise PCD questions linked to Designing highly scalable, available, and reliable cloud-native applications.
Building and testing applications practice questions
Practise PCD questions linked to Building and testing applications.
Deploying applications practice questions
Practise PCD questions linked to Deploying applications.
Integrating Google Cloud services practice questions
Practise PCD questions linked to Integrating Google Cloud services.
Managing application performance monitoring practice questions
Practise PCD questions linked to Managing application performance monitoring.
PCD fundamentals practice questions
Practise PCD questions linked to PCD fundamentals.
PCD scenario practice questions
Practise PCD questions linked to PCD scenario.
PCD troubleshooting practice questions
Practise PCD questions linked to PCD troubleshooting.
Practice this exam
Start a free PCD practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this PCD question test?
Design Scalable and Highly Available Cloud Database Solutions — This question tests Design Scalable and Highly Available Cloud Database Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Separate frequently accessed columns (price, volume) from metadata (trade ID) into different column families — Option A is correct because separating frequently accessed columns like price and volume from metadata like trade ID into different column families optimizes read performance. In Bigtable, column families are stored separately on disk, so queries that only need price and volume can avoid reading the trade ID column family, reducing I/O and improving latency.
What should I do if I get this PCD 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.