Snowflake SnowPro Core Practice Test - Questions Answers, Page 51

Scalar functions in Snowflake (and SQL in general) are designed to return a single value for each invocation. They operate on a single value and return a single result, making them suitable for a wide range of data transformations and calculations within queries.

Snowflake Documentation: Functions

For directory tables, a named external stage allows for the automatic refreshing of metadata. This capability is particularly useful when dealing with files stored on external storage services (like Amazon S3, Google Cloud Storage, or Azure Blob Storage) and accessed through Snowflake. The external stage references these files, and the directory table's metadata can be automatically updated to reflect changes in the underlying files.

Snowflake Documentation: External Stages

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.

Snowflake Documentation: REVOKE ROLE

The VALIDATE table function in Snowflake would typically use a unique identifier, such as a UUID_STRING, as an input argument. This function is designed to validate the data within a table against a set of constraints or conditions, often requiring a specific identifier to reference the particular data or job being validated.

There is no direct reference to a VALIDATE table function with these specific parameters in Snowflake documentation. It seems like a theoretical example for understanding function arguments. Snowflake documentation on UDFs and system functions can provide guidance on how to create and use custom functions for similar purposes.

To insert JSON formatted string data into a VARIANT field in Snowflake, the correct function to use is PARSE_JSON. The PARSE_JSON function is specifically designed to interpret a JSON formatted string and convert it into a VARIANT type, which is Snowflake's flexible format for handling semi-structured data like JSON, XML, and Avro. This function is essential for loading and querying JSON data within Snowflake, allowing users to store and manage JSON data efficiently while preserving its structure for querying purposes. This function's usage and capabilities are detailed in the Snowflake documentation, providing users with guidance on how to handle semi-structured data effectively within their Snowflake environments.

Snowflake Documentation: PARSE_JSON

To insert JSON formatted string data into a VARIANT field in Snowflake, the correct function to use is PARSE_JSON. The PARSE_JSON function is specifically designed to interpret a JSON formatted string and convert it into a VARIANT type, which is Snowflake's flexible format for handling semi-structured data like JSON, XML, and Avro. This function is essential for loading and querying JSON data within Snowflake, allowing users to store and manage JSON data efficiently while preserving its structure for querying purposes. This function's usage and capabilities are detailed in the Snowflake documentation, providing users with guidance on how to handle semi-structured data effectively within their Snowflake environments.

Snowflake Documentation: PARSE_JSON

A materialized view in Snowflake denotes a pre-computed data set derived from a SELECT query specification and stored for later use. Unlike standard views, which dynamically compute the data each time the view is accessed, materialized views store the result of the query at the time it is executed, thereby speeding up access to the data, especially for expensive aggregations on large datasets.

Snowflake Documentation: Materialized Views

Characteristics of Snowsight worksheets in Snowflake include:

A . Worksheets can be grouped under folders, and a folder of folders: This organizational feature allows users to efficiently manage and categorize their worksheets within Snowsight, Snowflake's web-based UI, enhancing the user experience by keeping related worksheets together.

E . Users can import worksheets and share them with other users: Snowsight supports the sharing of worksheets among users, fostering collaboration by allowing users to share queries, analyses, and findings. This feature is crucial for collaborative data exploration and analysis workflows.

Snowflake Documentation: Snowsight (UI for Snowflake)

Object Name Resolution: When unqualified object names (e.g., table name without schema) are used in a UDF, Snowflake follows a specific hierarchy to resolve them. Here's the order:

Current Schema:Snowflake first checks if an object with the given name exists in the schema currently in use for the session.

PUBLIC Schema:If the object isn't found in the current schema, Snowflake looks in the PUBLIC schema of the current database.

Note: The SEARCH_PATH parameter influences object resolution for queries, not within UDFs.

Snowflake Documentation (Object Naming Resolution):https://docs.snowflake.com/en/sql-reference/name-resolution.html