Monitor and Tune Workloads ARA-C01 Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   When does Snowflake's result cache provide the most benefit?

   • AWhen a query runs for the first time on a large table.
   • BWhen the query uses a non-deterministic function like CURRENT_TIMESTAMP.
   • CWhen the same query is run repeatedly and the underlying data has not changed.
   • DWhen the warehouse is suspended.
   Reveal Solution Discussion Select an answer first
2. 7foundation · easy

   Why is it important to avoid very small data files when loading data into Snowflake?

   • ASmall files are not supported by Snowflake.
   • BSmall files cause data to be stored in a different region.
   • CSmall files increase the number of micro-partitions, which can lead to metadata overhead and slower scans.
   • DSmall files prevent the use of clustering keys.
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   What is the primary purpose of a resource monitor in Snowflake?

   • ATo manage user permissions and access control.
   • BTo automatically scale warehouses based on query load.
   • CTo track and limit the credit usage of warehouses or accounts.
   • DTo monitor query performance and identify slow-running queries.
   Reveal Solution Discussion Select an answer first
5. 9expert · hard

   A team is deciding whether to enable Search Optimization Service (SOS) on a large 'customer' table (5 TB) that is frequently queried with point lookups on 'customer_id'. The table also has a materialized view for a daily aggregation. The team is concerned about the cost of SOS. Which statement is correct regarding the cost and maintenance of SOS?

   • ASOS costs are only incurred when queries are run.
   • BSOS is free as long as the table has a clustering key.
   • CSOS costs are included in the warehouse compute costs.
   • DSOS incurs additional storage and compute costs for maintaining the search index, which are billed separately.
   Reveal Solution Discussion Select an answer first
6. 10application · medium

   A platform team wants to proactively detect when a warehouse's queries start spilling to local storage, which indicates memory pressure. They want to be alerted before performance degrades significantly. Which monitoring approach is most appropriate?

   • AEnable the 'Spill' metric in the warehouse's monitoring dashboard.
   • BSet up an alert using the ACCOUNT_USAGE.QUERY_HISTORY view with a condition on 'BYTES_SPILLED_TO_LOCAL_STORAGE' and a notification via email.
   • CUse the QUERY_PROFILE function to manually inspect queries each day.
   • DCreate a task that runs every minute and queries the QUERY_HISTORY view for 'BYTES_SPILLED_TO_LOCAL_STORAGE' > 0.
   Reveal Solution Discussion Select an answer first