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NEW QUESTION # 383
Which Snowflake table is an implicit object layered on a stage, where the stage can be either internal or external?
- A. Temporary table
- B. Directory table
- C. A table with a materialized view
- D. Transient table
Answer: B
Explanation:
A directory table in Snowflake is an implicit object layered on a stage, whether internal or external. It allows users to query the contents of a stage as if it were a table, providing metadata about the files stored in the stage, such as filenames, file sizes, and last modified timestamps.
References:
Snowflake Documentation: Directory Tables
NEW QUESTION # 384
Which command removes a role from another role or a user in Snowflak?
- A. REVOKE ROLE
- B. ALTER ROLE
- C. USE ROLE
- D. USE SECONDARY ROLES
Answer: A
Explanation:
The REVOKE ROLE command is used to remove a role from another role or a user in Snowflake. This command is part of Snowflake's role-based access control system, allowing administrators to manage permissions and access to database objects efficiently by adding or removing roles from users or other roles.
References:
Snowflake Documentation: REVOKE ROLE
NEW QUESTION # 385
Which operation can be performed on Snowflake external tables?
- A. RENAME
- B. ALTER
- C. JOIN
- D. INSERT
Answer: C
Explanation:
Snowflake external tables are read-only, which means data manipulation language (DML) operations like INSERT, RENAME, or ALTER cannot be performed on them.However, external tables can be used for query and join operations3.
References:[COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 386
What are key characteristics of virtual warehouses in Snowflake? (Select TWO).
- A. Warehouses that are multi-cluster can have nodes of different sizes.
- B. Warehouses are billed on a per-minute usage basis.
- C. Warehouses can only be used for querying and cannot be used for data loading.
- D. Warehouses can be resized at any time, even while running.
- E. Warehouses can be started and stopped at any time.
Answer: D,E
Explanation:
Virtual warehouses in Snowflake can be started and stopped at any time, providing flexibility in managing compute resourcesThey can also be resized at any time, even while running, to accommodate varying workloads910. References: [COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 387
How often are the Account and Table master keys automatically rotated by Snowflake?
- A. 30 Days
- B. 90 Days
- C. 60 Days
- D. 365 Days.
Answer: A
Explanation:
Snowflake automatically rotates the Account and Table master keys when they are more than 30 days old.Active keys are retired, and new keys are created, ensuring robust security through frequent key changes1
NEW QUESTION # 388
While unloading data into a stage, how can the user ensure that the output will be a single file?
- A. Use the GET option FILES-SINGLE.
- B. Use the get option SINGLE-TRUE.
- C. Use the copy option files=single.
- D. Use the COPY Option SINGLE=TRUE .
Answer: D
Explanation:
To ensure that the output will be a single file when unloading data into a stage, you should use the COPY option SINGLE=TRUE. This option specifies that the result of the COPY INTO command should be written to a single file, rather than multiple files.
References:
Snowflake Documentation: COPY INTO <location>
NEW QUESTION # 389
While working with unstructured data, which file function generates a Snowflake-hosted file URL to a staged file using the stage name and relative file path as inputs?
- A. BUILD SCOPED FILE URL
- B. BUILD_STAGE_FILE_URL
- C. GET_ABSOLUTE_PATH
- D. GET_PRESIGNED_URL
Answer: B
Explanation:
The BUILD_STAGE_FILE_URL function generates a Snowflake-hosted file URL to a staged file using the stage name and relative file path as inputs2.
NEW QUESTION # 390
Why is a federated environment used for user authentication in Snowflake?
- A. To provide real-lime monitoring of user activities
- B. To enhance data security and privacy
- C. To separate user authentication from user access
- D. To enable direct integration with external databases
Answer: C
NEW QUESTION # 391
What is the MINIMUM Snowflake edition required to add masking policies to selectively mask plain-text data in a table or in view columns at query time?
- A. Enterprise
- B. Virtual Private Snowflake (VPS)
- C. Business Critical
- D. Standard
Answer: A
NEW QUESTION # 392
When should a multi-cluster virtual warehouse be used in Snowflake?
