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Question 399 of 1,446

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

A Cloud Spanner instance has a single node and is experiencing high write contention. The workload is 3000 writes per second with 2 KB mutations. Which two changes would improve write throughput? (Choose TWO.)

⚠ Common exam trap

Commonly, candidates think scaling nodes alone solves write contention, but the trap is that while adding nodes increases throughput capacity, it does not fix hotspotting from a poorly designed primary key—so both changes are needed for optimal write throughput.

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

Redesign the primary key to distribute writes evenly across splits.

High write contention in Cloud Spanner often stems from hotspotting, where all writes target the same split. By redesigning the primary key to distribute writes evenly across splits, you reduce contention and improve throughput. This is a fundamental design pattern for Spanner's distributed architecture.

Answer analysis

Option-by-option breakdown

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

  • Redesign the primary key to distribute writes evenly across splits.

    Why this is correct

    Even distribution reduces contention.

  • Increase the mutation size to 10 KB to reduce number of writes.

    Why it's wrong here

    Larger mutations don't reduce contention; they increase load.

  • Scale the instance to 2 nodes.

    Why this is correct

    More nodes increase write capacity.

  • Use a monotonically increasing primary key to improve index performance.

    Why it's wrong here

    Monotonically increasing keys cause hotspots.

  • Split the table into multiple smaller tables.

    Why it's wrong here

    Doesn't increase throughput.

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Last reviewed: Jul 4, 2026

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