- A
Denormalize data into wide tables to reduce the number of joins.
Why wrong: Denormalization increases storage and write amplification, and may not be necessary with interleaving.
- B
Use interleaved tables to co-locate related rows that are queried together.
Interleaving ensures parent and child rows are stored on the same split, reducing latency for joins.
- C
Use a single table with composite primary key to avoid joins.
Why wrong: Single table approach does not leverage Spanner's distributed architecture and can cause hotspots.
- D
Create secondary indexes on every column to optimize read queries.
Why wrong: Excessive indexes slow writes and are not always used; index design should be selective.
Question 431 of 1,000
Using Cloud Spanner Interleaved Tables for Global Low-Latency Reads
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.
A company is designing a Cloud Spanner database for a global user base. They need to support strong consistency and low-latency reads across multiple regions. Which schema design practice is most important?
Quick Answer
The correct answer is to use interleaved tables to co-locate related rows that are queried together. This schema design practice is essential for achieving global low-latency reads because Cloud Spanner physically stores parent and child rows on the same split, eliminating the need for cross-node communication during joins. When you interleave tables, related data resides in the same tablet, allowing Spanner to serve strongly consistent reads from a single regional replica without coordinating across distant nodes. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of how schema design directly impacts distributed database performance; a common trap is choosing denormalization or excessive indexing, which increase write overhead or storage costs without guaranteeing co-location. Remember the memory tip: “Interleave to retrieve, don’t index to fix”—if your queries always join a parent and child, interleaving is the performance shortcut that keeps reads fast across the globe.
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
✓
Use interleaved tables to co-locate related rows that are queried together.
Interleaved tables in Cloud Spanner physically co-locate parent and child rows on the same split, enabling local joins with strong consistency and low latency across regions. This design minimizes cross-node communication, which is critical for global workloads that require both strong consistency and fast reads.
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.
- ✗
Denormalize data into wide tables to reduce the number of joins.
Why it's wrong here
Denormalization increases storage and write amplification, and may not be necessary with interleaving.
- ✓
Use interleaved tables to co-locate related rows that are queried together.
Why this is correct
Interleaving ensures parent and child rows are stored on the same split, reducing latency for joins.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a single table with composite primary key to avoid joins.
Why it's wrong here
Single table approach does not leverage Spanner's distributed architecture and can cause hotspots.
- ✗
Create secondary indexes on every column to optimize read queries.
Why it's wrong here
Excessive indexes slow writes and are not always used; index design should be selective.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common mistake is thinking that denormalization or secondary indexes are the best way to optimize reads in Cloud Spanner, but the key to low-latency global reads is physical data locality via interleaved tables, not schema flattening or excessive indexing.
Detailed technical explanation
How to think about this question
Interleaved tables use the parent table's primary key as the prefix for the child table's primary key, ensuring that all rows of a parent and its children are stored in the same split. This allows Spanner to perform a local join without distributed transactions, achieving single-digit millisecond read latencies globally. In practice, this is ideal for hierarchical data like user profiles and their orders, where queries always filter by the parent key.
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 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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. 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.
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use interleaved tables to co-locate related rows that are queried together. — Interleaved tables in Cloud Spanner physically co-locate parent and child rows on the same split, enabling local joins with strong consistency and low latency across regions. This design minimizes cross-node communication, which is critical for global workloads that require both strong consistency and fast reads.
What should I do if I get this PCDE 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 →
Same concept, more angles
1 more ways this is tested on PCDE
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A startup is using Cloud Spanner for a global user base. They need to design a schema that minimizes interleaved table joins for common access patterns. Which schema design principle should they prioritize?
easy- A.Normalize all tables to reduce data redundancy.
- B.Store data in separate databases per region.
- C.Use secondary indexes on all foreign key columns.
- ✓ D.Use composite primary keys to colocate related data.
Why D: Option D is correct because Cloud Spanner uses interleaved tables to colocate parent and child rows physically on the same split, based on a shared prefix of the primary key. By designing composite primary keys that include the parent key as the leading column, related data is stored together, eliminating the need for distributed joins across nodes. This minimizes latency for common access patterns in a globally distributed database.
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Last reviewed: Jul 4, 2026
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