Snowflake Updated COF-C02 Exam Questions and Answers by mikhail

The GET_PRESIGNED_URL file function in Snowflake provides a URL with access to a file on a stage without requiring authentication and authorization. This is particularly useful for sharing data files stored in Snowflake stages with external parties securely and conveniently. The presigned URL generated by this function gives temporary access to the file, which expires after a specified duration.

Example usage of GET_PRESIGNED_URL:

SELECT GET_PRESIGNED_URL('', '');

This function generates a URL that can be used to directly access a file in the stage, making it easier to share data without compromising security.

When attempting to load large files, such as a 125 GB file, into Snowflake using SnowSQL, the process might encounter limitations related to the maximum execution time for queries or data loading operations. If the loading process exceeds this time limit (typically around 24 hours), it could be aborted without committing any part of the file to the database. This behavior is designed to prevent indefinite resource consumption and to maintain system stability, emphasizing the need for optimizing data load operations, possibly through file segmentation or parallel loading strategies.References: Snowflake Documentation on Data Loading Considerations

Snowflake supports a variety of subquery types, including both correlated and uncorrelated subqueries. The correct answers are B and E, which highlight Snowflake's flexibility in handling subqueries within SQL queries.

• Uncorrelated Scalar Subqueries: These are subqueries that can execute independently of the outer query. They return a single value and can be used anywhere a value expression is allowed, offering great flexibility in SQL queries.
• EXISTS, ANY/ALL, and IN Subqueries: These subqueries are used in WHERE clauses to filter the results of the main query based on the presence or absence of matching rows in a subquery. Snowflake supports both correlated and uncorrelated versions of these subqueries, providing powerful tools for complex data analysis scenarios.
• Examples and Usage:

SELECT * FROM employees WHERE salary > (SELECT AVG(salary) FROM employees);

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SELECT * FROM orders o WHERE EXISTS (SELECT 1 FROM customer c WHERE c.id = o.customer_id AND c.region = 'North America');

The JAROWINKLER_SIMILARITY function in Snowflake returns an integer between 0 and 100, indicating the similarity of two strings based on the Jaro-Winkler similarity algorithm. This function is useful for comparing strings and determining how closely they match each other.

• Understanding JAROWINKLER_SIMILARITY: The Jaro-Winkler similarity metric is a measure of similarity between two strings. The score is a number between 0 and 100, where 100 indicates an exact match and lower scores indicate less similarity.
• Usage Example: To compare two strings and get their similarity score, you can use:

SELECT JAROWINKLER_SIMILARITY('string1', 'string2') AS similarity_score;

• Application Scenarios: This function is particularly useful in data cleaning, matching, and deduplication tasks where you need to identify similar but not identical strings, such as names, addresses, or product titles.