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 #281
How many credits does a size 3X-Large virtual warehouse consume if it runs continuously for 2 hours?
- A . 32
- B . 64
- C . 128
- D . 256
Correct Answer: C
C
Explanation:
In Snowflake, the consumption of credits by a virtual warehouse is determined by its size and the duration for which it runs. A size 3X-Large virtual warehouse consumes 128 credits if it runs continuously for 2 hours. This consumption rate is based on the principle that larger warehouses, capable of providing greater computational resources and throughput, consume more credits per hour of operation. The specific rate of consumption is defined by Snowflake’s pricing model and the scale of the virtual warehouse.
References: Snowflake Pricing Documentation
C
Explanation:
In Snowflake, the consumption of credits by a virtual warehouse is determined by its size and the duration for which it runs. A size 3X-Large virtual warehouse consumes 128 credits if it runs continuously for 2 hours. This consumption rate is based on the principle that larger warehouses, capable of providing greater computational resources and throughput, consume more credits per hour of operation. The specific rate of consumption is defined by Snowflake’s pricing model and the scale of the virtual warehouse.
References: Snowflake Pricing Documentation
Question #282
Which privilege grants the ability to set a column-level security masking policy on a table or view column?
- A . APPLY
- B . CREATE
- C . SET
- D . MODIFY
Correct Answer: A
A
Explanation:
In Snowflake, the APPLY privilege is required to set a masking policy on a table or view column. This privilege allows a user to associate a masking policy with a specific column, thereby controlling how data in that column is masked or hidden.
Create a Masking Policy: Define a masking policy using the CREATE MASKING POLICY command.
Grant APPLY Privilege: Grant the APPLY privilege on the masking policy to the relevant roles or users.
Apply the Masking Policy: Use the ALTER TABLE or ALTER VIEW command to apply the masking policy to a column.
References:
Snowflake Documentation: Data Masking
Snowflake Documentation: CREATE MASKING POLICY
Snowflake Documentation: Privileges for Masking Policies
A
Explanation:
In Snowflake, the APPLY privilege is required to set a masking policy on a table or view column. This privilege allows a user to associate a masking policy with a specific column, thereby controlling how data in that column is masked or hidden.
Create a Masking Policy: Define a masking policy using the CREATE MASKING POLICY command.
Grant APPLY Privilege: Grant the APPLY privilege on the masking policy to the relevant roles or users.
Apply the Masking Policy: Use the ALTER TABLE or ALTER VIEW command to apply the masking policy to a column.
References:
Snowflake Documentation: Data Masking
Snowflake Documentation: CREATE MASKING POLICY
Snowflake Documentation: Privileges for Masking Policies
Question #283
Which object can be used to query the data loading history for the last 365 days for a Snowflake account?
A)
B)
C)
D)
- A . Option A
- B . Option B
- C . Option C
- D . Option D
Correct Answer: A
Question #284
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
A, C
Explanation:
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.
References: Snowflake documentation on performance tuning and query optimization techniques, specifically how query pruning affects data access.
A, C
Explanation:
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.
References: Snowflake documentation on performance tuning and query optimization techniques, specifically how query pruning affects data access.
Question #285
A table needs to be loaded. The input data is in JSON format and is a concatenation of multiple JSON documents. The file size is 3 GB. A warehouse size small is being used.
The following COPY INTO command was executed:
COPY INTO SAMPLE FROM @~/SAMPLE.JSON (TYPE=JSON)
The load failed with this error:
Max LOB size (16777216) exceeded, actual size of parsed column is 17894470.
How can this issue be resolved?
- A . Compress the file and load the compressed file.
- B . Split the file into multiple files in the recommended size range (100 MB – 250 MB).
- C . Use a larger-sized warehouse.
- D . Set STRIP_OUTER_ARRAY=TRUE in the COPY INTO command.
Correct Answer: B
B
Explanation:
The error “Max LOB size (16777216) exceeded” indicates that the size of the parsed column exceeds the maximum size allowed for a single column value in Snowflake, which is 16 MB. To resolve this issue, the file should be split into multiple smaller files that are within the recommended size range of 100 MB to 250 MB. This will ensure that each JSON document within the files is smaller than the maximum LOB size allowed. Compressing the file, using a larger-sized warehouse, or setting STRIP_OUTER_ARRAY=TRUE will not resolve the issue of the column size exceeding the maximum allowed.
