Practice Free SOL-C01 Exam Online Questions
Question #1
What is the purpose of the COPY INTO SQL command?
- A . To copy data into a virtual warehouse
- B . To copy data from one table into another
- C . To load data from a stage into a table
- D . To duplicate all files on a stage
Correct Answer: C
C
Explanation:
COPY INTO <table> loads data from staged files (internal or external stages) into a Snowflake table.
It supports pattern matching, file formats, error-handling modes, and parallel loading.
It does not move files, does not load to a warehouse (warehouses only supply compute), and table-to-table copying uses INSERT INTO…SELECT.
C
Explanation:
COPY INTO <table> loads data from staged files (internal or external stages) into a Snowflake table.
It supports pattern matching, file formats, error-handling modes, and parallel loading.
It does not move files, does not load to a warehouse (warehouses only supply compute), and table-to-table copying uses INSERT INTO…SELECT.
Question #2
Before below options what you need for executing INSERT command in Snowflake worksheet?
- A . Active Warehouse
- B . Schema
- C . Database
- D . All of them
Correct Answer: D
D
Explanation:
Executing an INSERT command in a Snowflake worksheet requires three components to be explicitly selected:
Active WarehouseC Provides compute resources to process the query. Without an active warehouse, DML operations cannot execute.
DatabaseC The table receiving the INSERT must reside in the active database context.
SchemaC The targeted table must be within a selected schema.
All three define the fully qualified context for locating and writing to the correct object. Snowflake’s compute/storage separation ensures compute is only used when warehouses are active. Schema and database selection ensure correct namespace resolution.
D
Explanation:
Executing an INSERT command in a Snowflake worksheet requires three components to be explicitly selected:
Active WarehouseC Provides compute resources to process the query. Without an active warehouse, DML operations cannot execute.
DatabaseC The table receiving the INSERT must reside in the active database context.
SchemaC The targeted table must be within a selected schema.
All three define the fully qualified context for locating and writing to the correct object. Snowflake’s compute/storage separation ensures compute is only used when warehouses are active. Schema and database selection ensure correct namespace resolution.
Question #3
What kind of information can be found in Query History in Snowsight? (Select THREE)
- A . Virtual Warehouse size used
- B . Credit consumption
- C . Execution Status (e.g. Succeeded, Failed)
- D . Duration of the query
- E . Query ID
Correct Answer: C, D, E
C, D, E
Explanation:
Query History in Snowsight includes:
• Query ID C A unique identifier for each executed query.
• Execution Status C Indicates whether the query succeeded, failed, or was canceled.
• Duration C Total time taken for the query to run.
While warehouse name is shown, warehouse size is not explicitly displayed. Credit consumption appears in Account Usage views, not directly in Query History.
C, D, E
Explanation:
Query History in Snowsight includes:
• Query ID C A unique identifier for each executed query.
• Execution Status C Indicates whether the query succeeded, failed, or was canceled.
• Duration C Total time taken for the query to run.
While warehouse name is shown, warehouse size is not explicitly displayed. Credit consumption appears in Account Usage views, not directly in Query History.
Question #4
Which of the following are benefits of using a multi-clustered warehouse in Snowflake? (Choose any 3 options)
- A . Improved query performance during peak load
- B . Automatic scaling of clusters based on query demand
- C . Reduced storage costs
- D . Increased compute capacity
Correct Answer: A, B, D
A, B, D
Explanation:
A multi-cluster warehouse raises Snowflake’s capability to handle concurrent workloads efficiently. When large numbers of users or queries hit the system, Snowflake can automatically start additional clusters (scaling out) to distribute workloads, reducing queuing and improving performance. As query demand drops, Snowflake scales in by shutting down clusters to conserve credits. This dynamic auto-scaling provides significantly increased compute capacity during peak usage periods and enhances responsiveness. Importantly, multi-cluster warehouses affect only compute, not storage, so they do not reduce storage costs. Their primary benefits revolve around performance stability, concurrency handling, workload isolation, and compute elasticity.
A, B, D
Explanation:
A multi-cluster warehouse raises Snowflake’s capability to handle concurrent workloads efficiently. When large numbers of users or queries hit the system, Snowflake can automatically start additional clusters (scaling out) to distribute workloads, reducing queuing and improving performance. As query demand drops, Snowflake scales in by shutting down clusters to conserve credits. This dynamic auto-scaling provides significantly increased compute capacity during peak usage periods and enhances responsiveness. Importantly, multi-cluster warehouses affect only compute, not storage, so they do not reduce storage costs. Their primary benefits revolve around performance stability, concurrency handling, workload isolation, and compute elasticity.
Question #5
What is the purpose of assigning roles to users in Snowflake?
- A . To manage and enforce permissions on objects
- B . To define user tasks
- C . To optimize query execution plans
- D . To control which data types users can query
Correct Answer: A
A
Explanation:
Snowflake uses a Role-Based Access Control (RBAC) model, whererolesare the containers of privileges. Assigning roles to users ensures that permissions on database objects (such as tables, schemas, warehouses, and functions) are enforced consistently and securely. Users do not receive privileges directly; instead, privileges are granted to roles, and roles are assigned to users.
This enables scalable, auditable, and manageable access control.
Roles do not determine tasks, do not affect query optimization, and do not govern which data types a user may query―permissions are object-based, not datatype-based.
A
Explanation:
Snowflake uses a Role-Based Access Control (RBAC) model, whererolesare the containers of privileges. Assigning roles to users ensures that permissions on database objects (such as tables, schemas, warehouses, and functions) are enforced consistently and securely. Users do not receive privileges directly; instead, privileges are granted to roles, and roles are assigned to users.
This enables scalable, auditable, and manageable access control.
