Optimize Query Performance COF-C03 Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   What is a benefit of Snowflake's result cache?

   • AIt automatically rewrites queries to be more efficient
   • BIt reduces query execution time and compute cost for repeated identical queries
   • CIt improves the performance of all queries on a table
   • DIt stores the query text for later auditing
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2. 22application · medium

   A query joins a large fact table (100 million rows) with a small dimension table (1,000 rows) on a non-distributed key. The query runs slowly, and the query profile shows that the join step processes a large amount of data. The fact table is filtered on a date column. What is the most effective way to reduce the join's intermediate data?

   • AIncrease the warehouse size.
   • BPush the date filter into a subquery before the join.
   • CUse a RIGHT OUTER JOIN instead of an INNER JOIN.
   • DAdd a clustering key on the join column.
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4. 23foundation · easy

   Which join type in Snowflake is most efficient when one table is significantly smaller than the other and the join key is not unique?

   • ALEFT OUTER JOIN
   • BFULL OUTER JOIN
   • CCROSS JOIN
   • DINNER JOIN
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5. 24foundation · easy

   What is the purpose of the EXPLAIN command in Snowflake?

   • ATo execute a query and return the results
   • BTo show the execution plan of a query without actually running it
   • CTo optimize a query automatically
   • DTo create an index on a table
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6. 25application · medium

   A table stores IoT sensor readings with columns `device_id`, `timestamp`, and `value`. Queries often filter on `timestamp` ranges and `device_id`. The table is large and unclustered. The team wants to improve query performance by reducing the number of micro-partitions scanned. What should they do?

   • ACreate a materialized view on the table.
   • BCreate a clustering key on `timestamp` and `device_id`.
   • CEnable search optimization on the table.
   • DUse a larger warehouse.
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