File Info
| Exam | SnowPro-Core |
| Number | SnowPro-Core |
| File Name | Snowflake.SnowPro-Core.VCEplus.2024-12-21.183q.vcex |
| Size | 509 KB |
| Posted | Dec 21, 2024 |
| Download | Snowflake.SnowPro-Core.VCEplus.2024-12-21.183q.vcex |
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Demo Questions
Question 1
How can a user improve the performance of a single large complex query in Snowflake?
- Scale up the virtual warehouse.
- Scale out the virtual warehouse.
- Enable standard warehouse scaling.
- Enable economy warehouse scaling.
Correct answer: A
Explanation:
Scaling up the virtual warehouse in Snowflake involves increasing the compute resources available for a single warehouse, which can improve the performance of large and complex queries by providing more CPU and memory resources.Reference:Based on general cloud data warehousing knowledge as of 2021. Scaling up the virtual warehouse in Snowflake involves increasing the compute resources available for a single warehouse, which can improve the performance of large and complex queries by providing more CPU and memory resources.Reference:Based on general cloud data warehousing knowledge as of 2021.
Question 2
Which clients does Snowflake support Multi-Factor Authentication (MFA) token caching for? (Select TWO).
- GO driver
- Node.js driver
- ODBC driver
- Python connector
- Spark connector
Correct answer: CD
Explanation:
Multi-Factor Authentication (MFA) token caching is typically supported for clients that maintain a persistent connection or session with Snowflake, such as the ODBC driver and Python connector, to reduce the need for repeated MFA challenges.Reference:Based on general security practices in cloud services as of 2021. Multi-Factor Authentication (MFA) token caching is typically supported for clients that maintain a persistent connection or session with Snowflake, such as the ODBC driver and Python connector, to reduce the need for repeated MFA challenges.Reference:Based on general security practices in cloud services as of 2021.
Question 3
What computer language can be selected when creating User-Defined Functions (UDFs) using the Snowpark API?
- Swift
- JavaScript
- Python
- SQL
Correct answer: C
Explanation:
The Snowpark API allows developers to create User-Defined Functions (UDFs) in various languages, including Python, which is known for its ease of use and wide adoption in data-related tasks.Reference:Based on general programming and cloud data service knowledge as of 2021. The Snowpark API allows developers to create User-Defined Functions (UDFs) in various languages, including Python, which is known for its ease of use and wide adoption in data-related tasks.Reference:Based on general programming and cloud data service knowledge as of 2021.
Question 4
If file format options are specified in multiple locations, the load operation selects which option FIRST to apply in order of precedence?
- Table definition
- Stage definition
- Session level
- COPY INTO TABLE statement
Correct answer: D
Explanation:
When file format options are specified in multiple locations, the load operation applies the options in the following order of precedence: first, the COPY INTO TABLE statement; second, the stage definition; and third, the table definition1 When file format options are specified in multiple locations, the load operation applies the options in the following order of precedence: first, the COPY INTO TABLE statement; second, the stage definition; and third, the table definition1
Question 5
Which statistics can be used to identify queries that have inefficient pruning? (Select TWO).
- Bytes scanned
- Bytes written to result
- Partitions scanned
- Partitions total
- Percentage scanned from cache
Correct answer: CD
Explanation:
The statistics that can be used to identify queries with inefficient pruning are 'Partitions scanned' and 'Partitions total'.These statistics indicate how much of the data was actually needed and scanned versus the total available, which can highlight inefficiencies in data pruning34. The statistics that can be used to identify queries with inefficient pruning are 'Partitions scanned' and 'Partitions total'.These statistics indicate how much of the data was actually needed and scanned versus the total available, which can highlight inefficiencies in data pruning34.
Question 6
Which ACCOUNT_USAGE schema database role provides visibility into policy-related information?
- USAGE_VIEWER
- GOVERNANCE_VIEWER
- OBJECT_VIEWER
- SECURITY_VIEWER
Correct answer: B
Explanation:
The GOVERNANCE_VIEWER role in the ACCOUNT_USAGE schema provides visibility into policy-related information within Snowflake.This role is specifically designed to access views that display object metadata and usage metrics related to governance12. The GOVERNANCE_VIEWER role in the ACCOUNT_USAGE schema provides visibility into policy-related information within Snowflake.This role is specifically designed to access views that display object metadata and usage metrics related to governance12.
Question 7
Which Snowflake data types can be used to build nested hierarchical data? (Select TWO)
- INTEGER
- OBJECT
- VARIANT
- VARCHAR
- LIST
Correct answer: BC
Explanation:
The Snowflake data types that can be used to build nested hierarchical data are OBJECT and VARIANT.These data types support the storage and querying of semi-structured data, allowing for the creation of complex, nested data structures The Snowflake data types that can be used to build nested hierarchical data are OBJECT and VARIANT.These data types support the storage and querying of semi-structured data, allowing for the creation of complex, nested data structures
Question 8
What is the MAXIMUM size limit for a record of a VARIANT data type?
- 8MB
- 16MB
- 32MB
- 128MB
Correct answer: B
Explanation:
The maximum size limit for a record of a VARIANT data type in Snowflake is 16MB. This allows for storing semi-structured data types like JSON, Avro, ORC, Parquet, or XML within a single VARIANT column.Reference:Based on general database knowledge as of 2021. The maximum size limit for a record of a VARIANT data type in Snowflake is 16MB. This allows for storing semi-structured data types like JSON, Avro, ORC, Parquet, or XML within a single VARIANT column.Reference:Based on general database knowledge as of 2021.
Question 9
What is the name of the SnowSQLfile that can store connection information?
- history
- config
- snowsqLcnf
- snowsql.pubkey
Correct answer: B
Explanation:
The SnowSQL file that can store connection information is named 'config'. It is used to store user credentials and connection details for easy access to Snowflake instances.Reference:Based on general database knowledge as of 2021. The SnowSQL file that can store connection information is named 'config'. It is used to store user credentials and connection details for easy access to Snowflake instances.Reference:Based on general database knowledge as of 2021.
Question 10
A Snowflake user has been granted the create data EXCHANGE listing privilege with their role.
Which tasks can this user now perform on the Data Exchange? (Select TWO).
- Rename listings.
- Delete provider profiles.
- Modify listings properties.
- Modify incoming listing access requests.
- Submit listings for approval/publishing.
Correct answer: CE
Explanation:
With the create data EXCHANGE listing privilege, a Snowflake user can modify the properties of listings and submit them for approval or publishing on the Data Exchange. This allows them to manage and share data sets with consumers effectively.Reference:Based on general data exchange practices in cloud services as of 2021. With the create data EXCHANGE listing privilege, a Snowflake user can modify the properties of listings and submit them for approval or publishing on the Data Exchange. This allows them to manage and share data sets with consumers effectively.Reference:Based on general data exchange practices in cloud services as of 2021.
