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Snowflake Certification
COF-C02 Exam
Snowflake.COF-C02.v2026-01-13.q618 Dumps

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Question 291

At what level is the MIN_DATA_RETENSION_TIME_IN_DAYS parameter set?

A.Account
B.Database
C.Schema
D.Table

Correct Answer: A

TheMIN_DATA_RETENTION_TIME_IN_DAYSparameter is set at theAccountlevel in Snowflake. This parameter specifies the minimum number of days Snowflake retains the historical data for time travel, which allows users to access and query data as it existed at previous points in time.
Here's how to understand and adjust this parameter:
* Purpose of MIN_DATA_RETENTION_TIME_IN_DAYS:This parameter is crucial for managing data lifecycle and compliance requirements within Snowflake. It determines the minimum time frame for which you can perform operations like restoring deleted objects or accessing historical versions of data.
* Setting the Parameter:Only account administrators can set or modify this parameter. It is done at the account level, impacting all databases and schemas within the account. The setting can be adjusted based on the organization's data retention policy.
* Adjusting the Parameter:
* To view the current setting, use:
SHOWPARAMETERSLIKE'MIN_DATA_RETENTION_TIME_IN_DAYS';
* To change the setting, an account administrator can execute:
ALTERACCOUNTSETMIN_DATA_RETENTION_TIME_IN_DAYS = <number_of_days>;
Reference:For more details on data retention and time travel in Snowflake, refer to the official documentation: https://docs.snowflake.com/en/sql-reference/account-usage/storage-usage.html#data-retention- time-travel

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Question 292

The effects of query pruning can be observed by evaluating which statistics? (Select TWO).

A.Partitions scanned
B.Partitions total
C.Bytes scanned
D.Bytes read from result
E.Bytes written

Correct Answer: A,C

Query pruning in Snowflake refers to the optimization technique where the system reduces the amount of data scanned by a query based on the query conditions. This typically involves skipping unnecessary data partitions that do not contribute to the query result. The effectiveness of this technique can be observed through:
Option A: Partitions scanned. This statistic indicates how many data partitions were actually scanned as a result of query pruning, showing the optimization in action.
Option C: Bytes scanned. This measures the volume of data physically read during query execution, and a reduction in this number indicates effective query pruning, as fewer bytes are read when unnecessary partitions are skipped.
Options B, D, and E do not directly relate to observing the effects of query pruning. "Partitions total" shows the total available, not the impact of pruning, while "Bytes read from result" and "Bytes written" relate to output rather than the efficiency of data scanning.
Reference: Snowflake documentation on performance tuning and query optimization techniques, specifically how query pruning affects data access.

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Question 293

Which object type is granted permissions for reading a table?

A.User
B.Role
C.Attribute
D.Schema

Correct Answer: B

In Snowflake, permissions for accessing database objects, including tables, are not granted directly to users but rather to roles. A role encapsulates a collection of privileges on various Snowflake objects. Users are then granted roles, and through those roles, they inherit the permissions necessary to read a table or perform other actions. This approach adheres to the principle of least privilege, allowing for granular control over database access and simplifying the management of user permissions.
Reference: Snowflake's official documentation on access control introduces the concept of roles and how they are used to manage permissions:
https://docs.snowflake.com/en/user-guide/security-access-control-overview.html#roles

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Question 294

Which command should be used to download files from a Snowflake stage to a local folder on a client's machine?

A.PUT
B.GET
C.COPY
D.SELECT

Correct Answer: B

The GET command is used to download files from a Snowflake stage to a local folder on a client's machine2.

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Question 295

What would cause different results to be returned when running the same query twice?

A.SAMPLE is used and the seed is set
B.sample is used and the seed is not set.
C.Fraction-based sampling is used.
D.Fixed-size sampling Is used.

Correct Answer: B

When using the SAMPLE clause in a query, if the seed is not set, Snowflake will use a different random seed for each execution of the query. This results in different rows being sampled each time, leading to different results. Setting a seed ensures that the same rows are sampled each time the query is run.
Snowflake Documentation: Sampling

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