- A. When dynamic vertical scaling is being used in the warehouse
- B. When there is significant disk spilling shown on the Query Profile
- C. When queuing is delaying query execution on the warehouse
- D. When there are no concurrent queries running on the warehouse
Answer: C
Explanation:
A multi-cluster virtual warehouse in Snowflake is designed to handle high concurrency and workload demands by allowing multiple clusters of compute resources to operate simultaneously. The correct scenario to use a multi-cluster virtual warehouse is:
A . When queuing is delaying query execution on the warehouse: Multi-cluster warehouses are ideal when the demand for compute resources exceeds the capacity of a single cluster, leading to query queuing. By enabling additional clusters, you can distribute the workload across multiple compute clusters, thereby reducing queuing and improving query performance.
This is especially useful in scenarios with fluctuating workloads or where it's critical to maintain low response times for a large number of concurrent queries.
References:
Snowflake Documentation: Multi-Cluster Warehouses at Snowflake Documentation
NEW QUESTION # 393
A JSON document is stored in the source_colum of type VARIANT. The document has an array called elements. The array contains the name key that has a string value How can a Snowflake user extract the name from the first element?
- A. Source_column.element[0]:name
- B. Source_column.element[1].name
- C. Source_column.element[1]:name
- D. Source_column.element[0]:name
Answer: B
Explanation:
In Snowflake, when dealing with semi-structured data such as a JSON document stored in a VARIANT column, the proper syntax to extract a value is to use the column name followed by the path to the specific element. Since arrays in JSON are zero-indexed, the first element is referenced with [0]. Therefore, to extract the name from the first element of the elements array, the correct syntax is Source_column:elements[0].name.References: Snowflake Documentation on Semi-Structured Data
NEW QUESTION # 394
How can a data provider ensure that a data consumer is going to have access to the required objects?
- A. Use the CURRENT_ function to authorize users from a specific account to access rows in a base table.
- B. Set the SIMULATED DATA SHARING CONSUMER session parameter to the name of the consumer account for which access is being simulated.
- C. Enable the data sharing feature in the account and validate the view.
- D. Use the CURRENT_ROLE and CURRENT_USER functions to validate secure views.
Answer: C
Explanation:
To ensure a data consumer has access to the required objects, a data provider can enable the data sharing feature and validate that the consumer can access the views or tables shared with them.References:Based on general data sharing practices in cloud services as of 2021.
NEW QUESTION # 395
What happens when a virtual warehouse is resized?
- A. The warehouse will be suspended while the new compute resource is provisioned and will resume automatically once provisioning is complete.
- B. When reducing the size of a warehouse the compute resources are removed only when they are no longer being used to execute any current statements.
- C. When increasing the size of an active warehouse the compute resource for all running and queued queries on the warehouse are affected
- D. Users who are trying to use the warehouse will receive an error message until the resizing is complete
Answer: C
Explanation:
When a virtual warehouse in Snowflake is resized, specifically when it is increased in size, the additional compute resources become immediately available to all running and queued queries. This means that the performance of these queries can improve due to the increased resources.Conversely, when the size of a warehouse is reduced, the compute resources are not removed until they are no longer being used by any current operations1.
References:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Virtual Warehouses2
NEW QUESTION # 396
Which of the following is an example of an operation that can be completed without requiring compute, assuming no queries have been executed previously?
- A. SELECT MIN(ORDER_AMT) FROM SALES;
- B. SELECT ORDER_AMT * ORDER_QTY FROM SALES;
- C. SELECT AVG(ORDER_QTY) FROM SALES;
- D. SELECT SUM (ORDER_AMT) FROM SALES;
Answer: C
Explanation:
Operations that do not require compute resources are typically those that can leverage previously cached results. However, if no queries have been executed previously, all the given operations would require compute to execute.It's important to note that certain operations like DDL statements and queries that hit the result cache do not consume compute credits2.
NEW QUESTION # 397
What type of query benefits the MOST from search optimization?
- A. A query that uses only disjunction (i.e., OR) predicates
- B. A query that uses equality predicates or predicates that use IN
- C. A query that includes analytical expressions
- D. A query that filters on semi-structured data types
Answer: B
Explanation:
Search optimization in Snowflake is designed to improve the performance of queries that are selective and involve point lookup operations using equality and IN predicates.It is particularly beneficial for queries that access columns with a high number of distinct values1.
References = [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation
NEW QUESTION # 398
Which Snowflake function and command combination should be used to convert rows in a relational table to a single VARIANT column, and unload the rows Into a file in JSON format? (Select TWO).
