Snowflake SnowPro Core Exam Practice Questions (P. 5)

GPT-4o - Answer

The correct term for increasing the maximum number of clusters in a multi-cluster warehouse in Snowflake is "scaling out." This action distributes the workload across more clusters rather than increasing the resources (like CPU and memory) of a single cluster, which would be "scaling up." It's imperative not to mix these two distinct methods of scaling, as each tackles different performance and capacity aspects.

GPT-4o - Answer

For the SnowPro Core exam, remember that Snowflake's architecture does not utilize traditional indexing methods like other databases. Instead, Snowflake organizes data into micro-partitions and uses metadata for processing queries efficiently, making the concept of migrating indexes non-applicable in their environment. So, understanding the unique storage and retrieval mechanisms in Snowflake is crucial.

GPT-4o - Answer

Snowflake indeed allows a maximum compressed row size of up to 16MB. This limit applies when dealing with semi-structured data types, like VARIANT, where each row can handle up to 16MB in size, inclusive of any other data within the same row. This size limitation is crucial for optimizing data processing and storage efficiency within the platform.

GPT-4o - Answer

The correct understanding of Snowflake's release management outlines that during updates, existing customer queries and connections are seamlessly handled without downtime because they're moved transparently to the newly updated version. Additionally, there is a designated upgrade window, typically 30 minutes, which customers can reschedule within a week for minor disruptions. This ensures continuity and reliability in service while deploying the latest functionalities and security updates. These mechanisms are crucial in the agile yet stable operational fabric of Snowflake, allowing businesses to adopt innovations swiftly without impacting their ongoing operations.