Snowflake SnowPro Core Practice Test - Questions Answers, Page 21

To ensure that additional multi-clusters are resumed with no delay, a virtual warehouse should be configured to a size larger than generally required.This configuration allows for immediate availability of additional resources when needed, without waiting for new clusters to start up

Topic 3, Exam pool C

Snowflake's architecture is divided into three layers: database storage, query processing, and cloud services. The metadata, which includes information about the structure of the data, the SQL operations performed, and the service-level policies, is stored in the cloud services layer. This layer acts as the brain of the Snowflake environment, managing metadata, query optimization, and transaction coordination.

Network policies in Snowflake can be applied to users and accounts.These policies control inbound access to the Snowflake service and internal stages, allowing or denying access based on the originating network identifiers12.

Clustering in Snowflake refers to the organization of data within micro-partitions, which are contiguous units of storage within Snowflake tables.Clustering keys can be defined to co-locate similar rows in the same micro-partitions, improving scan efficiency and query performance12.

The OPERATE privilege is required for a role to resume a suspended warehouse if auto-resume is not enabled.This privilege allows the role to start, stop, suspend, or resume a virtual warehouse3.

Snowflake automatically rotates the Account and Table master keys when they are more than 30 days old.Active keys are retired, and new keys are created, ensuring robust security through frequent key changes1

Clones in Snowflake have the advantage of being created almost instantly and saving space by not duplicating storage.This is due to Snowflake's zero-copy cloning feature, which allows for the creation of object clones without the additional storage costs typically associated with data duplication23. Clones are independent of the original table and do not stay in sync with it, nor do they inherently have better query performance.However, they do inherit the time travel history from the original table at the time of cloning

Efficient pruning in Snowflake is indicated by the number of partitions scanned out of the total available.If a small percentage of partitions are scanned, it suggests that the pruning process is effectively narrowing down the data, which can lead to improved query performance