Snowflake COF-C02 Practice Test - Questions Answers, Page 43
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Question 421

When using SnowSQL, which configuration options are required when unloading data from a SQL query run on a local machine? {Select TWO).
Explanation:
When unloading data from SnowSQL (Snowflake's command-line client), to a file on a local machine, you need to specify certain configuration options to determine how and where the data should be outputted. The correct configuration options required are:
C . output_file: This configuration option specifies the file path where the output from the query should be stored. It is essential for directing the results of your SQL query into a local file, rather than just displaying it on the screen.
D . output_format: This option determines the format of the output file (e.g., CSV, JSON, etc.). It is crucial for ensuring that the data is unloaded in a structured format that meets the requirements of downstream processes or systems.
These options are specified in the SnowSQL configuration file or directly in the SnowSQL command line. The configuration file allows users to set defaults and customize their usage of SnowSQL, including output preferences for unloading data.
References:
Snowflake Documentation: SnowSQL (CLI Client) at Snowflake Documentation
Snowflake Documentation: Configuring SnowSQL at Snowflake Documentation
Question 422

How can a Snowflake user post-process the result of SHOW FILE FORMATS?
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
Question 423

Which file function gives a user or application access to download unstructured data from a Snowflake stage?
Explanation:
The function that provides access to download unstructured data from a Snowflake stage is:
C . GET_PRESIGNED_URL: This function generates a presigned URL for a single file within a stage. The generated URL can be used to directly access or download the file without needing to go through Snowflake. This is particularly useful for unstructured data such as images, videos, or large text files, where direct access via a URL is needed outside of the Snowflake environment.
Example usage:
SELECT GET_PRESIGNED_URL('stage_name', 'file_path');
This function simplifies the process of securely sharing or accessing files stored in Snowflake stages with external systems or users.
References:
Snowflake Documentation: GET_PRESIGNED_URL Function at Snowflake Documentation
Question 424

When should a multi-cluster virtual warehouse be used in Snowflake?
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
Question 425

A JSON object is loaded into a column named data using a Snowflake variant datatype. The root node of the object is BIKE. The child attribute for this root node is BIKEID.
Which statement will allow the user to access BIKEID?
Explanation:
In Snowflake, when accessing elements within a JSON object stored in a variant column, the correct syntax involves using a colon (:) to navigate the JSON structure. The BIKEID attribute, which is a child of the BIKE root node in the JSON object, is accessed using data:BIKE.BIKEID. This syntax correctly references the path through the JSON object, utilizing the colon for JSON field access and dot notation to traverse the hierarchy within the variant structure. References: Snowflake documentation on accessing semi-structured data, which outlines how to use the colon and dot notations for navigating JSON structures stored in variant columns.
Question 426

Which Snowflake tool is recommended for data batch processing?
Explanation:
For data batch processing in Snowflake, the recommended tool is:
B . SnowSQL: SnowSQL is the command-line client for Snowflake. It allows for executing SQL queries, scripts, and managing database objects. It's particularly suitable for batch processing tasks due to its ability to run SQL scripts that can execute multiple commands or queries in sequence, making it ideal for automated or scheduled tasks that require bulk data operations.
SnowSQL provides a flexible and powerful way to interact with Snowflake, supporting operations such as loading and unloading data, executing complex queries, and managing Snowflake objects from the command line or through scripts.
References:
Snowflake Documentation: SnowSQL (CLI Client) at Snowflake Documentation
Question 427

How does the Snowflake search optimization service improve query performance?
Explanation:
The Snowflake Search Optimization Service is designed to enhance the performance of specific types of queries on large tables. The correct answer is:
Question 428

What compute resource is used when loading data using Snowpipe?
Explanation:
Snowpipe is Snowflake's continuous data ingestion service that allows for loading data as soon as it's available in a cloud storage stage. Snowpipe uses compute resources managed by Snowflake, separate from the virtual warehouses that users create for querying data. This means that Snowpipe operations do not consume the computational credits of user-created virtual warehouses, offering an efficient and cost-effective way to continuously load data into Snowflake.
References:
Snowflake Documentation: Understanding Snowpipe
Question 429

What is one of the characteristics of data shares?
Explanation:
Data sharing in Snowflake allows for live, read-only access to data across different Snowflake accounts without the need to copy or transfer the data. One of the characteristics of data shares is the ability to use secure views. Secure views are used within data shares to restrict the access of shared data, ensuring that consumers can only see the data that the provider intends to share, thereby preserving privacy and security.
References:
Snowflake Documentation: Understanding Secure Views in Data Sharing
Question 430

Which DDL/DML operation is allowed on an inbound data share?
Explanation:
In Snowflake, an inbound data share refers to the data shared with an account by another account. The only DDL/DML operation allowed on an inbound data share is SELECT. This restriction ensures that the shared data remains read-only for the consuming account, maintaining the integrity and ownership of the data by the sharing account.
References:
Snowflake Documentation: Using Data Shares
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