Snowflake COF-C02 Practice Exams
Last updated on Oct 24,2026- Exam Code: COF-C02
- Exam Name: SnowPro Core Certification Exam
- Certification Provider: Snowflake
- Latest update: Oct 24,2026
Question #271
Which view in SNOWFLAKE.ACCOUNT_USAGE shows from which IP address a user connected to Snowflak?
- A . ACCESS_HOSTORY
- B . LOGIN_HISTORY
- C . SESSIONS
- D . QUERY HISTORY
Correct Answer: B
B
Explanation:
The LOGIN_HISTORY view in SNOWFLAKE.ACCOUNT_USAGE shows from which IP address a user connected to Snowflake. This view is particularly useful for auditing and monitoring purposes, as it helps administrators track login attempts, successful logins, and the geographical location of users based on their IP addresses.
Reference to Snowflake documentation on LOGIN_HISTORY:
Monitoring Login Attempts
B
Explanation:
The LOGIN_HISTORY view in SNOWFLAKE.ACCOUNT_USAGE shows from which IP address a user connected to Snowflake. This view is particularly useful for auditing and monitoring purposes, as it helps administrators track login attempts, successful logins, and the geographical location of users based on their IP addresses.
Reference to Snowflake documentation on LOGIN_HISTORY:
Monitoring Login Attempts
Question #272
Which SQL command can be used to verify the privileges that are granted to a role?
- A . SHOW GRANTS ON ROLE <Role Name>
- B . SHOW ROLES <Role Name>
- C . SHOW GRANTS TO ROLE <Role Name>
- D . SHOW GRANTS FOR ROLE <Role Name>
Correct Answer: C
C
Explanation:
To verify the privileges that have been granted to a specific role in Snowflake, the correct SQL command is SHOW GRANTS TO ROLE <Role Name>. This command lists all the privileges granted to the specified role, including access to schemas, tables, and other database objects. This is a useful command for administrators and users with sufficient privileges to audit and manage role permissions within the Snowflake environment.
References: Snowflake Documentation: SHOW GRANTS
C
Explanation:
To verify the privileges that have been granted to a specific role in Snowflake, the correct SQL command is SHOW GRANTS TO ROLE <Role Name>. This command lists all the privileges granted to the specified role, including access to schemas, tables, and other database objects. This is a useful command for administrators and users with sufficient privileges to audit and manage role permissions within the Snowflake environment.
References: Snowflake Documentation: SHOW GRANTS
Question #273
What happens to the underlying table data when a CLUSTER BY clause is added to a Snowflake table?
- A . Data is hashed by the cluster key to facilitate fast searches for common data values
- B . Larger micro-partitions are created for common data values to reduce the number of partitions that must be scanned
- C . Smaller micro-partitions are created for common data values to allow for more parallelism
- D . Data may be colocated by the cluster key within the micro-partitions to improve pruning performance
Correct Answer: D
D
Explanation:
When a CLUSTER BY clause is added to a Snowflake table, it specifies one or more columns to organize the data within the table’s micro-partitions. This clustering aims to colocate data with similar values in the same or adjacent micro-partitions. By doing so, it enhances the efficiency of query pruning, where the Snowflake query optimizer can skip over irrelevant micro-partitions that do not contain the data relevant to the query, thereby improving performance.
References:
Snowflake Documentation on Clustering Keys & Clustered Tables1.
Community discussions on how source data’s ordering affects a table with a cluster key
D
Explanation:
When a CLUSTER BY clause is added to a Snowflake table, it specifies one or more columns to organize the data within the table’s micro-partitions. This clustering aims to colocate data with similar values in the same or adjacent micro-partitions. By doing so, it enhances the efficiency of query pruning, where the Snowflake query optimizer can skip over irrelevant micro-partitions that do not contain the data relevant to the query, thereby improving performance.
References:
Snowflake Documentation on Clustering Keys & Clustered Tables1.
Community discussions on how source data’s ordering affects a table with a cluster key
Question #274
Who can create and manage reader accounts? (Select TWO).
- A . A user with ACCOUNTADMIN role
- B . A user with securityadmin role
- C . A user with SYSADMIN role
- D . A user with ORGADMIH role
- E . A user with CREATE ACCOUNT privilege
Correct Answer: AD
AD
Explanation:
In Snowflake, reader accounts are special types of accounts that allow data sharing with external consumers without them having their own Snowflake account. The creation and management of reader accounts can be performed by users with the ACCOUNTADMIN role or the ORGADMIN role. The ACCOUNTADMIN role has comprehensive administrative privileges within a Snowflake account, including managing other accounts and roles. The ORGADMIN role, which is higher in hierarchy, oversees multiple accounts within an organization and can manage reader accounts across those accounts.
References: Snowflake Documentation: Creating and Managing Reader Accounts
AD
Explanation:
In Snowflake, reader accounts are special types of accounts that allow data sharing with external consumers without them having their own Snowflake account. The creation and management of reader accounts can be performed by users with the ACCOUNTADMIN role or the ORGADMIN role. The ACCOUNTADMIN role has comprehensive administrative privileges within a Snowflake account, including managing other accounts and roles. The ORGADMIN role, which is higher in hierarchy, oversees multiple accounts within an organization and can manage reader accounts across those accounts.
References: Snowflake Documentation: Creating and Managing Reader Accounts
Question #275
Which operations are handled in the Cloud Services layer of Snowflake? (Select TWO).
