Free Access Snowflake COF-C02 New Release

OPERATE. In Snowflake, to pause or resume a pipe, the OPERATE privilege is required on the pipe object. The OPERATE privilege allows users to perform operational tasks on specific objects such as pipes, tasks, and streams. Specifically, for a pipe, the OPERATE privilege enables the user to execute the ALTER PIPE ... SET PIPE_EXECUTION_PAUSED=TRUE or ALTER PIPE ... SET PIPE_EXECUTION_PAUSED=FALSE commands, which are used to pause or resume the pipe, respectively.

Here's a step-by-step explanation and reference:

• Understanding Pipe Operations: Pipes in Snowflake are used for continuous data loading from staging areas into Snowflake tables. Managing pipes involves operations such as creating, monitoring, pausing, and resuming.
• Privileges for Pipe Operations: The OPERATE privilege is essential for pausing and resuming pipes. This privilege is more specific than general object access privileges like SELECT or USAGE and is tailored for operational control.
• Granting the OPERATE Privilege: To grant the OPERATE privilege on a pipe, an administrator or a user with the necessary grants can execute the SQL command:

GRANT OPERATE ON PIPE TO ROLE ;

• Pausing and Resuming Pipes: Once the OPERATE privilege is granted, the user or role can pause the pipe using:

ALTER PIPE SET PIPE_EXECUTION_PAUSED=TRUE;

To resume the pipe, they use:

ALTER PIPE SET PIPE_EXECUTION_PAUSED=FALSE;

In Snowflake, the system-defined, read-only view that displays information on column lineage, which specifies how data flows from source to target in a SQL write operation, is ACCESS_HISTORY. This view is instrumental in auditing and analyzing data access patterns, as it provides detailed insights into how and from where the data is being accessed and manipulated within Snowflake.

Reference to Snowflake documentation on ACCESS_HISTORY:

• Using Access History to Audit Data Access

The PARTITION BY <expression> parameter option in the COPY INTO <location> command is used to split the output into multiple files based on the distinct values of the specified expression. This feature is particularly useful for organizing large datasets into smaller, more manageable files and can help with optimizing downstream processing or consumption of the data. For example, if you are unloading a large dataset of transactions and use PARTITION BY DATE(transactions.transaction_date), Snowflake generates a separate output file for each unique transaction date, facilitating easier data management and access.

This approach to data unloading can significantly improve efficiency when dealing with large volumes of data by enabling parallel processing and simplifying data retrieval based on specific criteria or dimensions.

References:

• Snowflake Documentation on Unloading Data: COPY INTO

The account usage views in Snowflake provide historical usage data about the Snowflake account, and they retain this data for a period of up to 1 year. These views include information about dropped objects, enabling audit and tracking activities. On the other hand, information schema views provide metadata about database objects currently in use, such as tables and views, but do not include dropped objects. The retention of data in information schema views varies, but it is generally shorter than the retention for account usage views, ranging from 7 days to a maximum of 6 months, depending on the specific view.References: Snowflake Documentation on Account Usage and Information Schema