PCDOE Optimizing service performance Practice Question
This PCDOE practice question tests your understanding of optimizing service performance. 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 data engineering team runs frequent aggregation queries on a large BigQuery table. Query performance is slow and costs are high. Which optimization technique would best improve performance and reduce cost?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use materialized views for pre-aggregated results
Materialized views pre-compute and store the results of frequent aggregation queries, allowing BigQuery to serve subsequent queries directly from the cached results rather than scanning the entire base table. This drastically reduces the amount of data processed, lowering both query latency and cost (since BigQuery charges by bytes processed). For repeated aggregation patterns, this is the most effective optimization.
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.
✓
Use materialized views for pre-aggregated results
Why this is correct
Materialized views pre-compute and store aggregation results, drastically reducing query time and cost.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Convert to non-partitioned table
Why it's wrong here
Removing partitioning increases data scanned, worsening performance and cost.
✗
Use clustering on the partition key
Why it's wrong here
Clustering organizes data but does not reduce the amount of data scanned for aggregations.
✗
Increase the number of slots in the reservation
Why it's wrong here
More slots increase concurrency but do not reduce query cost per query.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that clustering on the partition key is redundant and that increasing compute resources (slots) is the primary fix for cost and performance, when in reality reducing data scanned through pre-aggregation is the most impactful lever.
Detailed technical explanation
How to think about this question
BigQuery materialized views are automatically maintained incrementally; when the base table is updated, only the changed partitions are re-aggregated, not the entire view. Under the hood, BigQuery uses a combination of the base table's change history and the materialized view's stored results to refresh efficiently. In real-world scenarios, a team running hourly sales aggregations on a multi-terabyte table can reduce query costs by over 90% using materialized views, as each query only processes the incremental changes rather than the full dataset.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use materialized views for pre-aggregated results — Materialized views pre-compute and store the results of frequent aggregation queries, allowing BigQuery to serve subsequent queries directly from the cached results rather than scanning the entire base table. This drastically reduces the amount of data processed, lowering both query latency and cost (since BigQuery charges by bytes processed). For repeated aggregation patterns, this is the most effective optimization.
What should I do if I get this PCDOE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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