COF-C02 Exam Dumps - SnowPro Core Certification Exam

Two key metrics in Snowflake’s Query Profile that provide insights for performance improvement are:

Remote Disk IO: This measures the time the query spends waiting on remote disk access, indicating potential performance issues related to I/O bottlenecks.

Pruning: This metric reflects how effectively Snowflake’s micro-partition pruning is reducing the data scanned. Better pruning (more partitions excluded) leads to faster query performance, as fewer micro-partitions need to be processed.

These metrics are essential for identifying and addressing inefficiencies in data retrieval and storage access, optimizing overall query performance.

The correct function to use with the COPY INTO <location> statement to convert rows from a relational table into a single variant column and to unload rows into a JSON file is TO VARIANT. The TO VARIANT function is used to explicitly convert a value of any supported data type into a VARIANT data type. This is particularly useful when needing to aggregate multiple columns or complex data structures into a single JSON-formatted string, which can then be unloaded into a file.

In the context of unloading data, the COPY INTO <location> statement combined with TO VARIANT enables the conversion of structured data from Snowflake tables into a semi-structured VARIANT format, typically JSON, which can then be efficiently exported and stored. This approach is often utilized for data integration scenarios, backups, or when data needs to be shared in a format that is easily consumed by various applications or services that support JSON.

References:

Snowflake Documentation on Data Unloading: Unloading Data

Snowflake Documentation on VARIANT Data Type: Working with JSON

Snowflake’s Time Travel feature is used for the maintenance of historical data, allowing users to access and restore data that has been changed or deleted within a defined period4.