Roles do not determine tasks, do not affect query optimization, and do not govern which data types a user may query―permissions are object-based, not datatype-based.
Question #6
What is the purpose of auto-resume on a virtual warehouse?
- A . To restart the warehouse manually after suspension.
- B . To automatically start the warehouse when a query is submitted to it.
- C . To automatically scale up the warehouse size.
- D . To prevent the warehouse from suspending.
Correct Answer: B
B
Explanation:
When auto-resume is enabled, Snowflake automatically starts a suspended warehouse when a query or task is submitted. This ensures smooth operations without manual intervention.
It does not scale the warehouse, prevent suspension, or require manual restarting.
B
Explanation:
When auto-resume is enabled, Snowflake automatically starts a suspended warehouse when a query or task is submitted. This ensures smooth operations without manual intervention.
It does not scale the warehouse, prevent suspension, or require manual restarting.
Question #7
What is a key characteristic of a Snowflake virtual warehouse?
- A . It provides compute resources.
- B . It manages account roles.
- C . It permanently stores data.
- D . It encrypts data.
Correct Answer: A
A
Explanation:
A virtual warehouse is the compute engine of Snowflake. It provides CPU, memory, and temporary storage needed to execute SQL queries, data loading operations, and DML actions. Warehouses can be sized dynamically and suspended or resumed to optimize cost.
Warehouses donotstore data; Snowflake’s storage is independent and centralized. Warehouses do not manage roles―access control is handled through Snowflake’s RBAC system. Encryption is performed automatically by Snowflake’s storage and cloud services, not by warehouses.
Thus, the correct characteristic is that virtual warehouses supply compute.
If you’d like, I can provide Questions 42C55 next, with the same 150C200-word explanations.
You said:
Questions 42C55 next, with the same 150C200-word explanations
ChatGPT said:
Below are Questions 42C55, all formatted exactly per your requirements, with150C200-word explanations and every original option preserved exactly.
A
Explanation:
A virtual warehouse is the compute engine of Snowflake. It provides CPU, memory, and temporary storage needed to execute SQL queries, data loading operations, and DML actions. Warehouses can be sized dynamically and suspended or resumed to optimize cost.
Warehouses donotstore data; Snowflake’s storage is independent and centralized. Warehouses do not manage roles―access control is handled through Snowflake’s RBAC system. Encryption is performed automatically by Snowflake’s storage and cloud services, not by warehouses.
Thus, the correct characteristic is that virtual warehouses supply compute.
If you’d like, I can provide Questions 42C55 next, with the same 150C200-word explanations.
You said:
Questions 42C55 next, with the same 150C200-word explanations
ChatGPT said:
Below are Questions 42C55, all formatted exactly per your requirements, with150C200-word explanations and every original option preserved exactly.
Question #8
What SQL command will return a list of all files in a stage?
- A . PUT
- B . LIST
- C . GET
- D . COPY INTO
Correct Answer: B
B
Explanation:
LIST @stage_name displays all files present in a stage (internal or external).
PUT uploads local files to an internal stage.
GET downloads files from an internal stage.
COPY INTO loads or unloads data but does not list files.
B
Explanation:
LIST @stage_name displays all files present in a stage (internal or external).
PUT uploads local files to an internal stage.
GET downloads files from an internal stage.
COPY INTO loads or unloads data but does not list files.
Question #9
How is the initial activation of the Snowflake Data Exchange feature, which is necessary for establishing private exchanges, typically accomplished?
- A . Any Snowflake account administrator can enable Data Exchange with a click.
- B . Data Exchange is automatically enabled for all accounts.
- C . Activation requires a SQL command executed by ACCOUNTADMIN.
- D . Activation requires a request to Snowflake Support.
Correct Answer: D
D
Explanation:
Snowflake Data Exchange is not enabled by default. Accounts must open a support request to Snowflake Support, which then activates the feature. It cannot be enabled via UI or SQL. After activation, administrators may create private exchanges and listings.
D
Explanation:
Snowflake Data Exchange is not enabled by default. Accounts must open a support request to Snowflake Support, which then activates the feature. It cannot be enabled via UI or SQL. After activation, administrators may create private exchanges and listings.
Question #10
What is the function of the SKIP_HEADER file format option when loading CSV data?
- A . To include the header row as data.
- B . To ignore empty rows in the data file.
- C . To skip a specified number of header rows.
- D . To automatically create column names from the header row.
Correct Answer: C
C
Explanation:
The SKIP_HEADER option instructs Snowflake to ignore a defined number of initial rows, typically the column header row in CSV files.
For example:
CREATE FILE FORMAT my_fmt
TYPE=’CSV’
SKIP_HEADER=1;
When used with COPY INTO, Snowflake loads only the actual data rows while excluding header metadata. This prevents header values from being inserted as data and ensures consistent row structure.
Other options:
SKIP_BLANK_LINES controls handling of empty rows, not headers.
Snowflake does not auto-generate column names from header rows; table schemas must be predefined.
Including header rows as data is undesirable and incorrect in most pipelines.
Thus, SKIP_HEADER is used exclusively to omit header rows during ingestion.
C
Explanation:
The SKIP_HEADER option instructs Snowflake to ignore a defined number of initial rows, typically the column header row in CSV files.
For example:
CREATE FILE FORMAT my_fmt
TYPE=’CSV’
SKIP_HEADER=1;
When used with COPY INTO, Snowflake loads only the actual data rows while excluding header metadata. This prevents header values from being inserted as data and ensures consistent row structure.
Other options:
SKIP_BLANK_LINES controls handling of empty rows, not headers.
Snowflake does not auto-generate column names from header rows; table schemas must be predefined.
Including header rows as data is undesirable and incorrect in most pipelines.
Thus, SKIP_HEADER is used exclusively to omit header rows during ingestion.