Snowflake SnowPro Core Practice Test - Questions Answers, Page 11

External functions in Snowflake are a special type of User-Defined Function (UDF) that call code executed outside of Snowflake, typically through a remote service.Unlike traditional UDFs, external functions do not contain SQL code within Snowflake; instead, they interact with external services to process data2.

https://docs.snowflake.com/en/sql-reference/external-functions.html#:~:text=External%20functions%20are%20user%2Ddefined,code%20running%20outside%20of%20Snowflake.

Data shares in Snowflake can be created and managed through the Snowflake web interface, which provides a user-friendly graphical interface for various operations.Additionally, SQL commands can be used to perform these tasks programmatically, offering flexibility and automation capabilities123.

To generate a report listing all Snowflake logins within the last 90 days, theACCOUNT_USAGE.LOGIN_HISTORYview should be used.This view provides information about login attempts, including successful and unsuccessful logins, and is suitable for security audits4.

Semi-structured

JSON, Parquet

Snowflake supports unloading data in several semi-structured file formats, including Parquet and JSON.These formats allow for efficient storage and querying of semi-structured data, which can be loaded directly into Snowflake tables without requiring a predefined schema12.

https://docs.snowflake.com/en/user-guide/data-unload-prepare.html#:~:text=Supported%20File%20Formats,-The%20following%20file&text=Delimited%20(CSV%2C%20TSV%2C%20etc.)

The purpose of an External Function in Snowflake is to call code that executes outside of the Snowflake environment.This allows Snowflake to interact with external services and leverage functionalities that are not natively available within Snowflake, such as calling APIs or running custom code hosted on cloud services3.

https://docs.snowflake.com/en/sql-reference/external-functions.html

Topic 2, Exam pool B

Worksheets in Snowsight can be shared directly with other Snowflake users within the same account.This feature allows for collaboration and sharing of SQL queries or Python code, as well as other data manipulation tasks1.

Multi-cluster virtual warehouses in Snowflake are designed to manage user and query concurrency needs.They allow for the allocation of additional clusters of compute resources, either statically or dynamically, to handle increased loads and reduce or eliminate the queuing of concurrent queries2.

https://docs.snowflake.com/en/user-guide/warehouses-multicluster.html#:~:text=Multi%2Dcluster%20warehouses%20enable%20you,during%20peak%20and%20off%20hours.

Snowflake's architecture is designed to operate entirely on cloud infrastructure. It uses the core compute and storage services of each cloud provider, which allows it to leverage the scalability and reliability of cloud resources. Snowflake's services are deployed across multiple availability zones within a cloud provider's region to ensure high availability and fault tolerance.

Reference: [COF-C02] SnowPro Core Certification Exam Study Guide

In Snowflake, both materialized views and transient tables will incur storage charges because they store data. They will also incur compute charges when queries are run against them, as compute resources are used to process the queries.

Reference: [COF-C02] SnowPro Core Certification Exam Study Guide