- A . Security
- B . Data storage
- C . Data visualization
- D . Query computation
- E . Metadata management
Correct Answer: A, E
A, E
Explanation:
The Cloud Services layer in Snowflake is responsible for various services, including security (like authentication and authorization) and metadata management (like query parsing and optimization).
References: Based on general cloud architecture knowledge as of 2021.
A, E
Explanation:
The Cloud Services layer in Snowflake is responsible for various services, including security (like authentication and authorization) and metadata management (like query parsing and optimization).
References: Based on general cloud architecture knowledge as of 2021.
Question #276
Which Snowflake object can be used to record DML changes made to a table?
- A . Snowpipe
- B . Stage
- C . Stream
- D . Task
Correct Answer: C
C
Explanation:
Snowflake Streams are used to track and record Data Manipulation Language (DML) changes made to a table. Streams capture changes such as inserts, updates, and deletes, which can then be processed by other Snowflake objects or external applications.
Creating a Stream:
CREATE OR REPLACE STREAM my_stream ON TABLE my_table;
Using Streams: Streams provide a way to process changes incrementally, making it easier to build efficient data pipelines.
Consuming Stream Data: The captured changes can be consumed using SQL queries or Snowflake tasks.
References:
Snowflake Documentation: Using Streams
Snowflake Documentation: Change Data Capture (CDC) with Streams
C
Explanation:
Snowflake Streams are used to track and record Data Manipulation Language (DML) changes made to a table. Streams capture changes such as inserts, updates, and deletes, which can then be processed by other Snowflake objects or external applications.
Creating a Stream:
CREATE OR REPLACE STREAM my_stream ON TABLE my_table;
Using Streams: Streams provide a way to process changes incrementally, making it easier to build efficient data pipelines.
Consuming Stream Data: The captured changes can be consumed using SQL queries or Snowflake tasks.
References:
Snowflake Documentation: Using Streams
Snowflake Documentation: Change Data Capture (CDC) with Streams
Question #277
When cloning a database containing stored procedures and regular views, that have fully qualified table references, which of the following will occur?
- A . The cloned views and the stored procedures will reference the cloned tables in the cloned database.
- B . An error will occur, as views with qualified references cannot be cloned.
- C . An error will occur, as stored objects cannot be cloned.
- D . The stored procedures and views will refer to tables in the source database.
Correct Answer: A
A
Explanation:
When cloning a database containing stored procedures and regular views with fully qualified table references, the cloned views and stored procedures will reference the cloned tables in the cloned database (A). This ensures that the cloned database is a self-contained copy of the original, with all references pointing to objects within the same cloned database.
References: SnowPro Core Certification cloning database stored procedures views
A
Explanation:
When cloning a database containing stored procedures and regular views with fully qualified table references, the cloned views and stored procedures will reference the cloned tables in the cloned database (A). This ensures that the cloned database is a self-contained copy of the original, with all references pointing to objects within the same cloned database.
References: SnowPro Core Certification cloning database stored procedures views
Question #278
What is the recommended file sizing for data loading using Snowpipe?
- A . A compressed file size greater than 100 MB, and up to 250 MB
- B . A compressed file size greater than 100 GB, and up to 250 GB
- C . A compressed file size greater than 10 MB, and up to 100 MB
- D . A compressed file size greater than 1 GB, and up to 2 GB
Correct Answer: C
C
Explanation:
For data loading using Snowpipe, the recommended file size is a compressed file greater than 10 MB and up to 100 MB. This size range is optimal for Snowpipe’s continuous, micro-batch loading process, allowing for efficient and timely data ingestion without overwhelming the system with files that are too large or too small.
References:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Snowpipe1
C
Explanation:
For data loading using Snowpipe, the recommended file size is a compressed file greater than 10 MB and up to 100 MB. This size range is optimal for Snowpipe’s continuous, micro-batch loading process, allowing for efficient and timely data ingestion without overwhelming the system with files that are too large or too small.
References:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Snowpipe1
Question #279
How should a virtual warehouse be configured if a user wants to ensure that additional multi-clusters are resumed with no delay?
- A . Configure the warehouse to a size larger than generally required
- B . Set the minimum and maximum clusters to autoscale
- C . Use the standard warehouse scaling policy
- D . Use the economy warehouse scaling policy
Correct Answer: A
A
Explanation:
To ensure that additional multi-clusters are resumed with no delay, a virtual warehouse should be configured to a size larger than generally required. This configuration allows for immediate availability of additional resources when needed, without waiting for new clusters to start up
A
Explanation:
To ensure that additional multi-clusters are resumed with no delay, a virtual warehouse should be configured to a size larger than generally required. This configuration allows for immediate availability of additional resources when needed, without waiting for new clusters to start up
Question #280
What technique does Snowflake use to limit the number of micro-partitions scanned by each query?
- A . B-tree
- B . Indexing
- C . Map reduce
- D . Pruning
Correct Answer: D
D
Explanation:
Snowflake uses a technique called pruning to limit the number of micro-partitions scanned by each query. Pruning effectively filters out unnecessary micro-partitions based on the query’s filter conditions, which can significantly improve query performance by reducing the amount of data scanned1.
D
Explanation:
Snowflake uses a technique called pruning to limit the number of micro-partitions scanned by each query. Pruning effectively filters out unnecessary micro-partitions based on the query’s filter conditions, which can significantly improve query performance by reducing the amount of data scanned1.