Which semi-structured data function interprets an input string as a JSON document that produces a VARIANT value?
Correct Answer: A
The semi-structured data function that interprets an input string as a JSON document and produces a VARIANT value is PARSE_JSON.This function is used to parse a JSON formatted string and return it as a VARIANT data type, which can then be used for further processing within Snowflake3.
Question 62
Which function determines the kind of value stored in a VARIANT column?
Correct Answer: D
The function used to determine the kind of value stored in a VARIANT column in Snowflake is TYPEOF. Understanding VARIANT Data Type: VARIANT is a flexible data type in Snowflake that can store semi-structured data, such as JSON, Avro, and XML. This data type can hold values of different types, including strings, numbers, objects, arrays, and more. Using TYPEOF Function: The TYPEOF function returns the data type of the value stored in a VARIANT column. It helps in identifying the type of data, which is crucial for processing and transforming semi-structured data accurately. Example Usage: SELECT TYPEOF(variant_column) FROM my_table; This query retrieves the type of data stored invariant_columnfor each row inmy_table. Possible return values include ' OBJECT ' , ' ARRAY ' , ' STRING ' , ' NUMBER ' , etc. Benefits: Simplifies data processing: Knowing the data type helps in applying appropriate transformations and validations. Enhances query accuracy: Ensures that operations on VARIANT columns are performed correctly based on the data type. Snowflake Documentation: TYPEOF Snowflake Documentation: VARIANT Data Type
Question 63
Which features could be used to improve the performance of queries that return a small subset of rows from a large table? (Select TWO).
Correct Answer: A,B
The search optimization service and automatic clustering are features that can improve the performance of queries returning a small subset of rows from a large table. The search optimization service is designed for low-latency point lookup queries, while automatic clustering organizes data in micro-partitions based on specific dimensions to reduce the amount of data scanned during queries.
Question 64
Which of the following statements describe features of Snowflake data caching? (Choose two.)
Correct Answer: B,E
Snowflake's data caching features include the ability to clear the least-recently used data when the data cache is full to make room for new data. Additionally, the RESULT_SCAN table function can access and filter the contents of the query result cache, allowing users to retrieve and work with the results of previous queries. The other statements are incorrect: the data cache is not saved on the remote storage layer when a virtual warehouse is suspended, users can access queries from the query result cache that were run by other users, and there is no setting calledUSE_METADATA_CACHE in Snowflake. References: Caching in the Snowflake Cloud Data Platform, Optimizing the warehouse cache
Question 65
Which Snowflake governance feature allows users to assign metadata labels to improve data governance and database access control?
Correct Answer: C
Object tagging in Snowflake allows users to assign metadata labels to various database objects to improve data governance and access control. Tags can be used to categorize and manage data based on business needs, helping to enforce governance policies and streamline database administration. Snowflake Documentation: Object Tagging
