Snowflake COF-C02 Practice Test - Questions Answers, Page 15

A well-clustered table in Snowflake means that the data is organized in such a way that related data points are stored close to each other within the micro-partitions. This optimizes query performance by reducing the amount of scanned data.The diagram indicated by option C shows a well-clustered table, as it likely represents a more evenly distributed range of values across the micro-partitions1.

References =Snowflake Micro-partitions & Table Clustering

An explain plan is beneficial because it allows for the evaluation of how a query will be processed without the need to actually execute the query.This can help in understanding the query's performance implications and potential bottlenecks without consuming resources that would be used if the query were run

Snowflake supports the VARIANT and ARRAY data types for semi-structured data. VARIANT can store values of any other type, including OBJECT and ARRAY, making it suitable for semi-structured data formats like JSON.ARRAY is used to store an ordered list of elements

Snowflake recommends file sizes between 100-250 MB compressed when loading data to optimize parallel processing.Smaller, compressed files can be loaded in parallel, which maximizes the efficiency of the virtual warehouses and speeds up the data loading process

The Snowflake Enterprise edition includes database replication and failover for business continuity and disaster recovery, as well as extended time travel capabilities for longer data retention periods1.

The default file size when unloading data from Snowflake using the COPY command is not explicitly stated in the provided resources.However, Snowflake documentation suggests that the file size can be specified using theMAX_FILE_SIZEoption in theCOPY INTO <location>command2.

Data encryption and Time Travel are part of Snowflake's Continuous Data Protection (CDP) feature set that do not require additional configuration.Data encryption is automatically applied to all files stored on internal stages, and Time Travel allows for querying and restoring data without any extra setup

The Cloud Services layer in Snowflake is responsible for managing the result cache.When a query is executed, the results are stored in this cache, and subsequent identical queries can leverage these cached results without re-executing the entire query1.

Dynamic data masking is a feature in Snowflake that allows administrators to define masking policies to protect sensitive data.It enables partial visibility of the data to certain roles, such as functional managers, while hiding it from others, like end users