ARA-C01 Performance Optimization Practice Question
Which THREE factors should be considered when evaluating the cost-benefit of enabling the Search Optimization Service on a large table? (Choose three.)
⚠ Common exam trap
Candidates often assume the Search Optimization Service is 'free' or always beneficial, forgetting that it incurs both storage costs and performance overhead during frequent DML operations.
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 frequency and selectivity of point lookup queries.
The Search Optimization Service is a powerful tool, but it carries costs related to storage and maintenance. Enabling it for columns with very low selectivity (e.g., boolean flags) provides little benefit while incurring continuous costs. Architects must balance the gain in query performance for point lookups against the DML overhead and the additional storage required to maintain the index structures.
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 frequency and selectivity of point lookup queries.
Why this is correct
Search optimization is most effective when queries are frequent and highly selective, returning only a small number of rows. If queries are infrequent or scan a large portion of the table, the cost of the service will likely outweigh the performance benefits provided by the indexed lookup structure.
- ✓
The rate of DML operations on the table.
Why this is correct
DML operations (INSERT, UPDATE, DELETE) trigger updates to the search optimization metadata. High rates of DML can lead to increased maintenance costs and potential latency in index updates. Understanding the DML volume is crucial to ensuring that the performance gains in queries are not negated by the maintenance overhead.
- ✗
The total number of rows in the table.
Why it's wrong here
While table size matters, search optimization is specifically designed for huge tables where scanning is prohibitive. The primary consideration is not just the size, but the query patterns and selectivity. A massive table that is rarely queried via point lookups would not benefit from the service's overhead.
- ✓
The storage costs associated with the search optimization indices.
Why this is correct
Search optimization creates additional data structures that reside in storage and incur costs. Architects must weigh these ongoing storage costs against the performance requirements of the business. If the performance requirement is not critical, the added storage cost may not be justified for the given table or column.
- ✗
The number of concurrent users accessing the warehouse.
Why it's wrong here
Concurrent user load is managed by scaling the warehouse horizontally, not by search optimization. While search optimization speeds up individual queries, it does not solve concurrency issues. The decision to use search optimization should be driven by query efficiency needs rather than the total number of active users.
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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.