Courseiva

PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions

A team is designing a Cloud Spanner schema for a global social media application. The table 'Posts' has a primary key of (UserId, PostId) where PostId is a UUID. They notice write hotspots on the server with monotonically increasing UserId values. What is the most effective schema design change to distribute writes evenly?

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

Add a hash prefix to the UserId to create a composite primary key like (HashUserId, UserId, PostId)

Using a hash prefix on the first part of the primary key (e.g., hash of UserId) helps distribute writes across splits, avoiding hotspots. Using a UUID for PostId is good but UserId ordering still causes hotspots. Adding a timestamp as a second part doesn't help. Interleaving with User is fine but doesn't fix the hotspot issue.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Add a hash prefix to the UserId to create a composite primary key like (HashUserId, UserId, PostId)

    Why this is correct

    Hashing the UserId distributes writes across splits, reducing hotspots while allowing range scans on UserId after filtering.

  • Create a secondary index on PostId

    Why it's wrong here

    Secondary indexes don't affect primary table write distribution; hotspots remain.

  • Place PostId first in the primary key

    Why it's wrong here

    If PostId is UUID, it distributes writes, but the query pattern likely filters by UserId; reversing order may hurt performance.

  • Use a monotonically increasing integer for PostId instead of UUID

    Why it's wrong here

    Monotonically increasing keys cause hotspots; UUIDs are better. This would worsen the problem.

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