COF-C03 Practice Question: Performance Optimization, Querying, and Transformation
Which TWO conditions must be met for the Query Acceleration Service (QAS) to boost the performance of a query?
⚠ Common exam trap
Candidates often assume QAS automatically accelerates all queries. They miss that it only triggers for specific scan-heavy operations and requires the explicit warehouse parameter to be set.
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
✓
The query must be identified by the system as having a large scan component.
The Query Acceleration Service (QAS) acts like a 'turbocharger' by offloading parts of a query to a shared pool of compute resources. It is specifically designed for queries that are bottlenecked by scanning large amounts of data or performing heavy filtering, and the warehouse must have QAS enabled with a valid scale factor.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The query must involve complex window functions or recursive CTEs.
Why it's wrong here
QAS is primarily designed to accelerate the scanning and filtering of large datasets rather than complex computational logic like window functions or recursion. These operations usually happen later in the query pipeline and are handled by the main virtual warehouse resources rather than the acceleration service.
- ✓
The query must be identified by the system as having a large scan component.
Why this is correct
Snowflake's optimizer determines if a query is eligible for QAS based on whether it needs to scan a massive number of micro-partitions. If a query only processes a small amount of data, the overhead of coordinating with the acceleration service would not provide any benefit.
- ✓
The virtual warehouse must have the ENABLE_QUERY_ACCELERATION parameter set to TRUE.
Why this is correct
QAS is not enabled by default for all warehouses. An administrator must explicitly enable the service on the warehouse and can optionally set a scale factor to limit the maximum amount of additional compute resources the service can utilize for any single query.
- ✗
The table being queried must be a clustered table.
Why it's wrong here
QAS works independently of whether a table is clustered. In fact, QAS is often most helpful for tables that are not perfectly clustered, as it provides the massive parallel scanning power needed to quickly sift through unorganized micro-partitions to find the relevant data.
- ✗
The query results must be larger than 100 GB.
Why it's wrong here
The size of the final result set is not a determining factor for QAS eligibility. QAS focuses on the work performed at the beginning of the query execution—specifically the scanning of raw data—rather than the volume of data that is eventually returned to the user.
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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
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