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  2. Snowflake Certification
  3. SnowPro-Core Exam
  4. Snowflake.SnowPro-Core.v2024-10-07.q429 Dumps
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Question 296

Which of the following are best practice recommendations that should be considered when loading data into Snowflake? (Select TWO).

Correct Answer: C,D
Explanation
https://docs.snowflake.com/en/user-guide/data-load-considerations-prepare.html
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Question 297

What are common issues found by using the Query Profile? (Choose two.)

Correct Answer: D,E
The Query Profile in Snowflake is used to identify performance issues with queries. Common issues that can be found using the Query Profile include identifying inefficient micro-partition pruning (D) and data spilling to a local or remote disk (E). Micro-partition pruning is related to the efficiency of query execution, and data spilling occurs when the memory is insufficient, causing the query to write data to disk, which can slow down the query performance1.
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Question 298

True or False: Reader Accounts are able to extract data from shared data objects for use outside of Snowflake.

Correct Answer: B
Reader accounts in Snowflake are designed to allow users to read data shared with them but do not have the capability to extract data for use outside of Snowflake. They are intended for consuming shared data within the Snowflake environment only.
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Question 299

Which categories are included in the execution time summary in a Query Profile? (Select TWO).

Correct Answer: A,C
In the execution time summary of a Query Profile in Snowflake, the categories included provide insights into various aspects of query execution. "Pruning" refers to the process by which Snowflake reduces the amount of data scanned by eliminating partitions of data that are not relevant to the query, thus improving performance.
"Initialization" represents the time taken for query planning and setup before actual execution begins. These metrics are crucial for understanding and optimizing query performance.
Reference: Snowflake Documentation on the Query Profile, which outlines the different metrics and categories included in the execution summary:
https://docs.snowflake.com/en/user-guide/ui-query-profile.html#execution-summary
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Question 300

Will data cached in a warehouse be lost when the warehouse is resized?

Correct Answer: C
When a Snowflake virtual warehouse is resized, the data cached in the warehouse is not lost. This is because the cache is maintained independently of the warehouse size. Resizing a warehouse, whether scaling up or down, does not affect the cached data, ensuring that query performance is not impacted by such changes.
References:
* [COF-C02] SnowPro Core Certification Exam Study Guide
* Snowflake Documentation on Virtual Warehouse Performance1
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