- A. GET
- B. COPY
- C. PUT
- D. OBJECT CONSTRUCT
- E. EXPORT
Answer: B,D
Explanation:
To convert rows in a relational table to a single VARIANT column and unload the rows into a file in JSON format, you can use the COPY command in combination with the OBJECT_CONSTRUCT function. The OBJECT_CONSTRUCT function converts the row into a JSON object stored in a VARIANT column, and the COPY command can then be used to unload this data into a JSON file.
References:
Snowflake Documentation: OBJECT_CONSTRUCT
Snowflake Documentation: COPY INTO <location>
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NEW QUESTION # 399
Which of the following are characteristics of Snowflake virtual warehouses? (Choose two.)
- A. A user cannot specify a default warehouse when using the ODBC driver.
- B. Auto-resume applies only to the last warehouse that was started in a multi-cluster warehouse.
- C. SnowSQL supports both a configuration file and a command line option for specifying a default warehouse.
- D. The default virtual warehouse size can be changed at any time.
- E. The ability to auto-suspend a warehouse is only available in the Enterprise edition or above.
Answer: C,D
Explanation:
Snowflake virtual warehouses support a configuration file and command line options in SnowSQL to specify a default warehouse, which is characteristic C. Additionally, the size of a virtual warehouse can be changed at any time, which is characteristic E.These features provide flexibility and ease of use in managing compute resources2.
References = [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation
NEW QUESTION # 400
What command is used to export or unload data from Snowflake?
- A. INSERT @mystage
- B. GET @mystage
- C. COPY INTO @mystage
- D. PUT @mystage
Answer: D
Explanation:
The command used to export or unload data from Snowflake to a stage (such as a file in an S3 bucket, Azure Blob Storage, or Google Cloud Storage) is the PUT command. The PUT command is designed to upload data files from a local file system (in the case of SnowSQL or other client) or a virtual warehouse to a specified stage. This functionality is critical for scenarios where data needs to be extracted from Snowflake for use in external systems, backups, or further processing.
The syntax for the PUT command follows the structure: PUT file://<local_file_path> @<stage_name>, where <local_file_path> specifies the path to the file(s) on the local file system that you wish to upload, and <stage_name> specifies the destination stage in Snowflake.
It's important to distinguish that the PUT command is used for exporting data out of Snowflake, whereas the COPY INTO <table> command is used for importing data into Snowflake from a stage. The GET command, on the other hand, is used to download files from a stage to the local file system, essentially the inverse operation of the PUT command.
References:
Snowflake Documentation on Loading and Unloading Data: [Loading and Unloading Data](https://docs.snowflake.com/en/user-guide/data-load
NEW QUESTION # 401
How can a Snowflake user post-process the result of SHOW FILE FORMATS?
- A. Assign the command to RESULTSET.
- B. Put it in the FROM clause in brackets.
- C. Use the RESULT_SCAN function.
- D. Create a CURSOR for the command.
Answer: C
Explanation:
first run SHOW FILE FORMATS
then SELECT * FROM TABLE(RESULT_SCAN(LAST_QUERY_ID(-1)))
https://docs.snowflake.com/en/sql-reference/functions/result_scan#usage-notes
NEW QUESTION # 402
How does Snowflake describe its unique architecture?
- A. A multi-cluster shared nothing architecture using a siloed data repository and symmetric multiprocessing (SMP)
- B. A single-cluster shared data architecture using a central data repository and massively parallel processing (MPP)
- C. A multi-duster shared nothing architecture using a soloed data repository and massively parallel processing (MPP)
- D. A single-cluster shared nothing architecture using a sliced data repository and symmetric multiprocessing (SMP)
Answer: B
Explanation:
Snowflake's unique architecture is described as a multi-cluster, shared data architecture that leverages massively parallel processing (MPP). This architecture separates compute and storage resources, enabling Snowflake to scale them independently. It does not use a single cluster or rely solely on symmetric multiprocessing (SMP); rather, it uses a combination of shared-nothing architecture for compute clusters (virtual warehouses) and a centralized storage layer for data, optimizing for both performance and scalability.
References:
Snowflake Documentation: Snowflake Architecture Overview
NEW QUESTION # 403
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