References: COPY INTO Error during Structured Data Load: “Max LOB size (16777216) exceeded…”
B
Explanation:
The error “Max LOB size (16777216) exceeded” indicates that the size of the parsed column exceeds the maximum size allowed for a single column value in Snowflake, which is 16 MB. To resolve this issue, the file should be split into multiple smaller files that are within the recommended size range of 100 MB to 250 MB. This will ensure that each JSON document within the files is smaller than the maximum LOB size allowed. Compressing the file, using a larger-sized warehouse, or setting STRIP_OUTER_ARRAY=TRUE will not resolve the issue of the column size exceeding the maximum allowed.
References: COPY INTO Error during Structured Data Load: “Max LOB size (16777216) exceeded…”
Question #286
Which role is responsible for managing the billing and credit data within Snowflake?
- A . ORGADMIN
- B . ACCOUNTADMIN
- C . SYSADMIN
- D . SECURITYADMIN
Correct Answer: A
A
Explanation:
The ORGADMIN role in Snowflake is responsible for managing organization-level administrative functions, which include managing billing and credit data. This role has the highest level of administrative privileges and can oversee multiple Snowflake accounts within an organization.
References: Snowflake Documentation: Account and Organization Roles
A
Explanation:
The ORGADMIN role in Snowflake is responsible for managing organization-level administrative functions, which include managing billing and credit data. This role has the highest level of administrative privileges and can oversee multiple Snowflake accounts within an organization.
References: Snowflake Documentation: Account and Organization Roles
Question #287
Which formats does Snowflake store unstructured data in? (Choose two.)
- A . GeoJSON
- B . Array
- C . XML
- D . Object
- E . BLOB
Correct Answer: A, C
A, C
Explanation:
Snowflake supports storing unstructured data and provides native support for semi-structured file formats such as JSON, Avro, Parquet, ORC, and XML1. GeoJSON, being a type of JSON, and XML are among the formats that can be stored in Snowflake.
References: [COF-C02] SnowPro Core Certification Exam Study Guide
A, C
Explanation:
Snowflake supports storing unstructured data and provides native support for semi-structured file formats such as JSON, Avro, Parquet, ORC, and XML1. GeoJSON, being a type of JSON, and XML are among the formats that can be stored in Snowflake.
References: [COF-C02] SnowPro Core Certification Exam Study Guide
Question #288
What type of function returns one value for each Invocation?
- A . Aggregate
- B . Scalar
- C . Table
- D . Window
Correct Answer: B
B
Explanation:
Scalar functions in Snowflake (and SQL in general) are designed to return a single value for each invocation. They operate on a single value and return a single result, making them suitable for a wide range of data transformations and calculations within queries.
References: Snowflake Documentation: Functions
B
Explanation:
Scalar functions in Snowflake (and SQL in general) are designed to return a single value for each invocation. They operate on a single value and return a single result, making them suitable for a wide range of data transformations and calculations within queries.
References: Snowflake Documentation: Functions
Question #289
Which of the following accurately describes shares?
- A . Tables, secure views, and secure UDFs can be shared
- B . Shares can be shared
- C . Data consumers can clone a new table from a share
- D . Access to a share cannot be revoked once granted
Correct Answer: A
A
Explanation:
Shares in Snowflake are named objects that encapsulate all the information required to share databases, schemas, tables, secure views, and secure UDFs. These objects can be added to a share by granting privileges on them to the share via a database role
A
Explanation:
Shares in Snowflake are named objects that encapsulate all the information required to share databases, schemas, tables, secure views, and secure UDFs. These objects can be added to a share by granting privileges on them to the share via a database role
Question #290
Which solution improves the performance of point lookup queries that return a small number of rows from large tables using highly selective filters?
- A . Automatic clustering
- B . Materialized views
- C . Query acceleration service
- D . Search optimization service
Correct Answer: D
D
Explanation:
The search optimization service improves the performance of point lookup queries on large tables by using selective filters to quickly return a small number of rows. It creates an optimized data structure that helps in pruning the micro-partitions that do not contain the queried values3.
References: [COF-C02] SnowPro Core Certification Exam Study Guide
D
Explanation:
The search optimization service improves the performance of point lookup queries on large tables by using selective filters to quickly return a small number of rows. It creates an optimized data structure that helps in pruning the micro-partitions that do not contain the queried values3.
References: [COF-C02] SnowPro Core Certification Exam Study Guide