Snowflake User-Defined Functions (UDFs) allow users to define custom functions that can return specific types of values. The two types of values a UDF can return are Scalar and Tabular, depending on its implementation and use case. Here's a detailed explanation:
* Scalar UDF
* A Scalar UDF is designed to process one input value and produce one output value.
* Scalar UDFs are used in SELECT statements, WHERE clauses, and similar SQL expressions.
* Example: A Scalar UDF might take an integer as input and return its square as output.
* Syntax Example:
CREATE OR REPLACE FUNCTION multiply_by_two(val INT)
RETURNS INT
LANGUAGE SQL
AS 'val * 2';
* Execution:
SELECT multiply_by_two(4); -- Output: 8
* Tabular UDF
* A Tabular UDF returns a set of rows as its result, similar to a table or a view.
* These functions are particularly useful when working with table-valued functions (TVFs) to process multiple rows and return complex data structures.
* Example: A Tabular UDF might return a subset of a table based on some processing logic.
* Syntax Example:
CREATE OR REPLACE FUNCTION get_filtered_table(val INT)
RETURNS TABLE (col1 INT, col2 STRING)
LANGUAGE SQL
AS '
SELECT col1, col2
FROM my_table
WHERE col1 > val
';
* Execution:
SELECT * FROM TABLE(get_filtered_table(10));
Key Points about UDF Return Values:
* UDFs do not return Python objects like dictionaries (Dictionary) or lists (List) directly because Snowflake operates in a SQL-based environment.
* UDFs also cannot return arbitrary objects (Object) in the sense of programming object-oriented paradigms.
* The two valid return types supported by UDFs are Scalar and Tabular, making them highly flexible for database-specific operations.
References:
* Snowflake Documentation: User-Defined Functions
* Snowflake Documentation: Table Functions
* Snowflake UDF Best Practices

Snowflake's default Multi-Factor Authentication (MFA) service is powered by Duo Security. Users are required to install the Duo Mobile application on their devices to use MFA for increased login security when connecting to Snowflake. This service is managed entirely by Snowflake, and users do not need to sign up separately with Duo1.

In Snowflake, when an object is created, it is owned by the role that is currently active. This active role is the one that is being used to execute the creation command. Ownership implies full control over the object, including the ability to grant and revoke access privileges. This is specified in Snowflake's documentation under the topic of Access Control, which states that "the role in use at the time of object creation becomes the owner of the object." References:
* Snowflake Documentation: Object Ownership

Multi-Factor Authentication (MFA) provides increased login security for users connecting to Snowflake. Snowflake's MFA is powered by Duo Security service, which adds an additional layer of security during the login process.

Micro-partitions in Snowflake are immutable objects, which means once they are written, they cannot be modified. This immutability supports the use of Time Travel, allowing users to access historical data within a defined period. Additionally, micro-partitions can significantly reduce the amount of I/O from object storage to virtual warehouses. This is because Snowflake's query optimizer can skip over micro-partitions that do not contain relevant data for a query, thus reducing the amount of data that needs to be scanned and transferred.
Reference:
https://docs.snowflake.com/en/user-guide/tables-clustering-micropartitions.html