To view warehouse usage over time, the Query history view and the WAREHOUSE_METERING__HISTORY View can be utilized.The Query history view allows users to monitor the performance of their queries and the load on their warehouses over a specified period1.The WAREHOUSE_METERING__HISTORY View provides detailed information about the workload on a warehouse within a specified date range, including average running and queued loads2.Reference:[COF-C02] SnowPro Core Certification Exam Study Guide

Alation is known for specializing in data catalog solutions and is a partner of Snowflake. Data catalog solutions are essential for organizations to effectively manage their metadata and make it easily accessible and understandable for users, which aligns with the capabilities provided by Alation.

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake's official documentation and partner listings

Parquet is a columnar storage file format that is optimized for performance in Snowflake. It is designed to be efficient for both storage and query performance, particularly for complex queries on large datasets. Parquet files support efficient compression and encoding schemes, which can lead to significant savings in storage and speed in query processing, making it the most performant file format for loading data into Snowflake.

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Data Loading1

TheCOPY INTOcommand in Snowflake can be configured to output data into a single file by setting theMAX_FILE_NUMBERoption to 1. This option limits the number of files generated by the command, ensuring that only one file is created regardless of the amount of data being exported.

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Data Unloading

Fail-safe is a feature in Snowflake that provides an additional layer of data protection. After the Time Travel retention period ends, Fail-safe offers a non-configurable 7-day period during which historical data may be recoverable by Snowflake. This period is designed to protect against accidental data loss and is not intended for customer access.

Provisioning time can vary based on the size of the warehouse. A4X-Large Warehousetypically has more resources and may take longer to provision compared to aX-Small Warehouse, which has fewer resources and can generally be provisioned more quickly.Reference:Understanding and viewing Fail-safe | Snowflake Documentation

The size of the virtual warehouse for a task can be configured to handle concurrency automatically using a Multi-cluster warehouse (MCW). This is because tasks are designed to run their body on a schedule, and MCW allows for scaling compute resources to match the task's execution needs without manual intervention.Reference: [COF-C02] SnowPro Core Certification Exam Study Guide

The Information Schema and Account Usage Share in Snowflake provide metadata and historical usage data for various objects within a Snowflake account. Specifically, they offer storage information forTables,Databases, andInternal Stages. These schemas contain views and table functions that allow users to query object metadata and usage metrics, such as the amount of data stored and historical activity.

Tables: The storage information includes data on the daily average amount of data in database tables.

Databases: For databases, the storage usage is calculated based on all the data contained within the database, including tables and stages.

Internal Stages: Internal stages are locations within Snowflake for temporarily storing data, and their storage usage is also tracked.

The default file format for the COPY command in Snowflake, when not specified, is CSV (Comma-Separated Values). This format is widely used for data exchange because it is simple, easy to read, and supported by many data analysis tools.