ARA-C01 Performance Optimization Practice Question
An architect is considering the Query Acceleration Service (QAS) for a specific workload. Which type of query is most likely to benefit from QAS?
⚠ Common exam trap
Candidates often assume QAS improves all slow queries, whereas it specifically targets large-scale scans that would otherwise consume excessive resources on the primary warehouse.
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
✓
A query that scans a large volume of data but filters it down significantly.
The Query Acceleration Service (QAS) acts like an 'adhoc' burst of compute for specific parts of a query, typically large scans or filters. It is most effective for 'outlier' queries that scan massive amounts of data but produce few rows, allowing the main warehouse to avoid being bogged down by a single massive scan.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Small, frequent point-lookups on a table with Search Optimization enabled.
Why it's wrong here
Point lookups that already use the Search Optimization Service do not benefit from QAS. SOS already minimizes the amount of data scanned to a very small number of rows. QAS is designed to help with massive scans where the warehouse nodes are the bottleneck in reading data from storage.
- ✓
A query that scans a large volume of data but filters it down significantly.
Why this is correct
QAS is ideal for queries that perform massive table scans or filters that are compute-intensive. By offloading these scans to the QAS shared compute resources, the query can complete much faster without requiring the user to permanently resize their warehouse to a larger, more expensive T-shirt size.
- ✗
A query that is currently spilling data to remote storage during a sort.
Why it's wrong here
QAS currently focuses on offloading scan and filter operations. It does not provide additional memory for sort or join operations that are causing spilling. To resolve spilling issues, the architect should still look at increasing the warehouse size (Vertical Scaling) to provide more local resources.
- ✗
A query that is entirely served from the Snowflake Result Cache.
Why it's wrong here
If a query is served from the Result Cache, no compute resources are used at all, as the result is already pre-calculated and stored in the Global Services layer. QAS would never be invoked for such a query because there is no scanning or processing required to return the result.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This ARA-C01 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the ARA-C01 exam.