- A
Create a separate column family for each event type.
Why wrong: Column families are logical groupings and do not directly improve filtering performance.
- B
Add a secondary index on the event_type column.
Why wrong: Cloud Bigtable does not support secondary indexes; row key design is the primary access pattern.
- C
Use a separate Bigtable instance for each event type.
Why wrong: This is an overly complex and expensive solution, not a schema design change.
- D
Change the row key to 'event_type#customer_id#timestamp'.
This allows efficient range scans for a specific event type across all customers.
Quick Answer
The answer is to change the row key to 'event_type#customer_id#timestamp'. This is correct because Cloud Bigtable stores rows in lexicographic order by row key, so placing the event type first allows a scan to target a contiguous range of rows for a specific event type, dramatically improving filter performance. On the Google Professional Cloud Database Engineer exam, this tests your understanding that Bigtable’s single-index design forces you to model query patterns into the row key itself—a common trap is assuming secondary indexes or column families can substitute for key design. Remember the memory tip: “First in the key, first in the scan”—the leftmost part of the row key determines the primary access pattern, so always lead with your most frequent filter criterion.
PCDE Design and implement database schemas Practice Question
This PCDE practice question tests your understanding of design and implement database schemas. 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.
An e-commerce platform uses Cloud Bigtable for real-time analytics on customer behavior. The table uses a row key of 'customer_id#timestamp' (customer ID followed by reverse timestamp). Queries for a specific customer's recent events are fast, but queries that filter by event type (e.g., 'purchase') across many customers are slow. What schema change can improve query performance for event-type filtering?
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
Change the row key to 'event_type#customer_id#timestamp'.
Option A is correct because by making the row key start with the event type, scans can efficiently filter by event type. Option B is incorrect because Bigtable does not support secondary indexes natively (you can use row key design or column families, but not indexes like relational databases). Option C (adding a column family) does not help with filtering. Option D (using a different database) is an architecture change.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a separate column family for each event type.
Why it's wrong here
Column families are logical groupings and do not directly improve filtering performance.
- ✗
Add a secondary index on the event_type column.
Why it's wrong here
Cloud Bigtable does not support secondary indexes; row key design is the primary access pattern.
- ✗
Use a separate Bigtable instance for each event type.
Why it's wrong here
This is an overly complex and expensive solution, not a schema design change.
- ✓
Change the row key to 'event_type#customer_id#timestamp'.
Why this is correct
This allows efficient range scans for a specific event type across all customers.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related PCDE NAT questions on configuration and troubleshooting.
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FAQ
Questions learners often ask
What does this PCDE question test?
Design and implement database schemas — This question tests Design and implement database schemas — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Change the row key to 'event_type#customer_id#timestamp'. — Option A is correct because by making the row key start with the event type, scans can efficiently filter by event type. Option B is incorrect because Bigtable does not support secondary indexes natively (you can use row key design or column families, but not indexes like relational databases). Option C (adding a column family) does not help with filtering. Option D (using a different database) is an architecture change.
What should I do if I get this PCDE question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related PCDE NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 24, 2026
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.
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