Question 1,166 of 1,446
Cloud Spanner Primary Key Design — UUID vs Sequential to Avoid Hotspotting
A company is designing a database schema for a global e-commerce platform. Orders are created with high frequency, and order status updates occur frequently. The team needs to choose a primary key strategy for the orders table in Spanner. Which approach minimizes hot-spotting?
Quick Answer
The answer is to use a universally unique identifier (UUID) as the primary key. This approach minimizes hot-spotting because UUIDs are randomly distributed across the key space, whereas a monotonically increasing key like a sequential integer or timestamp would concentrate all new writes onto a single tablet server, creating a bottleneck. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of Spanner’s distributed architecture and the importance of write throughput—a common trap is assuming sequential keys are fine for indexing, but in Spanner they cause contention. Remember the memory tip: “UUID spreads the load, sequential overloads the node.”
⚠ Common exam trap
Google Cloud often tests the misconception that composite keys with a user_id prefix are sufficient to avoid hot-spotting, but the trap is that any time-ordered component (like order_date) in the key still causes sequential writes to target the same tablet, negating the distribution benefit.
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 a universally unique identifier (UUID) as the primary key
In Spanner, monotonically increasing or time-ordered primary keys cause hot-spotting because all new writes are directed to the same tablet server, creating a single point of contention. UUIDs are randomly distributed, ensuring writes are spread evenly across the entire key space, which minimizes hot-spotting and maximizes write throughput.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a monotonically increasing integer (e.g., auto-increment)
Why it's wrong here
Causes hot-spotting on the last split.
- ✗
Use a timestamp as the primary key
Why it's wrong here
Causes hot-spotting on the most recent timestamp split.
- ✗
Use a composite key with user_id and order_date
Why it's wrong here
If user_id is sequential or order_date is monotonically increasing, hot-spotting may still occur.
- ✓
Use a universally unique identifier (UUID) as the primary key
Why this is correct
Distributes writes uniformly across splits.
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Same concept, more angles
1 more way 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. Refer to the exhibit. The team notices high write latency on the Events table. They are inserting 1,000 events per second. The EventId is generated by a sequence. What is the most likely issue?
hard- ✓ A.The sequential primary key creates a hotspot on a single split.
- B.The allow_commit_timestamp option on CreatedAt column adds overhead.
- C.The BYTES(MAX) data type causes excessive writing.
- D.The node count is insufficient for the write throughput.
Why A: The sequential primary key (EventId generated by a sequence) causes all new writes to be directed to the last tablet or split in the table, creating a hotspot. In Cloud Spanner, this leads to contention on a single split, increasing write latency despite adequate overall throughput capacity.
Last reviewed: Jun 30, 2026
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