Question 883 of 955
Google PCA Practice Question: Analyze and optimize technical and business processes
A company uses BigQuery for analytics. They have a large partitioned table that is queried frequently. The query performance has degraded over time. Which optimization should they try first?
⚠ Common exam trap
Google Cloud often tests the misconception that adding more slots (Option B) is the default performance fix, when in reality the first step should be to reduce data scanned through clustering or partitioning optimization.
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
✓
Apply clustering on frequently filtered columns.
Clustering on frequently filtered columns reorganizes the data within partitions based on the values of those columns, which allows BigQuery to prune blocks more effectively during queries. This directly addresses the performance degradation by reducing the amount of data scanned, without requiring additional storage or compute resources.
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 materialized view for each frequent query.
Why it's wrong here
Materialized views help but are not the first optimization.
- ✗
Increase the number of slots for the project.
Why it's wrong here
More slots improve concurrency but not per-query performance.
- ✓
Apply clustering on frequently filtered columns.
Why this is correct
Clustering sorts data, reducing scanned data for filters.
- ✗
Denormalize the table to reduce joins.
Why it's wrong here
Denormalization may reduce joins but increases storage.
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Last reviewed: Jun 30, 2026
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